Here are some random quotes and thoughts on the article titled An Observational Scaling Model for Climate Sensitivity Estimates and Global Projections through 2100. This was the first statement I noticed:
We estimate the model and the forcing parameters through Bayesian inference, which enables us to analytically calculate the transient climate response and equilibrium climate sensitivity as: 1.7 + 0.3 – 0.2 K and 2.4 + 1.3, respectively – 0.6 K (likely range).
I always get nervous when someone says they are using “Bayesian Inference”. The problem is not with Bayesian theory, which is correct. Basically, it is said that the likelihood of something happening depends in part on what happened before, the so-called “Bayesian Priors”. And clearly, in many situations this is true.
The problem lies in the choice of priorities. It depends on human judgment and some pre-existing theory about what is going on. I am sure you can see the problems with it. First, human judgment is … well … let me call it “not universally correct” and leave it at that. And next … what pre-existing climate theory should we use when studying climate theory?
Then came this statement.
The ecological consequences of global warming could be severe. Therefore, better limitation of climate sensitivity is of the utmost importance in order to meet the urgency of adapting economic and environmental policy.
This makes the sweat break out on my forehead because it’s one of the building blocks of a whole host of theories … but it’s rarely supported by the weakest evidence. It is only given as an indisputable truth, as in this paper. They make no attempt to justify it.
Every realistic description I’ve read of gradual warming over the past three centuries has some verifiable facts:
- Things are warmer now than they were during the Little Ice Age.
- In general, this increased warmth was beneficial to both humans and animals and plants.
- There were no “climate disasters” due to this warming.
Combine that with the following data …
… And it becomes very difficult to believe that “the ecological consequences of global warming could be dire”.
Given these facts, the alarmists’ fallback position is usually “But mah sea level! Mah sea level will all drown. “… However, as I have shown time and time again, even the longest records of sea level show no acceleration due to warming.
So we start from far behind, crippled by false assumptions. And these false assumptions, these “Bayesian Priors” are based on the IPCC’s initial mistake, which I called the “Picasso Problem”. Said Picasso
“What use are computers? They can only give you answers …
At first I neither understood nor believed that. I mean, I’m a computer guy. Why does a painter question my computer use? … But at some point I saw that we shouldn’t be looking for the right answers. Instead, we should focus on looking for the right questions. As the old saying goes, “Ask a stupid question, you will get a stupid answer.”
And tragically, the wrong question was asked of the IPCC at the beginning. When the IPCC was first set up, it was tasked with answering the question:
“What CO2 content is dangerous for mankind?”
In fact, they should have been hired to answer the question:
“Is the increase in CO2 a threat to humanity?”
And obviously the current paper suffers from the same problem – it answers the wrong question … and not only that, it answers the question with computers …
Let me anticipate some definitions from the paper for the next issue:
Emerging properties of the earth’s climate, ie properties that are not specified a priori, are then derived from GCM simulations. Equilibrium Climate Sensitivity (ECS) is one such property; it refers to the expected change in temperature after an infinitely long time after the atmospheric carbon dioxide (CO2) concentration has doubled. Another is the transient climate response (TCR), which is defined as the change in temperature after the atmospheric CO2 concentration has gradually doubled over 70 years at a rate of 1% per year.
They continue with these definitions:
Since the report by the United States National Academy of Sciences (Charney et al. 1979), the likely range for the ECS has not changed and remains in place [1.5,4.5] 𝐾.
The problem with this is that they say it as if it’s a good thing … when in fact it is a clear indication that they are making false assumptions. In fact, as they clearly don’t want to admit, the likely range has increased and has not stayed the same. You can see this problem below:
And this increase in the range of equilibrium climate sensitivity should be a big danger signal. I mean, in what other area of science has not only been there no progress on a central issue in forty years, but has uncertainty actually increased? I don’t know of any other scientific field than climate science where this is true.
You continue:
Future anthropogenic forcing is prescribed in four scenarios, the representative concentration paths (RCPs) established by the IPCC for CMIP5 simulations: RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 (Meinshausen et al. 2011). They are named after the total radiative forcing expected in Wm – 2 in 2100 and are motivated by complex economic projections, expected technological developments and political decisions.
There are a couple of problems with that. First, these assumptions of future forces form another part of the Bayesian priorities discussed above. And since these priorities are based on “complex economic projections, expected technological developments and political decisions”, they are infinitely adaptable to the investigators’ wishes and theories.
A more fundamental problem, however, is the relationship between the drives and the response of the models. As Kiehl emphasized over a decade ago in “Climate Model Reaction and Climate Sensitivity of the 20th Century”:
It turns out that the total anthropogenic forcing for a large number of climate models differs by a factor of two and that the total forcing is inversely correlated with the climate sensitivity. Much of the uncertainty in the entire anthropogenic forcing results from a three-fold uncertainty range of the aerosol forcing used in the simulations.
This is an important paper that has been conspicuously ignored by scholars in the field. If you assume larger forces, the model shows a lower climate sensitivity and vice versa. Not only that, but as I demonstrated in Life Is Like A Black Box Chocolates, the relationship between the forcing and the model output is both linear and ridiculously simple, namely:
The outputs of the climate models are emulated very well by a simple delayed and scaled version of the inputs.
Here is an example of my analysis showing how well the model output can be emulated using this absurdly simple formula:
This formula contains only three coordinated parameters: Lambda (scaling factor), Tau (lag factor) and a volcanic adjustment. (Oddly enough, the current paper agrees that volcanic adjustment is required, saying, “The instantaneous temperature response [to the eruptions] is weaker than expected with linear response theory. “)
This shows that, despite their complexity, the result of the climate models can be emulated almost perfectly using a simple formula. A further implication is that the calculations of the equilibrium climate sensitivity (ECS) and the transient climate response (TCR) from the results of these models are completely meaningless. This is supported by the fact that no progress has been made in refining the estimates of the ECS and the ECS TCR over the past forty years.
As I read on, I eventually lost both the plot and any further interest in the newspaper when they said (emphasis mine):
To make progress, Hasselmann et al. (1997) proposed a response function made up of a sum of N exponentials – effectively an N-box model (although without the use of differential equations: the boxes were only implicit). Yet, they finally made up their minds 𝑁 = 3 for practical reasons – to adapt GCM outputs.
To translate, they define reality based on whether or not their description of reality matches the output of computer models … and that’s where I stop reading.
Seriously, I couldn’t go any further. Any study that claims that a description of reality only makes sense if it matches the results of absurdly simple climate models is not worth my time to investigate.
Best holiday greetings to everyone on this day after Christmas,
w.
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