Covid Python Delays Play + BlueSky

I got hit pretty hard by covid which has limited my engagement for the last 5 months, and it isn’t done with me yet. Hope for better luck for the rest of you.

I have been developing a set of python packages that let me download and manipulate the data way faster, as well as allowing for automated testing and fast prototyping.

I’m moving towards BlueSky (@ReesCatOphuls.bsky.social), and away from X (@ReesCatOphuls), but will likely post in both places for a while.

My first graphic: °C Milestones – From First Appearance to Permanence used the Berkeley Earth dataset (See GMST Data Sets), which were pretty easy to use.

My second graphic: 1000 Days above 1.5C before Trend passes 1.5C? uses Copernicus ERA-5 data, which seemed easy to use, but as per my rather dull article Copernicus 1850-1900 Baseline – Daily GMST Anomaly … it turned out that getting an accuracy of better than 0.05C per day needed quite a bit more work, testing and calibration against the numbers published directly by Copernicus themselves. When I finally update the 1000-days graphic with the latest data, some of the numbers will change a bit for the “>0.25C”, “>0.5C”, “>0.75C”, “>1.00C”, “>1.25C” series .. due to the improved accuracy. The actual graph lines basically don’t move from the original. Amazingly we have had zero days over 1.75C since I created that graphic.

I have a bunch of new ideas to keep me busy, so I’ll be posting some new graphics over the next few weeks.

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