Climate Model Bias 4: Convection and atmospheric circulation

By Andy May

In part 3 we discussed the relationship between changes in solar activity and climate changes. Exactly how solar changes affect climate is not understood. It isn’t the immediate change in radiation delivered to the Earth, since that is too small to have much of an effect. So, it must be how Earth’s climate system reacts to the changes. The observed impact of solar irradiance changes over the solar cycle on the climate is much larger than the change in delivered radiation can account for.[1] A likely amplifying mechanism is Earth’s convection and atmospheric circulation system. This post examines that idea. It is yet another important idea that the IPCC and AR6 ignore and brush away as unimportant, vis-à-vis global warming.

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Climate Model Bias 3: Solar Input

By Andy May

Christian Freuer has translated this post into German here.

In part 2 we discussed the IPCC hypothesis of climate change that assumes humans and our greenhouse gas emissions and land use choices are the climate change “control knob.”[1] This hypothesis underpins their attempts to model Earth’s climate. But the model output fails to match many critical observations and in some cases the model/observation mismatches are getting worse with time.[2] Since these mismatches have persisted through six major iterations of the models, it is reasonable to assume the flaw is in the assumptions, that is within the hypothesis itself, as opposed to being in the model construction. In other words, it is likely the IPCC conceptual model should be scrapped, and a new one using different assumptions constructed. In this post we examine their underlying assumption that the Sun has not varied significantly, at least from a climate perspective, over the past 150-170 years.

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Climate Model Bias 2: Modeling Greenhouse Gases

By Andy May

Christian Freuer has translated this post into German here.

Since the late 19th century, with the work by Svante Arrhenius, climate models have been used to estimate the amount of global warming due to human greenhouse gas emissions.[1] Due to the complexity of Earth’s weather and climate, the connection between climate change/global warming and greenhouse gases cannot be observed or measured, it can only be estimated with a model. Arrhenius constructed the first such model and speculated that temperature changed linearly with the logarithm of the CO2 concentration, specifically he estimated that as CO2 doubled in the atmosphere, surface temperature should increase 4°C.[2]

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Climate Model Bias 1: What is a Model?

By Andy May

Christian Freuer has translated this post into German here.

There are three types of scientific models, as shown in figure 1. In this series of seven posts on climate model bias we are only concerned with two of them. The first are mathematical models that utilize well established physical, and chemical processes and principles to model some part of our reality, especially the climate and the economy. The second are conceptual models that utilize scientific hypotheses and assumptions to propose an idea of how something, such as the climate, works. Conceptual models are generally tested, and hopefully validated, by creating a mathematical model. The output from the mathematical model is compared to observations and if the output matches the observations closely, the model is validated. It isn’t proven, but it is shown to be useful, and the conceptual model gains credibility.

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Sorry, the Little Ice Age Does Exist

By Andy May

This post has been translated into German by Christian Freuer here.

Renee Hannon (@hannon_renee) pointed out that Raphael Neukom, et al. (2019) compares the modern instrumental temperature record to the Pages2K proxy temperature record and declares that:

“… we find that the coldest epoch of the last millennium—the putative Little Ice Age—is most likely to have experienced the coldest temperatures during the fifteenth century in the central and eastern Pacific Ocean, during the seventeenth century in northwestern Europe and southeastern North America, and during the mid-nineteenth century over most of the remaining regions.”

Neukom, et al., 2019
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Hurricane Frequency and Sunspots

By Andy May

Today, Roger Pielke Jr. posted a plot of the 3-year frequency of global major hurricanes (he uses a simple count of them) created by Ryan Maue (@RyanMaue). Dr. Maue also posted this plot on his twitter feed here. I noticed it looked like an inverse sunspot plot and overlaid the SILSO monthly sunspot count. In the figure, the blue is Maue’s plot, and the orange is a plot of monthly SILSO sunspots. The correlation, or strictly speaking, the anti-correlation is obvious and very interesting. I don’t think Ryan Maue’s plot has been formally published yet.

It appears that some extreme weather is influenced by changes in solar activity.

Figure 1. The blue line is Ryan Maue’s 3-year cumulative count of major global hurricanes. The orange line is the simple monthly sunspot count from SILSO.

OK, I’ll speculate.
Sunlight penetrates deeply (up to 1,000 meters) into the ocean before it is absorbed. Greenhouse gas radiation cannot penetrate the ocean surface. The residence time of sunlight energy is longer as a result. This magnifies solar changes since Watt-for-Watt changes in sunlight matter more than changes in greenhouse gases.

Storms are a function of temperature differences, when an imbalance (increase in energy storage) happens in the tropics at the top of the solar cycle, the temperature difference between the tropics and the mid-latitudes increases. This causes storminess and hurricanes to increase, the increase doesn’t stop until the next solar minimum. Solar peaks appear to initiate an increase in storminess. Just a guess, take it for what it’s worth.

Lazard’s LCOE

By Andy May

This post has been translated into German by Christian Freuer here.

Lazard’s levelized cost of energy (LCOE) is cited on the internet all the time as the source for “solar and wind are cheaper than fossil fuels.” They don’t really mean “energy,” they mean “electricity.” The world consumed only 18% of its energy in 2021 as electricity, so LCOE is just the cost of 18% of our total consumption, a fact often lost in these discussions.

However, just a quick look at their data shows that solar and wind are clearly not cheaper. Even within their April 2023 report they are not consistent in their numbers. To make matters worse, they bury critical details in the fine print and do not define their terms. I doubt some of their numbers, but for this discussion I only use the numbers in their report.

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Climate, CO2, and the Sun

By Andy May

Christian Freuer has translated this post into German here.

In my previous post on multiple regression of known solar cycles versus HadCRUT5, I simply threw the solar cycles, ENSO, and sunspots into the regression blender and compared the result to various models that included CO2. Before reading this post, it is a good idea to read the previous one, since much of this post relies on the information in it. It was a very simple statistical analysis designed to show that the IPCC conclusion that rising CO2 and other greenhouse gases are “responsible” for “1.1°C of warming since 1850-1900” is probably erroneous. The difference between the HadCRUT5 1850-1900 average and the 2018-2023 (through all of 2022) is 1.18°C, so they are saying that essentially all the warming since the 19th century is due to humans. The analyses described in this post show they cannot be certain of their conclusion because they have ignored persuasive evidence that changes in the Sun caused at least some of the warming.

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Modeling HadCRUT5 with CO2 and without CO2

By Andy May

I hate statistics, as many of you know. Some people think statistics and/or statistical models that meet standard statistical criteria are facts. The IPCC can be like that. They statistically model global surface temperatures with models of volcanic and anthropogenic forcing and compare the model to one with only volcanic forcing. Then they turn to us, with a straight face, and say the comparison shows anthropogenic forcing is driving all the warming. What about solar? Oh, they considered that they say, the Sun makes no difference, see their chart in figure 1 from AR6.[1] Solar is assumed to be zero and volcanism is small, thus the model assumes all recent warming is due to humans, then draws the same conclusion in a perfect example of circular reasoning. But what if the solar forcing is not zero? What difference does that make?

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John Constable’s talk at Universidad de las Hespérides

By Andy May

h/t Wim Röst

The Universidad de las Hespérides is in the Canary Islands, off the coast of Morocco. The Hespérides are the nymphs of the evening and golden sunsets, so I imagine it is a beautiful location to travel to. Dr. Constable’s talk can be viewed in full here. The beginning is in Spanish, but they turn to English about 4 minutes in.

His talk is about our energy economy and how it has evolved over time. He makes the critical point that fossil fuels are a very high-quality energy source and have produced a very wealthy and high productivity world. As a result, the medieval hold that landowners had over the peasants of a feudal society was broken. Land ownership in the past controlled the food supply, since travel and food transport were prohibitively expensive and time consuming. Controlling food meant the landowners (lords and kings) controlled, and basically enslaved, the general population.

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