IPCC used circular reasoning to exclude natural variability. IPCC relied on climate models (CMIP5), the hypotheses under test if you will, to exclude natural variability:
“Observed Global Mean Surface Temperature anomalies relative to 1880–1919 in recent years lie well outside the range of Global Mean Surface Temperature anomalies in CMIP5 simulations with natural forcing only, but are consistent with the ensemble of CMIP5 simulations including both anthropogenic and natural forcing … Observed temperature trends over the period 1951–2010, … are, at most observed locations, consistent with the temperature trends in CMIP5 simulations including anthropogenic and natural forcings and inconsistent with the temperature trends in CMIP5 simulations including natural forcings only.”
(Ref.: Working Group I contribution to fifth assessment report by IPCC. TS.4.2 Surface Temperature)
It is more clearly seen that the argument is circular if we decompose the argument:
– The theory that CO2 increase is causing the observed temperature increase is built into the models
– When the CO2 input to the model is not increased – then the model output does not show a temperature increase
– Therefore it is concluded that the temperature increase cannot be caused by anything else than CO2 increase
Now it can be seen more clearly that the conclusion is included in the premise. The conclusion has been at least partly been built into the models. Models which were used to show that the conclusion was correct.
This in itself is a sufficient reason to suspend judgement on climate based on the conclusions of United Nations IPCC.
However – could it be that the models are reliable? Could it be that the models has been corroborated by having survived severe testing?
As the following will show,that it is not the case.
Could it be that the models has been properly tested and accurately represents nature?
Let us start by taking a look at the following comment at realclimate.org
17 Mark says:
3 Nov 2015 at 6:41 PM
Apparently Roy Spencer’s CMIP5 models vs observations graph has gotten some “uninformed and lame” criticisms from “global warming activist bloggers,” but no criticism from any “actual climate scientists.” Would any actual climate scientists, perhaps one with expertise in climate models, care to comment?
Models vs. Observations: Plotting a Conspiracy?
[Response: Happy to! The use of single year (1979) or four year (1979-1983) baselines is wrong and misleading. The use of the ensemble means as the sole comparison to the satellite data is wrong and misleading. The absence of a proper acknowledgement of the structural uncertainty in the satellite data is wrong and misleading. The absence of NOAA STAR or the Po-Chedley et al reprocessing of satellite data is… curious. The averaging of the different balloon datasets, again without showing the structural uncertainty is wrong and misleading. The refusal to acknowledge that the model simulations are affected by the (partially overestimated) forcing in CMIP5 as well as model responses is a telling omission. The pretence that they are just interested in trends when they don’t show the actual trend histogram and the uncertainties is also curious, don’t you think? Just a few of the reasons that their figures never seem to make their way into an actual peer-reviewed publication perhaps… – gavin]”
(Gavin Schmidt is Climatologist, climate modeler and Director of the NASA Goddard Institute for Space Studies (GISS) in New York).
From this it should be quite clear that the models, models which IPCC base their conclusions on, are regarded to be affected by partly overestimated forcing as well as model responses, even by one of it´s proponents.
What about H2O, water vapor and clouds?
What about clouds then? When I look out the window in the morning to see if it is raining, windy or what the temperature is like – there is one variable which tells me a lot about the temperature I might expect: clouds.
Is the cloud cover constant in these models? Can´t there be a year, which on average, is just a little bit less cloudy than the previous year. Can´t there be a decade, which on average, is just a little bit less cloudy than the previous decade. Don´t the average cloud cover on the earth vary at all? I am quite sure I have both experienced very clear warm summers and very cloudy and cold summers, a huge difference in temperatures.
If we look for H2O, water vapor and clouds under natural forcing in Assessment Report 5 by IPCC, we will not find it. The only factors listed under “natural forcing” is solar irradiance and volcanic aerosols.
(Ref; WGI; AR5; Chapter 8 Anthropogenic and Natural Radiative Forcing; Page 662)
IPCC does not regard clouds as natural forcing. IPCC regard clouds as feedback from CO2. (The IPCC report is voluminous but it is searchable).
Roy Spencer has a take on clouds in his book The great warming blunder:
“The insistence of the IPCC and the scientific “consensus” that clouds cannot cause climate variations continues to astound me. All atmospheric scientists know that clouds are controlled by a multitude of factors; my position is that causation between clouds and temperature flows in bot directions. In contrast, the IPCC´s position is that clouds can only change in response to temperature change (temperature cause clouds). But neglecting causation in the opposite direction (clouds cause temperature) can lead to large errors in our understanding of how and why the climate system changes, as well as in our diagnosis of how sensitive the climate system is to human influences.”
Judging from the following paper there is no doubt that Roy Spencer is right about his claim about IPCC´s position. The following demonstrates that IPCC regarded cloud cover as closely correlated to temperature and also that the cloud feedback parameter was set by choice:
Climate forcings in Goddard Institute for Space Studies SI2000 simulations; J. Hansen et al
I find the following section immensely telling:
“The bottom line is that, although there has been some narrowing of the range of climate sensitivities that emerge from realistic models [Del Genio and Wolf, 2000], models still can be made to yield a wide range of sensitivities by altering model parameterizations. We suggest that the best constraint on actual climate sensitivity is provided by paleoclimate data that imply a sensitivity 3 ± 1°C for 2 CO2 [Hansen et al., 1984, 1993, 1997b; Hoffert and Covey, 1992]. It is satisfying that the a priori sensitivity of the SI2000 model comes out near the middle of the empirical range of 2 – 4°C for 2 CO2. However, for the sake of interpreting observed climate change and predicting future change it is appropriate to consider climate sensitivity as an uncertain parameter that may, in fact, be anywhere within that range.
Therefore we include the possibility of altering the model’s climate sensitivity. We do this by adjusting an arbitrary cloud feedback as defined in the appendix of Hansen et al. [1997a]. Specifically, the cloud cover is multiplied by the factor 1 + cT , where T, computed every time step, is the deviation of the global mean surface air temperature from the long-term mean in the model control run at the same point in the seasonal cycle and c is an empirical constant. For the SI2000 second-order model we take c = 0.04 and -0.01 to obtain climate sensitivities of 2°C and 4°C for 2 CO2.”
This indicates that the assumptions that clouds cover is a feedback effect closely correlated to temperature, and that temperature is mostly affected by CO2 are built into this model. The models are tuned to match what has been observed. The idea that clouds can cause significant natural variation in temperature isn´t even considered.
There is one other quote in the paper linked above I find amusing:
“Most of the six forcing mechanisms were included in our earlier study with the Wonderland model [RF-CR], but the new results are useful for several reasons.”
I find it amusing for no other reason that it reminds me of a quote from Alice in Wonderland:
“Alice laughed: “There’s no use trying,” she said; “one can’t believe impossible things.”
“I daresay you haven’t had much practice,” said the Queen. “When I was younger, I always did it for half an hour a day. Why, sometimes I’ve believed as many as six impossible things before breakfast.”
Alice in Wonderland.
The uncertainty related to clouds feedback is not unknown by IPCC:
In Box TS.4 | Model Evaluation :
“The model spread in equilibrium climate sensitivity ranges from 2.1°C to 4.7°C and is very similar to the assessment in the AR4. There is very high confidence that the primary factor contributing to the spread in equilibrium climate sensitivity continues to be the cloud feedback.”
And that is a remarkable use of language. IPCC makes it sound like a good thing. It is like saying “we are very confident that we do not have a proper understanding of this.”
The authors are off course aware of this:
“New approaches to diagnosing cloud feedback in General Circulation Models (GCMs) have clarified robust cloud responses, while continuing to implicate low cloud cover as the most important source of intermodel spread in simulated cloud feedbacks. The net radiative feedback due to all cloud types is likely positive. This conclusion is reached by considering a plausible range for unknown contributions by processes yet to be accounted for, in addition to those occurring in current climate models. Observations alone do not currently provide a robust, direct constraint, but multiple lines of evidence now indicate positive feedback contributions from changes in both the height of high clouds and the horizontal distribution of clouds. The additional feedback from low cloud amount is also positive in most climate models, but that result is not well understood, nor effectively constrained by observations, so confidence in it is low.”
In Technical summary cloud feedback is listed as a key uncertainty:
“The cloud feedback is likely positive but its quantification remains difficult.”
In Summary for policymakers we find this very obfuscating statement:
“The net feedback from the combined effect of changes in water vapour, and differences between atmospheric and surface warming is extremely likely positive and therefore amplifies changes in climate. The net radiative feedback due to all cloud types combined is likely positive. Uncertainty in the sign and magnitude of the cloud feedback is due primarily to continuing uncertainty in the impact of warming on low clouds.”
This sentence about cloud feedback is the one only statement about cloud feedback in Summary for policymakers. From this statement it is clear that IPCC has not provided policy makers with a balanced scientific statement about the uncertainty related to cloud feedback. The report is deceiving with regards to the uncertainty related to clouds. The assessment report has many statements about the uncertainty related to clouds, the summary for policy makers contains only one obfuscating section containing the word cloud.
Based on the observations above, I find the following argument reasonable:
– there are no proper historical record of clouds
– the cloud feedback parameter is arbitrarily set in the models
– the cloud feedback parameter is set to match observations
– the models are likely adjusted to match recent observations
– in recent observations there was a warming period from 1975 – 2000
I find it reasonable to maintain my claim that United Nations IPCC excluded natural variation by circular reasoning. That leaves the conclusion by IPCC invalid.
What about oceans then? – can oceans cause some natural variation?
Sure they can – this post is about the huge uncertainty of oceans:
Reason nr. 1 to regard United Nations climate theory as flawed: The missing warming is hiding in the deep oceans!
IPCC has not provided policymakers with relevant information about the uncertainties related to natural variations by clouds and oceans, and certainly not about the logical flaw in the reasoning to exclude natural variation.
Look, matey, I know a dead parrot when I see one, and I’m looking at one right now.
No no he’s not dead, he’s, he’s restin’! Remarkable bird, the Norwegian Blue, idn’it, ay? Beautiful plumage!
Science or fiction:
The plumage don’t enter into it. It’s stone dead.
Nononono, no, no! ‘E’s resting!