Friday, June 3, 2016

NCEP/NCAR down 0.164°C in May

The NCEP/NCAR index continued its steady descent in May, from 0.635°C in April to 0.471°C in May (anomaly base 1994-2013). That is down about 0.3°C since March. However, it is still the warmest May in that record. Breaking the pattern of recent months, it was rather cold in Siberia and N Asia. Warm in Australia and Central Europe. Cool in S USA, but warm in W Canada. The ENSO plume is now rather cool.

I should mention that at WUWT, Walter Dnes is doing somewhat similar analysis, with regression-based links to the major indices. His NCEP/NCAR integration gives similar results.

In other news, UAH V6 also dropped considerably, from 0.71°C to 0.55. But Arctic Sea Ice is still well down on previous years.


  1. Nick, for the UM CCI CFSR/CFSV2 for May 2016 I get a global temperature average of 15.78C, which is 0.42C higher than for the 1981-2010 climatic period. This estimate is based on the average of all of the final daily averages posted by UM CCI for May. They have posted final monthly estimates through April and show a value for May, but as near as I can tell the May value is not complete and only includes the first 18 days of May. I have posted updated graphs based on the UM CCI monthly estimates here and plan on updating these monthly:

    The UM CCI CFSV2 May global temperature anomaly estimate is down 0.14C from April and down 0.3C from the February peak. The May global temperature estimate is also the highest May temperature in the UM CCI CFSR/CFSV2 record back to 1979, although it is arguably easily within the uncertainty range compared to the second highest 15.70C for May 2002.

    I understand there is some controversy over the changes made in going from CFSR to CFSV2. This change occurred beginning April 2011 according to UM CCI. They claim that the analyses are compatible and can be used for comparisons across the entire period. I have compared their CFSR/CFSV2 to estimates they also provide for ERA/ERAI and there are obviously some differences, but I don't know enough about how both of these reanalyses are performed to make any assessment. The ERA/ERAI seems to track closer to the GHCN based global temperature anomaly estimates through 2015. I have not seen ERAI estimates for 2016 yet.

    The RSS V3.3 global TLT anomaly estimate is out now for May at 0.43C, down from 0.66C in April, and greatly down from the peak of 0.88C in February, compared to the 1981-2010 climatic reference period.

    1. Bryan,
      Thanks for all that. It seems a consistent story - atmospheric temperatyres are on the way down from the peak.

      " They claim that the analyses are compatible and can be used for comparisons across the entire period."
      Well, UM CCI just echo the data; they don't originate it. Reanalysis is generally not rated as homogeneous over time. It collects so much data from so many sources, that homogeneity is vary hard to neasure. And the data sources keep changing. It is really meant to be used on a forecasting timescale, not over decades. I did say here that May was the highest in the dataset, but I usually try to avoid comparisons over long periods. My excuse here is that the May was actually a lot higher than measures from decades ago, so there is a buffer for error. As an excuse, it's passable but not excellent.

      And that is worse when they change versions, because they don't want to recalculate the old data according to V2. DSS/RDA emphasize this issue when they say that their mission is to maintain a heterogeneous archive. There is a paper here on CFSv2.

    2. Nick, sources of data for the GHCN-based global temperature estimates are also not homogeneous over time so I don't see much difference in that regard. I like the CFSR approach because it utilizes much more input data. It certainly is not as good as I would like, but it has potential to be better than the GHCN estimates because of better spatial coverage. I am not sure the methodology of the reanalyses is optimal and there may be room for improvement there.

      What I would really like is to see is a global climatological reference network including anchored ocean buoys that could be used independently and/or in conjunction with CFSR and GCN (I say GCN because in some cases many non-GHCN stations have been included as with BEST). Wishful thinking I am sure.

      Thanks for the links. I will check them out.

    3. Bryan,
      "Nick, sources of data for the GHCN-based global temperature estimates are also not homogeneous over time"
      Well, you actually need homogeneity to make comparisons, so saying something else lacks it doesn't help. But people give a lot of attention to surface temperature homogeneity, and where they find it lacking, make strenuous efforts to correct (not always appreciated). Land-based records do have an inherent basis for homogeneity - measured in the same place, mostly, and by instruments which can be calibrated against each other. SST records are harder, and we saw a recent example. There has been a change in the mix between buoys and ships over thirty years. Each is done as well as possible, but the are different. They can be compared, but only by finding cases where buoy and ship are measuring in about the same time and place. These matches have accumulated, and in 2011 Kennedy et al were able to say fairly accurately what the difference was, and so correct for that inhomogeneity, as in Karl 2015.

      This sort of change of mix is happening all the time with reanalysis, and they have no real reason to make the huge effort that would be required to determine and correct for the inhomogeneity.