A group of Finnish researchers have found that there is a distinct lack of experimental evidence suggesting anthropogenic global warming or man-made climate change are things in a report verified by a Japanese team (archived). The Finns found that the present computers being used all grossly discount the existence of clouds and their profound impact on climate.
After all the noise and political thrashing about over a "crisis" supported by a peculiar, bureaucratic, and subsidized niche of the publishing industry, it seems the pile can be written off as a very Soviet sort of state propaganda.
The full extracted text of the indictment is presented below:
NO EXPERIMENTAL EVIDENCE FOR THE SIGNIFICANT
ANTHROPOGENIC CLIMATE CHANGE
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 lit-
erature. The smallest values estimated are very close to zero while the highest
ones are even 9 degrees Celsius for a doubling of CO 2 . 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 cli-
mate 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 com-
ment 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 tem-
perature anomaly in that figure. The red and blue envelopes are computed using
climate models. We do not consider computational results as experimental evi-
dence. Especially the results obtained by climate models are questionable because
the results are conflicting with each other.
Date: July 2, 2019.
Figure 1. Figure TS.12 on page 74 of the Technical Summary of
the IPCC Fifth Assessment report (AR5).
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 CO 2 and it seems to
be far beyond the accuracy of the climate models.
LOW CLOUD COVER
Figure 2.  Global temperature anomaly (red) and the global
low cloud cover changes (blue) according to the observations. The
anomalies are between summer 1983 and summer 2008. The time
resolution of the data is one month, but the seasonal signal is
removed. Zero corresponds about 15°C for the temperature and
26 % for the low cloud cover.
The red curve in Figures 2 and 3 corresponds to the black curve, between years
1983 and 2008, in the above-mentioned subfigure “Land and ocean surface”. If the
clouds and CO 2 were taken into account correctly in the climate models both the
blue and red envelopes should overlap the observed black curve. As we see the trend
of the blue envelope is more like decreasing. We suggest this is due to a wrong or
missing processing of the low cloud cover contribution. In the report AR5 it is even
recognized that the low clouds give the largest uncertainty in computation. In spite
of this IPCC still assumes that the difference between the blue and red envelopes
in Figure 1 is the contribution of greenhouse gases.
Unfortunately, the time interval (1983–2008) in Fig 2 is limited to 25 years
because of the lack of the low cloud cover data. During this time period the CO 2
concentration increased from 343 ppm to 386 ppm and both Figures 1 (IPCC)
and 2 show the observed temperature increase of about 0.4°C. The actual global
temperature change, when the concentration of CO 2 raises from C 0 to C, is
∆T 2CO 2 ln C/C 0
− 11°C · ∆c,
where ∆T 2CO 2 is the global temperature change, when the CO 2 concentration is
doubled and ∆c is the change of the low cloud cover fraction. The first and second
term are the contributions of CO 2  and the low clouds, respectively. Using
Figure 3.  Global natural temperature anomaly (blue) super-
imposed on the observed (red) temperature anomaly. The blue
anomaly is derived using the observed low cloud cover data from
Figure 2. There are half a dozen very sharp ghost spikes in the
observed (red) temperature anomaly. The Pinatubo eruption and
the strong El Niño are clearly seen.
the sensitivity ∆T 2CO 2 = 0.24°C derived in the papers [3, 2, 4] the contribution
of greenhouse gases to the temperature is only about 0.04°C according to the first
term in the above equation. This is the reason why we do not see this small increase
in temperature in Figure 3, where the temperature anomaly is quite noisy with one
month time resolution. It is clearly seen in Figure 2 that the red and blue anomalies
are like mirror images. This means that the first term is much smaller than the
absolute value of the second term (11°C · ∆c) in equation (1).
It turns out that the changes in the relative humidity and in the low cloud
cover depend on each other . So, instead of low cloud cover we can use the
changes of the relative humidity in order to derive the natural temperature anomaly.
According to the observations 1 % increase of the relative humidity decreases the
temperature by 0.15°C, and consequently the last term in the above equation can
be approximated by −15°C∆φ, where ∆φ is the change of the relative humidity at
the altitude of the low clouds.
Figure 4 shows the sum of the temperature changes due to the natural and
CO 2 contributions compared with the observed temperature anomaly. The natural
component has been calculated using the changes of the relative humidity. Now
we see that the natural forcing does not explain fully the observed temperature
anomaly. So we have to add the contribution of CO 2 (green line), because the timeLOW CLOUD COVER
Figure 4.  Observed global mean temperature anomaly (red),
calculated anomaly (blue), which is the sum of the natural and
carbon dioxide contributions. The green line is the CO2 contribu-
tion merely. The natural component is derived using the observed
changes in the relative humidity. The time resolution is one year.
interval is now 40 years (1970–2010). The concentration of CO 2 has now increased
from 326 ppm to 389 ppm. The green line has been calculated using the sensitivity
0.24°C, which seems to be correct. In Fig. 4 we see clearly how well a change in
the relative humidity can model the strong temperature minimum around the year
1975. This is impossible to interpret by CO 2 concentration.
The IPCC climate sensitivity is about one order of magnitude too high, because
a strong negative feedback of the clouds is missing in climate models. If we pay
attention to the fact that only a small part of the increased CO 2 concentration is
anthropogenic, we have to recognize that the anthropogenic climate change does
not exist in practice. The major part of the extra CO 2 is emitted from oceans ,
according to Henry‘s law. The low clouds practically control the global average
temperature. During the last hundred years the temperature is increased about
0.1°C because of CO 2 . The human contribution was about 0.01°C.
We have proven that the GCM-models used in IPCC report AR5 cannot compute
correctly the natural component included in the observed global temperature. The
reason is that the models fail to derive the influences of low cloud cover fraction
on the global temperature. A too small natural component results in a too large
portion for the contribution of the greenhouse gases like carbon dioxide. That is why
IPCC represents the climate sensitivity more than one order of magnitude larger
than our sensitivity 0.24°C. Because the anthropogenic portion in the increased
CO 2 is less than 10 %, we have practically no anthropogenic climate change. The
low clouds control mainly the global temperature.
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Department of Physics and Astronomy, University of Turku