Because our collective eyes right now are fairly attuned to the colors of these grids and how changes in individual stations affect the contours, it’s interesting to take a look at these new contoured maps and compare them both to each other and to the GISS contour map.
First the CRUTEM3 (top), HadCRUT3 (middle), GISS (Nov 13 version – 250 km smoothing rather than 1200 km of the frontpage GISS image).
First a small point. Living in Toronto, I often look first at how the maps represent Toronto since I know what the weather’s been like here. For the most part the land portion of the HadCRUT3 map is identical to the CRUTEM3 map, but not where I live. In CRUTEM world, we experienced a colder than average October (which is how it felt on the ground here), while in HadCRU world we experienced a warmer than average October. One possible and even likely explanation is that HadCRU includes temperatures from the Great Lakes (which weren’t warm for swimming this year.) I didn’t go swimming at our place on Lake Ontario once this year. But maybe October water was less chilly than usual.
More points after you look at the graphics.
A second small point in the light of our watching the ball as stations got added to the GISS map of the Canadian Arctic. The land station contributions to HadCRU3 look like a slightly later GHCN version than CRUTEM3. HadCRU3 has a gridcell a bit to the southwest of Ellesmere Island (presumably Resolute) that got added after Nov 7, according to Gavin Schmidt. This gridcell is absent from the CRUTEM3 version. The Nov 13 GISS version lacks both Resolute and Alert for reasons, presumably because of an oversight as they put patches on patches.
A third point – the global average in the GISS 250 km version is 0.78 deg C, while it’s 0.61 deg C in the 1200 km version.
The CRUTEM3 version looks a lot like the GISS version. Although these compilations are often described as “independent”, recent events have clarified (if clarification were needed) that these compilations are not “independent”. Both rely almost exclusively on GHCN – GISS adds a few series around the edges.
The reverse engineering of CRUTEM3 looks almost pathetically easy given that we’ve already waded through step 0 of GISS, where they collate different GHCN versions (dset0) into a single station history (dset1.) CRU doesn’t have the bewildering sequence of smoothing operations that Hansen uses at multiple stages (though Hansen, mercifully, doesn’t use Mannian butterworth smoothing).
To my knowledge, unlike GISS, CRU does not make the slightest attempt to adjust for UHI, relying instead of articles like Jones et al 1990 purporting to show that UHI doesn’t “matter”.
We can already emulate GISS step0 – not that it makes any sense, but it provides a benchmark. Here’s all that seems to be necessary to produce a gridded CRUTEM3 series given a dset1 data set. First, create an anomaly-version of the series. I have a simple function anom on hand and this could be done as follows:
Then one could make an average of dset1 series within gridcell i as follows, where info is an information dataset in my usual style containing for each station, inter alia, its lat, long and gridcell number (called “cell” here):
for (i in 1:2592) grid[,i]=apply(dset1.anom[,info$cell==i],1,mean,na.rm=T)
This would yield the CRUTEM3 series. My guess as to why they don’t want to show their work is because they probably use hundreds of line of bad Fortran code to do something that you can do in a couple of lines in a modern language. Anyway, I’ll experiment with this at some point, but this is my hypothesis on all that’s required to emulate CRUTEM3. CRU has been funded by the US DOE; if, like GISS, they are doing nothing other than trivial sums on GHCN data, one feels that the money would be better spent on beefing up QC and data collection at GHCN.
I downloaded CRUTEM3.nc (today’s version) and checked for gridcells with October anomalies of 5 deg C or higher and then checked to see what stations were in those gridcells. I obtained teh following list, all but one in Siberia, the other one being Barrow, Alaska (where there is an extraordinary contrast between nearby stations that deserves comment.)
1710 22223724000 NJAKSIMVOL’ 62.43 60.87
1716 22223921000 IVDEL’ 60.68 60.45
1729 22224817000 ERBOGACEN 61.27 108.02
1720 22224125000 OLENEK 68.50 112.43
1723 22224329000 SELAGONCY 66.25 114.28
1721 22224143000 DZARDZAN 68.73 124.0
1724 22224343000 ZHIGANSK 66.77 123.4
1686 22220069000 OSTROV VIZE 79.5 76.98
1688 22220292000 GMO IM.E.K. F 77.72 104.3
1693 22221432000 OSTROV KOTEL’ 76 137.87
1685 22220046000 GMO IM.E.T. 80.62 58.05
3361 42570026000 BARROW/W. POS 71.3 -156.78
It looks like CRU has been paying attention to the GHCN commotion and has avoided using one of the problem versions. It is however interesting that some of the above stations (Olenek, Erbogacen etc) were problem stations and one would hope that one of the data distributors has actually checked these stations against original daily versions.