Looking at GHCN V4 beta

The long-awaited GHCN V4 is out in beta, here (dir). The readme file is here. It is a greatly increased dataset, which transfers a lot of data from The large daily archive to monthly. There are 26129 stations in the inventory, instead of 7280. 11741 reported in September, where usually only about 1800 report in GHCN V3. But it is not so clear that the extra numbers add a great deal. In V3, the stations were reasonably evenly distributed, except for a lot in the US, and some bare patches. In V4, there seem to be more regions with unnecessary coverage, and the bare patches, at least in stations currently reporting, are not much improved.

I'll be interested in practicalities such as how propmtly the data will appear in each month. GHCN V3 was prone to aberrations in reporting; that may get worse. We'll see. Anyway, I've run it through TempLS grid. The initial run of the mesh version will take several hours, so I'm waiting to get some decisions right. It's possible I should opt for a subset of stations, and I'll probably want to modify the policy on SST stations. Currently I reduce from a 2°x2° grid to a 4°x4°, mainly because otherwise SST would be over-treated relative to land. This is partly to reduce effort, but also to reduce the tendency for SST values to drift into undercovered land regions. Now the original SST grid is comparable to land, so the case for saving effort is less. The encroachment issue may remain.

The other issue is whether the land data should be pruned in some way. I think it probably should.

Anyway, I'll show below the WebGL plot, with land stations marked, for September 2015, done by TempLS grid. I think it is the best way to see the distribution. You can zoom with the right button (N-S motion), and Shift-Click to show details of the nearest station. The gadget is similar to the maintained GHCN V3 monthly page, which you can use for comparison. You can move the earth by dragging, or by clicking on the top right map. Incidentally, the gadget download is now about 4Mb, and may take a few seconds. I'll work on this.




The plot shows the shaded anomalies for September. Incidentally, the average was 0.788°C, vs 0.761°C for V3. Generally, the differences in TempLS grid are very small. August was almost identical. You can see that some regions have very dense cover, for example, Germany, Japan, Australia and the US. Regions that were sparsely covered in V3, such as the swathe through Nabibia, Zaire etc, are still sparse. I don't see much improvement in Antarctic, and Arctic has some extra, but still not good coverage.

Here is a list of the top 20 countries reporting in September. You can see the excessive numbers in the US, Australia and Canada, and proportionately, in Germany and Japan. Almost half are in the US. I think I will have to thin these out. The inventory, however, is now just bare data of lat, Lon, Alt and name. So it isn't easy to pick out rurals, for example.

Number Country 5212 United States 711 Canada 577 Australia 495 Russia 213 China 152 Japan 152 Germany 82 Spain 79 India 76 Brazil

Number Country 73 Indonesia 69 Argentina 62 Mexico 61 Kazakhstan 50 Turkey 49 Ukraine 49 Algeria 47 France 44 Thailand 41 Mongolia