Tamino’s radiosonde problem, Part 1

RSS vs. RATPAC tamino

Figure 1. Original found here: https://tamino.wordpress.com/2015/12/11/ted-cruz-just-plain-wrong/

A good month ago, the perennially unsavoury character calling himself Tamino once again tried to hold up the spotty “global” network of radiosondes (weather balloons) as somehow a better gauge of the progression and trend of tropospheric temperature anomalies over the last 37 years than the satellites, by virtue of being essentially – as he would glibly put it – “thermometers in the sky”.

So his simple take on the glaring “drift” between current surface records and the satellites over the last 10-12 years is this: The surface records are right and the satellites are wrong. Why? Because the surface records agree with the radiosondes while the satellites don’t! The radiosondes implicitly – in his world – representing “Troposphere Truth”.

And so, when your starting premise goes like this: the radiosondes = thermometers in the sky = troposphere truth, then any “drift” observed between them and the satellites (as in Fig.1 above) will – by default – be interpreted by you as a problem with the latter.

To repeat Tamino’s fairly simplistic reasoning, then, in the form of some sort of logical-sounding argument: Surface and satellites don’t agree. Radiosondes and satellites don’t agree. But surface and radiosondes do agree. Which means the latter two are right, their agreement robustly verifying the ‘rightness’ of each. (And also, the radiosondes represent “Troposphere Truth”.) Which leaves the satellites out in the cold …

There is, however, a definite issue to be had with this line of argument.

It doesn’t hold up to scrutiny … Continue reading

Why “GISTEMP LOTI global mean” is wrong and “UAHv6 tlt gl” is right

Ten days ago, Nick Stokes wrote a post on his “moyhu” blog where he – in his regular, guileful manner – tries his best to distract from the pretty obvious fact (pointed out in this recent post of mine) that GISS poleward of ~55 degrees of latitude, most notably in the Arctic, basically use land data only, effectively rendering their “GISTEMP LOTI global mean” product a bogus record of actual global surface temps.

Among other things, he says:

“The SST products OI V2 and ERSST, used by GISS then and now, adopted the somewhat annoying custom of entering the SST under sea ice as -1.8°C. They did this right up to the North Pole. But the N Pole does not have a climate at a steady -1.8°C. GISS treats this -1.8 as NA data and uses alternative, land-based measure. It’s true that the extrapolation required can be over long distances. But there is a basis for it – using -1.8 for climate has none, and is clearly wrong.

So is GISS “deleting data”? Of course not. No-one actually measured -1.8°C there. It is the standard freezing point of sea water. I guess that is data in a way, but it isn’t SST data measured for the Arctic Sea.”

The -1.8°C averaging bit is actually a fair and interesting point in itself, but this is what Stokes does; he finds a peripheral detail somehow related to the actual argument being made and proceeds to misrepresent its significance in an attempt to divert people’s attention from the real issue at hand. The real issue in this case of course being GISS’s (bad) habit of smearing anomaly values from a small collection of land data points all across the vast polar cap regions, over wide tracts of land (where for the main part we don’t have any data), over expansive stretches of ocean (where we do have SST data readily available) AND over complex regions affected by sea ice (where we indeed do have data (SSTs, once again) when and where there isn’t any sea ice cover, but none whatsoever when there is), all the way down to 55-60 degrees of latitude. Continue reading


Happy New Year to everyone!

There is a very good reason why the trend and general progression of tropospheric temp anomalies since 2000, as rendered by the new UAH.v6 dataset, are most likely correct. (Read this post to understand why it was necessary for UAH to update their tlt product from its version 5.6 in the first place.)

The reason is that they both match to near perfection the trends and general progression of incoming and outgoing radiation flux anomalies, as rendered by the CERES EBAF ToA Ed2.8 dataset, over that same period. They’re all flat …:


Figure 1. Incoming radiant heat (ASR, “absorbed solar radiation”) (gold) vs. outgoing radiant heat (OLR, “outgoing longwave radiation”) (red) at the global ToA, from March 2000 to July 2015. Continue reading