Tuesday, June 27, 2017

Temperature station distribution - equal area plot

I have been experimenting with maps that are a byproduct of my systematising a cubed sphere grid. I thought it would give a better perspective on the distribution of surface stations and their gaps, especially with the poles. So here are plots of the stations, land and sea, which have reported April 2017 data, as used in TempLS. The ERSST data has already undergone some culling.

It shows the areas in proportion. However, it shows multiple Antarctica's etc, which exaggerates the impression of bare spots, so you have to allow for that. One could try a different projection - here is one focussing on a strip including the America's:

So now there are too many Africa's. However, between them you get a picture of coverage good and bad. Of course, then the question is to quantify the effect of the gaps.


  1. Nice work Nick. A very interesting perspective on surface temperature data density. It's pretty obvious the sparse coverage areas coincide with low population density, including large deserts, large jungles, and the polar regions. We need more automated stations to fill the gaps. Only a tiny percentage of all the money being wasted on supposed "climate change" mitigation could easily pay for this. A global climate reference type network similar to USCRN would be ideal. Easier said than done.

    1. What is an example climate change mitigation spending that you think is "being wasted"?

    2. JCH, for starters, I suspect many millions of dollars have been wasted every year on the useless climate change conferences that are supposedly aimed at mitigation commitments, but are more political shows than anything else. That money alone would pay for quite a few global CRN sites.

    3. The waste is that they hire the incompetent Roy Spencer to make sense of sattelite readings that cover the majority of the earth. Open source the raw data and we could figure it out in short order.

    4. Easily tested: Hold out subsets of the data and do a global reconstruction (using a sensible estimator which handles coverage appropriately) to see what difference it makes.

      Some more stations (and buoys) would be useful in the 19th and early 20th centuries. Not sure how much funding that would take.

    5. I was right that old Roy Boy was incompetent:

      What does he have...like thousands of lines of Fortran code? And the problem was drift in the orbit? I was working timing and leap year calibrations from GPS ephemeris data for my last paid job and find it astounding that they could make obvious mistakes like that. In Roy's case, all those extra lines of source code were putting lipstick on a pig. What's really important is focussing on the salient parts of the algorithm and calibrating that stuff.

      Like I said, we could do much better than these fundie hacks.