The latest version of the CRU station data is called CRUTEM5 which when combined with the new Met Office sea surface temperature data HadSST4 becomes the new official global temperature dataset HadCRUT5. This was released about 2 weeks ago and is now operational. We have already seen that HadSST4 increases recent temperatures mainly by updating the historic corrections of bucket and engine room intake temperatures. In addition CRU have used a method of infilling sparse 5 degree bins similar to that of Cowtan & Way, which now becomes obsolete. I decided to have a look at the new data.
The main difference for programmers is that all the data are now stored in Net CDF files, which means you have to rewrite all the data handling software. The particular format they use is not documented as far as I can tell. So I used the NCDUMP utility to work out the structure of their NetCDF files. All the station files are now also in netCDF files instead of simple text files.
My method of calculating global temperatures uses a spherical triangulation of measurement points across the surface of the earth. This has the advantage of naturally covering the full surface area. The size of individual triangles just changes with measurement density. So the grid “cells” are 3D triangles rather than 2D Lat,Lon cells. The temperature of each triangle is the average of the 3 vertices. After a couple of days effort I now have it working.
HadCRUT5 temperature distribution for December 2020 determined by spherical triangulation
So how do my results compare with theirs? Here is a direct comparison for the annual temperature anomalies.
Comparison of the official HadCRUT5 annual temperature anomalies and the Spherical triangulation method.
My results are remarkably similar to theirs whereas this was not the case with HadCRUT4. The reason why they are now in good agreement is because HadCRUT5 extrapolates a fit into empty grid cells using a method similar to that of Cowtan & way. As a result HadCRUT5 has now become one of the “warmer” datasets whereas HadCRUT4 was one of the coolest. Despite this CRUTEM5 has not really expanded much in station data. I find 10631 stations but of these only 7734 have data within the normalisation period 1961-1990, which is not much more than in CRUTEM4 (10295 & 7680).
Finally here are the monthly results.
HadCRUT5 Monthly temperature anomalies. calculated using spherical triangulation.
My monthly and annual temperature anomalies can both be viewed as simple text files.
The software written in IDL is also available on request.
https://rclutz.wordpress.com/2021/01/19/global-warming-ends/
The animation is an update of a previous analysis from Dr. Murry Salby. These graphs use Hadcrut4 and include the 2016 El Nino warming event. The exhibit shows since 1947 GMT warmed by 0.8 C, from 13.9 to 14.7, as estimated by Hadcrut4. This resulted from three natural warming events involving ocean cycles. The most recent rise 2013-16 lifted temperatures by 0.2C. Previously the 1994-98 El Nino produced a plateau increase of 0.4C. Before that, a rise from 1977-81 added 0.2C to start the warming since 1947.
Clearly El Nino had a marked effect on temperatures in 1998 and 2016 but then you would expect a drop in global temperatures with a consequent La Nina. Several people (me included) had noticed a 60 year oscillation in the temperature data but the expected downturn post 2010 did not appeared.
Clearly the climate has warmed but I suspect there may well also be a systematic effect in the way temperature data have been processed, corrected and homogenised. If you expect a result from theory you can sometimes fool yourself into making a selection bias to support your theory.