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.
Figure 1. Note, base period here is 1981-2010, not 1951-1980. Data from KNMI Climate Explorer. 1200 km smoothing product.
Why does the thick golden curve in Fig.1 rise so much less from 1970 to 2015 than the thin black curve on top of it? The two after all cover the exact same latitudinal band, from 55 degrees north to 55 degrees south. Where 98-99% of the world’s human population happens to reside.
The reason is of course that the golden curve includes both the land AND the ocean surface, while the black one represents the land portion only. Land surfaces naturally warm (and cool) much faster than sea surfaces, both in the short term (as seen in the general interannual noise level) and in the longer term (as seen in multidecadal trends). The average of the two (land+ocean) thus always ends up somewhere in between either, depending on their respective area weighting. Within the 55N-55S band, the ocean/land ratio is 2.77 : 1, within the 55-90S band (the Antarctic), the ratio is 2.29 : 1 (sea ice excluded), while within the 90-55N band (the Arctic), it is 1 : 1.1 (again, sea ice excluded).
Let’s have a look, then, at GISTEMP’s 90-55N polar cap, the extended Arctic:
Yeah, so all of a sudden, there is a near-perfect match between the total curve (golden, meant to be land+ocean) and the land only curve (black).
Stokes says, in the quote above:
“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.”
I wonder, what “basis” might he be referring to …?
What’s “clearly wrong” here is Stokes implying that all GISS do is simply leaving out ice covered areas, specifically whenever they are ice covered, because then we can no longer speak of the temperature of the actual sea surface in those particular areas (which is in itself true).
But that’s obviously not what they’re doing. They quite clearly ignore (remove, delete) existing SST data all the way down to 60-55 degrees of latitude, summer and winter, ice or no ice. And replace it fully with land data. In a region where the land data coverage is especially poor to begin with, at least beyond 60-65 degrees. In other words, they invent data, invent extra warming. Warming that isn’t really there. For as we all know, in a warming world, land data will rise at a much higher rate than ocean data, from differing thermodynamic properties alone. And when you then take out ocean data and put in land data in its stead, you increase the overall warming rate! It’s as simple as that.
So how can we tell if this is really what’s happening with the “GISTEMP LOTI global mean” product?
Once again, let’s bring “CERES EBAF ToA” in as the final arbiter.
First though, here’s how GISTEMP LOTI lines up with UAHv6 tlt within the 55N-55S band:
Not too bad, is it? The small divergence over the last couple of years is mostly a natural consequence of “The Blob” phenomenon in the North East Pacific Ocean, previously discussed here.
Watch what happens when we include the OLR data from CERES:
This is just what we would expect. The surface heats the troposphere and the troposphere in turn emits (most of) Earth’s heat loss to space (as OLR at the ToA). This plot makes perfect physical sense.
But what if we were to move up to the 90-55N polar cap? Would we recognise this same tight relationship?
Well, between tropospheric temps (UAHv6) and the ToA OLR (CERES) we indeed still would (see Fig.6 below). But what about the surface, which we now know in this region is all land, according to GISS, even when it’s not …?
Bear in mind, the troposphere is heated by the entire surface underneath, land AND ocean, not just the land. This goes for the 55N-55S band, and it likewise goes for the 90-55N polar cap. Naturally. Hence the obvious divergence here, where the surface all of a sudden appears to warm much faster than the troposphere above it, simply because the white curve is no longer the average of land and ocean; it is all land, no sea surfaces included … Watch how the amplitudes are considerably larger at the surface than in the troposphere. Now compare this inherently unnatural situation to the one in the 55-55 band (Fig.3 above), where things are how they should be.
We bring in the OLR once more:
Once again fits very well, if not perfectly, with the tropospheric temps. But no longer with GISS’s version of surface temps. And the reason is – still – very simple: They no longer include the oceanic portion, only the land part, weirdly replacing the ocean, thus effectively doubled in extent …
GISS quite evidently haven’t got this right.
You purport to compile a balanced (weighted) global surface temperature record, but include the ocean surface only between 55/60N and 55/60S, while beyond those latitudes you use land data only. Then what do you expect? Of course your 90N-90S warming rate will be higher than your 55/60N-55/60S warming rate. That goes without saying …
But does this peculiar way of doing things make your record correct? Of course not! It makes it completely detached from reality! It’s a bogus record!
The UAH team, on the other hand, seems to have nailed it quite nicely with their version 6. The tight agreement between tlt and OLR, not just globally, but also, as seen here, within separate zonal bands, gives great credence to their temperature product. Their 2000-2015 trend is almost certainly very close to spot on …!
Since the title of this post intentionally replicates the pattern of this one from a month ago, underlining the neat compatibility between the (adjusted) HadCRUt3 and the UAHv6 tlt datasets, this final plot should come as no surprise to anyone. It shows how the global surface temperature anomaly in reality – if you simply go by the right source – correlates wonderfully with that of the troposphere on top of it, with which it is tightly convectively coupled, and, as a consequence, also with Earth’s total radiant heat loss anomaly at the top of the atmosphere towards space. As it bloody well should!
This isn’t so hard. Tropospheric temps follow directly from surface temps, and OLR at the ToA in turn follows directly from tropospheric temps: