Another popular activity is selecting stations which fail to show recent warming. So I've presented here a different kind of plot which shows all the GHCN stations on a world map, with shading to indicate the trend over the last 30, 45 or 60 years (you can choose). It derives from the plot I posted for November temperatures. It takes advantage of HTML 5 linear color shading, and uses a triangular mesh. Each station has a color corresponding to its trend for the chosen period; although the colors can vary locally, the station neighborhood itself should have the correct color. Note that there is no spatial averaging (except for the shading); the individual station trends determine the coloring.
One result that I found interesting is that while there are patchwork regions, eg USA, there are also large regions with fairly uniform trends, particularly the ocean.
So here's the plot. It is interactive - you can rearrange it, magnify, show the stations, click to see station detail and numbers etc. Use Ctrl+. Ctrl- to get it the right size for your screen. The mechanics are explained below.
Click on this map to orient the world plot.
How it worksMore details here. The flat map at top right is your navigator. If you click a point in that, the sphere will rotate so that point appears in the centre. The buttons below allow modification. Set what you want, and press refresh. You can show stations, and the mesh, and magnify 2×, 4×, or 8× (by setting both). You can click again to unset (and press refresh). Then you can click in the sphere. At the bottom on the right, the nearest station name and anomaly will appear. You may want to have stations displayed here. The selection menu chooses the period; if you change the period, the plot changes without need for refresh.
How the trends are calculated.Calculating station trends is not trivial, because of missing values and seasonal variation. Obviously missing winter values at one end will bias the trend. A reasonable fix is to subtract the mean for each month and work with anomalies. But the means don't correspond exactly to the same period. I used a weighted least squares method similar to that used in TempLS. The weighting simply has unit value for months with readings, zero without. The model is xmy ~ Lm + Tr Jmy where x are the station readings, L the monthly offsets, Tr the trend, and J a linear progression of months, in century units. The suffixes m for month, y for year. This is fitted by least squares. The resulting formula is similar to OLS. If we now say that J has zero values for missing x, and I is a similar vector which is 1 mostly, but zero where x is missing, then the OLS trend formula would be
Tr = f(x) / f(J) where f(x) = S(Jx) - S(J) S(x) / S(I)where S represents summation over all month/year. Denoting Sy as the process of summing over individual months, and Sm summing the resulting 12 sums, the formula from the above fit is:
Tr = f(x) / f(J); f(x) = S(Jx) - Sm( Sy(J) Sy(x) / Sy(I))
You may see a few ocean stations appearing on land. The reason is that I artificially create ststions at the centre of each 4x4 deg cell. If there is enough sea in the cell for HADSST to report a SST value, that will be assigned to that central point, even if it is on land.
Note that the color scheme suggests cooling, but most of the blue range is actually positive (though smaller) trend.
Stations are included in the trend analysis if they have at least 80% of months reporting within the range.