I didn’t vet this before posting and have no idea as to its real strengths or weaknesses. Have at it.~ctm
J. KAUPPINEN AND P. MALMI
Abstract. In this paper we will prove that GCM-models used in IPCC report AR5 fail to calculate the inﬂuences of the low cloud cover changes on the global temperature. That is why those models give a very small natural temperature change leaving a very large change for the contribution of the green house gases in the observed temperature. This is the reason why IPCC has to use a very large sensitivity to compensate a too small natural component. Further they have to leave out the strong negative feedback due to the clouds in order to magnify the sensitivity. In addition, this paper proves that the changes in the low cloud cover fraction practically control the global temperature.
The climate sensitivity has an extremely large uncertainty in the scientiﬁc literature. The smallest values estimated are very close to zero while the highest ones are even 9 degrees Celsius for a doubling of CO2. The majority of the papers are using theoretical general circulation models (GCM) for the estimation. These models give very big sensitivities with a very large uncertainty range. Typically sensitivity values are between 2–5 degrees. IPCC uses these papers to estimate the global temperature anomalies and the climate sensitivity. However, there are a lot of papers, where sensitivities lower than one degree are estimated without using GCM. The basic problem is still a missing experimental evidence of the climate sensitivity. One of the authors (JK) worked as an expert reviewer of IPCC AR5 report. One of his comments concerned the missing experimental evidence for the very large sensitivity presented in the report . As a response to the comment IPCC claims that an observational evidence exists for example in Technical Summary of the report. In this paper we will study the case carefully.
2. Low cloud cover controls practically the global temperature
The basic task is to divide the observed global temperature anomaly into two parts: the natural component and the part due to the green house gases. In order to study the response we have to re-present Figure TS.12 from Technical Summary of IPCC AR5 report (1). This ﬁgure is Figure 1. Here we highlight the subﬁgure “Land and ocean surface” in Figure 1. Only the black curve is an observed temperature anomaly in that ﬁgure. The red and blue envelopes are computed using climate models. We do not consider computational results as experimental evidence. Especially the results obtained by climate models are questionable because the results are conﬂicting with each other.
In Figure 2 we see the observed global temperature anomaly (red) and global low cloud cover changes (blue). These experimental observations indicate that 1 % increase of the low cloud cover fraction decreases the temperature by 0.11°C. This number is in very good agreement with the theory given in the papers [3, 2, 4]. Using this result we are able to present the natural temperature anomaly by multiplying the changes of the low cloud cover by −0.11°C/%. This natural contribution (blue) is shown in Figure 3 superimposed on the observed temperature anomaly (red). As we can see there is no room for the contribution of greenhouse gases i.e. anthropogenic forcing within this experimental accuracy. Even though the monthly temperature anomaly is very noisy it is easy to notice a couple of decreasing periods in the increasing trend of the temperature. This behavior cannot be explained by the monotonically increasing concentration of CO2 and it seems to be far beyond the accuracy of the climate models.