CO2 and Temperature

By Andy May

I had a very interesting online discussion about CO2 and temperature with Tinus Pulles, a retired Dutch environmental scientist. To read the whole discussion, go to the comments at the end of this post. He presented me with a graphic from Dr. Robert Rohde from twitter that you can find here. It is also plotted below, as Figure 1.

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Autocorrelation in CO2 and Temperature Time Series

By Andy May

In my last post I plotted the NASA CO2 and the HadCRUT5 records from 1850 to 2020 and compared them. This was in response to a plot posted on twitter by Robert Rohde implying they correlated well. The two records appear to correlate because the resulting R2 is 0.87. The least square’s function used made the global temperature anomaly a function of the logarithm to the base 2 of the CO2 concentration (or ‘log2CO2‘). This means the temperature change was assumed to be linear with the doubling of the CO2 concentration, a common assumption. The least squares (or ‘LS’) methodology assumes there is no error in the measurements of the CO2 concentration and all error resulting from the correlation (the residuals) resides in the HadCRUT5 global average surface temperature estimates.

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#autocorrelation, #co2, #durbin-watson, #temperature

Clouds and Global Warming

Figures 4 and five have been updated to correct a programming error (7/5/2021).

By Andy May

This post is inspired by an old post on the CERES cloud data by Willis Eschenbach that I’ve read and re-read a lot, “Estimating Cloud Feedback Using CERES Data.” The reason for my interest is I had trouble understanding it, but it looked fascinating because Willis was comparing CERES measured cloud data to IPCC modeled cloud feedback. I love obscure, back-alley comparisons of models and data. They tend to show model weakness. I learned this as a petrophysical modeler.

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The Greenhouse Effect, A Summary of Wijngaarden and Happer

By Andy May

This post was updated 9/24/2021 to reflect reader comments.

The phrase “greenhouse effect,” often abbreviated as “GHE,” is very ambiguous. It applies to Earth’s surface temperature, and has never been observed or measured, only modeled. To make matters worse, it has numerous possible components, and the relative contributions of the possible components are unknown. Basic physics suggests that Earth’s surface is warmer than it would be with a transparent atmosphere, that is no greenhouse gases (GHGs), clouds, or oceans. If we assume Earth is a blackbody, then subtract the solar energy reflected, from the hypothetically non-existent clouds, atmosphere, land, ice, and oceans; we can calculate a surface temperature of 254K or -19°C. The actual average temperature today is about 288.7K or roughly 15.5°C. This modeled difference of 35°C is often called the overall greenhouse effect.

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Temperature Regulated Cooling Dominates Warming and Why the Earth Stopped Cooling At 15°C

Guest Post by Wim Röst

Abstract

It is said that the Earth’s surface temperature variations are controlled by [human-induced] greenhouse gases1. This is not the case. When cooling systems dominate, surface temperatures are set by the cooling system and not by the system that is warming the surface. On Earth the surface cooling system dominates; temperatures are set by the natural cooling system. The strength of natural surface cooling is set by temperature. Adding greenhouse gases to the atmosphere does not make any difference for surface temperatures. Their initial warming effect is neutralized by extra surface cooling and by a diminished uptake of solar energy. The cooling system dominates.

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Greenland Ice Core CO2 during the past 1,000 years

Guest Post by Renee Hannon

Introduction

This post compares CO2 ice core measurements from Greenland to those from Antarctica over the last millennium. Paleoclimate studies typically use only Antarctic ice cores to evaluate past CO2 fluctuations. This is because the entire Greenland CO2 datasets were deemed unreliable due to chemical reactions with impurities in the ice and therefore have not been used in studies since the late 1990’s. This post will demonstrate that CO2 data from Greenland ice cores have scientific value and respond to key paleoclimate events such as the Little Ice Age and Medieval Warm Period.

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Holocene Antarctic CO2 Variability or Lack Of

Guest Post by Renee Hannon

Introduction

This post examines CO2 ice core measurements from Antarctica during the Holocene Epoch. The key CO2 dataset for paleoclimate studies is the EPICA Dome C (EDC) data also known as Dome Charlie or Dome Concordia. Dome C is located on the eastern Antarctic Plateau, one of the coldest places on Earth and our planet’s largest frozen desert. The average air temperature is -54.5 degrees C with little to no precipitation throughout the year. CO2 measurements from the unique conditions at Dome C are compared to other Antarctic ice cores.

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The Paleocene-Eocene Thermal Maximum or PETM

By Andy May

The PETM or Paleocene-Eocene Thermal Maximum was a warm period that began between 56.3 and 55.9 Ma (million years ago). The IPCC AR6 report (actually a draft, not a final edited report), released to the public on August 9, 2021, suggests that this warm period is similar to what is happening today and they expect to happen in the future (IPCC, 2021, pp. 2-82 & 5-14). During the PETM, it was very warm and average global surface temperatures probably peaked between 25.5°C and 26°C briefly, compared to a global surface temperature average of about 14.5°C today, as shown in Figure 1.

Figure 1. The estimated global average surface temperature for the past 150 million years. Modified from: Christopher Scotese, the Paleomap Project, link.
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The Old Farmer’s Almanac Seasonal Forecasts

By Andy May

The Old Farmer’s Almanac has been making yearly long-term weather forecasts for 230 years. We pay attention to them because they are normally 80% accurate. They did not do as well last winter but were 72% in predicting the direction of temperature change, and 78% accurate in the change in precipitation. This is pretty remarkable because while the U.S. weather forecasts are 90% accurate five days in advance, they are only 80% accurate seven days out. The Old Farmer’s Almanac forecasts are far less specific, they only predict the direction of change, but their forecasts are for twelve months in the future, quite impressive. Figure 1 is their forecast for the lower 48 United States, for this winter.

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