Saturday, July 6, 2019

June global surface TempLS up 0.096°C from May.

Update - see revision here. The average is down by just 0.03°C, but SSTs were wrong month, and the map now looks different (correct version below).

The TempLS mesh anomaly (1961-90 base) was 0.811deg;C in June vs 0.715°C in May. This contrasted with the drop (0.056) in the NCEP/NCAR reanalysis base index. It was the hottest June in the record, 0.1°C higher than June 2016.

I am now showing TempLS LOESS as the alternative (rather than grid); I think it is about as good a method as mesh. It showed a rise of 0.114°C.

There was a marked global pattern (caused by error - see update), with tropics and SH mostly warm, and the extratropical NH cool, with the notable exception of Europe, which was very warm indeed, and NE Siberia likewise. The mostly cool Antarctica was also an exception.
Here is the temperature map, using the LOESS-based map of anomalies.

And here is the map of stations reporting:

This post is part of a series that has now run since 2011. The TempLS mesh data is reported here, and the recent history of monthly readings is here. Unadjusted GHCN is normally used, but if you click the TempLS button there, it will show data with adjusted, and also with different integration methods. There is an interactive graph using 1981-2010 base period here which you can use to show different periods, or compare with other indices. There is a general guide to TempLS here.

The reporting cycle starts with a report of the daily reanalysis index on about the 4th of the month. The next post is this, the TempLS report, usually about the 8th. Then when the GISS result comes out, usually about the 15th, I discuss it and compare with TempLS. The TempLS graph uses a spherical harmonics to the TempLS mesh residuals; the residuals are displayed more directly using a triangular grid in a better resolved WebGL plot here.

A list of earlier monthly reports of each series in date order is here:
  1. NCEP/NCAR Reanalysis report
  2. TempLS report
  3. GISS report and comparison with TempLS


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