Global projections for TempLS temperature reporting.

A couple of years ago I described here my way of implementing equal area projections for global data, and in particular the Mollweide and Robinson projections. Robinson would not have been a high priority, except that GISS ofers it for its temperature projections, so I can use that for comparison.

Events intruded, and I didn't implement it for routine use immediately, and when I later did, then of course mission creep crept in, and I thought of ways to use the pixel mapping methods for the actual integration (not that I am lackimg options).

However, it really should be done. The rectangular lat/lon method that I use conveys the necessary information in an easily understood way, and I will still be using it for some internal purposes, but it overweights behaviour near the poles visually. I calculated. Here is a table of the % by pixel of colors in my plots for March 2022, shown also below. Color 11 is the warmest (>4°C)

Color:	2	3	4	5	6	7	8	9	10	11
Lat/Lon	0.19	0.55	1.85	5.1	10.39	13.51	24.74	21.63	13.63	8.41
Robinson	0.22	0.66	2.17	5.55	10.68	14.18	28.01	23.13	11.22	4.18
Mollweide	0.23	0.65	2.23	5.56	10.68	13.95	28.54	23.23	11.15	3.77

March was a month in which the Arctic was very warm, and you can see that there were more than twice s many of the warmest pixels in the lat/lon projection (approx 8% vs 4%). The other projections are close to the true % on the sphere.

I plan to show the three projections in a single frame, with navigation buttons. Robinson will show initially, but you can cycle to Mollweide or lat/lon using the buttons below.