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The Climate Show 21: Carbon, coal and BEST

Posted on 10 November 2011 by John Cook

The Climate Show has released Episode 21Gareth and Glenn discuss bad news on carbon emissions balanced by good news on solar photovoltaics, a Medicane bringing dramatic flash flooding to Italy and France, a scientist who thinks the Arctic could be effectively ice free in late summer in only four years, and the inside story on what the New Zealand election might mean for climate policy down under.

I talk to them about the new BEST temperature record but let's face it, Dana's GIFs are the real star of the show :-)

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Comments 1 to 6:

  1. Well who doesn't love an animated GIF, after all? is now live, by the way.
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  2. I knew you'd come through for me in time, Dana :-)
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  3. John, Dana, Hats off to you both.
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  4. Well, there's my Friday evening entertainment all sorted... :-P
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  5. John: Sorry to spoil the narrative, but the stuff about CRUTEM3 is wrong. Not your fault - the BEST team messed up the comparison again. The problem is that - just with GISS dTs - CRUTEM3 is not a land-area average and therefore not comparable to the others. The problem is discussed in AR4 here. Once they fix this, I expect the final figure to look more like this: all. (I generated corrected CRUTEM3 data by re-averaging the gridded data, but a weighted average of the hemispheric sets should give a very similar result. The graph also depends on the choice of baseline, of course.) Extrapolation over the arctic is not a factor for CRUTEM3, since it is a land-only product. The residual differences between CRU and the others seem to come down to the following factors: 1. Different (smaller) set of station data (~4k stations). 2. Constant angle grid, leading to undersampling of high latitudes. 3. No extrapolation into empty cells. I'm looking at these, and my tentative conclusions are as follows: For CRUTEM3, (1) causes the lack of warming over the last decade. (2) leads to a suppression of the total temperature of the last decade, but doesn't change the picture within the last decade. (3) has a smaller effect than the other two (weak evidence only). Of course all the differences in the land indices could easily be swamped by the fact the global indices (which are what we are really interested in) use different SST data. I haven't even started looking at that.
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  6. Sigh. I withdraw all of the previous comment. I was fooling myself by adjusting the baselines. Sorry. I now think that BEST have got the CRUTEM3 data correct. I can reproduce the BEST, NOAA and CRUTEM3 lines from their plot, although to do so I have to tweak the baseline for the CRUTEM3 value. (I suspect the difference between the weighted combination of hemispheres and the global cell average is the issue here). I'm still having trouble reproducing their GISS line though, even with the data Robert pointed us to.
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