The sun caused 1,1 °C of the warming since the 17th century

The sun explains 93% of seawater surface temperature variance up to and including 1980s; ozone layer depletion caused more solar radiation on Earth’s surface in 1990s, resulting in a persistent spurious relation between CO2 & temperature; afterwards the sun caused further warming in 21st century

May 17, 2020 – Author: Martijn van Mensvoort | English version | Nederlandse versie

In 2020, KNMI researcher Geert Jan van Oldenborgh describes the strong statistical correlation between temperature and CO2 as “an almost perfect connection”¹. However, the link between sun and climate is not understood^2,3. This article describes, based on a total of 40 years around the solar minima over the past 130 years, that the correlation between CO2 and temperature is based on a spurious relation that arises from 2 factors, to wit: a gradual increase in total solar irradiance + an increase in the quantity of solar radiation reaching Earth’s surface due to ozone layer depletion.
Seawater surface temperature variance [HadSST3⁴] up to and including the 1980s is explained for 93% by total solar irradiance [LISIRD TSI⁵], after a correction applied to the years around the secondary minima. The 22-year solar cycle provides the physical basis for this correction because the secondary minima occur during the phase when the magnetic poles of the sun have switched positions; while the primary minima arise during the phase with the poles in their original position. The mean values over 3 year periods near TSI minima up to and including the 1980s show a correlation of +0,963 [p=0,000] with sea surface temperature; the correlation between CO2 and sea surface temperature for the same period is only +0,656 [p = 0,000]. A regression analysis shows that the combination of TSI and CO2 does not increase the explained variance for this period compared to the explained variance for the TSI separately; this also applies to when the influence of stratospheric aerosols [AOD⁶] and ENSO [ENS ONI⁷] are also included in the analysis. This implies that the alleged ‘footprint’ of CO2 is numerically absent in the years around the solar minima through the 1980s.
The relationship between the TSI at the top of the atmosphere and sea surface temperature shows a solar sensitivity of 1,2 °C per W/m2 (involving just the TSI values above 1360 W/m2) for the 3-year average around the minima of the solar cycle; this relation also explains the recent warming between the 3-year periods around the primary solar minima between 1996 and 2017. This connection implies that the sun has been responsible for approximately 1,1 °C of global warming since the Maunder minimum at the end of the 17th century.

During the past 300 years, seawater surface temperature has warmed approximately 1,5 °C; the global temperature rise is 0,15-0,30 °C higher based on a value of about 1,65 °C according the HadCRUT4 and about 1,80 °C according the GISSTEMPv4. 1,1 °C of the warming is attributed to the sun and 0,2 °C to ozone depletion. For the past 130 years the combination of TSI and ozone⁸ explains 96% of the variance in temperature. About 0,2 °C of the sea surface warming remains unexplained. CO2 may have played some role in this, possibly combined with other factors that have had relatively little influence on the long-term trend, such as: ENSO, AOD and aerosols in the lower atmosphere. It is also shown that the same pattern is found in 4 TSI data sets & 4 temperature data sets for the primary minima in in the pre-satellite era; for the satellite era the PMOD-ACRIM controversy is a crucial matter.

In the context of this study, it is important that the IPCC recognizes in AR5 (2013) that the solar cycle phase during minima is both “more stable” and “more relevant” for the long-term trend than it is during maxima.⁹. Also, there is consensus among climate experts that ocean heat content is a “more reliable” indicator of global warming than the atmospheric warming^10-12; logically, therefore the warming of seawater surface temperature is very likely also a more significant indicator. Based on Henry’s law, a small part (~15%) of the rise in the CO2 concentration in the atmosphere is the result of sea surface water warming^13-14; it is also known that in the perspective of natural cycles CO2 follows the temperature and not the other way around.

TIP: Figure 10B + figure V show that since the end of the 19th century the solar cycle minima show that seawater surface temperature followed total solar irradiance continuously, with exception to the period between the mid-1980s and mid-1990s.

CONTENTS

• I – CO2 shows a comparable characteristic dynamic in relation to both temperature and total solar irradiance
• II – Sea surface temperature and TSI show a comparable high correlation with CO2 near solar minimum years
• III – After correction, sun shows almost perfect correlation with seawater surface temperature for period including mid-1980s
• IV – Until the 1980s, the sun explains no less than 93% variance in seawater surface temperature
• V – Since the late 19th century, sun and ozone explain 96% of variance in seawater surface temperature
• VI – Since the 17th century, the sun caused ~1.1 °C warming of the seawater surface temperature
• VII – Pre-satellite era: other data sets show the same profile around primary minima
• VIII – Satellite era: ACRIM-PMOD controversy crucial to impact of the sun
• IX – Physical substantiation for impact of sun is conceptually more simple than CO2 hypothesis
• X – Discussion & conclusion

• References

(Data: Excel data file)

I – CO2 shows a comparable characteristic dynamic in relation to both temperature and total solar irradiance

Figure 1 presents a graph made by KNMI researcher Geert Jan van Oldenborgh which describes the statistical relationship between global temperature [GISS] and CO2. The size of the correlation between the two factors is 0,942 [p=0,000; the level of significance is determined using PSPP]. Van Oldenborgh has illustrated the correlation inside the graph with a pink trend line. For the period 1880-1970, the correlation between CO2 and the GISS temperature is considerably lower: 0,616 [p=0,000]. However, these correlations do not unveil the potential relationship between temperature and CO2 in terms of cause and effect. Van Oldenborgh assumes the temperature rise is largely the result of the greenhouse gas CO2 ¹. However, Henry’s law describes an inverse relationship between both factors because the concentration of CO2 in the atmosphere depends, among other things, on the temperature of the seawater surface. This implies that the ocean system is less able to absorb CO2 from the atmosphere when the seawater temperature rises. Therefore it is necessary to analyze the dynamics between the two factors in order to determine and understand the nature of the statistical relationship.

In this study the dynamics between temperature and CO2 is studied by means of the most stable phase of the solar cycle: the solar minima. Figure 1 shows the primary and secondary solar minima years accentuated with dark blue and light blue respectively. The values show that up to and including 1985 the temperature during the secondary minima was constantly slightly higher than during the directly surrounding primary minima. At the end of this paragraph is described that the sun shows an opposite phenomenon. Subsequently, a correction will be introduced in paragraph III in order to neutralize the impact of these opposing phenomena.

Figure 1: CO2 shows a strong correlation (r = 0,942 [p=0,000]) with the GISS temperature data set; however, the magnitude of the correlation does not unveil whether there is a causal relationship. For, the period 1880-1970 shows a significantly lower correlation (r = 0,616 [p=0,000]). Based on the LISIRD TSI data set, the primary and secondary solar minimum years are shown in respective with dark blue and light blue color.

The GISS data set (chosen by van Oldenborgh in order to study the relationship between CO2 and temperature) starts in 1880. For this reason this study is focused on the period starting from the year 1880 as well. The analysis is initially focused on 40 years, consisting of the year 1880 plus thirteen 3-year periods surrounding the minima of the 22-year magnetic solar cycle based on the LISIRD TSI data set. The year 1880 is not a solar minimum year, but this year follows immediately after the secondary minimum year 1879. The year 1880 is therefore part included in the analysis, just like all years immediately before and after the 13 minimum years (7 primary minima & 6 secondary minima) according the LISIRD TSI data set.

Just like figure 1, figure 2 describes the relationship between temperature and CO2 as well, but the GISS temperature data set has been replaced by the HadCRUT4 temperature series¹⁵. For the entire period 1880-2018 the correlation between the HadCRUT4 and CO2 is 0,918 [p=0,000], which is only slightly lower than for the GISS temperature data set and CO2 combination. For the 1880-1970 period the HadCRUT4 vs. CO2 correlation is 0,713 [p=0,000], which is an order of magnitude higher compared to the correlation for the same period between the GISS and CO2 (r = 0,616 [p=0,000]).

This shows that the HadCRUT4 describes a more stable correlation with CO2 relative to the GISS; after all, the correlation difference between the two periods is clearly smaller for the HadCRUT4 (difference: 0,918 – 0,713 => 0,205) relative to the GISS (difference: 0,942 – 0,616 => 0,326). Based on this comparison, it can be stated that numerically the instability of the correlation between temperature and CO2 for the GISS is 59% [= (0,326-0,205) / 0,205] higher relative to the HadCRUT4.

Figure 2: CO2 also shows a strong correlation with the HadCRUT4 temperature data set (r = 0,918 [p=0,000].

Figure 2 exhibits that the course of both the primary and secondary minimum years is approximately representative for the course of the entire data set. Both minima series show an oscillating pattern where a magnetic solar cycle featured with a drop in temperature is followed by two successive magnetic solar cycles featured with a temperature rise. In addition to this characteristic dynamic, the primary and secondary minima also show clear differences. In the secondary minima the temperature difference over the double magnetic cycle in the period 1902-1943 represents almost the same temperature difference that is seen for the triple magnetic cycle in the period 1943-2008; the values are in respective: +0,398 °C in 41 years vs. +0,399 °C in 65 years. The primary minima show a temperature increase that is approximately 3x larger during the most recent 2 magnetic cycles in the period 1976-2017 (41 years) compared to during the double magnetic cycle in the period 1912-1954 (42 years). In short, the direction of the movement shows a strong parallel between the primary and secondary minima, but the proportions involving the magnitude of the temperature differences vary strongly between the two minima series.

Figure 3 describes the relationship for the HadSST3 seawater surface temperature series and CO2. For the entire period 1880-2018 the correlation between HadSST3 and CO2 is: 0,878 [p=0,000], which is slightly lower compared to the global temperature series (HadCRUT4 and GISS). For the period 1880-1970 the correlation is: 0,710 [p=0,000], which corresponds fairly accurately to the HadCRUT4 temperature series. This implies that the HadSST3 vs. CO2 combination shows a slightly more stable correlation (difference: 0,878 – 0,710 => 0,168) compared to both global temperature series; the instability of the correlation in the GISS is even up to 94% higher relative to the HadSST3.

Figure 3 also shows for both minima series an oscillation pattern that includes a magnetic solar cycle accompanied with a temperature drop which is followed by two successive magnetic solar cycles featured with a temperature rise. In addition to this characteristic dynamic, the primary and secondary minima also show clear differences here – though these differences are in the perspective of the HadSST3 seawater surface temperature slightly smaller relative to the global HadCRUT4 temperature series.

Figure 3: CO2 also shows a strong correlation with the HadSST3 temperature data set (r = 0,878 [p=0,000]).

The analysis so far shows that prior to 1970 the magnitude of the correlations between CO2 and the various temperature series is clearly much lower than the correlation for the entire period from 1880. In addition, figure 3 shows that the temperature rise of the seawater surface during the 41 years between the secondary minimum years 1902 and 1943 (+0,408 °C) is even significantly larger than the temperature rise during the 43 years between secondary minimum years 1965 and 2008 (+0,368 °C). This indicates that CO2 may not have been largely responsible at all for the temperature rise during both periods.
With regard to the primary minima, it is also striking that figure 3 shows a rate of temperature rise in the 20-year period between 1976 and 1996 that is hardly below the rise during the 21-year period between 1996 and 2017. This provides another indication that CO2 may not have been largely responsible for the temperature rise during these periods.

The characteristic dynamics are not exclusive for just the minimum years of the solar cycle, because the two purple curves in figure 4 clearly show that the characteristic pattern also becomes manifest in the 3-year average values around the minimum.

The two blue curves in the lower part of figure 4 show that the characteristic dynamics also become manifest in the total solar irradiance. After all, the primary minima series of the TSI show an approximately similar pattern: after a fall in the primary TSI minima during a solar cycle, two successive magnetic solar cycles follow with an increase of TSI. Additionally, one can notice here that the TSI secondary minima show a deviation in the pattern during the transition from the period 1901-1903 to the period 1921-1923 with a (small) decrease, while the temperature shows an increase.

Figure 4: The total solar irradiance (TSI) shows for the 3-year average values around the minima almost the same characteristic pattern that is present in the temperature data. Only the secondary minima show a difference in direction at the first temperature and TSI transition.

A striking difference between sea surface water temperature and TSI is that only in the latter perspective the curve with the secondary values is largely found below the primary values. In the period up to and including the 1980s the curve of the secondary temperature values is largely above the primary temperature values. This points towards the possibility that the content of the solar radiation during primary and secondary solar minima differs substantially from each other, so that lower secondary TSI may be associated with higher secondary temperatures. This phenomenon shows a clear parallel with the Gnevyshev-Ohl rule¹⁶, which is associated with solar proton events and structural changes in the sun’s magnetic field¹⁷ – this field determines the amount of cosmic rays that can reach Earth. According simple logics, the magnetic cycle of the sun therefore also plays a role in the composition of the Earth’s atmosphere, which has an influence on the climate¹⁸.

Figure 4 shows for both perspectives a trend channel in the form of yellow zones based on the first 3 primary minima (which represent the most stable phase of the solar cycle). After all, only at the primary minima the poles of the sun are in the original position; while the poles have switched positions when the secondary minima become manifest. Only the average TSI values of the last two primary periods (1984-86 and 2016-18) are inside the corresponding trend channel, while for the seawater surface temperature the average values of the last two primary periods are found well above the trend channel. A confirmation for this represents the relatively large distance between the temperature and the TSI during these periods. A major difference between the temperature and the TSI becomes manifest at the transition between the primary years 1975-77 and 1995-97: only the temperature has clearly increased during this transition, while the TSI shows a minimal increase only.

Figure 4 also shows that the distance between temperature and TSI remains stable up to and including the 1984-86 period. This suggests that the warming that becomes manifest on top of the impact of the gradually increased activity of the sun did not clearly start yet during the mid-1980s. Also, one should notice here that temperature and TSI both have a significantly lower value for the secondary 1984-86 period compared to the secondary 1942-44 period (both perspectives also show values for the 1964-66 period which are slightly lower than the 1984-86 period).

Ozone layer depletion + the emergence of the seasonally related hole in the ozone layer at the South Pole have become manifest from the year 1979. Because the ozone layer is responsible for blocking ultraviolet [UV] solar radiation – a large part of the high-frequency part of solar irradiance is therefore being prevented from reaching the Earth’s surface – this implicates that ozone depletion has contributed to the warming of the lower atmosphere. Figure SPM.5 in IPCC AR5 confirms that ozone [O3] can be held responsible for a significant contribution to the warming of the atmosphere. For, O₃ plays a role in the radiative forcing of no less than 5 anthropogenic emitters. 4 Out of 5 factors provide a net contribution to the increase in radiative forcing¹⁹; the largest contribution is associated with methane [CH4].

Consistent with figure 4, paragraph II will demonstrate that near the solar minimum years the correlation between CO2 and the seawater surface temperature does not differ much from the correlation between CO2 and the TSI. Subsequently, paragraph III and paragraph IV present two different analysis techniques which present results showing that the combination of sun and ozone largely explains the gradual warming during the past 130 years.

II – Sea surface temperature and TSI show a comparable high correlation with CO2 near solar minimum years

The first paragraph presented the dynamics for the minimum years; in this paragraph the perspective of the analysis is made larger by including the years immediately before and after the minima. Figure 5 describes the correlation between seawater surface temperature and CO2 (for the period starting from 1880 at the primary minimum years + the immediately surrounding years), which shows almost the same size for the correlation between seawater surface temperature and TSI. These correlations relate to a total of 21 years around the primary minima; the correlation value is, respectively, for seawater surface temperature & CO2: 0,916 [p=0,000] and for seawater surface temperature & TSI: 0,902 [p=0,000].

The period up to and including the late 1970s shows in figure 5 for the correlation between TSI & CO2 a value of 0,813 [p=0,000], which is not much smaller than the correlation for the entire period. On the other hand, the correlation between temperature & CO2 shows a value of 0,544 [p=0,018], which is considerably lower than the correlation for the entire period.

Figure 5: In the 21 years around the primary solar minima for the entire period starting from the year 1880, seawater surface temperature [HadSST3] vs. CO2 (r = 0,916 [p=0,000]) shows a correlation of comparable magnitude relative to the correlation for seawater surface temperature vs. TSI [LISIRD] (r = 0,902 [p=0,000]). The period up to and including the 1970s exhibits that seawater surface temperature only shows a stable correlation with TSI as it is comparable with the correlation for the entire period; while for CO2 the correlation at the primary minima for the period up to and including the 1970s is much lower.

Subsequently, figure 6 shows for the secondary years + the directly surrounding years that the correlation between seawater surface temperature and CO2 in the period starting from 1880 shows exactly the same value as seen for the correlation between seawater surface temperature and TSI. These correlations relate to a total of 19 years and both have the value 0,832 [p=0,000].

For the period up to and including the 1970s, the correlation for TSI and sea surface temperatur shows a value of 0,808 [p=0,000] whic is also not much lower compared to the secondary minima covering the entire period. While the correlation for CO2 and sea surface temperature show with a value of 0,633 [p=0,010] a considerably lower value compared to the entire period. In short, the primary and secondary years separately show roughly the same overall picture: a stable correlation is found only for the combination of the seawater surface temperature and TSI.

Figure 6: The 19 years near the secondary solar minima exhibit for the entire period starting from 1880 that seawater surface temperature [HadSST3] and CO2 produce a correlation (0,832 [p=0,000]) that is also found for seawater surface temperature and TSI. The period up to and including the 1970s exhibits that seawater surface temperature only shows a stable correlation in relation to TSI; for CO2 the correlation during this period at the secondary minima is significantly lower.

Figure 7 shows for the primary and secondary years combined that the overall picture hardly changes in a comparison to the primary and secondary years separately. For the 40 years spread over the entire period the correlation between the seawater surface temperature and CO2 shows a value of 0,885 [p=0,000], which deviates only slightly from the average correlation for the primary and secondary years separately. The correlation for sea surface temperature and TSI is approximately of the same size, even though this correlation is slightly smaller with a value of 0,841 [p=0,000].

For the period up to and including the late 1970s, the correlation value for CO2 (r = 0,547 [p=0,001]) involving the combination of primary and secondary minima is again much lower than for the TSI (r = 0,728 [p=0,000]) is.

Figure 7: The 40 years around the solar minima for the period starting from the year 1880 show for seawater surface temperature [HadSST3] a correlation of the same magnitude with respect to CO2 (r = 0,885 [p=0,000]) and TSI (r = 0,841 [p=0,000]).

Figures 5 to 7 show that for the years near the solar cycle minima the high correlation between seawater surface temperature and CO2 is by no means unique. Both the primary minima & secondary minima and the combination of both minima series, the correlation between seawater surface temperature and TSI consistently shows a magnitude of comparable size. Moreover, the values in the 100-year period between 1880 and the late 1970s show that the correlations between temperature and sun is clearly more stable than the correlations with CO2 involved.

Important as well, only the correlation between TSI and the sea surface temperature does not include any uncertainty in terms of cause and effect. One can only speculate about the possibility that the correlations involved are based on a spurious connection – though in terms of the fundamentals there is no specific reason to suspect that this is actually the case, because after all: the sun is without any doubt the driving force behind the climate system.
In contrast, the correlation between CO2 and seawater surface temperature is by no means based on an unambiguous mechanism in terms of cause and effect. For, on the one hand, CO2 as a greenhouse gas has the potential to contribute to a temperature rise itself. However, on the other hand, Henry’s law shows that an increase in ocean temperature can lead to a higher value of CO2 in the atmosphere. So, there is a clear inconsistency involved. Actually, in 2020 the greenhouse theory is still mainly based on ‘consensus’, while this theory can by no means be considered ‘proven’ based on empirical data. In 2015 the very first empirical evidence was claimed demonstrating that CO2 has some influence – ~10% of the trend – on the ‘back radiation’ of long-wave radiation (= infrared radiation) from the atmosphere²⁰. Another significant side note involves the fact that it is known from the natural cycles that CO2 follows temperature and not the other way around. This latter point applies to short and long term cycles, such as: the diurnal cycle ²¹, the seasonal cycle ²¹ and the ice age cycle ²².

Finally, figure 7 shows another significant detail. Only the TSI shows for the period up to and including the 1970s a clearly lower correlation after the two minima series have been combined (r = 0,728 [p=0,000]); while figures 5 & 6 show correlations that are much higher for both the primary minima (r = 0,813 [p=0,000]) and the secondary minima (r = 0,808 [p=0,000]). The following paragraph will show that this phenomenon can be neutralized by means of a correction (aimed at the secondary minima); after applying the correction, the average values over 3 years around the minima exhibit for seawater surface temperature & TSI an almost perfect correlation for the period up to and including the 1980s.

III – After correction, sun shows almost perfect correlation with seawater surface temperature for period including mid-1980s

In the first paragraph figure 4 shows a structural phenomenon related to the 22-year magnetic solar cycle; it shows for the primary and secondary minima a parallel with the Gnevyshev-Ohl rule (though this rule only involves the sunspots number at maxima). The secondary TSI values are structurally below the nearest primary TSI values; however, temperature shows a tendency in the opposite direction. Subsequently, figure 7 in the second paragraph points out that after merging primary and secondary minima a considerable part of the correlation between sea surface temperature and TSI is lost – this effect is particularly visible in the period up to and including the 1970s.

Curiously, the impact of the correlation loss can be reversed via a simple correction aimed at the secondary minima (where TSI values have been increased with a value of: +0,123 W/m2). Figure 8 describes the result after applying the correction; the correction only applies to the panel on the right side of figure 7, the panel on the left side of figure 7 has remained unchanged in figure 8. After applying the correction, the correlation between seawater surface temperature and TSI for the combined minima series in the period up to and including the 1970s rises to a value of 0.813 [p = 0.000]. The new correlation corresponds exactly to the correlation value for the primary minima (r = 0,813 [p=0,000]); also, the deviation from the correlation value for the secondary minima (r = 0,808 [p=0,000]) is just small. Moreover, after applying the correction the correlation for the entire periode (r = 0,874 [p=0,000]) has also increased slightly compared to the value without the correction (note: figure 7 shows for the primary and secondary minima combined before the correction for the entire period a value of 0,841 [p=0,000]).

Figure 8: After increasing the TSI secondary minima with a value of 0,123 W/m2, the correlation between seawater surface temperature and TSI for the period up to and including the 1970s becomes for the two minima series combined restored to a value of 0,813 [p=0,000]; the corrected correlation value exactly matches the value at the primary minima (r = 0,813 [p=0,000]) and the deviation is also very small compared to the value for the secondary minima only (r = 0,808 [p=0,000]).

Figure 8 describes for the temperature impact of the sun during the most recent period starting from the 1990s, an average value of 1.14 °C per W/m2 around the minima. This value corresponds approximately to the average value of 1.08 °C per W/m2 found for the years around the minima in the period 1880-1980s. In addition, various intermediate periods show values of the same magnitude.
Also, the correlations between temperature and sun show in a comparison between the period up to the 1970s and the entire period a very high level of consistency (difference: 0.874 – 0.813 => 0.061). While the correlations between temperature and CO2 show in a comparison focused on both periods a low level of consistency (difference: 0.885 – 0.547 => 0.338).

Following figure 8, the result after the correction based on the 3-year average values around the minima is shown in figure 9. The left panel of figure 9 shows for CO2 a likewise characteristic oscillating dynamic that has also been described in section I for the individual primary and secondary minima separately. This implicates that the characteristic dynamic is also present in the perspective of the 3-year average at the minima.
In the right panel of figure 9 the sun shows an almost perfect correlation with temperature over the entire period, with exception to the transition between the minima in the 1980s and 1990s. The period from 1979 to the mid-1990s became known as the period in which the ozone problem became manifest. In 1991 the ozone concentration first reached the level of 100 DU and a few years later it bottomed out in 1994; from the late 1990s ozone levels have subsequently stabilized²³.

Figure 9: After applying the correction (targeted at the secondary minima with a value of: +0,123 W/m2), the 3-year TSI average at the solar minima shows an almost perfect correlation with the sea surface temperature over almost the entire period. Only the transition between the minima in the 1980s and 1990s shows an inconsistent course between both factors. This inconsistency coincides with the time span in which the season-related hole in the ozone layer at the South Pole became manifest. The most recent trough phases of the multi-decadal cycle are also shown; the intermediate period is likely representative for the short phase of the Gleisberg cycle.

Figure 9 shows a remarkable picture, because: for the period up to and including the mid-1970s, the period up to and including the 1980s, as well as the entire period, the combination of seawater surface temperature and total solar irradiance shows an almost perfect correlation. In addition, it also shows that based on the 3-year average at the minima the correlations between temperature and CO2 (left panel in figure 9) are consistently lower for all three periods than the correlations between temperature and total solar irradiance (right panel in figure 9). Only the correlations involving the sun show a stable development for all three periods. This shows that the sun represents an underlying explanatory factor for the emergence of the strong statistical correlation between CO2 and temperature. In short, the stable consistent correlations between sun and temperature show that the sun has been largely responsible for the temperature rise according simple logics (in paragraph VI the possibility is examined whether CO2 also plays a role in this).

Figure 10 shows the impact of the correction based on the 22-year solar cycle (via the secondary TSI minima) in a more direct format based on the 3-year average values. Figures 10A and 10B describe the perspective without and with the correction; figure 10C describes the impact of a neutralization of the (inconsistent) transition between the minimum periods in the 1980s and 1990s.
Figure 10 shows in just 2 steps how a consistent and ‘almost perfect correlation’ is found for the 3-year periods at the minima with regard to the combination of the sun and the temperature for the entire period. The relationship between the scales for temperature and total solar irradiance has been determined by means of a regression analysis based on the 3-year values for the minima in the period up to and including the 1980s (note: this involves data over a period of almost 100 years starting from the 3-year period around the primary minimum in 1890). This ratio of the scales corresponds to a solar sensitivity of 1,26 C per W/m2 based on the TSI at the top of the atmosphere (section IX provides a numerical description for the perspective of Earth’s surface + the necessity for a physics enhancing mechanism for the influence of the sun).

Figure 10: After corrections for the 22-year magnetic solar cycle and the ozone problem, total solar irradiance shows a consistent and ‘almost perfect correlation’ with seawater surface temperature. Figure 10A shows the 3-year mean minima values for the LISIRD TSI and HadSST3 seawater surface temperature; in figure 10B the secondary [S] TSI values have been raised with a value of +0,123 W/m2 (= a correction due to the exchange of the magnetic poles in the perspective of the 22-year solar cycle); finally, a second correction has been applied in figure 10C (in connection with the ozone problem), whereby the impact of the transition between the periods 1984-86 and 1995-97 has been neutralized for the last 3 minima periods. NOTE: The multiplication factor 1,26 °C per W/m2 only applies to the part of the TSI value above 1360 W/m2.

Figure 10 shows that next to the part of the global warming that has arisen due to the ozone problem (impact: 0,266 °C), the remainder (impact: 0,548 °C) of the total global warming (impact: 0,814 °C) is explained by the sun – after applying the correction aimed at the secondary minima [S]. Because both figure 10A and figure 10B describe that the sun has caused a warming of 0.581 °C in the perspective of the primary minima [P] and the combination of figures 10B & 10C show indicatively that the sun combined with the ozone problem caused a warming at the order of 0.847 °C (= 0.581 °C + 0.266 °C). Striking about figure 10C is that the deviation between temperature and TSI is only relatively large for the first 5 minima periods (1890s to 1930s), while the most recent 7 minima periods (1940s to 2010s) show relative small differences.

However, figure 10 does not yet take into account the possibility that the sun combined with other factors might possible explain a larger part of the variance. The following paragraphs aim to investigate this further on the basis of 5 climatic components: TSI, ozone, CO2, AOD & ENSO.

IV – Until the 1980s, the sun explains no less than 93% variance in seawater surface temperature

An analysis involving five climatologic components shows that the adjusted TSI (after the correction aimed at the secondary minima) leaves little room for the influence of other factors. The overview below shows for the period up to and including the 1980s that in the perspective of 3-year minima, no less than 93% of variance in seawater surface temperature is explained by the adjusted TSI.

• TSI [LISIRD] with adjustment (+0,123 W/m2) of secondary values:
– Full period: R = 0,93; R-square = 0,87 (explained variance = 87%); p=0,000
– Period up to and including ’80s: R = 0,96; R-square = 0,93 (explained variance = 93%); p=0,000

• TSI [LISIRD] without adjustment of secondary values:
– Full period: R = 0,89; R-square = 0,80 (explained variance = 80%); p=0,000
– Period up to and including ’80s: R = 0,85; R-square = 0,72 (explained variance = 72%); p=0,002

• CO2:
– Full period: R = 0,92; R-square = 0,84 (explained variance = 84%); p=0,000
– Period up to and including ’80s: R = 0,66; R-square = 0,44 (explained variance = 44%); p=0,037

• Ozone (size hole in ozone layer):
– Full period: R = 0,82; R-square = 0,67 (explained variance = 67%); p=0,001
– Period up to and including ’80s: (no analysis possible because all values are zero for this period)

• AOD [NASA]:
– Full period: R = 0,30; R-square = 0,09 (explained variance = 9%); p=0,323
– Period up to and including ’80s: R = 0,01; R-square = 0,00 (explained variance = 0%); p=0,986

• ENSO [ENS ONI with 6 months impact delay]:
– Full period: R = 0,11; R-square = 0,01 (explained variance = 1%); p=0,712
– Period up to and including ’80s: R = 0,39; R-square = 0,15 (explained variance = 15%); p=0,271

This overview shows for the individual components that only the TSI explains more than 50% of variance in seawater surface temperature up to and including the 1980s; this applies to the TSI both with and without the correction.

Also, with a single regression analysis [executed with the statistics program PSPP] is investigated whether CO2 combined with the corrected TSI can contribute to the explained variance for the period up to and including the minimum period 1984-86. This is not the case because the explained variance based on the corrected TSI only is 93%, while the corrected TSI combined with CO2 results in an explained variance of just 91% (based on ‘adjusted R-squared’ values); moreover, the contribution of CO2 is also not significant here.
Investigated as well is to what extent AOD and/or ENSO contributes to the explained variance, with and without CO2; this is not the case for the individual factors and neither for all possible combinations with these factors involved. This implies that for the period up to and including the 1980s the other factors do not generate any significant added value compared to the impact of the adjusted TSI.

Also, the combination of TSI and CO2 provides no added value for the 72% explained variance found based on the uncorrected TSI. For, a regression analysis shows that the explained variance based on the adjusted R-square decreases to 70% for the combination involving the uncorrected TSI and CO2. Here as well only the TSI component makes a significant contribution to the combination. Combinations with AOD and/or ENSO for the period up to and including the 1980s do not generate any added value here in terms of the explained variance (based on ‘adjusted R-squared’ values).

V – Since the late 19th century, sun and ozone explain 96% of variance in seawater surface temperature

Paragraph III has been used to describe a first indicative estimate for the impact of the adjusted TSI combined with ozone; however, implicit it was assumed that the impact of the ozone problem has remained stable since the 1990s. Earlier, the February article made use of the size of the seasonal hole in the ozone layer near Antarctica⁸ in order to study the influence of the weakened ozone layer.

A regression analysis based on 3-year average values shows that the adjusted TSI combined with ozone layer hole size produces an adjusted R-squared value of 0,96; this implies that 96% of sea surface temperature variance in the perspective near the minima is explained by the combination of sun and ozone for the entire period from the 3-year period around the minimum year 1890. In addition, both components make a highly significant contribution to this result (with p-value: 0,000). Without the correction aimed at the minima, the combination explains 91% of the variance in seawater surface temperature for the entire period in the years near the minima.

Also, it has been investigated to what extent the components CO2, AOD and ENSO generate added value for the entire period in terms of the explained variance within the perspective of the 3-year average values at the minima. This is by no means the case and this also applies to both the TSI values without and with the correction aimed at the secondary minima.

Figure V: A regression analysis produces a temperature model for the TSI and ozone that explains 96% of the variance in surface water temperature based on the 3-year mean around the minima. The temperature model explains 93.7% of the 0,831 °C warming that has arisen since the period 1889-1891; the sun explains 0,567 °C (= 69,7%) of this warming. This implies that the warming contribution of ozone is 0,195 °C (rounded: 0,2 °C). NOTE: The multiplication factor of 1,23 °C per W/m2 only applies to the part of the TSI value above 1360 W/m2; figure V describes only the TSI part above 1360 W/m2.

VI – Since the 17th century, the sun caused ~1.1 °C warming of the seawater surface temperature

In paragraph III figure 10 describes (after applying the correction aimed at the secondary minima) a solar sensitivity of 1,26 C per W/m2; this value applies to the TSI value above 1360 W/m2 and has been established with a regression analysis. In addition, figure 10C shows that after an additional correction focused on the transition between the minima periods 1984-86 and 1995-97, the sun shows an indicative “near-perfect correlation” with the seawater surface temperature.

Subsequently, paragraph IV shows that after applying the correction aimed at the secondary minima, the TSI explains 93% of the variance in the seawater surface temperature for the period up to and including the 1980s. And then paragraph V describes that the corrected TSI combined with the size of the hole in the ozone layer at the South Pole explains as much as 96% of the variance over the entire period since the last decade of the 19th century.

It is important to be aware that these results are based on values over a 3-year period. When the solar sensitivity for the average values over 3 years for the entire period is calculated combined with the size of the hole in the ozone layer, a value is found of 1,23 °C per W/m2 (explained variance: 96%).

However, when the solar sensitivity is calculated on the basis of the individual years up to and including the 1980s, a value of just 1,07 °C per W/m2 is found for the solar sensitivity (accompagnied with an explained variance of 63%). And a calculation of the solar sensitivity based on the individual years combined with the size of the hole in the ozone layer results in a value of 0,96 C per W/m2 (accompagnied with an explained variance of 84%). This induces the impression that in the perspective of individual years ‘climate noise’ plays a role in masking the sun’s sensitivity, for example via phase differences.

The value found for solar sensitivity therefore depends strongly on the chosen calculation method. Since the highest explained variance (96%) is found for the solar sensitivity of 1,23 °C per W/m2 (based on the 3-year average over the entire period via the combination of the sun and ozone), this value is chosen in order to estimate the warming caused by the sun since the Maunder minimum at the end of the 17th century.
In the meantime, the TSI has increased from a value of 1360.274 W/m2 during the minima during the last 4 decades of the 17th century to a value of 1361,215 W/m2 during the most recent primary minimum year 2017. This corresponds to an increase of 0,941 W/m2 over a period of approximately 330 years.

This increase of 0,941 W/m2, combined with a solar sensitivity of 1,23 °C per W/m2, results in a temperature increase of 1,157 °C in 330 years. This corresponds to an average temperature rise of more than 0,35 °C per century; however, for the most recent period the average value is 2x larger, for: after the 3-year minimum around the year 1912 the sun explains more than 0,7 °C of the warming during the past 110 years (of which 0,38 °C for the 3-year minima between 1912 and 1996 involving a period of 84 years = by average 0,45 °C per 100 year).

* The February article refers to Zharkova et al. (June 24, 2019)²⁴ who associate their research based on various magnetic properties of the sun, a parallel with the work of Akasofu (2010) where a natural impact trend of by average 0,5 °C for the 20th century is described. On March 4, 2020, Zharkova’s publication has been withdrawn by the journal Nature despite objections made by 3 of the 4 authors (this action was taken under pressure of arguments primarily related to an assumption made regarding the existence of uncorrelated fluctuations in the movement of sun and Earth around the barycenter; the magnitude and direction of these fluctuations is disputed by peer reviewers, who assume that the motion of sun and Earth are each under the same influence of the planet Jupiter + some other planets).

VII – Pre-satellite era: other data sets show the same profile around primary minima

The previous paragraphs describe that the LISIRD TSI data set shows for the years near the minima a particularly strong parallel with the HadSST3 data set for seawater surface temperature. This paragraph places the combination of both data sets in a broader perspective through a comparison between values based on the 3-year primary minima for the pre-satellite era. A total of 4 TSI data sets (LISIRD, IPCC AR5, Satire S&T and NRLTSI2) and 4 temperature data sets (HadSST3, HadCRUT4, GISSTEMP v4 and GISS SST) are used in this comparison. Only the HadSST3 data set and GISS SST data set involve seawater surface temperature.

Figure 11 shows that all 8 data sets show approximately the same profile for the primary minimum years in the pre-satellite era. The 3-year period near 1912 describe the lowest value in every data set; 1890 and 1933 show higher values and 1954 and 1976 show even higher values. It is also striking that the average values of the 4 TSI data sets and the average values of the 4 temperature data sets produces a correlation of 0,928 [p=0,011].

Figure 11: A comparison between 4 TSI data sets (LISIRD, IPCC AR5, Satire S&T and NRLTSI2) and 4 temperature data sets (HadSST3, HadCRUT4, GISSTEMP v4 and GISS SST) reveals the same pattern for all data sets involving the primary minima in the pre- satellite era. All data sets produce the lowest value for the 3-year period near 1912; 1890 and 1933 show higher values and the highest values are found for 1954 and 1976.

Figure 11 also describes that the internal consistency between the 4 TSI data sets is slightly higher in comparison to the 4 temperature data sets. This can partly be explained by the fact that 2 of the temperature data sets relate to the temperature of the seawater surface (HadSST3 and GISS SST) and the 2 other temperature data sets relate to the global temperature (HadCRUT4 and GISSTEMP v4). However, it is also noteworthy that the GISS SST temperature data set from NASA in particular describes a relatively large deviation from the other data sets. This implies that the GISS SST is far less consistent with the other 6 data sets than the GISSTEMPv4, while the other seawater surface data set HadSST3 shows a much higher consistency with the other data sets.

Also, the correlation between the GISS SST and GISSTEMP v4 shows a value of 0,942, which is also clearly less consistent compared to the 0,993 correlation between the HadSST3 and the HadCRUT4 data sets. In short, the Hadley Center data sets are clearly more consistent with each other than the two NASA data sets.

Curiously, the GISSTEMP v4 data set shows with 3 of the 4 TSI data sets in figure 11 a correlation with a value barely lower than the value of the correlation with the associated GISS SST data set. From a comparison between all 8 data sets can be concluded from these observations that the GISS SST data set by far shows the greatest deviation. Also striking, the difference between the GISS SST and the two temperature data sets of the Hadley Center (HadCRUT4 and HadSST3) is clearly larger than the mutual differences between various TSI and temperature data sets.

This implies that the profile of the TSI data sets and the temperature data sets are not easily distinguishable from each other. The internal consistency between various combinations of TSI and temperature data sets appears to be even greater than between the two temperature data sets of the Hadley Center and NASA – whereby again the GISS SST in particular manifests as a data set with a strikingly large deviation from the other data sets.

Relevant as well, the LISIRD shows with 6 out of the 7 other data sets a correlation that is higher than the correlation between the average values for the 4 TSI data sets and the average values for the 4 temperature data sets. The GISS SST is the only exception here as well. And it is also striking that the correlation between LISIRD TSI and the average values of the 4 temperature data sets (0,962) is higher than the correlation between the GISS SST and the average values of the 4 temperature data sets (0,919).
The overall picture shows that, in contrast to the exceptional position of the GISS SST data set, the corresponding GISSTEMP v4 data set for the global temperature shows relatively strong correlations with the four TSI data sets (where the correlation values consistently have the p=0,01 significance level). In short, the two global temperature data sets collectively show a stronger pattern of correlations with the TSI data sets than the average of the two seawater surface temperature data sets.

The profile that is described to be present in all 8 data sets can be specified further for the 4 temperature data sets. The overview below shows very small temperature differences between especially the periods around 1912 and 1976 (these two periods involve the most recent bottom phases of the multi-decadal cycle, as described in the August 2019 article). The differences are within a bandwidth of just 0,022 °C. This means that the 4 temperature data sets show more or less the same temperature increase between the two 3-year periods around the years 1912 and 1976. This implies that there is a high consensus found for the size of the temperature rise in the period between those 2 minima; this involves both seawater surface temperature data sets and both global temperature data sets.

1890 (= 1889-1891): HadSST3 +0,215 °C; HadCRUT4 +0,163 °C; GISSTEMP v4 +0,160 °C; GISS SST +0,230 °C;
1912 (= 1911-1913): HadSST3 +0,0 °C; HadCRUT4 +0,0 °C; GISSTEMP v4 +0,0 °C; GISS SST +0,0 °C;
1933 (= 1934-1935): HadSST3 +0,298 °C; HadCRUT4 +0,288 °C; GISSTEMP v4 +0,193 °C; GISS SST +0,133 °C;
1954 (= 1953-1955): HadSST3 +0,440 °C; HadCRUT4 +0,394 °C; GISSTEMP v4 +0,320 °C; GISS SST +0,266 °C;
1976 (= 1975-1977): HadSST3 +0,374 °C; HadCRUT4 +0,354 °C; GISSTEMP v4 +0,360 °C; GISS SST +0,376 °C;
1996 (= 1953-1955): HadSST3 +0,711 °C; HadCRUT4 +0,767 °C; GISSTEMP v4 +0,800 °C; GISS SST +0,683 °C;
2017 (= 2016-2018): HadSST3 +1,029 °C; HadCRUT4 +1,158 °C; GISSTEMP v4 +1,316 °C; GISS SST +1,035 °C.

In the final paragraph (X Discussion & conclusion) is calculated that the warming between the 17th century (when the Maunder minimum occured) and the 3-year period around the year 1912 amounts to approximately 0,5 °C based on the solar sensitivity. This implies that seawater surface temperature has increased by 1,5 °C in total since the 17th century; for the atmosphere the value is 0,15-0,30 °C higher with a value of 1,65-1,80 °C.

Finally, the percentage increase between the 3-year periods around 1996 and 2017 relative to the increase between the 3-year periods around 1976 and 1996 shows a remarkable difference. Because the two data sets from the Hadley Center show a slight delay in the temperature rise, while the two data sets from NASA show a relatively large acceleration.

Overview of the percentage differences during the last 2 solar cycles:

– data sets Hadley Centre: HadSST3 -5,6%; HadCRUT4 -5,3%;
– data sets NASA: GISSTEMP v4 +17,3%; GISS SST +14,7%.

These percentage differences describe a fundamental inconsistency between the two data sets of the Hadley Center and the two data sets of NASA.

VIII – Satellite era: ACRIM-PMOD controversy crucial to impact of the sun

Paragraph VI of the February article describes a controversy over the influence of the sun that started in the 1990s. Two of the three research teams responsible for all facets of TSI satellite measurements since the beginning of satellite measurements in 1978, have publicly distanced themselves from the PMOD method which is part of the IPCC vision in AR5^25-27.

This is a crucial issue, for, figure 8.10 in AR5 ⁹ (= figure 12, see illustration) shows that only the PMOD describes TSI minima to have a negative trend, while both the ACRIM, RIMB and SORCE/TIM describe a positive trend for the minima starting from the 1980s – especially when the 22-year magnetic solar cycle is taken into account. The Belgian RIMB describes a continuous increase from the minimum of the mid- 1980s similar to the LISIRD TSI data set.

The IPCC does recognize in AR5 that for studying long-term changes in the activity of the sun, attention is usually focused on the minima because they are a more “stable” and a more “relevant” indicator for the long-term trend compared to the maxima⁹ However, the IPCC then uses the following reasoning to completely ignore the significance of the minima:

“To avoid trends caused by comparing different portions of the solar cycle, we analyze TSI changes using multi-year running means.”⁹

It is also important that the IPCC in its descriptions frequently refers to the 11-year solar cycle; however, the 22-year magnetic solar cycle is never being mentioned. In the report of the “expert review comments” accompanying the IPCC AR5 report (2013), one expert reviewer referred to the 22-year cycle in passing, but in the IPCC response the phenomenon is not mentioned²⁸.

In addition to the IPCC’s choice not to take into account in its analysis that the minima in particular are indicative of the long-term trend of total solar irradiance, the missing of the 22-year magnetic solar cycle is another fundamental shortcoming is the IPCC framework. For, only the 22-year cycle can serve to identify the relative importance of the primary minima, which is also important for the impact of ‘climate noise’ due to for example the relatively large fluctuations in the UV spectrum of the sun (these fluctuations can be at the order of 100x larger than the fluctuations within the entire spectrum²⁹). This point is also relevant for studying the temperature impact of the ozone depletion, which is known to play a crucial role in blocking UV rays that are harmful to humans.

In paragraph VII of the February article a detailed description is presented for the LISIRD data set. Though the LISIRD is not an “official” TSI, in the view of LASP’s principal investigator Greg Kopp (figure 13) it does present the best values available to the experts; the satellite era data is based on the Community-Consensus TSI Composite³⁰.

Figure 13: LISIRD author Greg Kopp describes the controversy among TSI experts about the impact of the sun in climate change.

IX – Physical substantiation for impact of sun is conceptually more simple than CO2 hypothesis

This paragraph presents a description of the physical mechanisms for the sun (IX-a) and CO2 (IX-b) in the climate system.

• IX-a The physical mechanism behind the influence of the sun on the climate

The sun is known as the driving force behind all climate and weather phenomena. The mechanism is basically easy to understand: Earth surface temperature follows the total solar irradiance during the phase where the primary minima become manifest in the perspective of the 22-year magnetic solar cycle. The 22-year solar cycle arises from a complex of short and long-term cycles (all are based on magnetic activity) which determines both the amount & composition of solar radiation that reaches planet Earth’s atmosphere.

The phase of the primary minima is the most stable and reliable indicator of long term solar activity. The minima arise when the pressure component in the energy waves of the sun is accompanied by a lower frequency³¹, combined with: a higher amplitude + a greater number of active regions³². It is also known that the composition of solar radiation shows large fluctuations, especially at the maxima; this is even accompanied by the formation of two maxima which are spread over submit a period of 2-3 years. The first maximum is characterized by, among other things, a high level of the far UV + many small sunspots & solar flares; the second maximum is characterized by large sunspots as well as large solar flares and auroras.

This explains why ‘climate noise’ arises relatively easily during maxima; Earth’s atmosphere can more easily reflect (through for example Albedo) or absorb (through for example degradation of UV radiation in the ozone layer) the less powerful high-frequency solar energy. The December article describes that the correlation between TSI and temperature is for years near solar minima up to 4x higher than for years near solar maxima.

The correction for the secondary minima is justified on the basis of the magnetism: The switch of the magnetic poles of the sun occurs during the maxima of both the TSI and the sunspot cycle. And the magnetic field of the solar poles reaches the highest value during the TSI minima. In addition, TSI minima are on average accompanied by lower temperature values than the temperatures during the TSI maxima. This implies that the phase that is featured with a strong magnetic field at the solar poles is associated with both a low TSI and a relatively low temperature on Earth. In the perspective of a comparison between minima and maxima, the TSI is more dominant than the magnetic field of the solar poles.
When comparing the primary and secondary TSI minima, on the other hand, an opposite dynamic is found: the magnetic field becomes dominant with regard to temperature. Also, the temperature is structurally higher during the secondary TSI minima than is the case with the primary TSI minima. The WSO measurements for the magnetic field (see figure B1 in the December article) shows that the magnetic field of the solar poles during the secondary TSI minima usually also reached relatively high values relative to the directly surrounding primary TSI minima.
This shows that at the minima the magnetic field becomes more dominant for temperature development; this can be understood easily because the influence of the TSI during the minima is relatively small but the magnetic field is relatively large. Result: a greater magnetic flux is generated, which is accompanied by a higher impact from solar wind. The correction of the secondary dynamics neutralizes the impact of this inverse dynamic; this can be justified on the basis of both the phase differences and the opposite dynamics visible in the data. In numbers, an estimate can also be made with regard to the temperature sensitivity due to the magnetic field of the solar poles, which involves a value of about 0,5 °C per Gauss based on the perspective of the WSO measurements. In climate science, the magnetic field of the solar poles is not (yet) taken into account, nor is the phase difference with the TSI taken into account.

UV solar radiation is the primary source of energy for the atmosphere and it plays a central role in both the vertical, thermal and electronic structure of the atmosphere. It should be noted here that the UV spectrum forms 8% of the total solar spectrum at the top of the atmosphere, but only 3-5% at the surface of planet Earth. In addition, UV radiation plays a crucial role in the ozone cycle of the atmosphere. This is also important because ozone generates heat in the stratosphere through absorption of the sun’s ultraviolet radiation in the higher atmosphere (stratosphere) and by absorbing rising infrared radiation from the lower atmosphere (troposphere).

The sun generates every day about 12% of all ozone in the atmosphere via UV radiation; the damage to the ozone layer ensures that more of the high-energy UV-C and UV-B radiation in particular can penetrate deeper into the atmosphere. Of the 3 possible factors (UV, cosmic rays and/or solar wind) that can play a role in the creation of the reinforcing factor, represents UV a candidate that can potentially have large effects in the circulation of the atmosphere. However, circulation models suggest that the variations are relatively small. Nevertheless, the cooling of the stratosphere that has arisen since the early 1980s logically indicates vertical transport of energy from the higher atmosphere to the lower atmosphere, in which UV plays a key role.

Both the December article and the February article describe patterns which show that the sun also has a clear ‘footprint’ in the ENSO cycle.

The scientific literature describes the temperature difference between a passive and active sun to be in the order of 1 °C on the basis of holes in Earth’s crust or ice caps³³; Svensmark describes a slightly higher value for this: 1-2 °C ³⁴. These values are close to the estimate of 1,1 °C warming caused by the sun since the Maunder minimum (see section VI). But this requires a high reinforcing factor because the fluctuations in the TSI are relatively small in terms of the energy involved. However, the sun’s energy is not just the photons measured through the TSI, because the energy of the sun also reaches Earth through magnetism and energetic particles. Both the impact on the climate and the associated physical mechanism of these 2 additional factors are not included in the view of the IPCC. It became clear in 2019 that for example the power of the magnetic field of the sun has been underestimated until very recently with a factor 10.

The recent extreme solar conditions also manifest in number of sunspots. In 2004 scientists working at the Max Planck institute determined that the number of sunspots in the 2nd half of the 20th century has reached a record level within the perspective of the past 8,000 years³⁵. However, in 2008 the basic value for the TSI was lowered from 1365 W/m2 to 1361 W/m2. Adjustments were subsequently made in 2015 as well with regard to the sunspots; as a result, the exceptional sun conditions of recent decades attract less attention.The video presentation by Prof. dr. Nir Shaviv below describes the continuing influence of the sun on climate in the perspective of the history of the Earth.

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VIDEO: DTU lecture by Prof. dr. Nir Shaviv on the continuing role of the sun in climate change;
starting from 13:30 the video also discusses the perspective shown in figure 14 below.

Figure 14: The sun has a large temperature impact during the 11-year solar cycle; the impact is 5-7 times larger than expected based on total solar irradiance (TSI) only³⁴.

TSI SHOWS THE DIRECT PART OF THE ENERGY OF THE SUN ONLY

At first glance the explanation for the influence of the sun may seem relatively simple; however, especially the aspect of the necessary reinforcing factor concerns a complex matter in terms of the numbers involved. One should be aware that the solar radiation measured at the top of the atmosphere only partly reaches and warms Earth’s surface. Taking into account the spherical shape of Earth + an albedo factor of 30-39% (percentages according to Wikipedia), per square meters only about 15,25-17,5% of TSI reaches Earth’s surface. Svensmark describes for the solar signal force in the ocean system involving the 11-year sunspot cycle a value of 0,2 W/m2³⁴ (see figure 14).
In terms of the energy the presence of a reinforcement mechanism is necessary. Experts in this specific matter assume that for the natural mechanism involved with the amplification of the solar signal there are 3 potential candidates: UV, cosmic rays and/or solar wind. Svensmark and Shaviv describe an (indirect) amplification factor for the 11-year solar cycle signal in the ocean system with an impact in the order of 5 to 7 times larger than the TSI signal itself^34,36. The description of Svensmark (see ‘figure 16’ in figure 14) implies that the 11-year solar cycle TSI amplitude of 0,5 W/m2 (= 5x the value of 0,1 W/m2 at Earth’s surface) at the top the atmosphere (TOA) produces a temperature amplitude of 0,05-0,08 °C.
Svensmark’s descriptions imply an impact of only 0,50-0,80 °C per W/m2 at Earth’s surface; however, the solar sensitivity described in section III and section IV for the minima corresponds to a value of 6,0 °C per W/m2 at Earth’s surface (after using the same multiplication factor of 5x used by Svensmark combined with the value: 1,2 °C per W/m2). This means that the long-term perspective of the minima in temperature development requires a reinforcing factor of 7,5x to 12x on top of the perspective of the solar cycle; this corresponds to an amplification factor of in total 37,5x to 84x compared to the TSI signal in the ocean system at Earth’s surface.
The magnitude of these numbers can be understood via the fact that fluctuations for the TSI as a whole are relatively small with a variation of the order of 0,1%; however, the magnitude of the fluctuations varies greatly. For example: the UV spectrum variation is at the order of 10-20% of total TSI – which is approximately a factor of 100-200 higher compared to the entire solar spectrum²⁹. Svensmark describes that the fluctuations at a wavelength of 120-121 nm are accompanied by changes of the order of 40%, which is 400x higher than the fluctuations of the entire TSI spectrum³⁴. Extremely ultraviolet [EUV] frequencies show variations that can be as high as 6%, which equals to a factor of 30x higher than the 0,02% that applies to visible light. It is also important that EUV radiation consists of high-energy photons, which can have a large impact on the atmosphere.
UV proxies based on algae show that in Antarctica the amount of UV radiation at the end of the 20th century increased by about 50% compared to the previous peaks with values of less than 1.2 Tscy/TCC that have occured halfway the previous millennium. This results in a hockey stick graph that is even steeper than is the case with the sunspots with values of almost 1.8 Tscy/TCC³⁷ (see figure 15).

In short, the dynamics due to the influence of the sun are clearly visible, but numerically the mechanism is not understood. This is probably because the energy of the sun arises from a combination of a direct influence of: (1) photons [UV], combined with indirect influences of: (2) energetic particles [solar wind] and (3) magnetic fields [cosmic rays].
The TSI measures only the direct influence of photons. However, the fluctuations of the sun are based on magnetism; this shows instantly that the impact of solar magnetism (combined with the influence of cosmic rays) can logically be at least as large in the perspective of dynamics that result from cosmic constellations. The following quotation from the work of van Geel & Ziegler ³⁸provides an illustrative indication for this influence:

“Measurements show that between 1964 and the 1990s the total magnetic flux leaving the Sun (solar wind) increased by a factor of 1.4 with surrogate measurements indicating that it increased since the Little Ice Age by 350%, while the GCR flux decreased by about 50% to reach a low in the 1990s.”

Figure 15: UV proxies based on scytonemine pigment formed by bacteria in algae in Antarctica (top part) show very high levels at the end of the 20th century (~1,8 Tscy/TCC), which results in a likewise ‘hockey stick’ shape graph that is also present for the perspective of the sun spots (bottom part); for the UV proxies the shape is even steeper for the sunspots³⁷. The regional decrease of ozone from 350 UD to 50 DU in the period 1960-2000 is shown in a separate box.

• IX-b The physical mechanism behind the influence of CO2 on the climate

Since the start of the industrial revolution, global CO2 concentration in the atmosphere has increased by about 50% from about 277 ppm around the year 1700 to values above 415 ppm in mid-April 2020. In a timespan of 320 years the amount of CO2 has increased from nearly 3 particles to over 4 particles per 10.000 particles in the atmosphere.

NASA describes the temperature impact of the total greenhouse effect to be 33 °C, including a cooling effect resulting from clouds of -5 °C³⁹. According the IPCC, the impact of clouds corresponds to a radiative forcing of -13 W/m2⁴⁰. According logics this implicates that all greenhouse gases together are responsible for a temperature effect of 38 °C (without the impact of clouds). The assumption is made that 9-26% of this temperature effect is generated by CO2; this implies an overall temperature effect for CO2 at the order of 3,42-9,88 °C (without considering a possible logarithmic effect that will depress the impact). A 50% increase in atmospheric CO2 should therefore logically result in a warming of 1,71-4,94 °C according this view. The IPCC hereby assumes that global warming since the beginning of the industrial revolution can be attributed largely to greenhouse gases. AR5 describes that it is thought that the temperature rise since the beginning of the industrial revolution may even be entirely due to greenhouse gases. It is argued that the greenhouse effect of CO2 is enhanced by feedback systems dominated by positive feedback; this also explains why the temperature impact of the increase in CO2 is higher than the 1,1 °C which has been found under laboratory conditions for a doubling of CO2. Since the 1990s the IPCC has been talking about a ‘climate sensitivity’ with a likely bandwidth of 1,5-4,5 °C, which refers to the temperature effect of a doubling of CO2.

However, this description is based almost entirely on a theoretical view. For, it was only in 2015 that direct empirical evidence was presented by researchers for the first time for the existence of the mechanism within the climate system described by the greenhouse theory²⁰. Those researchers have described in 2015 that CO2 has some influence (~10% of the trend) on the ‘back radiation’ of long wave (infrared) radiation from the atmosphere.

A fundamental problem in this view involves the fact that for every particle of CO2 in the atmosphere there are about 62,5 particles of the most dominant greenhouse gas available, namely: water vapor [H2O] (= ~2% for the first 15,5 miles; though there are other sources which describe 0,4% only for the full atmosphere). In other words, in addition to the 4 particles of CO2 per 10,000 particles in the atmosphere, there are approximately 200/250 particles of water vapor present in the climate system. In addition, approximately about the same amount of radiative forcing is attributed to 1 molecule of CO2 and 1 molecule of water vapor [H2O]. Logically, we can deduce from this that, in theory, water vapor can be held largely (possibly more than 98%) responsible for the greenhouse effect of 38 °C on the basis of the quantity compared to the other greenhouse gases. This perspective is confirmed by the magnitude of the temperature effect due to a doubling of CO2 under laboratory conditions, because the temperature rise of 1,1 C involved implies a contribution of less than 3% compared to the total greenhouse effect of 38 °C (without the impact of clouds). This percentage is also significantly lower than the CO2 contribution of 9-26% within the framework of the IPCC based on the greenhouse theory. The impact of CO2 compared to the other greenhouse gases (apart from the impact of water vapor) is estimated in AR5 at approximately 70%; for methane one thinks of a contribution of 4-9% and for ozone one thinks of a contribution of 3-7%. The latter percentages are representative of the so-called ‘consensus’.

The view which attributes a lower impact for CO2 as a greenhouse gas on the basis of the quantitative ratios is consistent with among other things: Henry’s law + the fact that CO2 follows temperature in the natural cycles and not the other way around. Henry’s law describes that the increase of CO2 concentration in the atmosphere is partly due to the rise in temperature of the seawater surface. Based on expert judgements the rise in temperature accounts for about 15% of the rise in CO2 since the start of the industrial revolution. At a temperature rise of 1 degree Celsius, approximately 3% less CO2 can be dissolved in the ocean water surface. Fundamentally, this shows that a significant part of the rise in CO2 logically results from the rise in temperature and not the other way around. Moreover, the numerical analysis in this article shows that for the period up to and including the 1980s there is no room for a significant contribution of CO2, nor in the period after the 1980s; the contribution of ozone in the greenhouse effect (via the damage to the ozone layer) is indirectly considerably larger compared to CO2.

In short, both the perspective of the sun and CO2 show inconsistencies involving the magnitude of the ratios. For the sun this concerns mainly a reinforcing factor of 37,5 to 84; for the greenhouse theory the availability of an average of 62,5 particles of water vapor (or ~80% of this amount) compared to 1 particle of CO2 in the atmosphere represents a comparable ratio. Both factors are difficult to investigate empirically in the climate system. Especially because water vapor particles within the climate system manifest themselves in various states which each have a variable impact. The results under laboratory conditions for a doubling of CO2 indicate that the much greater availability of water vapor can potentially be bridged.
However, only the perspective of the CO2 theory includes fundamental inconsistencies which indicate that the impact of CO2 within the climate system is considerably more complex than what has been assumed under laboratory conditions. In addition, the climate system largely consists of negative feedback systems. The inconsistencies with regard to CO2 (involving Henry’s law + the fact that CO2 is the temperature within the natural cycles) indicate that negative feedback systems are dominant inside the climate system, also with regard to the impact of CO2. Within the framework of the IPCC, it is assumed that positive feedback systems are responsible for an enhanced greenhouse effect. The PMOD-ACRIM controversy shows that the role of the sun became nihilized with arbitrary arguments. This is done on the basis of assumptions and adjustments that have been identified by several research teams at the highest level more than 2 decades ago; these very experienced researchers speak of a method that is not representative of what satellite data actually describe:

“Several TSI satellite composites have been proposed: ACRIM, PMOD, RMIB and those suggested by Scafetta and Dudok de Wit et al. Although these composites use different sets of TSI satellite records and merging methodologies, they are relatively equivalent since about 1992, the beginning of the ACRIM2 record, because they are all based on high-quality TSI observations. Yet, as clarified below, PMOD used their own modified versions of the original results compiled by the experiment teams for the SMM/ACRIM1, UARS/ACRIM2 and Nimbus7/ERB records to cover the period 1978-1992 and, therefore, its proposed record cannot be considered a real TSI satellite composite but a model construction. The ACRIM-PMOD controversy is about the scientific legitimacy of such modifications.“⁴¹

X – Discussion & conclusion

This article demonstrates that 93% of the variance in seawater surface temperature [HadSST3] is explained by total solar irradiance [LISIRD], based on 3-year solar minima periods which cover the time span starting from the last decade of the 19th century up to and including the mid-1980s. This includes a correction aimed at the secondary minima. Also, for the entire period since the 1890 minimum, 96% of the variance is explained by the combination of total solar irradiance and decrease in ozone.

Also has been described that CO2, AOD and ENSO do not generate any significant value for the explained variance. This implies that the strong statistical relationship between CO2 and temperature represents a spurious relationship that is fully explained by the sun until the mid-1980s. During the transition between the 1985 and 1996 minima the emergence of the ozone problem has temporarily supported this sham relation. Ozone layer depletion due to the use of the artificial CFCs (not due to production of the by origin natural CO2) resulted in more UV solar radiation reaching Earth’s surface. During the transition between the 1985 and 1996 minima the total solar irradiance shows a slight decrease, but subsequently it shows a continued rise between 1996 and 2008 and between 2008 and 2017.

The spurious relation between CO2 and temperature manifests itself in the perspective of both the primary and secondary minima, as well as in the combination of both minima series. Only the correlations between seawater surface temperature and total solar irradiance show a stable relationship for both the period prior to the ozone problem and the entire period since 1880. After a correction aimed at the 3-year average TSI secondary minima (+0,123 W/m2), the magnitude of the correlation between seawater surface temperature and TSI for both periods is higher than the correlation between seawater surface temperature and CO2.

The relation between TSI [TOA] and sea surface temperature shows a solar sensitivity of 1,2 °C per W/m2 (involving just the TSI values above 1360 W/m2) for the 3-year average at the primary minima (+ as well for the secondary minima after applying the correction). This relationship explains also the entire warming between the 3-year periods near the 1996 and 2017 minima. The solar sensitivity also implies that the sun can be taken responsible for approximately 1,1 °C of the warming that became manifest since the Maunder minimum at the end of The 17th century, based on an interim TSI increase of 0,941 W/m2 up to including the solar minimum year 2017.

Paragraph VI in the December article describes a temperature trend of +0,0316 °C per decade for the period 1810-1902 based on the PAGES 2k proxies. Since the year 1902 is a secondary minimum and the year 1810 is a primary minimum (with the succession of 2 primary minima in a row in the first decades of the 18th century taken into account), the correction should also be applied to the secondary minimum year 1802 in order to make a comparison with the PAGES 2k proxies. The 3-year TSI average around the years 1810 and 1902 yields an increase of 0,052 W/m2. Combining this value with the correction aimed at the secondary minima (+0.123 W/m2) this results in a total increase of +0,175 W/m2, which produces a value of +0,21 C via the solar sensitivity of 1,2 °C per W/m2. The calculated temperature difference based on the sun is therefore only about 0,1 °C smaller for the period 1810-1902 compared to the temperature trend found for the same period based on the PAGES 2k proxies.

A similar calculation has been made for the warming between the Maunder minimum and the 3-year period around the year 1810. The PAGES 2k proxies show a development with a slightly lower temperature near the Maunder minimum compared to the year 1810. The total solar irradiance suggests for the warming between the Maunder minimum and the 3-year period around the year 1810 a value of 0,40 °C; this results in a temperature increase of in total 0,61 °C for the period between the Maunder minimum and the 3-year period around 1902.
A control calculation involving the temperature difference between the Maunder minimum and the 3-year period around the primary minimum year 1912 (which has provided a stable reference point in paragraph VII compared to the period around 1976) yields a temperature rise of 0,51 °C. So, the results are consistent for the PAGES 2k proxies and the TSI; both methods produce a small temperature rise for both the 18th century and the 19th century. Combined with the overview presented in paragraph VI concerning the temperature development relative to 1912, one can deduce that the warming of the seawater surface temperature since the Maunder has been more than 1,5 °C. Meanwhile, the global temperature has risen about 0,15-0,30 °C faster than the seawater surface: the HadCRUT4 data set produces a value just over 1,65 °C and the GISSTEMPv4 data set produces a value just over 1,80 °C.

Because of phase differences between the sun and the ocean system (for example, the impact of ENSO is delayed with up to around 6 months) the data based on 3-year periods around the solar minima is likely more stable and a more reliable compared to data on based on the individual minimum years. Apparently, the impact of ‘climate noise’ has been reduced to a very low level. Also, the first 2 decades of the 21st century are characterized by low volcanism; therefore this might also explain a (small) part of the temperature rise since the 17th century; however, this involves likely not much more than a few hundredths of a degree Celsius.

Additionally, 55% of the HadSST3 warming between the 3-year periods near the 1976 and 2017 minima is explained by the sun, as shown in figure 10B. The ozone problem has ensured that more solar radiation has been able to reach Earth’s surface; this largely explains the rest of the interim warming during this period.

Recently, several claims have been presented in the scientific literature by researchers who are using different research approaches in order to conclude that CFCs have had a temporary but nevertheless very significant impact in the development of the relatively rapid warming since the 1970s. In 2013 Prof. dr. Qing-Bin Lu of the University of Waterloo (Canada) claimed that CFCs combined with cosmic rays (under the influence of the sun’s magnetic field) are the main cause of the warming since 1850⁴². Also, in January 2020 a group of researchers from the US, Canada and Switzerland reported that CFCs explain about 1/3 of the warming + about half of warming at the North Pole between 1955 and 2005⁴³. Since the year 2009, geophysicist Peter Langdon Ward has presented research centralizing the role of ozone in the climate.

With the use of 4 TSI data sets + 4 temperature data sets has been shown that all data sets show the same characteristic pattern at the 3-year average around the primary minima for the period 1890 to 1976. The lowest value within this pattern always manifests at the 3-year average near the 1912 minimum; the 1890 and 1933 minima show markedly higher values and the 1954 and 1976 minima show even higher values. Also relevant, the 4 TSI data sets do not clearly differ from the 4 temperature data sets; the variance within both groups of data sets is clearly greater than between the two data set groups. The two groups show a correlation with a value of 0,928 [p=0,000] based on the mean values.
For 2 out of 4 TSI data sets (LISIRD & IPCC AR5) as well as for both temperature data sets presented by the Hadley Center (HadSST3 and HadCRUT4), the 5 minimum values based on the 3-year average show exactly the same sequence. The most differentiating data set concerns the GISS SST data set.
Also striking, the perspective of the primary minima shows for both data sets of the Hadley Center a slight delay in the temperature development during the last two full solar cycles (1976-1996 and 1996-2017) while both NASA data sets show a relatively strong acceleration.
The highest correlation found in this perspective with a combination of a TSI data set and a temperature data set concerns the couple that is has produced the main results in this study, namely: the combination of the LISIRD and the HadSST3.

A description has been presented for the physical mechanism that explains the influence of the sun on the climate. The scientific literature presents detailed descriptions for three candidates (UV, cosmic rays and/or solar wind) involved with the emergence of the reinforcing mechanism necessary to explain the temperature effect found during the 11-year solar cycle. In this study it has become clear that an even greater reinforcing mechanism is active in the course of the minima between the 3-year periods around the 1890 and 2017 minima – which involves a period of 130 years in total.

This study has identified some crucial shortcomings in the IPCC’s framework. On the one hand, these shortcomings explain how the alleged “not understood” link⁴⁴ between solar activity and Earth’s climate has become manifest, and on the other hand these points provide tools serving for a better understanding of the relationship between sun & temperature

• 1 – The IPCC analysis does not take into account the 22-year magnetic solar cycle
• 2 – The IPCC analysis does not sufficiently take into account the significance of solar minima
• 3 – The IPCC analysis does not take into account the influence of the magnetic field of the sun (especially important for the minima)
• 4 – The IPCC analysis builds its conclusion regarding the sun on the PMOD data set, despite the fact that various TSI expert teams perceive the PMOD to be not representative for the satellite measurements
• 5 – The IPCC assumes the temperature effect of the 11-year sunspot cycle is only 0,06 °C (based on CMIP5 climate models); however, Wikipedia describes the impact to be 2-4 times higher, namely: 0,18 +/- 0,06 °C, based on Camp & Tung (2007)⁴⁵
• 6 – The IPCC does not take into account that within the natural cycles CO2 follows the temperature and not the other way around
• 7 – The IPCC does not take into account Henry’s law (~ 15% of the CO2 rise is due to the temperature rise; this results in a theoretical inconsistency with the theory that CO2 is largely responsible for the temperature rise since 1850)
• 8 – With regard to long-term trends, the IPCC does not take into account the fundamental difference before and after the manifestation of the ozone problem (+ the emergence of the inverse relationship between temperature development in the lower and higher atmosphere)
• 9 – The IPCC puts too much emphasis on short-term trends: in the study of recent trends in global temperature, the influence of the multi-decadal natural cycle must be taken into account (globally this is mainly caused by the sun; cycles within the ocean system play a role locally).

These points show that the IPCC describes an incomplete unbalanced view with the role of the sun structurally being nihilized, combined with a tendency to attribute changes in the climate system to anthropogenic influences. Inconsistencies in the statistical relationship between temperature development and CO2 are structurally being ignored. Illustrative for this is the research showing that in the year 2015 researchers reported that they had found the first piece of empirical evidence for the existence of any influence of CO2 on the impact (just ~10% of the trend) of the radiation of the atmosphere based on data over a period of only 11 years²⁰.

The inverse relationship between temperature development in the lower atmosphere (troposphere) and the higher atmosphere (stratosphere) only started emerging in the early 1980s; this development coincides with the period in which the ozone layer became depleted. The IPCC assumes that CO2 can be held responsible for this. However, the IPCC does not make any demands with regard to consistent trends in its models for the periods before and after this inverse relationship has arisen. This study describes that the total solar irradiance around the minima shows consistent correlations with the temperature development for almost all periods starting from the year 1880, with exception to the transition between the minima around the years 1985 and 1996 – note: ozone level reached an absolute low in the year 1994. However, this does not imply that the strong relationship between sun and temperature is limited to the minima; for, there are several research approaches known that can demonstrate the strong relationship between sun and temperature⁴⁶.

Based on the analysis above, it may be concluded that the temperature development is largely determined by the sun combined with the antropogenic influence on the ozone layer. Based on the decrease of the impuls momentum in the movement of the sun around the barycenter (which correlates with the power of the sun), a temperature impact at the order of -0,1 °C for the coming 3 decades can be taken into account – in accordance with the description in the work of Scafetta described in the December article. In addition, based on the expected recovery of the ozone layer in the next 3 decades, the possibility of an impact at the order of -0,2 °C can also be taken into account. Logically, both effects can potentially lead to a temperature impact of in total -0,3 °C towards the year 2050. This is in line with the decrease of several hundredths of a degree Celsius described in the supplementary appendix in the article of June 2019 that can be foreseen based on an analysis focused on the multi-decadal climate cycle. That earlier estimate was made without being aware that the sun is largely in control of the climate cycle.

Quick summary: temperature follows the total solar irradiance (TSI) during the minima up to and including the mid-1980s; subsequently, ozone depletion disrupts this relationship, especially in the period between 1984-86 and 1995-97.

* A word of thanks to André Bijkerk for his editorial advices on the series of 5 articles (all devoted to the influence of natural cycles on the climate) presented since June 2019; André wrote several articles about the influence of the sun via cloud cover (this topic is also discussed in Prof. Shaviv’s video presentation in section IX-a), see: HERE and HERE.

Figure A: solar flare arising from solar magnetic activity.

VIDEO: NASA description for the solar cycle.

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The solar cycle is accompanied by a cosmic movement of the sun around the barycenter;
the mechanism is described by detail in the appendix of the December article.

References:

1 – Artikel in Volkskrant: Warmt CO2 het klimaat echt wel op? (en nog drie knellende vragen die klimaatsceptici vaak stellen) [Article in Volkskrant: ‘Does CO2 really heat up the climate? (and three more pressing questions climate skeptics often ask)’] (Feb 8, 2020).
2 – Artikel in Trouw: De zon is de meest nabije ster, maar we begrijpen er nog niet veel van [Trouw article: ‘The Sun is the closest star, but we don’t understand much yet] (Dec 15, 2019).
3 – The Sun and the Earth’s Climate: Solar signals in surface climate – J.D. Haigh (October 2007).
4 – Met Office Hadley Centre observations datasets: HadSST3.1.1.0 Data [annual globe] (2019).
5 – LISIRD – Historical Total Solar Irradiance Reconstruction, Time Series (2018); author: Greg Kopp is lead researcher of SORCE/TIM project by LASP (biography).
6 – NASA: Stratospheric Aerosol Optical Thickness.
7 – Ensembloe Oceanic Nino Index (ENS ONI).
8 – Ozone Hole Area – NASA.
9 – IPCC, 2013: Climate Change 2013: The Physical Science Basis – 8 Anthropogenic and Natural Radiative Forcing – page 689 (chapter 8): “The year 1750, which is used as the preindustrial reference for estimating RF, corresponds to a maximum of the 11-year SC. Trend analysis are usually performed over the minima of the solar cycles that are more stable. … Maxima to maxima RF give a higher estimate than minima to minima RF, but the latter is more relevant for changes in solar activity.”
10 – 2018 Continues Record Global Ocean Warming – L. Cheng et al. (maart 2019) – Quote: “The vast majority of global warming heat ends up deposited in the world’s oceans, and ocean heat content (OHC) change is one of the best – if not the best – metric for climate change (Cheng et al., 2019)”.
11 – WMO: Key Climate Change Indicators from the Ocean (2017 update).
12 – Copernicus (EU): ‘INSIGHTS INTO THE ROLE OF THE OCEANS IN THE EARTH ENERGY BUDGET’ – K. von Schuckman (November 2017) – Citaat sheet 10: “The Earth energy imbalance can best be estimated from changes in ocean heat content, complemented by radiation measurements from space (von Schuckmann et al., 2016, NCC)”.
13 – The unstable CO2 feedback cycle on ocean planets – D. Kitzmann et al. (August 2015).
14 – Greenhouse gas growth rates – J. Hansen & M. Sato (September 2004); source describes 14% for period 1850-2003, adjusted for 1850-2018 the percentage increases to 15%.
15 – Met Office Hadley Centre observations datasets: HadCRUT4 Data: download [global (NH+SH)/2] (2019)
16 – The Gnevyshev-Ohl Rule and Its Violations – N.V. Zolotova (February 2015).
17 – Gnevyshev-Ohl rule for strong solar proton events – M. Ogurtsov & M. Londholm (March 2016).
18 – The Gnevyshev-Ohl Rule for Physical Parameters of the Solar Magnetic Field: The 400-Year Interval – Yu.A. Nagovitsyn et. al. (October 2008).
19 – IPCC, 2013: Figure SPM.5
20 – Observational determination of surface radiative forcing by CO2 from 2000 to 2010 – D.R. Feldman, et al. (2015).
21 – Seasonal and Diurnal CO2 Patterns at Diekirch, LU 2003 – 2005 – F. Massen et al. (March 2007); section 4.1 & 4.3.
22 – Breakpoint lead-lag analysis of the last deglacial climate change and atmospheric CO2 concentration on global and hemispheric scales – Zhi Liu et al. (May 2018).
23 – Stratospheric ozone concentration – H. Ritchie & M. Roser (June 2018).
24 – Oscillations of the baseline of solar magnetic field and solar irradiance on a millennial timescale – V. Zharkova, et al. (June 2019).
25 – Astronomy and the Climate Crisis – A. Cooke (January 2012); pages 116-119.
26 – ACRIM3 and the Total Solar Irradiance database – R.C. Willson (February 2014).
27 – Modeling Quiet Solar Luminosity Variability from TSI Satellite Measurements and Proxy Models during 1980-2018 – N. Scafetta, et al. (November 2019).
28 – Expert Review Comments on the IPCC WGI AR5 First Order Draft — Chapter 8 (2013) – comment 8-745.
29 – A solar irradiance climate data record – O. Coddington et al. (July 2016).
30 – Solar Irradiance Variability: Comparisons of Models and Measurements – O. Coddington et al. (December 2019); figure 6a.
31 – Background solar irradiance spectrum at high and low phases of the solar activity cycle – V. Ramió et al. (September 2002).
32 – Solar p modes in 10 years of the IRIS network – D. Salabert et al. (2004)
33 – The Role of the Solar Forcing in the 20th century climate change – N.J. Shaviv (2012)
34 – FORCE MAJEURE The Sun’s Role in Climate Change – H. Svensmark (2019).
35 – Max Planck Institute: The Sun is more active now than over the last 8000 years (2004)
36 – Using the oceans as a calorimeter to quantify the solar radiative forcing – N. Shaviv (2008).
37 – An 800-year ultraviolet radiation record inferred from sedimentary pigments in the Ross Sea area, East Antarctica (July 2015)
38 – IPCC underestimate the sun’s role in climate change – B. van Geel & P.A. Ziegler (2013)
39 – NASA – ISCCP: International Satellite Cloud Climatology Project (2008); quotation: “The net effect of clouds on the climate today is to cool the surface by about 5°C (9°F).”.
40 – IPCC First Assessment Report.1990. UK: Cambridge University Press.table 3.1 (1990); quotation: “Clouds increase the global reflection of solar radiation from 15% to 30%, reducing the amount of solar radiation absorbed by the Earth by about 44 W/m². This cooling is offset somewhat by the greenhouse effect of clouds which reduces the outgoing longwave radiation by about 31 W/m². Thus the net cloud forcing of the radiation budget is a loss of about 13 W/m².”.
41 – Modeling Quiet Solar Luminosity Variability from TSI Satellite Measurements and Proxy Models during 1980-2018 – N. Scafetta, et al. (November 2019).
42 – Cosmic-Ray-Driven Reaction and Greenhouse Effect of Halogenated Molecules: Culprits for Atmospheric Ozone Depletion and Global Climate Change – Q.-B. Lu (May 2013).
43 – Substantial twentieth-century Arctic warming caused by ozone-depleting substances – L.-M. Polvani et al. (January 2020).
44 – Klimaat brochure ‘Klimaatverandering, Wetenschap en Debat’ – Koninklijke Nederlandse Academie van Wetenschappen [‘Climate change, Science & Debat’ – Royal Dutch Academie of Sciences] (2011).
45 – Surface warming by the solar cycle as revealed by the composite mean difference projection – C.D. Camp & K. Kit Tung (July 2007).
46 – Re-evaluating the role of solar variability on Northern Hemisphere temperature trends since the 19th century – W. Soon et al. (August 2015).

By Andre Bijkerk|2020-05-20T23:05:08+02:0020 May 2020|99 Comments

99 Comments

Bas Post 21 May 2020 at 10:27

Martijn published this article some weeks ago on a Dutch-language blog and also sent it to a climate scientist at the KNMI (Royal Dutch Metereological Institute).
After a thorough analysis of the article by Martijn van Mensvoort, I came to the conclusion that this is a very confusing gishgallop full of mathematical, statistical, physical and logical errors. The same conclusion was drawn by others who responded on the blog (“painfull”, “absurd”,…) as well as the scientist from KNMI (“most bizarre”, “proven errors”, “misunderstanding fundamental concepts”, “errors in the methodology used, opportunistic selection of data and the lack of substantiation”,…). I had several mail-exchanges with him, wher he failed to address the main mistakes he makes, and always diverted towards minor points or irrelevant distractions. He eventually stopped replying to my questions for clarification.

What is he trying to prove? That the increase in temperature in recent years can be fully explained by solar cycles and the ozone hole. According to him, there is no need to claim that CO2 is the cause of the current warming. Here I give a (non-exhaustive) list of errors I already found in the article, concentrating mainly on the errors around figure 10:

Physics:
– Martijn does not give any sound scientific explanation why he only uses the years around the minimums in his analyzes. The sun shines not only at the time of the minima, but every day of the year and every day of the entire cycle. Moreover, the TSI is higher during the other years, so the possible impact on temperature is higher. He does not present any scientific argument for not taking into account the TSI of all those other years, although they also contribute to the energy balance of the atmosphere and oceans over the years.
– In figure 10C he makes an adjustment with 0.266 ° C. He does not provide the physical justification for this, except that this is “due to the ozone problem”. In a reaction on the Dutch blog, he gives an confusing answer on why he believes this is due to ozon, and how he claculates this 0.266. Between 1984-86 and 1995-97, “something” happened for which he thinks he should compensate, and he comes up with a formula in his response, explaining “I have deliberately chosen not to present a detailed description because this nothing to add ”. Yes Martijn, if you present results, the explanation of what you do exactly, why you do it, the physical justification, and so on, just adds very much! By the way, a very important phenomenon that occurred at the time is that the CO2 has started to rise quickly! But that this had an impact on the temperature, you apparently do not want to include that in your model. Simply claiming it is due to ozon, is not a justification, it is only an excuse to do what you want to do!
– Martijn makes an adjustment with +0.123 of the TSI values for the secondary minima. The “explanation” that he gives for this is that this results in a better correlation. That’s not a physical explanation! This is simply falsifying the data so that you get a desired result. He does have a vague explanation as to why secondary minima would be different from primary minima, but the TSI at the time is what it is. Is it lower than you like? Then that is a fact. But you shouldn’t just add something because you do not like the fact!
– He obtains the number 1.26 by using only the minima from the years 1890 to 1985 (information obtained by email). The LSIRID values for the secondary minima have also been adjusted with the value 0.123. Why only that period was used for this calculation, he gives no scientifically sound explanation for that either. When I use the years 1850 to 1985 (from his own Excel, average of 3 years and with 0.123 added to 1879 and 1856), I do not get 1.26 but 1.66.
– Martijn believes that there is a difference in the impact of TSI on temperature between primary and secondary minima. He cannot explain the physical principle behind it, except that it must have something the do with a reversal of magnetic poles. But if there really was an impact from the phase of the 22-year cycle, then this also applies to every moment of the phase, and then he should not just eliminate all those other years. His argument therefore contains a contradiction.
– The source of the data for the “ozone hole” also provides the data for the minimum ozone concentrations in the Southern Hemisphere. It is unclear why he uses he size of the ozonhole as data, rather than that concentration. Or better yet, the global concentration. The concentration of the ozone has a more direct impact on the energy balance than the ozone hole.

Mathematical / Statistical:
– Martijn gives the LISIRD values for the TSI. In his Excel table he gives values for this from the year 1850 onwards. But in his analyzes he only uses the values starting at the solar minimum of 1890. I suspect he does that because the value of the solar minimum of 1867 is exceptionally high, and that fits not really with his beliefs, because the temperature is still very low during that period. As an excuse, he uses the statement “The GISS data set that van Oldenborgh uses to study the relationship between CO2 and temperature begins in the year 1880; that is why this study also focuses entirely on the period from 1880 onwards. ”. But he doesn’t use CO2 or GISS in his analyzes at all, so that’s just a false argument for eliminating the data for 1890.
– Martijn thinks he sees a difference between primary and secondary minima in the solar cycles. He compensates for this with a value of 0.123. But how was the 0.123 calculated? He does not describe that either. I found out via email that he did this by trying “numbers” manually, until he got a “desired” result: he took the value that gave him the highest correlation as the “correct” value. That is not correct statistical analysis. If you want an adjustment for those secondary minima, you determine that by using multiple regression or another statistical method (that it is physically justified, that is another point, here it is about mathematics). That gives me a value of 0.178, not 0.123.
– For the size of the ozone hole, it shows in its Excel table for all years before 1979 the value “0” (zero). That is not correct. The value is unknown. So you cannot write that it is “0” either. You have to leave those cells empty (NB: this is a very minor issue, but this is the one tht Martijn latched on to critisise me, rather than all the other points I mentioned!)
– Why is the regression analysis that calculates the number 1.26 based on the 3-year average around minima? Why is this value not calculated on the years of the minima alone, or why is the regression not included each year separately? Starting from averages is not statistically the optimal approach if you do not explain why you do this.

Logical errors:
– As an argument for only using the minimums, Martijn refered in his Dutch text to a sentence in an IPCC report. He therefore relies on the authority of the IPCC. But on the other hand, he does not want to accept the same authority, because he believes that he sees “crucial shortcomings in the IPCC’s framework of thought”. So it is contradictory. Moreover, he misinterpreted that sentence in the IPCC report. He has now apparently accepted that he was wrong, because he no longer mentions this in het English text. That creates a new problem: he has no justiifcaton whatsoever in his text why he uses only the data of the minima and why he ignores all other years!
– He does his analysis between temperature and TSI for the period from 1880, although he has data in his Excel from 1850. He does this because “The GISS data set (chosen by van Oldenborgh in order to study the relationship between CO2 and temperature) starts in 1880. For this reason this study is focused on the period starting from the year 1880 as well”. But in this analysis, he doesn’t use GISS or CO2, so that’s a faulty argument. Perhaps he was looking for an excuse to be able to eliminate the data from 1867, because the LSIRID is very high there, and therefore does not fit his vision.
– Martijn concludes here that “CO2, AOD and ENSO do not generate any significant value for the explained variance.” But in an earlier article he wrote that the best results are obtained “when the AOD value becomes relatively high granted ”http://klimaatcycle.nl/klimaat/1890-1976-zon-toont-perfecte-correlatie-met-temperature-influence-CO2-blijkt-nihil.htm. So he also contradicts himself here, but does not go into this. Which of his two conclusions should actually be accepted? Or neither one of the two?
– Martijn claims that there is no need for CO2 to explain the rise in temperature. In doing so, he ignores the scientific knowledge and insights of the past decades. He thinks he knows better than hundreds of eminent climate researchers. Putting existing knowledge aside is a big logical error.
– He started his article by showing that there is a good correlation between CO2 and temperature, without having to make all kinds of dubious “corrections” and without having to ignore about 75% of the data. But he does not want to draw a conclusion from that good correlation and from all that scientific knowledge. He prefers to write a whole section with all kinds of things that you find on blogs, etc., but not in the scientific literature.
– Martijn ignores data that he does not like. In the LISIRD data (which is a mixed bag of all kinds of proxies), the TSI minima of 2008 and 2017 are higher than the previous ones. But in the satellite data of TSI (ACRIM, PMOD, …) these minima are much lower, which puts the validity of the LISIRD proxy into question. His argument that the current rise in temperature is due to the solar radiation is completely shattered by this decrease in TSI. The difference between LSIRID and the satellite data has nothing to do with the “ACRM-PMOD controversy” that he refers to, because the two satellite data sets both show a lower trend in this respect, which you do not see in LSIRID. That controversy is only a faulty argument that he brings in to confuse the reader.
– last but not least: Martijn refers to the figure SPM.5 of the IPCC report of 2013 to justify that ozon has an impact on climate. Bt that figure als shows that the impact of CO2 and CH4 is much higher. This he ignores completely. You cannot cherrypick what fits your beliefs and ignore what is right next to it, simply because it proves you wrong!

These are the points I presented to him. Most of them, he has not addressed properly. He still has no explanation why he ignores 75% of teh data. He has no explanation why he ignores that the TSI has been decreasing and the temperature rising. He cannot explain why he refers to an IPCC-figure, but then ignores most of the data in it.

This article is not “sciencetalk”. It is pseudoscientific gishgallop to try to justify an ABC-theory (“Anything-but-CO2-theory”). A theory that does not explain the facts!
- Martijn van Mensvoort 21 May 2020 at 16:36
  
  Thanks for your efforts Bas.
  
  I’ll limit my response to your first and last pont:
  
  – Regarding your very first argument under your header ‘physics’:
  
  “Martijn does not give any sound scientific explanation why he only uses the years around the minimums in his analyzes. The sun shines not only at the time of the minima, but every day of the year and every day of the entire cycle.”
  
  Source 9 in the article shows that the IPCC actually confirms explicit that the solar minima are “more relevant” in the perspective of the studying radiative forcing [= RF] changes in solar activity, see:
  
  “9 – IPCC, 2013: Climate Change 2013: The Physical Science Basis – 8 Anthropogenic and Natural Radiative Forcing – pagina 689 (hoofdstuk 8): “The year 1750, which is used as the preindustrial reference for estimating RF, corresponds to a maximum of the 11-year SC. Trend analysis are usually performed over the minima of the solar cycles that are more stable. … Maxima to maxima RF give a higher estimate than minima to minima RF, but the latter is more relevant for changes in solar activity.””
  
  NOTE: In my preceding article (which I presented in february 2020) I have also referred to table 8.SM.4 on page 8-SM10, which shows that the IPCC has made an analysis focussed on just the minima because they are actually very aware that an analysis of solar radiative forcing is only possible for similar phases in the solar cycle, see:
  
  https://www.ipcc.ch/site/assets/uploads/2018/07/WGI_AR5.Chap_.8_SM.pdf
  
  – Regarding your final argument involving figure SPM.5:
  
  “– last but not least: Martijn refers to the figure SPM.5 of the IPCC report of 2013 to justify that ozon has an impact on climate. Bt that figure als shows that the impact of CO2 and CH4 is much higher. This he ignores completely. You cannot cherrypick what fits your beliefs and ignore what is right next to it, simply because it proves you wrong!”
  
  I referred to that figure only in order to make the reader aware that ozon does play a significant part in the IPCC framework; I have described this explicit in the 2nd final alinea in paragraph I as follows:
  
  “Figure SPM.5 in IPCC AR5 confirms that ozone [O3] can be held responsible for a significant contribution to the warming of the atmosphere. For, O3 plays a role in the radiative forcing of no less than 5 anthropogenic emitters. 4 Out of 5 factors provide a net contribution to the increase in radiative forcing; the largest contribution is associated with methane [CH4].”
  
  Therefore your use of ‘logics’ does not make much sense to me as you are implicit suggesting that I am not allowed to refer to the IPCC report unless I accept everything they write – which is unrealistic in the perspective of how science works.
  
  For me it is quite obvious that you have misperceived probably both the nature & objective of the contents presented in my thoroughly constructed article.
  
  PS. You have described the contents of my article to represent sort of a “gish gallop”; I hope you are aware that your long response might actually induce similar associations.
  - Bas Post 21 May 2020 at 18:58
    
    Martijn,
    We are going in circles… You come with the same arguments as you did when we discussed this by mail, but they are faulty arguments. I explained by email why they are faulty. Still, you fail to register it and repeat the same faulty arguments!
    
    It is true that the IPCC stated in 2003 that “Trend analysis are usually performed over the minima of the solar cycles“. But you have to read that in the context where it was written: it is only about the RF, not about the impact of TSI on the temperature on Earth. They do not see this as an excuse to ignore 75% of all the years. What’s more, because the years you ignore are more varied, they can have a more varied/unpredictable impact on global warming, so hey should definitly NOT be ignored! But you continue to deliberately misinterpreting what was written there. And I write it again: the next paragraph there states: ” The best estimate from our assessment of the most reliable TSI reconstruction gives a 7-year running mean RF between…“. So they used running means containing ALL THE DATA to get “the best estimate”. But I know, you don’t want to use running means, because then your whole story falls to pieces. Then there is no longer a good correlation! Even with 11-year running means, you only get r=0.65.
    
    You write “you are implicit suggesting that I am not allowed to refer to the IPCC report unless I accept everything they write – which is unrealistic in the perspective of how science works.”. That is blatantly a wrong interpretation of what I wrote. The point is that you want to accept one part of an analysis, but don’t want to accept another part OF THE SAME ANALYSIS. Figure SPM.5 shows indeed that “ozone [O3] can be held responsible for a significant contribution to the warming of the atmosphere”. If I add it all up, I guess it is 0.5 W/m2. The fact that you referred to this analysis, inferred that you accepted it as a valid analysis. But in the very same analysis that you accept as being valid, they also found that the contribution of CO2 is 1.5 W/m2 – at least 3x more. It is blatantly absurd not to want to accept that part of the analysis, simply because it does not fit in your believe. You do not have to agree with the whole IPCC report, but agreeing with only one part of a result and not another part of the result of a same analysis, that is absurd!
    - Martijn van Mensvoort 21 May 2020 at 19:35
      
      Bas Post, in your reply (+ your dozens of emails) you have not bothered to face the consequent the 2nd part of source 9 involving these crucial passage in IPCC AR5:
      
      “… Maxima to maxima RF give a higher estimate than minima to minima RF, but the latter is more relevant for changes in solar activity.”
      
      (Neither did Rob Dorland in his feedback, which included quite a few questions for me to explain… not sure that I was looking for answers because so far I have not received a follow-up reply)
      
      PS. A proper analysis of the impact of the 22-year solar cycle requires an evaluation focussed on years that involve the same phase of the solar cycle. Such an approach reveals that only the solar maxima show an unusual pattern in comparison with temperature… therefore I think one should somehow put less weight on those years and the most simple approach to do that is to focus simply on the minima years. After all, that is sort of what the quote above says.
      Now, therefore your argument involving the need to include all years may not make much sense at all… because that almost sounds like an attempt to paternalize in an inappropriate manner, because there are no such rules in climate research at all. After all, in order to study the impact of individual phases of the solar cycle it is actually necessary to focus on only some of the years. However, of course it is also important to put things then into perspective to the other years – regarding this point (which you haven’t made in specific) I have some work ahead to catch up with, though by principle it is not necessary to go beyond a single rather surprising observation involving the minima years. As it wouldn’t make sense to claim…the maxima show a different picture so the minima are not important. Again, the IPCC cleary describes the minima to be more “relevant” than the maxima for changes in solar activity – basically they are saying: be aware that the maxima are less important than the minima. Unfortunately, you appear not open minded to face the consequence of what the IPCC describes for this specific matter.
      - Bas Post 21 May 2020 at 22:13
        
        Martijn, you are desperately trying to interpret that text of the IPCC so that it justifies what you want to do: ignore 75% of the data. But it all boils down to an “appeal to authority”. You cannot come up with a justification yourself. You cannot explain in scientific terms why to ignore all those other years, so you have to appeal to the authority of the IPCC and misinterpret what they wrote. I repeat: that text is only about the RF, not about the impact of TSI on the temperature on Earth! You misinterpret what is there!
        
        As usual, you always have a “PS”… That starts with “A proper analysis of the impact of the 22-year solar cycle…”. That reveals (again) what your believe is: you are obsessed with an effect of solar cycles on the global temperature!. So you only want to ‘prove’ that that is the one and ignore all other possible causes. “A proper analysis”, should look at all possible factors that could affect global temperature, not just your favorite one. The results of a “proper analysis” are shown in that Figure SPM.5, where you have been cherrypicking. That “proper analysis shows that the effect of the sun is minimal. It is smaller than the contribution of ozon and smaller than the contribution of man-made CO2.
        
        I had a whole list of errors. The choice to exclude 75% of the data is only one of them, and you fail to present a scientifically sound justification for that.
        Maybe the most relevant error in my list was: “Martijn claims that there is no need for CO2 to explain the rise in temperature. In doing so, he ignores the scientific knowledge and insights of the past decades. He thinks he knows better than hundreds of eminent climate researchers. Putting existing knowledge aside is a big logical error.” Can you explain why you decide to ignore the scientific knowledge and insights of the past decades?
      - Martijn van Mensvoort 21 May 2020 at 23:20
        
        Bas, the incoming sunlight (TSI) is at the basis of how the radiative forcing is defined:
        
        “Radiative forcing or climate forcing is the difference between insolation (sunlight) absorbed by the Earth and energy radiated back to space.”
        
        By the way, you are suggesting that I have excluded factors in general without describing what you exactly have in mind. My article describes that I have assessed the role of CO2 with and without other factors, so you words show a lack of specificity regarding what is actually described inside my article.
        
        Your feedback refers to a lot of points and details;
        would you mind to present me a list of your top 5 issues?
        
        (Maybe we can then discuss your worries in a more disciplined manner step by step)
      - Bas Post 22 May 2020 at 10:42
        
        Martijn, look again at the definition of TSI that you give yourself and what you write about it: “the incoming sunlight (TSI) is at the basis of how the radiative forcing is defined”. But what you do in your analysis, is not using the TSI, but subtract a value of this TSI for the secondary minima. So you don’t use the TSI, but adjusted values! Moreover, you adjust without proper physical justification and with a value that you obtained by trial-and-error! Don’t you see that there is a contradiction in what you write here and what you did in your calculations in your desire to achieve a good correlation?
        
        Again, you ignore what I wrote: “You cannot explain in scientific terms why to ignore all those other years, so you have to appeal to the authority of the IPCC and misinterpret what they wrote.” You still give no explanation why you ignore these 75% of the data. Your only argument is referring to the IPCC, an “appeal to authority”. You also wrote that it is unrealistic to accept everything the IPCC writes. Well, if I don’t accept that single sentence of the IPCC, you do not have any argument to ignore 75% of the data. So another contradiction in what you write!
        
        You believe (but cannot prove) that the minima are “more relevant”. Well, if they really are relevant factors, then they capture the effect of the entire solar cycle of 11 years. Then you would expect that there is a correlation between a minimum and the subsequent maximum. But when you look at the correlation between the LISIRD (average of 3 years) of the minima and the LISIRD (average of 3 years) of the subsequent maxima, you only find 0.29! There is thus an absence of any correlation between minima and maxima. The correlation with the previous maximum is also small: 0.48! What this means is: the minima do not provide information on the TSI over the whole cycle. The maxima give additional information about the solar irradiation. You cannot ignore these maxima! In fact, you have to use all the data to capture all the information on TSI, to assess its possible impact on temperature.
        
        You ask me to give my top 5 of issues? Well, let us start with 2 issues, that I addressed in the previous messages and that you keep ignoring:
        1/ what is your scientifically sound justification to ignore 75% of all the years?
        2/ why do you accept one aspect of Figure SPM.5, but not the entire figure, since it is one analysis?
      - Martijn van Mensvoort 22 May 2020 at 13:34
        
        Bas, you’ve quoted my words but you didn’t show any attempt to reflect on those words with regard to the IPCC passage which confirms that the minima are “more reliable” than the maxima. Therefore you are leaving the impression to me that you are walking away from this essential point… without acknowledging the impact of this point in my research. This explains why you have not been able (yet) to understand the design of my research properly.
        
        Also, you are ignoring my point that one can not study the impact of individual phases of the 22-year magnetic solar cyclus without focussing on just the years involved.
        
        Please allow me to explain this once again more properly:
        
        The crucial point is: climate science does not understand the impact of the 11-year solar cycle on temperature. Estimates for the temperature effect of the 11-year cyclus vary from at least 0,02-0,26 K (though there are even higher values described in the scientific literature); the outcome heavily differs with the method used for studying the impact. One of those methods involves the use of the principle that temperature difference found between 2 minima provides a clue about this this method leads to the higher part of the bandwidth.
        
        The IPCC is using estimates that are at the lower side of the bandwidth (~0,06 K), which implicates that they are inclined to underestimate the temperature impact of the 11-year with about at least about a factor 5 relative to the upper side of the estimates.
        
        My study shows that the temperature impact of the sun should be estimated based on 22-year magnetic solar cycle via the minima years. This leads for both the primary minima and the secondary minima to climate sensitivity values similar to the 1,2 K per W/m2 when using the TSI values measured at the top of the atmosphere.
        
        Because both the primary and secondary minima produce similar values it makes sense to use the correction factor, which is not found through “trial and error” like you suggested. Statistically it would probably makes sense to define the correction required in terms of the explained variance.
        
        After I presented the results for the 3-year average values in my article, I can now also report that for the minimum years between 1890 and 1985 the explained variance is always 91% (no matter whether one used just the primary years, the secondary years… or the combined years with a correction factor). The explained variance method results again in a climate sensitivity value of exactly 1,20 K per W/m2 involving the TSI values at the top of the atmosphere. For the period 1890-1985 the value is a bit higher for the secondary minima and a bit lower for primary minima.
      - Bas Post 22 May 2020 at 19:08
        
        Martijn, you asked me to give my top 5 of issues, to discuss them in “a more disciplined manner step by step”. Well, I gave you 2 issues, that I addressed in the previous messages. But you keep ignoring them, rather than discussing them in “a more disciplined manner step by step”:
        1/ what is your scientifically sound justification to ignore 75% of all the years?
        2/ why do you accept one aspect of Figure SPM.5, but not the entire figure, since it is one analysis?
        
        You claim that “climate science does not understand the impact of the 11-year solar cycle on temperature”. That is actually a very good reason the take all the years of the cycle into account, because –according to your statement- we don’t know which parts are important. But then you are convinced that you understand it well enough, so that you can eliminate 75% of the data. Don’t you see that (again) you are contradicting yourself?
        In your reply, it becomes clear that you don’t even seem to understand the term “scientifically sound”. That means that you refer to proper studies and to the general field of knowledge, to justify what you are doing. Just because you find a high correlation when you cherrypick begin- and end-years and eliminate a lot of years, is not a justification. You also ignore what I wrote earlier today (ignnoreing is also not “scientifically sound”), that there is no correlation between the minima and the subsequent maxima, so it is clear that the minima do not provide information on the TSI over the whole cycle. The maxima give additional information about the solar irradiation. You cannot ignore these maxima! In fact, you have to use all the data to capture all the information on TSI, to assess its possible impact on temperature. You just ignore what I present in the discussion and only repeat the same old faulty arguments over and over again. And still no scientifically sound justification!
        
        You also ignored the second issue I raised.
      - Martijn van Mensvoort 22 May 2020 at 20:23
        
        I already addressed both matters but I’ll describe the core again briefly
        
        Ad 1) The IPCC confirms that the minima are “more relevant” than the maxima.
        Ad 2) For figure SPM.5 I have only referred to the fact that the IPCC confirms that ozone has contributed to the warming.
        
        My approach represents an observational innovation.
        To me it is odd to see you reason in the perspective of the nature of my that I should “refer proper to studies” in general without specifying what you exactly have in mind – especially since I have referred for both points to aspects inside the most recent IPCC report.
        
        (I don’t know why you keep suggesting that I have ignored your feedback; my short answers above show that I have not)
      - Bas Post 22 May 2020 at 22:01
        
        Martijn, it’s true, you “already addressed both matters”. But you keep repeating the same things and keep ignoring what I wrote in reply to these! There is no progress being made in this ‘discussion’ when you keep repeating the same things and ignoring anything new that is being said. A discussion that -by the way- already started weeks ago in the emails we exchanged.
        
        Just to make it clear, here is a summary of what I have already added to the discussion in the reactions above and what you are ignoring:
        
        For the first issue.
        “you have to read that [what the IPCC wrote] in the context where it was written: it is only about the RF, not about the impact of TSI on the temperature on Earth […] you continue to deliberately misinterpreting what was written there.”
        “You cannot explain in scientific terms why to ignore all those other years, so you have to appeal to the authority of the IPCC and misinterpret what they wrote”
        “You still give no explanation why you ignore these 75% of the data. Your only argument is referring to the IPCC, an “appeal to authority”. You also wrote that it is unrealistic to accept everything the IPCC writes. Well, if I don’t accept that single sentence of the IPCC, you do not have any argument to ignore 75% of the data.”
        “when you look at the correlation between the LISIRD (average of 3 years) of the minima and the LISIRD (average of 3 years) of the subsequent maxima, you only find 0.29! […] What this means is: the minima do not provide information on the TSI over the whole cycle. The maxima give additional information about the solar irradiation. In fact, you have to use all the data to capture all the information on TSI, to assess its possible impact on temperature.”
        
        For the second issue:
        “The point is that you want to accept one part of an analysis, but don’t want to accept another part OF THE SAME ANALYSIS […] It is blatantly absurd not to want to accept that part of the analysis, simply because it does not fit in your believe.”
        “You also ignored the second issue I raised.”
        
        You claim that you did not ignore my feedback. Sorry, but you ignored it! You still appealed to authority! You still cherrypicked out of that Figure SPM5 and ignored the other data in it. If you still want to reply, then build upon these comments, rather than just repeating your same beliefs. Give a scientifically sound argument to only use the minima (not “because IPCC says so”, not “because it gives the results I like”). Explain what you conclude out of the bigger RF for CO2 in that figure.
      - Martijn van Mensvoort 22 May 2020 at 22:25
        
        Bas, after I have responded (and rejected) some of your major points it doesn’t make much sense to me that you claim that I am “ignoring” your feedback.
        
        Your continued efforts on my reference to the 2nd quote from source 9 indicates to me that you probably do not have a background in physics, because you have continued to refer to the aspect of the radiative forcing [RF] even though this directly involves total solar irradiance [TSI].
        
        By the way, my finding regarding the 3-year average basically shows a similar result for the minima years… and for the 5-year up to 11-year average values; however, I have not publicly shared the data yet – but I will in the near future. So, I have to ask you to have a little patience regarding this aspect of my research.
      - Bas Post 23 May 2020 at 09:24
        
        Martijn, you keep repeating the same things and keep ignoring what I wrote in reply to these.
        
        For the first issue, you still don’t even try to explain in scientific terms why you ignore all those other years. You continue to use the logical fallacy by appealing to the authority of the IPCC and misinterpret what they wrote.
        
        You also continue to ignore the second issue I raised. It is blatantly absurd to refer to a part of a figure but not want to accept the entire analysis, simply because it does not fit in your believe. The logical fallacy of cherrypicking.
        
        You now try the logical fallacy to attack the messenger, by raising doubts about my scientific expertise. But failing to present decent arguments, is not a credit to your expertise…
        
        You now also argue in vague terms about “similar results” using “up to 11-year average values”. Not very convincing, because it only took me a few minutes to calculate the correlations in your Excel file. When going from 3-year to 11-year averages, the correlation decreases from 0.93 to 0.76. Not “similar” at all! Adding more data lowers the correlation! That is sure evidence that the correlation you found is spurious and has nothing to do with causation, so does not “explain” anything. What it shows is that all the years are important, and that there are other factors that affect the temperature of the air and the oceans. The figure you keep ignoring, identifies these other factors.
        
        With each reaction, you seem to get further away from presenting convincing arguments.
      - Martijn van Mensvoort 23 May 2020 at 14:37
        
        Bas, wanneer we kijken naar de minima periode 1890-1985 dan zien we op basis van de correctie van 0,123 W/m2 (gericht op de secundaire minima) een correlatie van 0,963 en wanneer we de correctie voor de 11-jarige waarden rond de minima verdubbelen naar 0,246 dan vinden we een correlatie van 0,922, zie:
        
        http://klimaatcyclus.nl/klimaat/pics/bassie.jpg
        
        Overigens, alle grijze blokken in de illustratie plaatje hebben dezelfde omvang.
        
        We zien dat bij de 3-jarige waarden bij alle 9 overgangen de TSI en de temperatuur in dezelfde richting bewegen; bij de 11-jarige waarden geldt dit voor 8 van de 9 overgangen (enkel bij de overgang tussen 1943 en 1954 is dit niet het geval).
        
        Bovendien zien we in het perspectief van zowel de TSI als de temperatuur dat de waarden voor de periode 1890-1933 allemaal lager zijn dan in de periode 1943-1985; ook zien we nog 4 andere patronen die in beide perspectieven worden aangetroffen.
        
        PS. Het gebruik van een hogere correctie waarde voor langere periodes rond de minima is in dit perspectief logisch i.v.m. het feit dat de waarden van de TSI stijgen bij de gemiddelde waarden over langere periodes rond de minima. We zien dus dat het flexibel gebruik van een correctie waarde duidelijk uitwijst dat zowel in het perspectief van de primaire en secundaire jaren als ook bij het perspectief van de combinatie van beide laat zien dat een groot deel van de parallel tussen TSI en temperatuur zich geenszins beperkt tot de minima jaren.
        
        (Overigens, bIj de minima jaren zelf heb ik inmiddels een parallel gevonden die nog sterker is dan bij de 3-jarige waarden; deze ga ik in mijn volgende artikel beschrijven)
      - Martijn van Mensvoort 23 May 2020 at 14:46
        
        PPS. Het is denk ik ook interessant om vast te stellen dat bij het 11-jarig gemiddelde rond de minima de parallel voor de periode 1890-1943 opmerkelijk genoeg zelfs iets sterker t.o.v. de waarden op basis van het 3-jarige gemiddelde.
        
        http://klimaatcyclus.nl/klimaat/pics/bassie.jpg
      - Martijn van Mensvoort 23 May 2020 at 15:09
        
        Bas, wanneer de waarde van de temperatuur van de 11-jarige periode rond het 1954 minimum duidelijk wat hoger zou zijn geweest… dan zou er weinig ruimte overblijven voor twijfel over het verband tussen de zon en de temperatuur.
      - Bas Post 23 May 2020 at 17:02
        
        Martijn, how many times do I have to repeat it? You keep ignoring what I write and keep believing that your calculations means anything. You asked me to give my top 5 of issues, to discuss them in “a more disciplined manner step by step”. But with each reply, you fail to address them properly.
        
        For the first issue, you still don’t even try to explain in scientific terms why you ignore all those other years. You used the logical fallacy by appealing to the authority of the IPCC and misinterpret what they wrote. Now you want to convince that, after cherrypicking these years and then continue adding some numbers to them, you get a correlations that somehow are meaningful and “explain” anything. No, that is not proper science!
        
        You also continue to ignore the second issue I raised. It is blatantly absurd to refer to a part of a figure but not want to accept the entire analysis, simply because it does not fit in your believe. The logical fallacy of cherrypicking.
        
        The only thing you keep doing is cherrypicking some years, changing the values of these years and then calculating correlations. Then you believe that correlation says something about causation. Well, I can play that game too. Your starting point is that you only want to look at the years around the minima and only for the period from 1880 onwards. Then you look for a correlation between LISIRD and ocean temperature, averaged around the 3 years of these minima. This gives you a correlation of 0.93. You claim this is important.
        
        Now, I have also done some calculations of correlations. For these same years as you used, the correlation between ocean temperature and CO2 is 0.88 – almost as good! Correlations are only indicative values – one cannot conclude that 0.93 is more important than 0.88 (and definitely not on cherrypicked years and corrections!). So you cannot ignore such a good correlation with CO2 – but you never even mention this (and neither can you ignore the correlation of van Oldenborgh, of course!).
        
        I only picked these years, because that are the years you selected. But I went a step further. I also tried it with gaps of 10 years (so 2018-2008-1998…1888). Then I get a correlation of 0.92 between ocean temperature and CO2. So I don’t need minima (of maxima) to get a good correlation with CO2. (It works for other years too)
        
        When I extend the period to 1867 and use your solar minima as timepoints, then I get a correlation of ocean temperature with LISIRD of 0.83, but for CO2 it’s 0.89. If you believe the value of correlation is important, then CO2 is better !!!
        
        Do my correlations prove that CO2 is responsible? Have I proven that CO2 explains >90% of seawater surface temperature variance up to and including 2018? No, off course not! And your correlations with LISIRD don’t prove anything either! Your correlations did not prove that “sun explains 93% of seawater surface temperature variance up to and including 1980s”. All these correlations only show that starting from one single conviction and only calculating correlations, rather than taking all factors and all knowledge into account, it’s easy to “prove” your conviction. But that is not science.
        
        If you do not want to address 2 of my top 5 issues, then maybe you can explain why we should ignore these high correlations between ocean temperature and CO2?
      - Martijn van Mensvoort 23 May 2020 at 17:55
        
        Bas, I have explained why I have rejected your first 2 arguments; the illustration involving a comparison between the 3-year and 11-year average values around the solar minimum years shows that I am not ignoring those years at all.
        
        http://klimaatcyclus.nl/klimaat/pics/bassie.jpg
        
        The major point is basically that the solar minimum years show a (hidden) pattern over a period of 100 years which shows that the sun has been in control of temperature.
        
        The fact that the solar maximum years show different dynamics is basically just a sidewalk here. because we know that those years show typically more erratic TSI values (which is reflected to the IPCC’s 2nd quote in source 9). This explains why the maxima show much lower correlations (even after applying the correction).
        
        Sorry, but in my perception your first 2 points are basically out of touch with reality – unfortunately you have given me the impression that this is probably because you don’t really understand the physics involved… for, you do not appear to understand that the radiative forcing directly relates to TSI. I can illustrate this with this quote from AR5 (TAR, page 352):
        
        “Radiative forcing due to changes in total solar irradiance (TSI) is estimated to be +0.3 ± 0.2 Wm−2 for the period 1750 to the present.”
        
        Source quote: https://www.ipcc.ch/site/assets/uploads/2018/03/TAR-06.pdf
        
        This quote shows very explicit that it doesn’t make sense to deny the relevance of the IPCC’s explicit statement that the TSI minima are more relevant in terms of RF than the maxima.
        
        The consequence is that you first argument is clearly invalid because as a matter of fact I have presented a valid justification via source 9.
      - Bas Post 24 May 2020 at 12:13
        
        Martijn, how many times do I have to repeat it? You keep ignoring what I write and keep believing that your calculations means anything. You asked me to give my top 5 of issues, to discuss them in “a more disciplined manner step by step”. But with each reply, you fail to address these issues properly.
        
        For the first issue, you still don’t even try to explain in scientific terms why you ignore all those other years. You used a logical fallacy by appealing to the authority of the IPCC (and misinterpret what they wrote as well). Now you want to convince that, after cherrypicking these years and then continue adding some numbers to them, you get a correlations that somehow is meaningful and “explains” anything. No, that is not proper science!
        
        You also continue to ignore the second issue I raised. It is blatantly absurd to refer to a part of a figure but not want to accept the entire analysis, simply because it does not fit in your believe. That is thee logical fallacy of cherrypicking.
        
        The only thing you keep doing is cherrypicking some years, changing the values of these years and then calculating correlations. Then you believe that correlation says something about causation. Well, I can play that game too. Your starting point is that you only want to look at the years around the minima and only for the period from 1880 onwards. Then you look for a correlation between LISIRD and ocean temperature, averaged around the 3 years of these minima. This gives you a correlation of 0.93. You claim this is important.
        Now, I have also done some calculations of correlations-starting from the the data in the Excel you show on your website. For these same years as you used, the correlation between ocean temperature and CO2 is 0.88 – almost as good as yours! Correlations are only indicative values – one cannot conclude that 0.93 is more important than 0.88 (and definitely not on cherrypicked years and corrections!). So you cannot ignore such a good correlation with CO2 – but you do: you never even mention this (and neither can you ignore the correlation of van Oldenborgh, of course!).
        
        I only picked these years, because that are the years you selected. But I went a step further. I also tried it with gaps of 10 years (so 2018-2008-1998…1888). Then I get a correlation of 0.92 between ocean temperature and CO2. So I don’t need minima (or maxima) to get a good correlation with CO2. (It works for other years too).
        
        When I extend the period to 1867 and use your solar minima as timepoints, then I get a correlation of ocean temperature with LISIRD of 0.83, but for CO2 it’s 0.89. If you believe the value of correlation is important, then CO2 is better !!!
        
        Do my correlations prove that CO2 is responsible? Have I proven that CO2 explains >90% of seawater surface temperature variance up to and including 2018? No, off course not! And your correlations with LISIRD don’t prove anything either! Your correlations did not prove that “sun explains 93% of seawater surface temperature variance up to and including 1980s”. All these correlations only show that starting from one single conviction and only calculating correlations, rather than taking all factors and all knowledge into account, it’s easy to “prove” your conviction. But that is not science.
        If you do not want to address 2 of my top 5 issues, then maybe you can explain why we should ignore these high correlations between ocean temperature and CO2?
      - Martijn van Mensvoort 24 May 2020 at 14:39
        
        Bas, you’ve only listed 2 point in response to my request to list a top 5.
        I guess this became indicative for that you are not willing to show any sort of cooperation to sort things out by detail.
        
        You have basically ignored the largely factual input that I gave in response.
        
        Since you have given me signals that you don’t really understand the vocabulary used in climate science and you have been repeating the same accusations, it would probably become fruitless to continue this process.
        
        Therefore you leave me no option than to simply reject your feedback – unless you are willing to show a little more reflection on the input (+ efforts) that I have presented so far in response to your feedback.
      - Bas Post 25 May 2020 at 08:10
        
        Martijn, your reply becomes quite pitfull now…
        
        I started with 15 issues, and you asked me three days ago to reduce that to “a list of your top 5 issues” so that “we can then discuss your worries in a more disciplined manner step by step”. I started with 2 issues, but you failed to discuss them in a “more disciplined manner”. Now, 3 days later, you complain that the list had 2 and not 5 issues…
        
        You claim that I “basically ignored the largely factual input that I gave in response” . What you actually did, was repeating all sorts of correlations, without ever addressing what I asked: give a scientifically sound justification for your interpretation that these correlations “explain” global warming. Rob van Dorland gave a good description of what scientifically sound can be: “onderbouwen met fysische mechanismen en referenties naar andere studies” (“substantiate with physical mechanisms and references to other studies”) https://www.climategate.nl/2020/05/de-zon-zorgde-voor-11-c-opwarming-sinds-de-17de-eeuw/#comment-2313356. You never did that.
        
        You also still fail to enlighten me on how you interpret the whole of that figure SPM5.
        
        You failed to “discuss [these 2 issues] in a more disciplined manner step by step”, but now you want 3 others? Pittyful…
        
        Now you also suddenly claim that I “don’t really understand the vocabulary used in climate science”. That is a bit weird, because you don’t seem to be in the right position to judge that vocabulary. After all, Rob van Dorland advised you some weeks ago: “Ook raad ik aan om je begrippen als (versterkt) broeikaseffect, stralingsforcering, feedbacks en klimaatgevoeligheid eigen te maken” (“I also recommend that you familiarize yourself with concepts such as (enhanced) greenhouse effect, radiation forcing, feedbacks and climate sensitivity.” )
        
        Rob had reviewed the Dutch version of your article. I advise you to read his comments again. What did he write about the use of minima by IPCC? “IPCC bedoelt hier dus dat als je langjarige trends wil afleiden dat je dan niet begin en eindpunt van je reeks in verschillende fases van de zonnevlekkencyclus moet nemen.” (“IPCC makes it clear that if you want to determine long-term trends, you do not take the start and end of your series in different phases of the sunspot cycle.” ). So, IPCC says you start and end at minima, or you start or end at maxima. They prefer starting and ending at minima, because they are “more stable”. That’s all they said. You can analyse all the years between start and end using running means. You cannot discard 75% of the data. That’s what the IPCC says there. That is what van Dorland also states. That is the point I make. Your reply to van Dorland made it clear that you did not understand the point he made. Because you know that if you take all the years, there is only a poor correlation, and you cannot present a scientific justification why you ignore those data.
        
        You ask me to “show a little more reflection on the input that I have presented”. I am happy to do that. The problem is that you fail to give me something scientific to reflect on. Just juggling some numbers without valid scientific arguments, is not something I can take serious. Explain with scientific arguments why you discard 75% of the data (“substantiate with physical mechanisms and references to other studies”), and I will reflect on the input.
        
        FInally, I can also ask you to “show a little more reflection on the input that I have presented so far in response to your feedback”. You never replied to those two issues in a clear way. You did not reflect on the correlations I calculated in my previous reply. What is your reflection on the high correlation between the temperature and CO2 at the years of the minima?
      - Martijn van Mensvoort 25 May 2020 at 15:41
        
        Bas, I perceive your input to represent not much more than just superficial rethorics.
        
        You’ve referred just once to the physical mechanism involving the switching of the solar magnetic poles – which I have described to provide an explanation for the impact of the correction (combined with the Gnevyshev-Ohl phenomenon). In response to van Dorland’s first point I have added an extra alinea to paragraph IX-a in order to describe the mechanism with more details.
        
        This part in your first input shows that you’ve basically ignored my efforts to provide an appropriate response:
        
        “– Martijn believes that there is a difference in the impact of TSI on temperature between primary and secondary minima. He cannot explain the physical principle behind it, except that it must have something the do with a reversal of magnetic poles. But if there really was an impact from the phase of the 22-year cycle, then this also applies to every moment of the phase, and then he should not just eliminate all those other years. His argument therefore contains a contradiction.”
        
        In your latest post you are talking as if I never gave any sensible responses.
        The truth is: van Dorland didn’t even mention the poles in his feedback.
        
        Bas, apparently you’re not really interested to discuss things properly because most of your input represents communication at interpersonal personal level.
        
        Your feedback is in my perception very unbalanced and rather subjective of nature.
      - Bas Post 25 May 2020 at 18:51
        
        “In your latest post you are talking as if I never gave any sensible responses.”
        Yes, you got it! That is exactly what I mean! You give responses, but not sensible responses!
        You have never given a sensible response that explained why you can ignore 75% of the data.
        You have never given a sensible response that explains how you interpret the whole of Figure SPM5.
        
        You create smokescreens by talking a lot of whiffle-whaffle, but your talking is not a scientifically sound explanation or a direct response to the issues I raised. Your “paragraph IX-a” does not give any justification for ignoring 75% of the data. What “paragraph IX-a” purports to show, it that there is a lot of variation in solar irradiation throughout a 22-year cycle. The conclusion then has to be: you have to take ALL years into account! The conclusion CANNOT BE: you can ignore 75% of the years! So where is your “sensible response” to ignore 75% of the data?
        
        “Bas, apparently you’re not really interested to discuss things properly because most of your input represents communication at interpersonal personal level”
        Martijn, this reminds me of a reaction that Ronald wrote, when discussing the Dutch version of this text of yours: “Misschien toch goed om eerst even serieus op mijn reactie in te gaan, voordat je jouw geliefde “betrekkingsniveau” weer van stal haalt 😉 ”. (climategate.nl/2020/05/de-zon-zorgde-voor-11-c-opwarming-sinds-de-17de-eeuw/; reaction “Ronald 8 mei 2020 om 15:21”)
        
        “Your feedback is in my perception very unbalanced and rather subjective of nature.”
        Martijn, your feedback is in my perception very unbalanced and rather subjective of nature. You reactions become more and more ad hominem. For days now, you fail to give clear answers on the two issues that I raised. Why do you ignore 75% of the data? What do you conclude from the whole of Figure SPM5? Can you give objective feedback?
        
        https://www.quotemaster.org/images/5d/5d0a0f4ac149915e546befa42b16be5f.jpg
      - Martijn van Mensvoort 25 May 2020 at 20:24
        
        I’ll finish by notifying that the identity ‘Bas Post’ exhibited similar behavior at the Climate.nl platform where he got banned due to troll-like behavior.
        
        Hans Labohm even wrote a blog post about Bas Post’s rather obstructive pattern of behavior which includes e.g. the use of (translated quote): “various pseudonyms, email addresses and IP addresses”:
        
        https://www.climategate.nl/2020/04/klimaatpsychose/
      - Bas Post 25 May 2020 at 22:02
        
        “various pseudonyms, email addresses and IP addresses”
        Isn’t it funny that I still use the same pseudonym. I have also communicated with you extensively with the same email address (see also my first reaction here 4 days ago: ” I had several mail-exchanges with him”). Don’t you realise that article was simply a rant full of false accusations by somebody who can’t accept fact-checks and has no good explanation to justify why he deletes them?
        
        Martijn, the fact that after such a lengthy exchange you have to resort to such shooting at the messenger, rather than the message, simply emplies you accept I have a point.You cannot give a scientifically sound explanation why you ignore 75% of the data – except that if fits with your beleive. You cannot interpret the whole of Figure SPM5 in a way that fits with your beliefs.
        
        link removed, Mod
Andre Bijkerk 26 May 2020 at 21:24

Obviously, the discussion below evolved from some scientific quality to mud throwing. However, for the moment I let it stand for future study of Behavioural scientists in the quest to answer late Freeman Dyson’s mystery:

….the central mystery of climate science. It is not a scientific mystery but a human mystery. How does it happen that a whole generation of scientific experts is blind to obvious facts? Freeman Dyson (Foreword to GWPF report #18 Goklany, I.M. 2015, Carbon dioxide, The good news)
- Bas Post 27 May 2020 at 13:22
  
  You are right that the exchange here degraded to mud-slinging, because there never was any proper discussion on the scientific issues I raised.
  But you are not convincing me with a claim that “a whole generation of scientific experts is blind to obvious facts“. Why should I believe Dyson – somebody who claims to be “unprejudiced” in that same text, but is in fact part of the Heartland Institute lobby? You are just using (like Martijn did), the false argument of appeal to authority.
  
  But if you like quotes, then maybe you could also consider this one:
  
  Despite the clear scientific consensus, a veritable brigade of self-proclaimed, underinformed armchair experts lurk on comment threads the world over, eager to pour scorn on climate science. Barrages of ad hominem attacks all too often await both the scientists working in climate research and journalists who communicate the research findings.
  David Robert Grimes
  
  I am neither working in climate research nor a journalist, but I do know about science. The ad hominem attack in the reply a few days ago, was not a surprise. The lack of proper, scientifically sound, justification by the underinformed armchair experts was also expected. What was unexpected was that Martijn continued to react, without ever presenting new or convincing arguments. Right from the start, he knew (from earlier mail exchanges) that he could not give a proper answer to these issues. He missed a great opportunity to keep quiet. As the saying goes: “if you are in a hole, stop digging!”. Martijn continued to dig.
Martijn van Mensvoort 28 May 2020 at 18:02

Even though my article is focussed on just the 3-year average values, in my preceding articles I had already presented analyses involving just the minimum years (february 2020 article) and minimum-to-minimum averages (december 2019 article).

I have now also calculated the impact of the correction with a more structured approach for the different perspectives (the correction factor was fine-tuned to 4 decimal places based on the average value of the correlation produced by the primary and secondary values separately). This rather simply calculation technique can be applied up to and including the 9-year average around the minima because for the 11-year average values the years start overlapping with 1 or 2 years at various periods. This explains why only the correction value at the 11-year average is clearly higher compared to the shorter minimum periods.

The results are very stable (with correction values between 0,114-0,142 W/m2 for the minima year, 3Y, 5Y, 7Y and 9Y average values):

– it is striking to see that in all TSI and HadSST3 perspectives (including the 11-year perspective) the first 5 values are all below the last 5 values;
– also, for all TSI and all HadSST3 perspective 1912 produces the lowest value value among the first 5 values and 1976 produces the lowest value among the last 5 values.

http://klimaatcyclus.nl/klimaat/pics/LISIRD-TSI-vs-HadSST3-values-for-solar-minimum-years-plus-3Y-5Y-7Y-9Y-and-11Y-average-minima.jpg
- Bas Post 29 May 2020 at 08:11
  
  Martijn, I repeat what I wrote before:
  
  Now, I have also done some calculations of correlations. I see that for these same years as you used [from 1890], the correlation between ocean temperature and CO2 is 0.88 – almost as good! So you cannot ignore such a good correlation (and neither can you ignore the correlation of van Oldenborgh, of course!). I only picked these years, because that are the years you selected. I also tried it with gaps of 10 years (sp 2018-2008-1998…1888). Then I get a correlation of 0.92 correlation between ocean temperature and CO2.
  […]
  When I extend the period to 1867 and use your solar minima as timepoints, then I get a correlation of ocean temperature with LISIRD of 0.83, but for CO2 it’s 0.89. If you believe the value of correlation is important, then CO2 is better !!!
  
  I got these correlations by using the 3-year averages (as you did), without any need for “correction values”, and without having to stop at 1985 but going all the way up to to year 2017. I basically did a much simpler analysis, and got a result as good as you convoluted approach. I wrote this in a reaction several days ago, you replied about other points, but you keep ignoring this crucial finding. I also repeat something else I wrote earlier:
  
  By the way, I can also ask you to “show a little more reflection on the input that I have presented so far in response to your feedback”. You never replied to those two issues in a clear way. You did not reflect on the correlations I calculated in my previous reply. What is your reflection on the high correlation between the temperature and CO2 at the years of the minima?
  
  There is not only a good correlation with CO2, there is also a vast amount of scientific literature to support that this is not only a correlation, but also a causation. But you want to ignore all this, because your are convinced that you you know it better than all the scientists of the world…
  - Martijn van Mensvoort 30 May 2020 at 01:39
    
    Bas, not sure that you are aware that the 0,88 correlation is mentioned up to 5x in the article (it is e.g. featured in both figure 7 & 8). Actually, the period 1890-1979 shows that the sun is responsible for the (spurious) high correlation for CO2 and sea surface temperature (and the same goes for global temperature).
    
    By the way, your comment was not really a response to my additional input in my previous post – which shows that the impact of the correction factor is similar for minima periods of various lengths (1y up to at least 9 years).
    
    PS. Hopefully you are aware that you rather violent link in your post #154 (showing a video game machine gun scene) was removed by the admin. You probably would not have posted such materials if your username had been authentic.
    - Bas Post 30 May 2020 at 18:07
      
      Martijn, you are correct: my response #159 was not really a response to your additional input in your previous post. But then again, most of your responses are not really responses to my previous posts. Every thime, you fail to give clear answers on the two issues that I raised multiple times. I repeat: For days now, you fail to give clear answers on the two issues that I raised. Why do you ignore 75% of the data? What do you conclude from the whole of Figure SPM5? There is no point in replying about the “additional input”, because they still are based on the same mistake you make: you blind conviction that TSI and not CO2 is the cause of global warming, your failure to understand the vast knowledge of climate science, your failure to give clear answers on these fundamental questions.
      
      By the way, your comment was also not really a response to my previous post. You ignore in #159 “There is not only a good correlation with CO2, there is also a vast amount of scientific literature to support that this is not only a correlation, but also a causation.” Yes, you did mention “0.88” in your article several times. But what you write about all this at the end of your section II, that is just wifflewaffle, pseudoscience, insinuations and even blatant lies. Your analysis is “spurious” and not supported by the vast amount of climate science, whereas the correlation between CO2 and sea surface temperature is in line with this vast knowledge base.
      - Martijn van Mensvoort 30 May 2020 at 21:19
        
        Bas, you make me feel like I am talking to a wall – since you’ve now quote often simply send my words in return.
        
        Again, in my earlier articles I have addressed all years (with similar results regarding the influence of the sun); I have also shown this in the additional illustration:
        http://klimaatcyclus.nl/klimaat/pics/LISIRD-TSI-vs-HadSST3-values-for-solar-minimum-years-plus-3Y-5Y-7Y-9Y-and-11Y-average-minima.jpg
        
        So, despite that I have addressed your 2 major topics and I have rejected your arguments and I despitie have given you responses on at least some of the contents in your posts…nevertheless you have continued to claim that I have not addressed the your points and the other content at all.
        
        So be it.
        
        (Your machine gun link says it all: your input is basically just an expression of sentiment in order to oppose and deny basically almost everything; apparently you feel fine showing this counterproductive behavior while you’re hiding behind a pseudonym)
      - Bas Post 31 May 2020 at 09:18
        
        Martijn, you make me feel like I am talking to a [brick] wall – since you’ve now quite often simply ignore the questions I ask.
        
        You have never given a good explanation why you only use the years around the minima – although I asked you already many times. In your latest reaction, you suddenly claim it is somewhere described in your earlier articles, but no reference is given. You also show the figure again, but that does not justify using only the years around the minima – it is not scientifically sound. You still use the minima, except that now you average more years around it. You do not do a trend analysis with all the years. That figure only shows that if you torture data long enough and invent “corrections” that are different in each panel, the data will tell you what you want. You claimed in your article that the IPCC considers the minima “more relevant”, but that is a misinterpretation of their sentence. The IPCC only says that, when you do trend-analysis, it is more relevant to start and end at a minimum. You fail to acknowledge you misinterpreted this although it has been pointed out to you by van Dorland and by me. You have given no other justification for using only the years around the minima, except that you do this because it gives you a desirable result (like in the figure you just gave…).
        
        You also have never explained what you conclude from the whole of figure SPM5 – although I asked you already many times. You wrote in your article “Figure SPM.5 in IPCC AR5 confirms that ozone [O3] can be held responsible for a significant contribution to the warming of the atmosphere”. The word “confirm” implies that you accept this figure as credible and you use it to support your believe about ozone. But you have never explained what you conclude from the whole of Figure SPM5 – specifically the part about CO2. That figure is one analysis. You fail to acknowledge that you cannot accept one part of an analysis and ignore another part, although it has been pointed out to you by me before.
        
        You have also never explained why you ignore the good correlation between CO2 and temperature (a correlation without have to resort to selective start and end-years, without limiting to minima, without “corrections”,…). Yes, you did mention “0.88” in your article several times. But what you write about the correlation between CO2 and temperature at the end of your section II, that is just wifflewaffle, pseudoscience, insinuations and even blatant lies. Your analysis is “spurious” and not supported by the vast amount of climate science, whereas the correlation between CO2 and sea surface temperature is in line with this vast knowledge base. You are blinded by your believe that solar minima are important, so every other result has to be ignored or discredited.
        
        (Not sure why you keep mentioning a machine gun. The link that was removed did not show a video game and did not show a machine gun). But somehow you feel the need for ad hominem attack.
Ronald 30 May 2020 at 10:23

Martijn could have point if he could accept a (temporary) decrease of the (TSI_min,T) correlation due to other geophysical phenomena than the solar minimum. A return of the correlation to a high value after the phenomenon impact has finished could support his point. Instead he tries to keep up the high correlation by applying artificial corrections in Figure 10. A time evolution of the (TSI_min,T) correlation until the most recent date could be more convincing than applying artificial corrections.

The temperature step within the indicated orange square in figure 10b is about the largest step over the complete 1880-2018 period, which suggests that global mean temperature is more sensitive to the (localized, both in time and space) antarctic ozon layer decline than to changes of solar minima. This undermines his point that solar minima ‘control’ global mean temperature.

It is true that ozon is a GHG, but following Figure SPM.5 in IPCC AR5 ozone depletion in the stratosphere, where the ozon layer resides, has an overall cooling effect (negative O3 bar for halocarbons, which are responsible for the ozon layer depletion). Martijn instead assigns a warming effect to ozon layer depletion in figure 10c which contradicts the IPCC figure he refers to.
- Martijn van Mensvoort 30 May 2020 at 19:38
  
  Ronald,obviously the numbers in my analysis do not confirm the numbers in figure SPM.5. And yes, the impact of my analysis is indeed in conflict with the impact attributed to ozone in the halocarbons category, however those numbers are based climate models (where the warming impact of more UV radiation in the lower atmosphere is underestimated, etc.). So you should not separate this inconsistency from the fact that my analysis shows a much higher solar sensitivity compared to what the IPCC describes.
  
  In general, the temperature development in the middle atmosphere (= stratosphere + mesosphere) is least understood; it basically depends on ozone…however, the temperature development is inconsistent between the mesosphere and the stratosphere. One use the reasoning: “more ozone generates a higher temperature due to absorption of UV”, however, this principe does not really work for the stratosphere at all because the highest concentration of ozone is found at the ozone layer which is actually located in the lower part of the stratosphere where the temperature is low compared to the upper part of the stratosphere and the lower part of the mesosphere. Crucial is that just below the ozone layer the stratosphere actually shows one of the coldest parts of the full atmosphere (basically only the mesopause is colder). So, things are much more complicated than what the IPCC numbers suggest.
  
  Your comments involving figure 10 are irrelevant in the perspective of figure V in paragraph V. The antarctic ozone hole data basically serves well as an estimate for global ozone levels, because such data is available only since the 2nd half of the 20 century (therefore it is impossible to perform an analysis going back to 1890 using that data).
  
  By the way, solar sensitivity does not depend on the impact of ozone. However, contrary to CO2 ozone does contribute to the explained variance combined with the influence of the sun (TSI).
  
  So, your input is basically irrelevant for the core finding… which involves the sun, not ozone.
  - Ronald 31 May 2020 at 00:09
    
    Martijn, thank you for your reply. First of all, you did not respond at all to my first remark. Can you please do?
    
    Second, in your paper you bring up the figure of SPM.5 as a reference to make a point. Now you claim the figure is inconsistent in many aspects. These are conflicting statements. At hindsight should the reference to the figure be removed from your paper?
    
    If not, can you confirm that you assign a warming effect to ozon layer depletion which contradicts the IPCC figure you refer to?
    
    You end with: “So, your input is basically irrelevant for the core finding… which involves the sun, not ozone.” But how do you explain the decrease of TSI_min from the mid ’80s to the mid ’90s while at the same time the temperature increases strongly with more than 0.2 degrees over slightly more than one decade! (orange box in figure 10b). Since you consider TSI_min and stratospheric ozone as the only contributors to the global mean temperature in figure 10, this suggests that ozone depletion in the stratospheric ozone layer has a much larger impact on the global mean temperature than TSI_min over this period. Do you agree?
    
    Ps. Your discussion on the upper stratosphere and mesosphere was of no relevance in the context of your paper, because it was not discussed therein.
    
    I hope you will try to answer all 4 questions, to the point. (Most above questions can be answered with yes or no with a short explanation)
    
    Many thanks in advance.
    - Martijn van Mensvoort 31 May 2020 at 01:12
      
      Ronald, I actually have addressed the stratosphere inside the article and if you would have read my article properly you would have known that the answers to your other questions are also found inside the article (including your first point).
      
      I consider your suggestion regarding my reference to SPM.5 to be inappropriate because I have only made the reference to illustrate that ozone plays a major role in the IPCC framework (even though ozon often hardly ever gets mentioned in climate research); I have also referred to a few similar studies where ozon has a likewise role.
      
      I am sure that you must have misread my words because I only referred to the inconsistency that you addressed in your question (which I have confirmed).
      
      Beyond the impact of the sun, the major point involving ozone is that it’s footprint is in the empirical data while the footprint of CO2 is not in the data when the large impact of the sun is accepted. All that’s left is the spurious relationship between CO2 and temperature.
      - Ronald 31 May 2020 at 09:56
        
        Dear Martijn van Mensvoort,
        
        Thank you very much for the discussion. It was short and disappointing. I did not receive any inspiration from your side to try and answer my questions. With that you show no interest to create an atmosphere to discuss at scientific level. I am not going to waste further time.
        
        Best regards.
      - Martijn van Mensvoort 31 May 2020 at 10:51
        
        Ronald, you haven’t addressed the fact that you and I already have discussed things by detail at the climategate.nl platform:
        https://www.climategate.nl/2020/05/de-zon-zorgde-voor-11-c-opwarming-sinds-de-17de-eeuw/
      - Ronald 31 May 2020 at 12:29
        
        You are right Martijn, we have discussed already quite a lot through mail and on climategate.nl, but from my perspective there are still a number of crucial open ends that have not been answered.
        
        I hoped that “Science Talks” would be a platform to go in more detail to the open ends, but if you are not willing to answer my questions there is no science talk.
      - Martijn van Mensvoort 31 May 2020 at 13:18
        
        “… but if you are not willing to answer my questions there is no science talk.”
        
        Ronald, your words suggest that you have positioned yourself in a role to serve science… but your anonymous online identity shows that you are not capable to do this in an authentic manner.
      - Ronald 31 May 2020 at 15:13
        
        Besides not willing to answer questions, you now start talking nonsense in addition, Martijn. Peer review is anonymous too.
      - Martijn van Mensvoort 31 May 2020 at 15:37
        
        No Ronald, peer review is not ‘anonymous’ because the journal involved is well aware of the identities of the reviewers. So you’ve basically presented a false comparison.
        
        If you had presented me specific questions I would have loved to answer your questions instantly.
        
        (You’ve formulated a question suggesting that the correction should relate to “geophysical phenomena” – which shows how you are turning your thoughts away from the sun by means of rhetorics only because the correction that I have introduced involves solar physics, more specific: an effect that directly relates to the switching of the solar magnetic poles)
      - Ronald 31 May 2020 at 16:12
        
        Martijn,
        it’s you who makes the false comparison. In peer review the reviewer is anonymous to the author as I (the reviewer) am anonymous to you (the author of your paper).
        
        Second, I suggested to NOT apply a correction. You obviously missed that point.
        
        It is embarrassing that you allow the discussion of your paper to escalate to this level.
      - Martijn van Mensvoort 31 May 2020 at 16:50
        
        Ronald, you first 3 sentences in your #161 post reveal that your words were posted to disqualify my efforts instantly. For, you instantly started talking about about me (Martijn) as the object in your first sentence… and referred to “he” in your third sentence.
        
        Then your second #165 post you are suggesting that you had expected a response to your “first remarkt”… but the truth is that at the Climategate.nl platform you had already disqualified my new article on the night before it was presented at that platform, see 6 mei 2020 om 10:08 + 6 mei 2020 om 17:00:
        
        https://www.climategate.nl/2020/05/klimaat-voorspellingen-zijn-zoals-horoscopen-niet-geschikt-voor-klimaatbeleid/
        
        You probably wrote those words by impulse… and might have forgotten, but those words show the nature of your often rather subjective and interpersonal input; I could even share the details about how ‘Klaas’ got caught instantly.
        
        Using a pseudonym is one thing, but abusing a pseudonym is another thing.
        Apparently you do not value sincerity and straightforward communication.
        
        I have nothing to hide Ronald.
      - Ronald 31 May 2020 at 19:05
        
        “disqualify”? Even that is misunderstood by you. The remark is positive instead. I give you an alternative to make your point, without the need for the artificial corrections you had to apply in your paper to try and make your point. I actually offered you an opportunity here, but it was misinterpreted by you.
        
        By the way, I read your article already before publication on climategate.nl. It was freely accessible through your own website! Clearly, I knew what to expect the night before publication. So my words were not even of prophetic nature ;-).
        
        In my opinion, you are hiding yourself, i.e., behind words, by producing a lot of words but not willing to answer questions.
        
        Let’s try to finish this in a positive spirit, Martijn, with a question you should be able to answer. What is the status of the process of peer review of your paper? Did you receive feedback already from other sources? Clintel? Shaviv?
      - Martijn van Mensvoort 31 May 2020 at 23:11
        
        Ronald, get real… your very first point is not really different from what I actually described in the article via the ‘tip’:
        
        “TIP: Figure 10B + figure V show that since the end of the 19th century the solar cycle minima show that seawater surface temperature followed total solar irradiance continuously, with exception to the period between the mid-1980s and mid-1990s.”
        
        Indeed, your very first words in your first sentence sound as a positive start… but those words got spoiled immediately in the same sentence. Your words in terms of correlations are meaningless there because the dynamics that you propose are actually presented in a different format in my article. For, I have described that the strong relationship between sun and temperature is only not seen in the transition between the mid 1980’s and mid 1990’s… so I don’t see any fundamental difference with your description in terms of correlations.
        
        Therefore I consider you suggestion to represent nothing but inappropriate rhetorics.
        You are misleadingly suggesting that your words include something positive, all you’ve done there is to position yourself in a top dog position… because your suggestion does not offer any added value on top of the content that is already present inside the article.
      - Bas Post 31 May 2020 at 19:08
        
        Just a reminder of what André Bijkerk wrote a few days ago: “Obviously, the discussion below evolved from some scientific quality to mud throwing” (reaction #155). ANd again we see here: Martijn cannot answer the probing questions in a scientifically sound way, it degrades to ad hominem reactions.
        
        Martijn: anonymity is not a problem. It is WHAT somebody writes; not WHO that somebody is. But you have attacked me (#153) and now you also keep writing stuff about machineguns (#164; #171), although I have no idea what that is about (#167). You also made rather suggestive comments about Rob van Dorland on climategate.nl, after he was so kind to review your manuscript. Now you are attacking Ronald. Just grow up, and accept that you cannot give proper answers when scientists poke holes in your conviction. Just face it: you did not do a proper scientific analysis – you just tried to calculate towards a desired solution and made several mistakes along the way.
        
        Additionally, I also want to state that I agree with what Ronald writes, such as:
        “I hoped that “Science Talks” would be a platform to go in more detail to the open ends, but if you are not willing to answer my questions there is no science talk.”
        “I did not receive any inspiration from your side to try and answer my questions. With that you show no interest to create an atmosphere to discuss at scientific level.”
        “It is embarrassing that you allow the discussion of your paper to escalate to this level.”
      - Martijn van Mensvoort 31 May 2020 at 22:52
        
        Bas, so… after you posted your machine gun animation in #154, you have now positioned yourself to tell me in the name of science: “just grow up”.
        
        The truth is that you started your respectless trash talk rants in your very first post, which ended with the following rather ‘flattering’ words:
        
        “This article is not “sciencetalk”. It is pseudoscientific gishgallop to try to justify an ABC-theory (“Anything-but-CO2-theory”). A theory that does not explain the facts!”
        
        These words of yours do not resemble the fact that the CO2-temperature relation is the center of attention in both paragraph 1 and paragraph 2, where I have demonstrated that the data between the 1880’s and 1970’s shows that the solar-temperature relation is clearly much stronger than the CO2-temperature relation.
        
        Your improper and non-scientific use of language is reflected in your attempt to characterize my research as ‘anything but carbon’ (ABC) despite the fact that both my analysis and the article are basically heavily loaded with CO2 data analysis.
        
        So, you have not only been ignoring the empirical facts in your very first post… on top of that you presented words which basically represent rather aggressive ‘parrot-talk’ with characterizations for the content of my article which are basically out of touch with reality.
      - Bas Post 31 May 2020 at 23:53
        
        Martijn, your “paragraph 1 and paragraph 2” (actually, they are sections), are not scientific, and you definitely did not “demonstrate” anything in them in a scientifically correct manner. You claim that “between the 1880’s and 1970’s shows that solar-temperature relation is clearly much stronger than the CO2-temperature relation”, but that is only because you do the unscientific approach of only using the minima rather than including all the data (by using moving averages), and decided to stop in the 1970’s. The correlation between CO2 and sea surface temperature is in line with a vast knowledge base, but you simply dismiss all that by describing it as “spurious”.
        
        In my very first post, I listed 17 errors in your article. At the end of such a long list, I could not use “ ‘flattering’ words” to conclude. I could not call that article “sciencetalks” or describe it as “scientific”. With a text like that, you positioned yourself clearly as somebody who does not want to accept the scientifically very well documented AGW-theory, but you were unable to present scientific solid arguments for your own opinion that global warming is due to solar cycles. The blogosphere is full of these alternative “theories”, by non-scientific people who try to find anything as an alternative explanation for the global warming. Anything will do, except accepting that it is CO2. ABC… Anything-but-carbon.
Bas Post 31 May 2020 at 09:34

Martijn, you keep ignoring the questions I raised in my other reactions. You asked me over a week ago to give my top 5 of issues, to discuss them in “a more disciplined manner step by step”. Well, I gave you 2 issues, that I addressed in the previous messages. But you keep ignoring them, rather than discussing them in “a more disciplined manner step by step” (see reaction #167). Since you keep ignoring these questions, I will ask another important one, one that I also already mentioned in my very first reaction (#128).

In the LISIRD data (which is a mixed bag of all kinds of proxies), the TSI minima of 2008 and 2017 are higher than the previous ones. But in the satellite data of TSI (ACRIM, PMOD, …) these minima are much lower than the previous ones. This puts the validity of the LISIRD proxy into question. The difference between LSIRID and the satellite data has nothing to do with the “ACRM-PMOD controversy” that you refer to in your article, because the two satellite data sets both show a lower trend in this respect, which you do not see in LSIRID. That controversy is only a faulty argument that you bring in to confuse the reader. Even if you accept that the PMOD-data is not reliable, then the ACRIM-data still shows that there is a decrease in TSI, not an increase.

My question, Martijn, is: why don’t you acknowledge that the TSI is much lower in 2008 and 2017? What’s more, it is not just the minima, but the whole cycles that are less active. Can you give a scientifically sound explanation why you ignore this?
- Martijn van Mensvoort 31 May 2020 at 11:01
  
  Bas, your questions are merely provocative of nature: after I have at least tried to answer you questions… you responded repeatedly claiming that I have not addressed nor answered your questions.
  
  Your machine gun animation revealed the true nature of your input.
  - Bas Post 31 May 2020 at 18:48
    
    Martijn, two simple questions. Not “provocative of nature”, just assessing the facts:
    1. Are the solar minima of 2008 and 2017 as measured by satellite, higher or lower than the minima of 19986 and 1985?
    2. Are the solar minima of 2008 and 2017 as modeled using proxies in the LISIRD dataset, higher or lower than the minima of 1996 and 1985?
    - Martijn van Mensvoort 31 May 2020 at 19:16
      
      Ad 1) Higher, see: https://spot.colorado.edu/~koppg/TSI/TSI_Composite.png
      
      Ad 2) The LISIRD minima for the years 1985, 1996, 2008 and 2017 are not based on ‘proxies’, because those values are based on the “the instrument-based Community-Consensus TSI Composite for the recent era”. The LISIRD minima show a stable rise since 1985 see: h ttp://lasp.colorado.edu/lisird/data/historical_tsi/
      - Bas Post 31 May 2020 at 23:22
        
        Martijn,
        As Ronald wrote “In my opinion, you are hiding yourself, i.e., behind words, by producing a lot of words but not willing to answer questions.” It appears as if your reaction is not aimed to clarify, but to hide.
        
        In your Excel you show as LISIRD TSI-data for the minima of 2017; 2008; 1996 and 1985 the values 1.215; 0.979; 0.900 and 0.836 (add 1360 to get the actual LISIRD TSI). That is a steady increase for each cycle – “a stable rise since 1985”. The answer to question 2 is thus “higher”.
        
        Now look at w-ww.researchgate.net/figure/Comparison-of-the-ACRIM-and-PMOD-Composite-TSI-time-series-The-most-significant_fig5_262376602. This comes out of your own reference 26, by Willson et al (2014). There it is clear that the minimum of 2008 is lower than the one of 1996 and possibly also of the one of 1985. (2017 was not yet available). The answer to question 1 is thus “not clear”.
        
        Now look at w-ww.mdpi.com/2072-4292/11/21/2569/htm#. That is reference 27 in your article, by Scafetta, Willson, et al (2019). It states: “the quiet solar luminosity increased from the 1986 to the 1996 TSI minimum by about 0.45 W/m2 reaching a peak near 2000 and decreased by about 0.15 W/m2 from the 1996 to the 2008 TSI cycle minimum.” So 1996 and 2008 are lower. The answer to question 1 is thus “lower”
        
        Based on the references you supplied yourself, you should thus conclude that there is no clear consensus on what the actual TSI-values are and if there is “a stable rise since 1985” or not. You only used LISIRD and ignored the issue that other datasets will give you other results. Your correlations will be different if you were to use other TSI-values. You do not appear to be willing to address this issue.
        
        (And neither do you appear to be willing to clarify why you only use the years around the minima, rather than a moving average. And neither do you appear to be willing to clarify what you conclude about CO2 from figure SPM5)
      - Martijn van Mensvoort 31 May 2020 at 23:51
        
        Bas, your nuances regarding what the satellite measurements indicate are fully accurate.
        
        I should have mentioned that my answer to your first question also relates to the ‘Community-Consensus TSI Composite’ that I mentioned for your 2nd question.
        
        As a matter of fact, you should be aware that the measurements for all 4 minima that you mentioned have been produced by different satellite systems and for all 4 minima there are multiple satellite systems available which have produced different values… and all values need corrections because the satellite technology deteriorates instantly from the moment of first activity due to UV radiation. For this reason the TSI satellite technology has to get replaced after a few years.
        
        This picture gives you an idea involving the raw measurements:
        https://spot.colorado.edu/~koppg/TSI/TSI_sm.png
        
        (So, there are indeed no definitive answers available; one should also be aware that all measurements require corrections)
      - Ronald 1 Jun 2020 at 22:53
        
        Yes Bas, it is good to see that Martijn acknowledges the need for homogenization. On climategate.nl this is always linked to conspiracy theories, but merely because these people are ignorant on working with measured time series from different instruments.
        
        I also pointed Martijn a couple of times to the uncertainty in the TSI data sets and recommended him to take this into account into his correlation calculations by adding error bars, reflecting this uncertainty. This could have undermined his firm conclusions but on the other hand would have made the analysis scientifically more sound. Martijn has chosen to walk the scientifically less sound pathway by ignoring the uncertainty of the TSI data sets.
      - Ronald 1 Jun 2020 at 22:56
        
        i.e., ignoring the uncertainty of the TSI data sets in his quantitative analysis
      - Ronald 31 May 2020 at 23:52
        
        “get real”? Well, I am real. What I suggested is to make a correlation plot over time of (TSI_min,T). Then you would see high values from end 19-th century up to the mid ‘1980s followed by a small decrease (orange dashed box), but an increase again after the mid ‘1990s. For me that would have been much more convincing than applying some artificial correction, based on stratospheric ozone depletion, to keep the correlation at a high level over the complete period as you do in Figure 10c.
        
        You are too much focused on high/perfect correlations in your work. It is more realistic to accept the presence of geophysical phenomena (besides the sun and stratospheric ozone depletion), mentioned e.g. in the figure of SPM.5 to which you refer, which also impact the global mean temperature but reduce your correlations because you do not take these into account in your analysis. I would accept lower correlation values, because of excluding certain geophysical phenomena, more than artificially pumping up correlations to get as close as possible to a value of 1.
        
        That was my positive recommendation to you, which will make your paper much more easy to sell and makes it much less complex, because you can skip the complete stratospheric ozone layer depletion impact part, which to my opinion is a weak part in your paper.
Bas Post 8 Jun 2020 at 19:39

Martijn,
You show four datasets for TSI in the Excel table in your article: LISIRD, IPCC AR5, Satire S&T en NRLTSI2. They cover the period from 1850 to present. You claim in your section VII that there is “internal consistency between the 4 TSI data sets”, but that statement is very misleading: you only compared the period from 1880 to 1985. I have made a plot of all four of them. This way, I notice that for the periods before 1880 and after 1985, the LISIRD dataset that you use, is quite different from the three others. Specifically, after 1985, the three others show a plateau and even a drop, whereas LISIRD goes up. There clearly is NO “internal consistency between the 4 TSI data sets”. The correlation between LISIRD and Satire S&T is only 0.55!

The satellite data, shown in the references 26 and 27 in your article, also show that the TSI is going down in the last few decades. Also, the number of solar spots is going down (at the minima as well as at the maxima). The latter suggests that this drop of TSI in most datasets is not due to “the satellite technology deteriorates instantly from the moment of first activity due to UV radiation” (as you claimed on 31 May 2020 at 23:51).

Taken together, this raises serious questions why you only rely on LISIRD, and don’t even mention that this dataset is different from all other available datasets. It is convenient that this LISIRD dataset helps you to “prove” that there is a correlation with temperatures. With all your “corrections” and for the minima from 1880 to 2017, you get a correlation of 0.92 between HadSST3 and LISIRD. But if you apply the same “corrections” on the NRLTSI2 data, you only get 0.68. Since you had the data right from the start, I would assume that you knew that the correlation of the other datasets with HadSST3 temperatures is much lower. But you did not mention this at all in your article.

You wrote in that latest reaction even that no dataset is conclusive: “So, there are indeed no definitive answers available; one should also be aware that all measurements require corrections”. Since you admit this, it makes is very questionable that you didn’t even mention this in your article, and that you don’t justify why you only use this one dataset and ignore the other ones. That is a very questionable attitude, verging on the fraudulent.

Your only argument to use LISIRD, seems to be “in the view of LASP’s principal investigator Greg Kopp (figure 13) it does present the best values available to the experts”. Since Kopp is the person who developed LISIRD, he hardly counts as a neutral person, so using his claim as your only argument, is a very weak argument. Basically, you do not appear to have any argument to use only LISIRD and ignore that it is different from all other datasets. LISIRD helps you to “prove” what you want to believe, but that is not a scientific approach. Knowing that the other ones exist but not presenting an analysis with them, is in the ‘best’ case dubious science, in the ‘worst’ case it is fraudulent science.
Martijn van Mensvoort 8 Jun 2020 at 23:53

Re: “The correlation between LISIRD and Satire S&T is only 0.55!”

The correlation for both data sets for the full period (1850-2012) is 0,81 and for the period since 1979 the correlation is 0,87.
You didn’t mention whether your 0,55 value involves the minima, however, you are probably ignoring the aspect involving the ACRIM-PMOD controversy which involves the periode sinds 1979 because the Satire S&T is based on the PMOD method and the LISIRD is not.

Only a few days ago you send me an (aggressive) email accusing me for not sharing the IPCC AR5, Satire S&T and NRLTSI2 data in de Excel file, even though the data is actually present in the file. Now that you have found the data you are ignoring other aspects of my paper, e.g. the fact that the analysis in figure 11 describes only a high internal consistency for the pre-satellite era.

Also, you have now started attacking the author of the LISIRD data set, despite his expertise and valuable work (he played a key role in 2008 establishing the now accepted lower TSI value of 1361 W/m² representative of solar minimum, while there was no consensus about this before until 2008).

The quality of your input is rather subjective and of and shows a lack of quality & ethics.

I guess you are probably overestimating the quality of your feedback on merely subjective grounds and you appear to cherish rather unrealistic perceptions about how to practice science + how to participate in a proper scientific discussion in a decent manner. Your efforts appear to be not much more than a series of mud throwing based on a combination of arbitrary & false arguments.

Your use of a machine gun animation in your 25 May 2020 at 22:02 post (which is now featured with a comment made by the editor: “link removed, mod”) is illustrative for the nature of your input.

Unfortunately your lack of response to my request is hardly a surprise because your behavior has been publicly exposed here in Dutch language:
https://www.climategate.nl/2020/04/klimaatpsychose/

You have been caught shamelessly using multiple anonymous usernames and you have given the impression that your username ‘Bas Post’ is probably also a fake identity.

I have already informed you via email that I will be ignoring your input in the future because your communication skills show a nasty combination involving a lack of decency, accuracy and even authenticity. Your ideas about ‘fraudulent science’ are way out of context here; at least I have shared all aspects of my data analysis publicly… Manning has actually refused to do that, even after court has declared that it would be appropriate to share his data publicly in the name of science.

I have asked you to adjust your communication style into a decent banner, but you’ve chosen to ignore my request.
Bas Post 9 Jun 2020 at 08:08

“The correlation for both data sets [LISIRD and Satire S&T] for the full period (1850-2012) is 0,81 and for the period since 1979 the correlation is 0,87. You didn’t mention whether your 0,55 value involves the minima”
Remarkable! Suddenly it is important for you to look at all the years, rather than at the minima! When it is convenient for you, you want to use all data, but in your whole article, you ignore most years and consider the minima “more relevant”. Don’t you see how absurd your arguments are?
Just a reminder: the correlation between ocean temperature (HadSST3) and LISIRD is 0.65, when you take all years into account and use 11-year moving averages. When you compare ocean temperature and CO2, then you find 0.91. But that is something you ignored right from the start!

I don’t “started attacking the author of the LISIRD data set”. I only pointed out that it is not scientific to blindly believe him. Don’t you understand the difference???

The remainder of you message is only personal attacks, which I have previously addressed (“25 May 2020 at 22:02”; “31 May 2020 at 09:18”; various emails,…). I will therefore just limit myself to the scientific arguments and ask (again and again and again) the scientific questions (that you continue to fail to address):
1/ what is your scientifically sound justification to ignore 75% of all the years? (I already asked yu that a month ago in reaction to your Dutch version of the text, and repeated it at least a dozen times, but you fail to answer this)
2/ why do you accept one aspect of Figure SPM.5, but not the entire figure, since it is one analysis?
3/ why don’t you acknowledge that the TSI is much lower in 2008 and 2017 according to all but the LISIRD dataset? What’s more, it is not just the minima, but the whole cycles that are less active. Can you give a scientifically sound explanation why you ignore this and only use this dataset in your ‘analysis’?
4/ Why do you ignore the high correlation between temperature and CO2, although this is in line with a vast knowledge base, but you simply dismiss all that by describing it as “spurious”?
- Martijn van Mensvoort 9 Jun 2020 at 11:25
  
  Nearly all aspects you’ve mentioned are addressed and explained in the article.
  
  Your final point shows the poor nature of your feedback: even though I have explained why the spurious nature of the high CO2-temperature correlation by detail… you are suggesting that I “ignore” this. You’ve presented arguments which are merely rhetorical of nature.
  
  (Meanwhile I have found that the scientific literature actually confirms that the impact of the sun on climate is much higher in the long term perspective; energy buffering inside the ocean system plays a key role in this matter, especially on the long term. The impact can vary from a factor 2 up to 10 relative to 11-year cycle depending on the timespan involved. In my research the impact turns out to be between a factor 4 and 5 for the period 1890-1985 in a comparison between with the 22-year cycle. The details will be shared in the scientific concept, which will be presented later this month)
  
  PS. I experience far most of your feedback to be unrealistic and counterproductive, so it would not make much sense for me to continue responding to your input in the future because I perceive most of your arguments do not really put things in a sensible perspective. I have addressed your unusual and rather provocative behaviors in my preceding post 8 Jun 2020 at 23:53.
  - Bas Post 9 Jun 2020 at 18:13
    
    “Nearly all aspects you’ve mentioned are addressed and explained in the article”
    It’s interesting that you use the word “nearly”…
    
    Anyway, I know you have addressed these “in the article”, but you ignore that I have already on many occasions pointed out what is wrong with your ‘explanations’ i“in the article”. You have never replied with solid scientific argument on any these comments from me. It is obvious that you cannot give clear, scientific answers. Again what you write today is a vague reply, that boils down to “somewhere I wrote something…”, but you don’t clearly explain what you wrote and where you wrote it. You try to create a smokescreen, rather than giving clear ansers(which you can’t give off course, but you do not want to admit that, and are not capable of simply keeping quiet when you are wrong).
    
    Regarding these 4 issues:
    1/You refer “in the article” to an IPCC-report to ‘justify’ why you limit your analysis to the solar minima. This is an “argument from authority”, not a scientific argument. But more importantly, Rob van Dorland has already informed you a month ago that you misinterpret what is written there. I also pointed it out in my reaction here (31 May 2020 at 09:18). But you have never admitted that you misinterpreted that sentence. It simply is not a justification to use the minima. So you have never given any (scientific) justification why you only use the minima.
    
    2/You have never explained why you accept only one part of Figure SPM5, but don’t want to accept that it also clearly shows that CO2 is the main driver for the global temperature increase. I asked you at least a dozen times to explain what you conclude from the whole of this figure, but you keep stubbornly ignoring that question.
    
    3/ You halfheartedly accepted that LISIRD shows an increase in TSI in the most recent decades, whereas no other dataset shows this. But you have not given a solid scientific argument why you ignore all these other datasets in your ‘analysis’. Only relying on the say-so of the person who developed the dataset, is not a scientific argument to only use this one and ignore the others (it is again an “argument from authority”). Ignoring the poor correlation you obtained with all the other datasets, is simply unscientific. You have to look at all the datasets and present and discuss the data –not in a misleading way as you did in “Paragraph VII”, but including all the minima (since you consider the minima as important)– but in a scientifically sound way. What do you conclude from the poorer correlation between temperature and the other datasets?
    
    4/ You claim that there is no “unambiguous mechanism in terms of cause and effect” between CO2 and global warming. The greenhouse theory is not just based on “consensus”– it is based on scientific analyses. It is simply untrue that “CO2 follows temperature and not the other way round”. These sentences “in the article” show clearly that you base yourself on what you read on blogs, not what you can learn from the vast scientific knowledge on CO2 and global warming.
    
    About your second-to-last paragraph: that is again an attempt to distract: you do not address the questions, and you come with vague and irrelevant arguments. You plan to present more ‘analyses’ later this month? How about this: send the manuscript to me before it is made public and I’ll do a peer review (maybe Ronald wants to do this too?). Then you can adapt it BEFORE it is public, which may save you a lot of embarrassment from all the errors I might point out.
    
    About your “PS”: why do you always try to make it an attack on the messenger, rather than addressing the message? It makes it all the more obvious that you have no solid scientific arguments to answer my scientifically justified questions…
ronald 9 Jun 2020 at 13:18

Martijn,
May be you are willing to explain how you arrived at the value of 0.123 W/m^2 increase you applied to the secondary minima?
- Martijn van Mensvoort 9 Jun 2020 at 13:32
  
  The number 0,123 W/m2 is just a pick indicative for what is required to find a consistent correlation both the combined primary and secondary values.
  
  PS. In the next article I present a more precise method based on the average correlation value for the primary and secondary values in the period 1890-1985; for the 3-year minima values this procudes a correction value of 0,114 W/m2. For 1-year up to 9-year minima periods the correlation value is always found in the bandwidth 0,110-0,142 W/m2… so the value 0,123 W/m2 turns out to be close to the average of this bandwidth.
  - ronald 9 Jun 2020 at 14:05
    
    Ok thanks, just a pick to get consistent overall and primary correlation values, no physical meaning. By the way, a correction value of 0,100 W/m^2 would have maximized the combined correlation to a value of 0.936, but probably at the expense of consistency between overall and primary correlation values.
    - Martijn van Mensvoort 9 Jun 2020 at 14:26
      
      The value 0,100 W/m2 will produce results good enough to see the basis effect. The size of the correction is similar to the size of the structural effect in the Gnevyshev-Ohl rule, which involves the flipping of the solar magnetic poles.
      
      So, the key-matter here is that the TSI-temperature relation shows a structural difference between the primary and secondary values. The use of a correction makes this effect (due to the flipping of the solar magnetic poles) visible… and thus it has indirect physical meaning via the Gnevyshev-Ohl rule.
      
      Formally the use of the correction value is not necessary in order to compare minima values; however, then one has to face the impact of the 22-year cycle by separating the primary minima from the secondary minima.
      
      (In the new article I will show that the Gnevyshev-Ohl rule shows for the LISIRD and sea surface temperature a similar structural effect for both the maxima and minima; I will describe how solar wind is directly involved in producing the temperature effect. Also, I will present a source which confirms (based on analyses involving the Maunder minimum and the Medieval warmth period) that the 22-year cycle is more relevant for the solar impact on climate than the 11-year cycles… so my observations involving the period 1890-1985 make sense for other periods back in time where climate has been dominated by natural forces with a prominent role – there is considerable consensus that until 1950 the climate system has been dominated by the sun)
      - ronald 9 Jun 2020 at 16:23
        
        Yes, I agree there is consensus that until 1950 the climate system has been dominated by the sun. I would like to add stratospheric aerosol (volcanoes) to that. But the impact of volcanoes is only on small time scales of several years, but potentially active on TSI minimum/maximum years, hence impacting global mean temperature in those years which in turn has an effect on the (TSI_min,T) correlation. On the long term I would say that volcanoes act as noise in temperature records.
        
        The question then is why did the sun dominate only until 1950 and no longer afterward? In other words, which phenomenon started to dominate (thus overrule the sun) the climate system after 1950?
Martijn van Mensvoort 9 Jun 2020 at 17:28

Re: “The question then is why did the sun dominate only until 1950 and no longer afterward?”

I think your question is preliminary, because after 1950 the controversy actually becomes more apparent:

The so-called consensus assumes that solar influence peaked in the last ’50-s because of high TSI maxima based on just two solar magnetic factors (Lean et al., 1995); however, there are other expert models featuring more than just 2 factors which indicate that TSI maxima peaked much later in the 20th century.

(The new article will describe that the correction basically also works for the maxima; however, for the maxima the impact is less relevant because the loss for the combination of the primary and secondary maxima is much lower compared to the minima combination)
- Bas Post 9 Jun 2020 at 18:16
  
  “The question then is why did the sun dominate only until 1950 and no longer afterward?”
  The answer can be found in these figures:
  .ipcc.ch/report/ar5/wg1/anthropogenic-and-natural-radiative-forcing/fig8-18-2/
  .ipcc.ch/report/ar5/wg1/anthropogenic-and-natural-radiative-forcing/fig8-19-2/
  
  To put it in perspective: the radiative forcing of the sun is around 0.1 W/m2.
  
  This is not a “so-called consensus“. This is the result of scientific analyses.
- ronald 9 Jun 2020 at 19:04
  
  Yes Bas, that’s also a good point, but if I understand Martijn correctly then the sun can be made fully responsible for the global climate until 1950 by considering TSI minima alone. However, considering TSI minima alone cannot explain the global climate after 1950. Am I right, Martijn?
- Martijn van Mensvoort 9 Jun 2020 at 20:09
  
  Ronald, my next article will show that according the LISIRD the sun can explain global climate very precisely for the periode 1912-1965 with an explained variance of 99%.
  
  IPPC figure 8,18 shows a forcing for the 11-year solar cycle at the order of ~0,2 W/m2 based on just the TSI values measured at the top of the atmosphere after adaptation for earth’s surface (0,175% of TSI TOA due to earth’s surface + Albedo).
  
  Figure 14 in my article shows that the actual solar cycle effect measured at earth’s surface is actually 5-7 higher: ~1,3 W/m2.
  
  So, the IPCC assessment does not explain the fact that the impact of the 11-year solar cycle is much higher than what the TSI solely suggests. Also, the IPCC model does not take into account the impact of the amplification factor of the solar signal e.g. through solar magnetism & solar wind, which are two factors that are not being taken into account.
  
  PS. The IPCC is using the PMOD which shows a downtrend for the minima since 1985… which is contradicted by the minima in the LISIRD data set & Belgian RMIB minima data which both show a consequent upward trend for the minima in the same period. One should also be aware that the ACRIM data is not far away from what LISIRD & RMIB show… but more importantly: the scientific validity of the PMOD model has been rejected from the start by multiple top level research teams since the 1990’s. This involves the issue that became known among solar expert teams as the ACRIM-PMOD controversy. The IPCC is basically denying this controversy in their model, they only acknowledge a small aspect of the controversy:
  
  “Although this indicates that metrics based only on TSI are not appropriate, UV measurements present several controversial issues and modelling is not yet robust.”
  
  Quote from page 690: https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter08_FINAL.pdf
  - ronald 9 Jun 2020 at 20:53
    
    It’s a pity that you did not answer my question, but instead introduce a new period. This time covering only 53 years. 99% is amazing! But only if it does not drop fast before and after this period. So, this makes me curious to the number for the subsequent 53 year period: 1965-2018.
  - Bas Post 9 Jun 2020 at 21:49
    
    “the periode 1912-1965”
    Why is this period relevant? And why did you not answer Ronald’s question?
    
    “Figure 14 in my article shows that the actual solar cycle effect measured at earth’s surface is actually 5-7 higher: ~1,3 W/m2.”
    This figure comes from a document (by Svensmark) pretending to be a scientific text but published by a known lobby-group. That is not a proper way to present a scientific argument. But if you dig deeper, the nyou find it is based on a publication by Shahiv.
    He finds a correlation, but cannot present any explanation. So there is no indication that there is a causation, or that an amplifying effect really exist. This was an article published in 2008, but since then, it looks as if neither he nor anybody else has been able to present any further evidence for the existence of such an amplifying mechanism. But you seem already accept this as proven!
    
    “Also, the IPCC model does not take into account the impact of the amplification factor of the solar signal”
    Well, first start presenting any evidence that such an amplification factor exists, and then the reviews by IPCC will take these into account!
    
    “the minima in the LISIRD data set & Belgian RMIB minima data which both show a consequent upward trend for the minima in the same period”
    And why should we only be looking at the minima, and not the whole cycle? This is one of the questions I asked that has remained unanswered ever since I asked it a month ago… You based the use of only the minima on a misinterpretation of one sentence in an IPCC report, and have never acknowledged this mistake you made. You keep ignoring this mistake and continue to go on as if nothing happened, just like you continue to ignore three other issues that don’t fit with your conviction (see “Bas Post 9 Jun 2020 at 18:13”).
    You write here now “The IPCC is basically denying…”, but in reality you are denying a lot of crucial issues yourself, not addressing the issues that I have raised, and are known to misinterpret what the IPCC writes.
Martijn van Mensvoort 9 Jun 2020 at 23:11

Re: Ronald “However, considering TSI minima alone cannot explain the global climate after 1950. Am I right, Martijn?”

In my article I address the combination of the sun combined with ozone, so I don’t think recognize the relevance of your question; in my response I have addressed that according my research the relevance of the sun does not end near 1950 because the period 1912-1965 shows an almost perfect explained variance.

(If you had read my answer properly you could have noticed that I actually did answer your question, but not with just a simple yes or no… your question is basically too narrow minded because no single factor can explain temperature development after 1950 including the drop in temperature until the late ’70s, but my article does describe that 2 factors explain 96% of temperature developed after 1950 via the 3-year minima)
- ronald 9 Jun 2020 at 23:56
  
  Well, ok, so the simple answer was that I was right that TSI minima alone cannot explain the global climate after 1950. Ok, that’s clear now, although you left it to me to confirm.
  
  Ps. Please don’t blame me for bringing up the year 1950, it came from you: “there is considerable consensus that until 1950 the climate system has been dominated by the sun”.
  
  And suddenly you upgrade to 1965! Ok, but now you started in 1912 and no longer in 1890 as before. Curious and no idea, why.
  
  And then it becomes interesting with your remark: “your question is basically too narrow minded because no single factor can explain temperature development after 1950”. I fully agree with that. On the other hand a single factor does explain temperature development before 1950. That’s amazing. Or not? One single factor only! Controlling the complete temperature development before 1950 (I did not see another mechanism in your analysis before 1950).
  
  Anyway, so what changed around 1950? What changed the sun dominance? Your answer: a second factor. Ozone! Well, more specificly, stratospheric ozone, the ozon layer, which got thinner, due to us, humans. Yes, humans can change climate. We agree on that. But according to your paper, figure V, stratospheric ozone starts to play a rol not before 1975.
  
  So that means that the sun was dominant not only until 1950, also not until1965, but at least until 1975! Where does this end?
  - Martijn van Mensvoort 10 Jun 2020 at 00:45
    
    Ronald, I think you are just fooling around with my words because I basically only mentioned regarding the year 1950 that there is considerable agreement that the period before 1950 is especially suitable for studying the influence of the sun. However, one can not draw any direct conclusions from that… except that there is considerable agreement that the influence of the sun became smaller after 1950, but that largely relates to the unexplained relationship between the solar cycle and temperature + the TSI peak (based on just 2 magnetic solar components) in the late 1950’s .
    
    For example these 2 perspective do not confirm the relevance of the assumption regarding the year 1950:
    
    – The TSI method presented by Hoyt & Schatten (1993) based on 5 solar magnetic components produces a graph which shows that temperature has followed the TSI a few decades longer, see: https://www.researchgate.net/figure/Comparison-between-the-updated-Hoyt-Schatten-Total-Solar-Irradiance-trends-red-dashed_fig19_282389821
    
    – But Prof. van der Werf describes in his 2014 AMO study using a 11-year solar cycle temperature amplitude of not much more than 0,01 K that CO2 already started slowly kicking in since the rise of temperature from around ~1910
    
    So, in my perception your short question sort of explores the opposite of my statement involving the year 1950, so I don’t think it serves any solid purpose.
    
    (By the way, I mentioned the period 1912-1965 because my next article will describe that this period has a 99% explained variance for the 1-year minima, which indicates that the period until at least 1965 is very suitable for studying the influence of the sun… but even the period until 1985 still shows a 91% variance for the 1-year minima – the percentages involve a correction value of 0,142 W/m2, see: http://klimaatcyclus.nl/klimaat/pics/LISIRD-TSI-vs-HadSST3-average-values-for-solar-minimum-years-plus-3Y-5Y-7Y-9Y-and-11Y-minima.jpg )
- Bas Post 10 Jun 2020 at 08:09
  
  “If you had read my answer properly you could have noticed that …”
  Martijn, you should practice what you preach: read texts properly. In your reference ,9 you quote from an IPCC report:
  
  “Trend analysis are usually performed over the minima of the solar cycles that are more stable. … Maxima to maxima RF give a higher estimate than minima to minima RF, but the latter is more relevant for changes in solar activity.”
  
  Rob van Dorland has pointed out to you already a month ago, “IPCC bedoelt hier dus dat als je langjarige trends wil afleiden dat je dan niet begin en eindpunt van je reeks in verschillende fases van de zonnevlekkencyclus moet nemen.” (“IPCC makes it clear that if you want to determine long-term trends, you do not take the start and end of your series in different phases of the sunspot cycle.” ). In other words, IPCC says you should start and end at minima, or you start or end at maxima. They prefer starting and ending at minima, because they are “more stable”. That’s all they said. You must analyse all the years between start and end using moving averages. That’s what the IPCC says there. This sentence does not mean that you can discard 75% of the data. That is what van Dorland also states. That is the point I made several times already. That is what you conclude from that sentence “If you had read it properly.
  Your reply to van Dorland made it clear that you did not understand the point he made, that you DID NOT read his comment properly.
  
  You CANNOT do any analysis just by using the solar minima. That DOES NOT make scientific sense. You HAVE NEVER given any sound scientific explanation why this should be relevant. Any conclusion from such analysis is completely irrelevant. You fail to accept this. All your analyses, all your texts, all your reactions are scientifically irrelevant because you base them on the unscientific assumption that you can draw conclusions just by using the data from the solar minima and ignore the remainder of the solar cycles.
  
  Add to that (as Ronald just pointed out): that you are also changing the start and end years of the periods you analyse all the time without any scientific justification.
  Add to that: for the period of 1912-1965 and your “explained variance of 99%”, you are most likely doing overfitting (but I suspect you have never heard of that term).
  Add to that also: you are assigning too much importance to the actual values of the correlation coefficients and beleiving that 0.92 is more important than 0.88 (rather that the correct interpretations of seeing them just as being indicative)
  Add to that: you even suggest that these correlations prove causative effects (“explain”).
  … and your conclusions are entirely unscientific and unjustified.
  
  Sorry that I have to be so crude, but I don’t know (after a month…) how otherwise to explain to you that your analyses are meaningless.
  - Martijn van Mensvoort 10 Jun 2020 at 13:30
    
    Van Dorland has not even mentioned the 2nd part which is quoted for source 9.
    Those words describe explicit that the minima (to minima) are “more relevant” than the maxima (to maxima):
    
    “Maxima to maxima RF give a higher estimate than minima to minima RF, but the latter is more relevant for changes in solar activity.”
    - Bas Post 10 Jun 2020 at 17:52
      
      Martijn, you keep repeating these sentences of the IPCC report. Just repeating it without further explanation, is not very constructive, especially when I already pointed out that you misinterpreted this text and when I have asked you several times to present a proper, scientifically sound, argument why you believe you can remove 75% of the data.
      
      That the minima are “more relevant” does not mean you can just ignore all the other years. What is more interesting, is actually the sentence that you did not use in your citation from that report:
      
      “Trend analysis are usually performed over the minima of the solar cycles that are more stable. For such trend estimates, it is then better to use the closest SC minimum, which is in 1745. To avoid trends caused by comparing different portions of the solar cycle, we analyze TSI changes using multi-year running means. …. a 7-year running mean RF between the minima of 1745 and 2008.
      
      So the IPCC DOES NOT use only the minima and ignores all the other years. They use running means. With “over the minima”, they mean “starting and finishing at a minimum”. In these additional sentences (that you omitted from your citation), they make it clear that they start at the minimum of 1745 and end at the minimum of 2008, because they are more stable points to start and end and so they “avoid trends caused by comparing different portions of the solar cycle”. It is blatantly clear from their entire description that you must analyse all the years between start and end using moving averages. That’s what the IPCC says there. At no stage do they say that you can discard 75% of the data and only work with the minima.
      
      But still, you keep repeating the phrases that suit you, ignore the whole context of these sentences, believe that these phrases justify removing 75% of the data, you ignore what the IPCC actually conveys and what they did and did not write. I can only repeat:
      
      You CANNOT do any analysis just by using the solar minima. That DOES NOT make scientific sense. The IPCC never suggested that. You HAVE NEVER given any sound scientific explanation why this should be relevant. Any conclusion from such analysis is completely irrelevant. You fail to accept this. All your analyses, all your texts, all your reactions are scientifically irrelevant because you base them on the unscientific assumption that you can draw conclusions just by using the data from the solar minima and ignore the remainder of the solar cycles.
      
      Sorry that I have to be so crude, but I don’t know (after a month…) how otherwise to explain to you that your analyses are meaningless.
- ronald 10 Jun 2020 at 09:27
  
  Valid points Bas, but let me first try to finish my discussion with Martijn. I’m almost there.
  
  Martijn, you mentioned 99% explained variance for the period 1912-1965 by the sun alone. You did not explicitly answer my question on explained variance by the sun alone in the subsequent 53 years: 1965-2018, but from your indirect answer I conclude it must be much smaller due to stratospheric ozone depletion. If you add the latter then you can explain over more than 90% of the temperature variance by sun + stratospheric ozone depletion. Great!
  
  Then, there is one remaining thing which I do not get clear. You state in your paper: “this implicates that ozone depletion has contributed to the warming of the lower atmosphere“. But, ozone is a greenhouse gas (GHG). I think we agree on that. Removing a GHG does cool the atmosphere (reduce radiative forcing, also nicely visualized in the top panel of Figure SPM.5 in IPCC AR5) not warm it. The ozon hole implies GHG reduction, but how can GHG reduction cause warming?
  - Martijn van Mensvoort 10 Jun 2020 at 13:11
    
    Ronald, in theory greenhouse gasses do not have the same impact in different atmospheric layers; for example, the Greenhouse theory describes that more CO2 in the atmosphere produces warming in the troposphere and cooling in the stratosphere. So. processes are much more complex than just the simple logics involved with the idea that a greenhouse gas generates warming.
    
    Figure SPM.5 shows that there are also mechanisms in opposite directions present for ozone. For example, due to depletion of the ozone layer more solar radiation (especially UV) will reach the troposphere, which contribute to the warming. This mechanism is also described in paragraph 1 in my article (looking back I should have mentioned the aspect of the opposite dynamics involved with ozone in figure SPM.5 in order to make my point more specified).
    
    When we assume that the IPCC is underestimating the impact of solar irradiance (which is realistic because they only account for TSI but they ignore the aspect involved with the amplification of the TSI signal because the impact of TSI is a factor ~5 higher), the logical consequence is that they overestimate the tropospheric warming effect of the greenhouse gasses… including ozone.
    
    (Assuming that this is part of reality this would have significant impact for the weights of the numbers presented by the IPCC in SPM.5, etc.)
    - ronald 10 Jun 2020 at 13:47
      
      Thanks Martijn, this is exactly the reply I expected. In your paper you introduced figure SPM.5 to make a point regarding ozone and its role in the global mean temperature: “Figure SPM.5 in IPCC AR5 confirms that ozone [O3] can be held responsible for a significant contribution to the warming of the atmosphere.”
      
      In the mean time you have denied almost all messages the figure brings forward, including the message regarding stratospheric ozone.
      
      The message regarding the latter is that halocarbons destroy ozone in the stratosphere causing a negative radiative forcing, hence cooling. In other words, the ozone hole causes cooling, not warming.
      
      The conclusion is that you have used the impact of the ozon hole on the global mean temperature in the wrong direction ………
      - Martijn van Mensvoort 10 Jun 2020 at 14:41
        
        Ronald, I repeat: I think you are just fooling around with my words.
        
        In this other AR5 chart (figure 8-15) we can see more explicit that the IPCC is not sure at all about the direction of the stratospheric ozone effect because the bandwidth covers both negative and positive values:
        https://i1.wp.com/www.climatechange2013.org/images/figures/WGI_AR5_Fig8-15.jpg
        
        This bandwidth is not shown in figure SPM.5… but figure 8-15 shows that they actually do think it is possible that ozone depletion has contributed to the warming of the lower troposphere.
        
        So, I have described the basic mechanism (ozone depletion results in more UV solar irradiance in the troposphere, we don’t really understand the impact); sources 42 & 43 confirm explicit in a similar manner like I did in my analysis that depletion of the ozone layer has contributed to the warming of the lower troposphere.
        
        (I repeat: Ronald, your process of thought is far too narrow minded because you only talk about uncertainties whenever you think it suits you… but here you are basically ignoring the uncertainties involved with ozone. Therefore you perception about me using ozone in the “wrong direction” is just a rhetorical argument that has no value in the perspective of the empirical reality which I have described in my analysis – featured with sources which present a similar analysis via a different route)
      - ronald 10 Jun 2020 at 16:17
        
        Martijn,
        with your response you confirm my statement that you have denied virtually all messages figure SPM.5 brings forward, including the message regarding stratospheric ozone. On the other hand you included a reference to this figure in your paper to make a point. I find no logics in doing this. You also deny virtually all messages from figure 8-15, so bringing up that one to make your point also lacks logic.
        
        Indeed, ozone depletion results in more UV solar irradiance in the troposphere, but also upwelling heat radiates more easily to space due to ozone depletion. You only told half of the story ……
        
        So yes, based on your reference figure SPM.5, you have used the impact of the ozon hole area (figure V) on the global mean temperature in the wrong direction.
        
        Ps. From your figure V, you can also conclude that the impact of stratospheric ozone is of the some order of magnitude as the impact of the sun. Your new figure 8-15 then gives a good indication of the impact of the sun on the radiative forcing by using stratosferic ozone as a proxy. And surprise, surprise, it agrees pretty well with the last row in figure 8-15: Solar irradiance.
        
        So what you have nicely demonstrated in your paper is that the impact of the sun on the global mean temperature compares well to that of stratospheric ozone, which is almost negligible from figure 8-15 and Figure SPM.5.
        
        Actually, with your paper you have nicely confimed IPCC findings!
      - Martijn van Mensvoort 10 Jun 2020 at 16:47
        
        Re: “Actually, with your paper you have nicely confirmed IPCC findings!”
        
        I repeat: you are just fooling around with my words because.
        
        (You are ignoring my assessment regarding the spurious nature of the CO2-temperature relation + that my regression analysis shows that the impact of CO2 is actually rather small + the fact that the IPCC is ignoring the amplification factor involved with the TSI signal)
        
        PS. In your last response you’ve ignored my point involving the fact that the IPCC model shows a pretty high level of uncertainty regarding the direction of the ozone effect… so you earlier comment where you assumed that my description for ozone is “in the wrong direction” is invalid. Now, you are using a similar form of poor quality rhetorics in order to suggest that my analyse confirms the IPCC analysis… which is sort of the opposite of your perception that my analysis describes things in the wrong direction. At best I can only say that your observation relates to the aspect in my analysis which indicates that the IPCC is underestimating the warming influence of both the sun and ozone depletion… because they are overestimating the warming influence of greenhouse gasses.
      - Bas Post 10 Jun 2020 at 18:08
        
        “Martijn, with your response you confirm my statement that you have denied virtually all messages figure SPM.5 brings forward, including the message regarding stratospheric ozone.”
        I fully agree with Ronald. This is also one of the key issues that I have repeatedly brought up and that Martijn keeps ignoring. I summarised my four key issues yesterday in reaction “Bas Post 9 Jun 2020 at 18:13”, but Martijn has decided not to react on that one. I think he is slowly learning what I wrote before (Bas Post 27 May 2020 at 13:22) “As the saying goes: “if you are in a hole, stop digging!”. Martijn continued to dig“. So he did not answer to point 2, because he knew he had no acceptable answer:
        
        2/You have never explained why you accept only one part of Figure SPM5, but don’t want to accept that it also clearly shows that CO2 is the main driver for the global temperature increase. I asked you at least a dozen times to explain what you conclude from the whole of this figure, but you keep stubbornly ignoring that question.
        
        Martijn now accuses Ronald of “You are ignoring my assessment regarding …“, but in fact it is Martijn himself who, right from the start, has been ignoring so many issues – even when they have been repeated over ten times.
        Moreover, we are not ignoring Martijn’s ‘assessments’: we have already pointed out that they are faulty (but he ignores that over and over again). The “the CO2-temperature relation” is thoroughly demonstrated in the vast knowledge of climate science (which Martijn ignores). The impact of CO2 is large according to SPM5 (which Martijn ignores), the “amplification factor” is only an assumption by Shahiv that he has failed to demonstrate (Bas Post 9 Jun 2020 at 21:49), the ozone effect is small compared to the CO2-effect,…
      - ronald 10 Jun 2020 at 18:55
        
        Well Martijn, I have used your own results and references to come to the conclusion that with your paper you have nicely confimed IPCC findings. I know this must have come as a shock, but it follows from simple reasoning of the results which you have presented. In agreement with IPCC you nicely demonstrated that the impact of the sun is compatible to the impact of the stratospheric ozone hole (area) (Figure V).
        
        Can you give a sound scientific reference confirming that the impact of the ozone hole area on global mean temperature is in the order of 0.3 degrees over the 1975-1995 period, i.e., 0.15 degrees per decade over that period? Because that is what you basically state in Figure V.
      - Martijn van Mensvoort 10 Jun 2020 at 20:10
        
        Re: “Well Martijn, I have used your own results and references to come to the conclusion that with your paper you have nicely confimed IPCC findings.”
        
        Get real Ronald, your perceptions show a high level of inconsistency:
        
        Earlier today you claimed (10 Jun 2020 at 13:47): “you have denied virtually all messages figure SPM.5…”.
        But now, only a few hours later, you’re suggesting (10 Jun 2020 at 18:55): “… you have nicely confimed IPCC findings”.
        
        (You made a farce of your own input)
      - ronald 10 Jun 2020 at 20:38
        
        Indeed Martijn, you have nicely confirmed the IPCC finding that the impact of the ozon hole is compatible to the impact of the sun (Figure V). This agrees very well with IPCC Figures SPM.5 and figure 8-15 to which you refer: similar impact. The rest of the messages in these figures are denied by you: that these impacts are very small, denial of the impact of aerosol, denial of the impact of CO2 and other GHG, etc. All denied by you.
        
        This brings me back to my last question. Can you give a sound scientific reference confirming that the impact of the ozone hole area on global mean temperature is in the order of 0.3 degrees over the 1975-1995 period, i.e., 0.15 degrees per decade over that period? Because that is what you basically state in Figure V.
Martijn van Mensvoort 10 Jun 2020 at 21:24

Re: Ronald “Can you give a sound scientific reference confirming that the impact of the ozone hole area on global mean temperature is in the order of 0.3 degrees over the 1975-1995 period, i.e., 0.15 degrees per decade over that period?”

The two sources in my article show temperature effects of similar size:

=> Source 43 (figure 1) describes for ozone depleting substances (ODS) a global radiative forcing effect of 0,3 W/m2 for the periode 1960-2000 and a temperature effect for the arctic region of 0,8 °C:

” Without the large cancellation from aerosols the relative contribution of ODS to the total forced Arctic climate change would be smaller. However, irrespective of aerosols, the absolute contribution of ODS—nearly 0.8 °C of warming and 0.7×106 km2 of September sea ice loss over only 50 years—is remarkably large”

http://www.columbia.edu/~lmp/paps/polvani+etal-NATURECC-2020.pdf

=> Source 42 (figure 11) describes a temperature effect of almost 0,6 degrees Celsius (0.9 K W-1m2) for the halogenated gasses in the periode 1960-2000, see:
https://arxiv.org/ftp/arxiv/papers/1210/1210.6844.pdf
- ronald 10 Jun 2020 at 23:42
  
  Martijn, you use false arguments. Your argument has always been that ozone depletion causes warming because more solar UV reaching the surface. And you you suddenly introduce ODS. This what your paper reference states: “We also demonstrate that the large impact of ODS on the Arctic occurs primarily via direct radiative warming, not via ozone depletion.”
  But also: “the dominant role of carbon dioxide is undisputed”. See also figure 1.
  
  So, when you bring up this reference, you implicitly accept the main findings. But that is not what you do, you cherry-pick what you need and deny all the rest. Cherry-picking is a bad habit and science unworthy. Both your references do not confirm your statement that more solar UV reaching the surface, due to ozone depletion, causes the warming you quantified in Figure V. They are both invalid in that sense.
  
  Martijn, let’s summarize this discussion. In short it can be summarized by 2 words: misinterpretation and cherry-picking. The extended version is as follows.
  
  You bring up figures but you virtually deny all messages in them (Figure SPM.5 and figure 8-15). You cherry-pick what you need (from figure 8-15) and deny everything else. What is the logic behind this way of working? At least it is not scientifically sound.
  
  The message from Figure SPM.5 is even more shocking because it shows that you have used the impact of the ozon hole on the global mean temperature in the wrong direction (figure V). You did not deny this conclusion from Figure SPM.5, which means that you had misinterpreted this figure in the first please. (Ps. there are more examples of misinterpretations from your side as mentioned by van Dorland and Bas)
  
  You stated before: “your question is basically too narrow minded because no single factor can explain temperature development after 1950”. The factor you introduced was warming due to increased UV radiation reaching the surface due to stratospheric ozone depletion. You have not been able to provide scientific evidence, from independent sources, for that statement. So there must be another factor (the sun alone could not due it according to you). But no alternative option came out of your analysis. So, your analysis must have failed.
  
  You have shown your way that the impact of the ozon hole is compatible to the impact of the sun. This is well in agreement with IPCC findings, so a very nice result of your work, although probably not desired from your side. But science is not about finding what you are after but being surprised by new findings …..
  
  And that is where I stop the discussion.
  - Martijn van Mensvoort 11 Jun 2020 at 01:25
    
    Ronald, I described source 43 as follows in my article:
    
    “Also, in January 2020 a group of researchers from the US, Canada and Switzerland reported that CFCs explain about 1/3 of the warming + about half of warming at the North Pole between 1955 and 2005 43.”
    
    it’s true that the researchers of source 43 have concluded that ODS represents the ‘primary’ mechanism. You should be aware that source 43 involves a climate model study and we know that the solar amplification factor is never included in such models; therefore I think the study is relevant as well because in my analysis I have not separated the ozone depletion effect from the ODS substances. Ozone depletion and ODS basically represent a combination of factors.
    
    Your idea about fully accepting “the main findings” does not violate my use of source 42 in my analysis.
    My answer to your question is more broad minded than what you probably expected; but in my answer I have followed my article.
    
    However, source 42 does cover what you had in mind; as a matter of fact, in that study the impact of ozone depletion is even larger than in my study. you have been ignoring the significance of my source 42 (which directly involves the ODS-ozone depletion relation) for your question as well.
    
    Source 42 describes a much more clear parallel with my findings:
    
    “In particular, a statistical analysis gives a nearly zero correlation coefficient (R=-0.05) between CO2 concentration and the observed global surface temperature corrected by the removal of the solar effect during 1850-1970. In contrast, a nearly perfect linear correlation with coefficients of 0.96-0.97 is obtained between corrected or uncorrected global surface temperature and total level of stratospheric halogenated molecules from the start of considerable atmospheric CFCs in 1970 up to the present.”
    
    https://arxiv.org/ftp/arxiv/papers/1210/1210.6844.pdf
    
    So, I think you are (ab)using the narrow minded nature of your question here in order to disqualify my broad answer to your question.
    
    Climate science includes many mysteries to be solved and the dynamics between the different layers of the atmosphere are definitely a part of this. So, I think source 43 serves very well for my analysis (the term ‘primary’ does not exclude the possibility that the ozone depletion goes parallel with the warming effect)… but maybe I should have followed the order of the 2 sources 42 & 43 in my article to answer your question because then you would probably not have ignored the 2nd part of my answer involving source 42.
    
    Maybe you are simply not really into trying to learn and understand things more properly.
    
    Because at the end the nature of your anonymous input is always very predictable:
    you are basically always trying to use the ‘consensus’ as an argument in order to reject anything that violates any party that has embraced the IPCC framework.
    
    (You’ve made a ridiculous statement by suggesting that I am not willing to answer questions… get REAL, I have spend dozens of hours answering many of your questions during the past year. But to me your statement shows that sometimes you are losing touch with reality. I repeat: I have nothing to hide)
    - Bas Post 11 Jun 2020 at 08:36
      
      “ Martijn, let’s summarize this discussion. In short it can be summarized by 2 words: misinterpretation and cherry-picking. The extended version is as follows.”
      That’s it, Ronald has nicely summarised Martijn’s attitude. And you can add to that: no understanding of science, the scientific method and the vast knowledge base of climate change.
      
      Martijn is right about one point “Climate science [still] includes many mysteries to be solved”.
      But they will not be solved by ignoring what is already known.
      They will not be solved by people whose knowledge of science is limited to calculating correlations and overinterpreting them: “a nearly zero correlation coefficient” and “a nearly perfect linear correlation with coefficients of 0.96-0.97”. Or even do absurd things such as calculating the difference between correlations “the correlation difference between the two periods is…”
      They will not be solved by people who post on blogs (sciencetalks, climategate.nl,…), websites of lobbygroups (GWPF,…) or non-peer reviewed (source 42).
      They will not be solved by people who try to degrade any discussion by attacking their opponent personally.
      
      “You’ve made a ridiculous statement by suggesting that I am not willing to answer questions”
      Martijn, that is not a suggestion, that is a fact. Scroll back through the entire discussion here. It is blatantly obvious that your ‘answers’ are more often than not smokescreens to really address the question. For example, I have asked already over ten times for a scientifically sound explanation to remove 75% of the data. You have still not answered that question. You create smokescreens such as “Nearly all aspects you’ve mentioned are addressed and explained in the article”, but you ignore that I have already on many occasions pointed out what is wrong with your ‘explanations’ “in the article”. (Bas Post 9 Jun 2020 at 08:08).
  - ronald 11 Jun 2020 at 08:53
    
    Martijn,
    “Ozone depletion and ODS basically represent a combination of factors.” Sure, we agree on that, but in your paper you have attributed the warming only to the increase of solar radiation to the surface and not to the combined factor. Please read again the first sentence of your paper:
    
    “In 2020, KNMI researcher Geert Jan van Oldenborgh describes the strong statistical correlation between temperature and CO2 as “an almost perfect connection”1. However, the link between sun and climate is not understood2,3. This article describes, based on a total of 40 years around the solar minima over the past 130 years, that the correlation between CO2 and temperature is based on a spurious relation that arises from 2 factors, to wit: a gradual increase in total solar irradiance + an increase in the quantity of solar radiation reaching Earth’s surface due to ozone layer depletion.”
    
    Not for the first time you introduced a new argument in the discussion to save your back. Actually, reference 43 refutes your hypothesis presented in this first sentence of your paper.
    
    So again, the arguments you bring in can be used against you very easy.
    
    The rethorics is all yours. Discussions went in the wrong direction when you started to make it personal. From that moment on you were no longer able to accept criticism and your main objective on climategate.nl is to discredit your opponents (Rob van Dorland, Bas Post and myself) whenever you get the opportunity. It proofs bad science to treat reviewers this way.
    
    I repeat: I did not hide in the discussion. You did with your bad habit of cherry-picking, use of false arguments and ignoring questions you were not willing to or could answer. The reader can confirm this strong statement from the discussion above.
    
    —- The End —-
    - Martijn van Mensvoort 11 Jun 2020 at 12:00
      
      Ronald, most of your comments here (+ on climategate platform) in response to my article served basically just as a side-track which made you avoid to even start discussing the data analysis in my article from the bottom in terms of the (spurious) relation between CO2 and temperature.
      
      I’ll step away here by notifying that I have lost trust in your contributions after becoming aware in februari that after I gave you trust to become involved in the preparation of my december and february article, you’ve spoiled this trust instantly & permanently on the day of the presentation of my february article by becoming involved with a 2nd identity (Klaas) in order to create support for your personal interpretation of the CO2-temperature relationship… a few hours before you started participating in that discussion with your ‘Ronald’ identity.
      
      You’ve never responded to my series of comments where I have reflected on this curious move of yours; not publicly and not in private.
      
      You are trying to save yourself + the person behind the fake name ‘Bas Post’ (who became notoriously known as a serial users of multiple anonymous identities at the Climategate platform after he got banned, not because his opinions about climate in particular but because of improper behaviors, including a series of nasty accusations against the platform host) by means of words like these:
      
      “… your main objective on climategate.nl is to discredit your opponents (Rob van Dorland, Bas Post and myself) …”
      
      You should have known by now that I have better things to do than to discredit authentic people who oppose my analyses, because I rather prefer to focus on the content. However, when anonymous persons present an attempt to question my motives… I don’t mind to give an appropriate response.
      
      The truth is that I have faced and shared any sort of criticism publicly.
      Again, I have nothing to hide; I wish you would be able to make a likewise claim in an authentic manner.
      
      Your believe (which in my perception is a false believe) that I have discredited Rob van Dorland is probably build on just the aspect in my communication where I have described van Dorland as a person who has communicated views on climate which can be described as ‘alarmistic’ of nature; in the interview video below van Dorland expresses his view on climate.
      
      https://www.youtube.com/watch?v=agzuz1NiFPs&
      
      The response of van Dorland (in Dutch language) to the Dutch version of my analysis is available here (16 mei 2020 om 19:51 + my response is presented there as well):
      h ttps://www.climategate.nl/2020/05/de-zon-zorgde-voor-11-c-opwarming-sinds-de-17de-eeuw/
      
      * The earlier Dutch version of my article is available here:
      h ttp://klimaatcyclus.nl/klimaat/zon-zorgde-voor-1,1-graad-Celsius-opwarming-sinds-17de-eeuw.htm
      - Bas Post 11 Jun 2020 at 21:09
        
        Once again, Martijn resorts to personal attacks on Ronald and me, and describing Rob van Dorland as ‘alarmistic’. He can’t cope with the valid comments on the weaknesses in his text, so rather than trying to lear from it, he attacks us. I believe this is called “knowledge resistance”.
        
        He repeats again all kinds of accusations about me, which I have already addressed previously (“Bas Post 31 May 2020 at 19:08”; “Bas Post 25 May 2020 at 22:02”; “Bas Post 9 Jun 2020 at 08:08”). But he just keeps ignoring what I wrote… Just like he also keeps ignoring the scientific weaknesses in his text, that I have highlighted in the past month (just look at “Bas Post 21 May 2020 at 10:27” and “Bas Post 9 Jun 2020 at 08:08” if you don’t want to read all the comments)
        
        But I will conclude with some advice, Martijn, advice that I have given you before by email: you have written that you hope to publish this (in another format) and other analyses one day in a peer-reviewed journal. Peer review is by anonymous reviewers, only known to the editor. You will receive their criticism on your manuscript. You have one opportunity to give scientifically sounds answers and/or to adapt your manuscript. If the editor or the reviewer concludes that you have not answered properly to the criticism and addressed the weaknesses, your manuscript will simply be rejected for publication. Case closed. You will not be able to have a month of replying with all kinds of excuses, smokescreens and claiming that they have not understood what you wrote. So in just one answer, you will have to convince them in a clear and scientific way.
        
        One final note for anybody else who might read this one day: Martijn finishes with “The earlier Dutch version of my article is available here: h ttp://klimaatcyclus.nl/...”. But he ‘forgets’ to mention that there also is another Dutch version, where you can read more critical comments about his unscientific approach: climategate.nl/2020/05/de-zon-zorgde-voor-11-c-opwarming-sinds-de-17de-eeuw
Martijn van Mensvoort 2 Jul 2020 at 01:43

The necessary PDF version is now also available (including some minor corrections in the list of references):

http://klimaatcyclus.nl/climate/PDFarticle.pdf

Meanwhile I am facing a decision involving 3 optional journals:

– Entropy
– SN Applied Sciences
– Solar Physics, which was founded in 1967 by Cornelis (Kees) de Jager

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