Mother Nature organized a climate test showing 70 % error in the calculated 2019 temperature

The Earth receives 99.97% of its energy from the Sun. The global warming impact caused by greenhouse gases is calculated in such a way that it corresponds to the change in solar radiation at the top of the atmosphere and is called Radiative Forcing (RF). If the magnitude of solar energy changes, then the change in radiation power multiplied by the climate sensitivity parameter directly gives the global warming effect. If the change had occurred in solar activity in a short period of time, it would be widely reported. When a change has occurred due to atmospheric conditions, scientists are not paying attention to the change, even though the result is exactly the same.


Sixteen climate change scientists, led by Nathan B. Gillett (later Gillett), published a study entitled "Constraining human contributions to observed warming since the pre-industrial period" in the journal Nature Climate Change (NCC) in March 2021, Reference 1.


The purpose of the researchers was to examine how the warming trend is taking place in relation to the Paris Climate Agreement, which aims to keep warming well below 2°C. The temperature measurement has been Hadley Center/Climatic Research Unit Temperature - temperature series HadCRUT4. The researchers carried out temperature simulations by 13 General Circulation models (GCMs) with results in accordance with the Detection and Attribution Model Intercomparison Project (DAMIP) from the 1850-1900 average to the 2010-2019 average, which in this story has been named the study period. The main results are graphically shown in Figure 1.

Figure 1. Human-induced temperature changes from 1850 to 1900 in 2010–2019. The average warming values for the period 2010–2019 on the right-hand side of the image have been estimated by the author from the graphs.


According to the study, the change in HadCRUT4 temperature during the study period was 1.1 °C and the warming caused by the anthropogenic factors was 0.9 °C to 1.3 °C meaning an average of 1.1 °C. The effect of anthropogenic factors consists of greenhouse gases from 1.2 °C to 1.9 °C (an average of 1.55 °C) and aerosols from -0.7 °C to -0.1 °C (average -0.4 °C). For the climate establishment (the IPCC and scientists supporting its climate change science), the results are excellent because the temperature calculated by computer models and the measured temperature is practically equal. It supports urgent measures to limit Anthropogenic Global Warming (AGW), in line with the Paris Agreement.


The study does not consider the strong positive change in shortwave (SW) radiation since 2000, which affects the warming calculated by the models. This finding also leads to another observation that the positive water feedback commonly applied in computer models causes a significant error in the warming calculated by the models. All this questions the scientific climate models of the IPCC, which are the basis of the Paris Agreement. There is one conflict in the study between graphical representation and the numeric values of the text.


I briefly summarized these findings and conclusions and submitted them to Nature Climate Change, but they refused to publish them on the grounds that “we are not persuaded that these points advance or clarify understanding of the paper”. This argument means that the NCC did not deny the accuracy of my findings, but they did not want to give them publicity because it would bring Gillett's research into a negative light. I published my findings in another paper in an extended form, Reference 2.


In my short research paper, I highlighted three flawed points in the Gillett study, and then I added the fourth point concerning the Paris Agreement. I have used two simple computer models, the IPCC model and mine (the Ollila model), which have the same basic structure for calculating the essential results of Gillett’s study.


Simple climate models


The warming values for any radiative forcing (RF) can be calculated using the following IPCC equation.

dT = λ * RF (1)

where dT is a global surface temperature change (K or °C), λ is a climate sensitivity parameter (K/(W/m2)) or (°C/(W/m2)). The climate sensitivity parameter λ used by the IPCC is 0.5 K/(W/m2), which means positive water feedback, and it is valid even for the scenario RCP8.5, where the equivalent carbon dioxide concentration is 1370 ppm CO2 in 2100. For example, according to equation (1), transient climate sensitivity (TCS) is 0.5 * 3.7 = 1.85 ⁰C, according to IPPC. It can be compared with the IPCC's official TCS value of between 1.0 °C and 2.5 °C, meaning an average of 1.75 ⁰C. According to the last AR5 report of the IPCC, the TCS value in Table 9.5 calculated by 30 computer model is 1.8 ⁰C.

Since it turned out that Gillett's simulations did not use the SW radiation anomaly, I have used my own simple climate model, which does not have a positive water feedback, but has a λ value of 0.27 K/(Wm-2).

I have used the RF values in the IPCC from the Assessment Report AR5, where RF values are grouped into three main groups, like Gillett's research, and in 2011 they were from 1750 to 2011 :


- Greenhouse gases 3.18 W/m2 ~ 1.58 °C - Aerosols, the impact of aerosols on clouds, and land use -0.97 W/m2 ~ 0.49 °C - Change in solar radiation intensity (natural causes) +0.05 W/m2 ~ 0.03 °C - Total 2.26 W/m2 (The IPCC reports 2.29!) ~ 1.15°C. Gillett’s warming value is slightly higher than the IPCC estimate in the AR5, but they have compared the warming, from 1951 to 2011. When the warming of the AR5 is calculated from 1750 to 2011, it is 0.5 * 2.29 = 1.15 °C.


The IPCC's RF values for greenhouse gases since 2011 can be found on NOAA's website, where is the AGGI file (The Annual Greenhouse Gas Index), Reference 3.


I have used a temperature change in my validation calculation between 2001 and 2019 and in my model, I have considered only the change in CO2 content as the impact of other greenhouse gases in this short term is nil:

RF = 3.12 * ln(C/280), (2)

where C is the CO2concentration (ppm).

Both in the IPCC model and in my model, the temperature effect of the ENSO (El Nino Southern Oscillation) effect has been calculated using the Oceanic Nino Index (ONI index) :


dT = 0.1 *ONI (3)

A six-month delay has been applied in equation (3).


The conflict between text and graphical representations


In the text of the study, Gillett states that the average warming caused by anthropogenic factors during the study period is 1.1 °C (brown graph) due to zero natural forgings (change in solar radiation). According to the graphical representation, as shown in Figure 1, the total warming value is approximately 0.8 °C, which is the sum of greenhouse gases of 1.3 °C and the aerosols of 0.5 °C. Similarly, the HadCRUT4 temperature value for the study period is approximately 0.8 °C. The temperature value of 1.1 °C appears to be the 2019 value in both cases. I can't find an explanation for this difference in the study.



The warming effect of the radiative forgings of aerosols and clouds


The most significant flaw in the study is the warming effect of aerosols, which is the lowest blue line in Figure 1. Its value has fallen to -0.5 °C around 1980 and has remained the same until 2019. This value can be compared to the AR5’s RF value of 0.97 W/m2 in 2011 and it can be concluded that it is the same, i.e. 0.5 * 0.97 = 0.5 °C.

Based on Gillett's graphical presentation, the effect of aerosols has been at -0.5 °C since 1990. There are several studies that show, based on both ground stations measurements and satellite observations, that Earth’s darkening turned to brightening around 1985-90. Brightening means that more solar radiation comes to the Earth's surface. The decisive direct measurement evidence has emerged from the measurements of CERES satellites, which became available in March 2000. The CERES satellites measure total solar radiance and upward reflected shortwave radiation SWup. The difference of these radiation fluxes is the SW radiation downwards SWdn, which is the same as the net Earth's energy received from the sun, about 240 W/m2, Figure 2.


Figure 2. Shortwave radiation trends SWup and SWdn since March 2000. The temperature effects have been calculated according to the IPCC simple model equation (1), which uses positive water feedback.


The effect of the change in SW radiation SWdn from 2000 to 2019 is approximately 0.6 W/m2, corresponding to a temperature change of 0.3 °C. If this effect is added to Gillett's value, the total temperature change would be between 1.2 °C and 1.6 °C. It is worth noting that the SWup reflected into space depends on all the factors that affect the SW radiation penetration and reflection of the atmosphere, clouds, and the Earth's surface. Gillett's research does not consider the change in SWdn at all, although it has been 1.61 W/m2 in 2019 - almost the same as carbon dioxide’s RF of 1.68 W/m2 from 1750 to 2011.


It should be noted that the change in SWdn has been addressed only in a few publications, References 2, 4, 5. That is why some people have been skeptical as to whether I have been able to calculate this SW radiation change correctly, because CERES data does not give a radiation value to SWdn directly, but it must be calculated by eliminating seasonal variation, reference 6. Norman Loeb is the director of the CERES program, and his last study (Reference 5) has a graphic representation of this SWdn trend, Figure 3.


Figure 3. Change in the SWdn radiating to the Earth in 2002-2020.


Figure 3 shows that the trend of SWdn radiation that I have used is the same as that used by Loeb et al., but there are two differences. Since CERES data starts in March 2000, SW radiation can be reliably calculated from September 2000, but Loeb et al. have started to use it from 2003 onward. For some reason, Loeb et al. has scaled this change so that it does not start from zero, giving an average difference of -0.6 W/m2 to my radiation value.


Positive water feedback in climate modeling, validation


The term "radiative forcing" is not found in Gillett's research, but it is an essential feature of the climate models used by the IPCC. Positive water feedback, which doubles the value of other radiation forcings, is a basic feature of all climate models approved by the IPCC. The existence of this feature in the 13 climate models used by Gillett can be tested using carbon dioxide, which has the best-known RF according to the AR5 (very high confidence). In 2019, according to Gillett's simulations, the warming effect of carbon dioxide was 1.0°C (the graphical presentation of supplementary information), Figure 4.


Figure 4. The global warming effect of carbon dioxide, according to Gillett.


If positive water feedback has been used for CO2, the warming value shall be obtained according to formula (1) using the "canonic" formula of Myhre et al. for CO2: RF = 5.35 * ln(C/280)


dT = 0.5 * 5.35 * ln(411.16/280) = 1.03 °C (4)


This proves that the climate models used by Gillett have used positive water feedback and the same values can be calculated using the simple IPCC climate model, equation (1).


Validation means testing whether the result calculated by any model corresponds to the value observed in nature. The warming result of 1.1 °C was calculated by 16 GCMs by Gillett for the study period, but the models do not consider a change in SWdn that would increase the temperature calculated by the models by 0.3 °C. Since the error is the average for the 2010-2019 period, it does not look too great, but the 2019 error is already an enormous +0.8°C. This error will be realized in the simulation of the temperature change over the period 2001-2019 using the IPCC model and my own model, Figure 5.


Figure 5. Temperature changes were calculated using the IPCC model and the Ollila model in 2001–2019 compared to HadCRUT4. An essential difference is the positive water feedback in the IPCC model.


In the IPCC model, the change in 2019 is due to three factors: greenhouse gases 0.29 °C, ENSO effect 0.08 °C, and SW radiation change 0.8 °C meaning a total change of 1.17 °C. In my model, the corresponding changes are greenhouse gases 0.1 °C, ENSO effect 0.08 °C, and shortwave radiation 0.37 °C, meaning the total of 0.55 °C. HadCRUT4 temperature change was 0.39 °C. If Gillett's calculations had taken into account the change in SWdn, the temperature change for 2019 would have increased from 1.1 °C to 1.9 °C, which would mean an error of approximately 70 percent.


Scientific criteria for the Paris Agreement on climate change


The scientific calculations of the Paris Agreement are based on IPCC science and the base scenario has been the very unlike or even impossible scenario RCP8.5, which has been used for calculating anthropogenic temperature changes in the future. The purpose of the Paris agreement is to limit warming to a maximum of 2.0 °C and preferably to keep it at 1.5 °C.


When the change in SW radiation is considered in the calculations, according to the IPCC models, the temperature increased to 1.9 °C in 2019 which is 0.8 °C greater than the 1.1 °C calculated by Gillett using computer models. Because there is an error of about 70 % in this value, it indicates that the positive water feedback is a wrong concept. The same positive water feedback also distorts the effect of anthropogenic factors.


Is this researchers’ unintentional mistake or a scam?


Researchers can make mistakes in their studies and their calculations can lead to the results not reflecting reality. It may also be a question of intentional falsification of research results, which can be classified into four different categories:

- Falsification meaning intentionally falsified measurement or research results.

- Artificial fabrication of measurement values and research results.

- Copying measurement values and research results from other researchers and presenting them as their own results.

- Selected use of measurement values and research results to support one's own theory (cherry-picking).


The latter case is the most common distortion of research results and one of the main tasks of peer reviewers is to ensure that this is not exploited in the research study. In this case, Gillett has not the applied SW radiation values from 2001 to 2019 in 16 GCM simulations although it has a significant impact on the final result and shows that positive water feedback does not occur in the climate.


Since we are talking about professionals who follow the research results and observation databases of the climate change field closely, it is not credible that Gillett et al. would not be aware of any significant changes in the SW radiation since 2001. Publications have been made and measurement data are publicly available as CERES data, which are by far the best observational radiation data.


It can be estimated that, even in this case, scientists supporting IPCC science have support from the climate community. This can be seen, for example, in the fact that the peer reviewers of the article have not intervened in this apparent selection of measurement data, i.e. the omitted measurement data. One of the most respected publications of climate science namely Nature Climate Change has refused to publish criticism of the identified shortcomings. All this has to do with the development of a strong hegemony in climate change science that defends and supports anthropogenic global warming (AGW) theory. Different views and research results are silenced, and errors are masked. Hegemony means the cultural or political domination of a group in society.


Final comments


Why, is there a desire to cover up the surge in SW radiation? Firstly, by excluding the warming impact of SW radiation, the temperatures of 2010-2019 calculated by computer models can be brought into line with the measured temperatures. Secondly, it shows that the natural forcings may have strong temperature effects when the climate establishment has declared that these impacts are next to nil. Thirdly, considering SW radiation reveals that the positive water feedback used by the climate establishment leads to a significant error in relation to the measured temperature, as indicated by the year 2019.


I estimate that this study will have a significant impact on the IPCC report AR6 to be published in August. The previous report, AR5, covered up the fact that the IPCC radiative forcings for 2011 were 2.29 Wm-2, which means a temperature change of 1.15 °C, but the temperature change was only 0.85 °C according to the IPCC meaning the error of around 35%. By excluding the change SW radiation downward from temperature impacts, the GCM calculated temperature and the observed temperature for the reference years are likely to be almost the same. If contrarian comments do not appear or they can be pressed down, then the IPCC will not hesitate to use this matter in the publication of the results of the AR6.


References


1. Gillett NP, Kirchmeir-Young M, Ribes A, Shiogama H, Hegeri GC, Knutti R, Gastineau G, John JG, Li L, Nazareno L, Rosenbloom N, Seland Ö, Wu T, Yukimoto S, Ziehn T, 2021. Constraining human contributions to observed warming since the pre-industrial period. Nat. Clim. Change, 11:207-212. https://www.nature.com/articles/s41558-020-00965-9.

2. Ollila A. Global Circulation Models (GCMs) Simulate the Current Temperature Only If the Shortwave Radiation Anomaly of the 2000s Has Been Omitted, 2021. Current Journal of Applied Science and Technology, 45-52. DOI: 10.9734/cjast/2021/v40i1731433.

3. NOAA, National Oceanic and Atmospheric Administration (NOAA), the Annual Greenhouse Gas Index (AGGI); 2021. Available: https://gml.noaa.gov/aggi/aggi.


4. Loeb NG, Thorsen TJ, Norris JR, Wang, Su W, 2018. Changes in earth's energy budget during and after the “pause” in global warming: An observational perspective. Climate, 6:62. https://www.mdpi.com/2225-1154/6/3/62.

5. Loeb, NG, Johnson GC, Thorsen TJ, Lyman JM, Rose FG, Kato S, 2021. Satellite and ocean data reveal marked increase in Earth’s heating rate. Geophys. Res. Lett., 48, e2021GL093047. https://doi.org/10.1029/2021GL093047.

6. NOAA, National Oceanic and Atmospheric Administration (NOAA) net pages, CERES EBAF-TOA Data;2021. Available https://ceres-tool.larc.nasa.gov/ord-tool/jsp/EBAFTOA41Selection.jsp.


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