The Moyhu TempLS mesh index was down, at 0.657°C, compared with 0.707°C in August. This was at variance with the reanalysis index, which was up by 0.06, and with TempLS grid, which was steady at a rather higher value of 0.749°C. This is all based on 4168 stations reporting; we can expect 2-300 more reports to come.
The warm areas were Russia W of urals, E Canada and US mid-west, and Brazil. Also E Pacific (but not SE). This is the same pattern as with the NCEP/NCAR reanalysis. The very cold place was Antarctica.
I was curious about the reason for discrepancy, especially with the TempLS versions, which just integrate the same data with different weights. Each month, I publish in the Mesh report a plot of attributions, described here. This shows the breakdown of the contributions to the weighted average. You can see, for example, that the contribution from Antarctica was large negative, nearly 0.1. That means that the global average would have been 0.1°C higher if Antarctica had been average instead of cold.
So I made a similar plot comparing the contributions for both grid and mesh, just in September.
You can see that Antarctica made a very small negative contribution to the grid average. That is because the same data has much smaller weight. Each station there sits in just one cell, and is weighted with that area, which is further reduced by converging longitudes. Most of the area has unoccupied cells, which get the default global average - ie don't reflect measued Antarctic cold. But the mesh weighting weights the few Antarctic cells by the whole land area.
You can see other effects; particularly that the sea contributes less with mesh. This again reflects Antarctica. Some of the big triangles there terminate in the sea, and those cold points get upweighted too. But the accounting assigns that part to the sea total. And these two negatives explain why in Sept, the grid mean was almost 0.1°C higher than the mesh. Actually, in the same way, other warm sparse regions, like Arctic, Africa and S America, made a greater warm contribution with mesh, which brings the total down a bit.
I'm developing new integration methods, Grid with Infill, and Spherical Harmonics based. I'm hoping these will give more consistency. In September, I think the mesh is formally more accurate, but with increased uncertainty, because of the high dependence on a few Antarctic stations. If more Antarctic data comes in, the average could change.
GHCN miss a hot spot in West Antarctica. I picked out the sector 60-90 S, 100-160W, from NCEP/NCAR in KNMI climate explorer, and the anomaly for September was +3 C warmer than in August.
ReplyDeleteGistemp have the stations Theresa and Byrd in this area, and may pick up some of this "heat", making Antarctica and the global index less cold. However, Byrd station is usually 2-3 months late in Gistemp, and will likely not be included in the first report coming soon.
Olof,
DeleteYes, you can see it here if you bring up the September monthly average (it's in the date table as if day 0). Of course, NCEP/NCAR may not be right. But it certainly contributes to the difference.
GFS still shows lower anomalies that NCEP for Antarctica in september (but not for the rest of the world) and did not catch the same warming in early october. Theresa as warmed a bit in the GISS analysis but still is very cold compared to 2014. Problem is that the main difference between GFS and NCEP lies in a region uncovered by GISS map (the ocean bordering WAIS) so it seems open for any interpretation.
ReplyDeleteAs for october, Maybe NCEP took in consideration some parameters not based on temperature, such as air pressure, in its model ? Indeed, Antarctic oscillation shifted from positive to negative phase in the begenning of october. Interesting also, I noticed that during strong El Ninos like 1997, Antarctica seems to be cold in september but starts warming in winter.
KC,
DeleteI have just put up another post which you might find interesting. It shows local detail of trends during the run-up to Oct 6th. There are big changes in Antarctica. Much of the changing area is over the sea ice.
One reason why NCEP GFS/CFSR show lower anomalies than NCEP/NCAR might be the " version break" in 2011. They made a major update but did not re-run the years before 2011. Hence, for absolute level of anomalies, or long term trends, I find NCEP/NCAR more reliable.
DeleteThanks, the trends on the map seems to confirm pressure patterns that may affect sea ice. As for differences between GFS and NCEP, I was not aware of that version break even though there is a cooling (and warming) bias affecting GFS. For GISS, it seems to be in between.
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