US Temperatures – Tony Heller

OPS-58 Something simple but interesting. This post is highlighting a recent video by Tony Heller that points out the absurd situation currently playing out in the US Historical Climatology Network (USHCN) Station temperature data. The USHCN temperature data for the first three months of 2022 appear to be classified as 100% fabricated (computer generated). Is this a human error, a coding problem or has the USHCN moved to the ridiculous position of officially ignoring the measured data? From a practical viewpoint, the official average temperature data has long been 100% computer generated (homogenization comes to mind), but at least the measured temperatures were used as a starting point. With a combination of ghost stations (decommissioned or virtual locations) and over-homogenization, the official temperature data has long been open to manipulation. And there is no doubt that the surface data is manipulated (the process is called homogenization). The underlying question is how much of that manipulation is justified?

#climatechange #delaythegreen #globalwarming #showusthedata

Knowingly ignoring the record heat waves and the vast majority of high temperature records set during the Dirty Thirties (CSS-8 – Earth Day 2021 and OPS-49 – Temperature Manipulation) is disingenuous to the many people that died or lost their livelihoods during that devastating historical period. If only the climate scientists of the early 19^th century could have controlled temperatures as easily as our current crop of “expert climate scientists” are able to do. I suppose those that died during that period can rest easier knowing that the temperatures were not as bad as they perceived them to be.

Another example is the very strong 1998 El Niño that was only 0.02 °C cooler than the similarly strong 2016 El Niño (based on the UAH satellite Lower Troposphere (OPS-56 – The PAUSE) measurements). The 2016 El Niño is not as prominent in the US surface temperature data. Is that a function of the surface data accuracy, homogenization process, time of year, geographic location, ideology bias or a combination of these and/or other potential parameters? Hard to say, the climate is complex and the homogenization process is not transparent.

Normally I focus on datasets that I can download for myself. The work that Tony Heller puts out is based on the software he developed to efficiently access the USHCN temperature database. Based on the magnitude and complexity of accessing that USHCN data, I have just used Tony Heller’s data plots in the past and will continue to use them (unless someone can show that the data he puts forward is falsifiable). To date, that has not happened. Homogenization is happening. I reviewed the process in my CSS-13 – A Look at Homogenization post.