After 5 days on Heron Island and a narrow escape from Cyclone Debbie, I am now back to spherical gridding!
The most elegant method for spatial integration of irregular temperature data must surely be spherical triangulation over the earth’s surface. This is because it treats each measurement equally by covering the earth’s surface with a triangular mesh of station & SST nodes. Unlike linear triangulation (described previously), spherical triangulation also spans polar regions. There is no need for any ‘kriging’ or linear interpolation into sparse polar regions, since they are naturally included. I finally deciphered IDL’s spherical triangulation output, thanks to Nick Stokes. Here then is the result in 3D for temperatures in January 2016. The shading for each triangle is the average of each node’s temperature anomaly (-5C – +5C).
I now need to find a better visualisation method as this one takes way too long, however at least it shows how triangulation now covers both poles.
Each triangular area shown in Figure 1 is calculated in 3D cartesian coordinates to derive the area weighting used for averaging. Figure 2 shows how the final spherical results compare to the 2D (lat,lon) triangulation results.
There is really very little difference in the annual temperature anomalies between the spherical results and the 2-D triangulation results. Based on these results it would seem that Cowtan & Way have exaggerated polar warming effects between 2005 and 2013. Figure 3 shows the monthly comparison and just how remarkably similar the 2-D and 3-D results are despite completely independent methods of integration.
Aesthetically the spherical triangulation grid is my favourite. Unfortunately, the extra effort makes only a tiny difference compared to the more easy 2D triangulation solution based on lat,lon coordinates. Despite this, both methods, in my opinion, are better than simple rectangular gridding as used by Hadcrut4 and (partially) by GISS and NOAA. Furthermore they avoid interpolation.
I will post the code and the data soon.