From Watts Up With That?

Richard Willoughby

The temperature measured across the globe in October 2023 has set a new record high anomaly.  With that as the backdrop, this essay looks at the predictive skill of climate models in forecasting the record.

Anomalies – A Brilliant Deception

Climate botherers are fixated on temperature anomalies and have convinced sufficient number of voters that 1.5C rise in global average surface temperature (GAST) is a critical threshold for the globe.  October 2023 came perilously close to breaching the threshold so it deserves closer analysis as to what it means and how well various climate models have managed to forecast this outcome.

Temperature of the Lower Troposphere

This analysis begins with the examination of the temperature of the lower troposphere produced by the satellite remote sensing system (RSS) and displayed below in Chart 1.

The data is available at KNMI but was last updated in July 2023, which is usually the yearly peak; reaching minus 0.16C in that month.  October is typically 2C lower that July.  A key feature of Chart 1 is the trend; rising at 2.1C/century.  The regression coefficient is only 6.29% due to the significant annual swing in the range 3 to 4 Centigrade degrees.  However, if this data is reduced to an anomaly relative to the same month over a 30 year period to iron out the annual variation, the result gets closer to a trend line as shown in Chart 2.

The trend line has almost the same slope; increasing at 2.1C/century as in Chart 1 but now the regression coefficient improves dramatically to 71.4%.  Given the high correlation, it is reasonable to expect this trend to continue for the next 76 years such that the RSS TLT will reach 1.1C in July 2100.  And there are certain to be many more months prior to that year when the 1.5C threshold will be exceeded.  In fact, October 2023 probably exceeded the 1.5C threshold.  The RSS TLT only needed to reach minus 2.85C in October 2023 to exceed the threshold.

Taking A Global Perspective

Reducing the monthly GAST to a single anomalous value is somewhat deceptive.  It is as if all surfaces are created equal so it is OK to average them over a whole range of different surface.  But this is not based on sound thermodynamic principals.  A first step in getting a better appreciation of the significance of record temperatures in 2023 is to examine the warmest month in 2023 with the same month in 1982, the early days of remote satellite sensing to observe how the entire global temperature has responded regionally per Image 1.

The first observation is that the entire globe has not warmed.  Some locations are up to 7.1C cooler than in July 1982 and some are 7.4C warmer.  The warmest regions are in the Northern Hemisphere while the coolest regions are in the Southern Hemisphere.  The area average increase in temperature is 1.3C corresponding to 3.2C/century so slightly above the trend.

Note also that even this satellite determined temperature is not global.  The coldest regions near the poles are excluded from the measurement.

Global Land

It is evident that the thermodynamic response of land surfaces and water surfaces are different.  Land responds faster and over a wider temperature range for a given thermal energy input than water.  Image 2 indicates the temperature difference from October 1982 to October 2023, the month of highest anomalous GAST, for just land surface, excluding Antarctica, based on the Global Historic Climatology Network (GHCN) measurement.

The area average temperature increase over the land is 2.5C, corresponding to 6.1C per century.  Some land surface has cooled by as much as 4.3C while some warmed by up to 14.1C.  The highest temperature increase is in the high latitudes in the Northern Hemisphere likely to have been permafrost back in 1982.  

Global Ocean

The Reynolds optimally interpolated ocean surface temperature data set is not yet available for the NH summer and fall of 2023 so the ocean surface analysis is stepped back a year by comparing August 2022 to August 1982 as displayed in Image 3.

The increase in area average temperature is 0.5 Centigrade degrees with a range in difference of minus 3.6 to plus 13.1 Centigrade degrees.  The region with the most warming is near the Russian coastline in the Arctic and likely due to earlier annual loss of sea ice in 2022 relative to 1982. 

There are large regions of the oceans in the SH that are now cooler than 1982.  The cool zone along the tropical Pacific was likely warmer in 2023 than 2022 due to El Nino conditions prevailing.  Combining the 0.5C for ocean with the 2.5C for land, gives an area average increase of 1.13C, which is slightly lower than the 1.3C over the same period for the RSS TLT.  It is more than likely that the October 2023 ocean temperature increase is slightly more than 0.5C due to El Nino conditions prevailing in 2023. 

Predictions from Selected Climate Models

The following four images, numbered 4 to 7, compare the predicted results for global temperature based on CMIP6 SSP85 input from various climate prognosticating groups based in regions as follows:

• ACCESS6 – Australia
• INM6 – Russia
• MIROC6 – Japan
• GISS6 – USA

The comparison is for October 2023 against the baseline of actual measured values using GHCN for land and MODIS for ocean surface.  MODIS was selected for SST because it is available for October 2023 but has some data gaps observed as greyed pixels in the images.  The colour scale for all images is ranged from minus 5 to plus 5 in Centigrade degrees.  Regions of red indicate where the model runs hot while blue indicates where the model runs cold.

Compared to measured data, all the models have a tendency to cool the NH and warm the SH.  The scale has a range of ten Centigrade degrees but that was chosen to produce nuanced images.  The variation is much wider for certain locations.  The Greenland Plateau has predicted temperature considerably lower than measured in all models.  The average temperature for each of the four models is:

• ACCESS6 – 15.7C
• INM6 – 14.7C
• MIROC6 – 16.3C
• GISS6 – 15.3C

The maximum difference of 1.6C is between the MIROC6 and INM6 models.  Image 8 shows how the difference varies across the globe.  The difference has a range from minus 9.4 to plus 25.4 Centigrade degrees.  The greatest difference is at both poles.

It might be assumed that the MIROC6 model has already reached the dreaded tipping point but the temperature in both polar regions is still well below freezing but just not as cold as the INM6 prediction.

Conclusion

As of October 2023 the difference in average temperature between the models already exceeds the 1.5C threshold and each of the models goes on to predict a future to 2100.  By then the difference in average temperature between the highest and lowest reaches 2.3 Centigrade degrees.  The regional differences between the two models cover a range of 34.8 Centigrade degrees.

The predictive capability of climate models at regional level is far worse than forecasting that any month of next year will be the same as the corresponding month this year.  In fact the measured temperature at any location for any month forty years ago is a better predictor at regional temperature now than any climate model. 

The common difference for all models relative to measured temperature, with the SH running hot and the NH running cold, indicates a systemic error in understanding the natural driver of climate change.  The models are incapable of producing any regional cooling trend so the observed regional cooling trends in the SH invalidate the models.

The notion that regional temperatures across the globe can be averaged to produce the GAST as something meaningful indicates no understanding of thermodynamics.  Debating the difference in GAST from one period to next to a fraction of a degree is mindless nonsense.  The notion the 1.5C increase in GAST will cause a tipping point is in the realm of utter nonsense. 

An Important Question

Do climate models offer a firm basis for attempting to re-engineer the entire global economy?

The Author

Richard Willoughby is a retired electrical engineer having worked in the Australian mining and mineral processing industry for 30 years with roles in large scale operations, corporate R&D and mine development.  A further ten years was spent in the global insurance industry as an engineering risk consultant where he developed an enduring interest in natural catastrophes and changing climate.