Wednesday, January 24, 2018

Satellite temperatures are adjusted much more than surface.

I continually come across claims that surface temperatures should be ignored in favour of satellite troposphere temperatures, because the surface temperatures are adjusted. It's an odd argument to conduct, because while at least there is a recognised surface temperature reading that can be adjusted, satellite temperatures are the product of a long and complex calculation sequence, in the course of which many judgement calls are made. Here, for example, is Roy Spencer's (+Christy + Braswell) explanation of the changes that were made in going to UAH version 6. He describes the need for it thus:
One might ask, Why do the satellite data have to be adjusted at all? If we had satellite instruments that (1) had rock-stable calibration, (2) lasted for many decades without any channel failures, and (3) were carried on satellites whose orbits did not change over time, then the satellite data could be processed without adjustment. But none of these things are true.
After 25 years of producing the UAH datasets, the reasons for reprocessing are many. For example, years ago we could use certain AMSU-carrying satellites which minimized the effect of diurnal drift, which we did not explicitly correct for. That is no longer possible, and an explicit correction for diurnal drift is now necessary. The correction for diurnal drift is difficult to do well, and we have been committed to it being empirically–based, partly to provide an alternative to the RSS satellite dataset which uses a climate model for the diurnal drift adjustment.
So instead of continually making small adjustments, as in the surface dataset, they produce new versions in which these decisions are revisited and often radically revised. The changes are much larger in overall effect than the changes to individual surface station averages.

Two years ago, I wrote a post about the changes that happened when Version 5.6 of the UAH index went to version 6. This decreased trends a lot, and so was popular with contrarians. I was prompted to write by Roy Spencer's claim:
"Of course, everyone has their opinions regarding how good the thermometer temperature trends are, with periodic adjustments that almost always make the present warmer or the past colder."
So I compared the change in TLT (lower troposphere) going from V5.6 to 6.0, to the cumulative effect of changes in GISS from archived time series of 2005 and 2011, with the then current 2015 GISS. GISS was far more stable than UAH, even though the period of changes was much longer.

Meanwhile, RSS also updated their troposphere data, going from V 3.3 to V4. RSS had been a favourite of contrarians, because it had a much lower trend than UAH. Roy spencer noted this, saying:
"But, until the discrepancy [in trend with UAH higher]] is resolved to everyone’s satisfaction, those of you who REALLY REALLY need the global temperature record to show as little warming as possible might want to consider jumping ship, and switch from the UAH to RSS dataset."
They needed little persuasion. Lord Monckton wrote a monthly series at WUWT about the length of the "Pause", which he defined as the maximal period of zero gradient of RSS TLT, starting about 1997. He scorned UAH then, as it was similar to the surface data. But RSS V4 turned that around too, showing much greater trends historically, and severely damaging the "Pause". I commented on some of this here, before any of the new versions.

Lord Monckton did not like it. His tamper tantrum is here. Any change which increases the trend is "tampering". Why going from V3.3 to V4 is tampering, but going from 3.2 to 3.3 or the earlier steps is not, was never explained.

Anyway, I thought it would be worth updating my graphs of Dec 2015 to include the changes to RSS. In fact, the two indices neatly changes places, so that RSS V4 is close to UAH V5.6, and UAH V6 is close to RSS V3.3. So in both cases the change is large.

An amusing sideshow of the more satisfactory UAH V6 is that surface datasets were being accused of fraud for differing from it - eg NOAA’s Fake SST’s Not Supported By Atmospheric Data. But the reviled discrepancies were not there with V5.6, which was far closer to the surface data than to V6. So was V5.6 also "fake"?

Anyway, here are the plots. I'm using the same old versions of GISS as in the previous post and sourced there. They can be got at the Wayback Machine. I convert everything to the same anomaly base, which this time is 1979-2008. I chose that because there isn't quite a 30 year span common to GISS2005 and the sat sets, but this reduces the gap to three years. So I set the other sets to zero average on this span; then I make the GISS2005 match the rebased GISS_current on its range.

First, as before, I just plot the time series. I use reddish colors for RSS versions, bluish for UAH, and greenish for GISS. Because the curves are tangled, there are four different color views of the same plot, which you can access with the buttons below. The text and content are the same for each, but transparency is used so that only one group stands out. Here is the plot:

This plot is good for a general appreciation of the deviations. The GISS variants bunch together, and the upper sat variants, UAH V5,6 and RSS V4.0, tend to follow them. The other pairing, RSS V3.3 and UAH V6, is the outlier, deviating rather markedly below from about 2008 onwards.

The values relative to each other are easier to see if they are expressed as differences from a common value, and for this I chose current GISS. In principle any value will do, but because the satellites respond with big spikes for El Niño, this would be inverted into a negative spike for GISS, which would be confusing. So I'm using the same colors, and choice of variants - GISS shows as the zero line:

Next I plot the difference from one version to the next - ie the "adjustment". In each case, it is new minus old. Again you can use the buttons to cycle through different colors.

This shows most clearly what happened in the recent changes. The trend of UAH went way down, and the trend of RSS went way up. These changes dwarf the minor and fairly trend-free changes to GISS. Interestingly, especially for RSS, most of the change happens post-2000.

Of course, GISS has more changes going further back. But satellites do not have an advantage there. They have no data at all.


  1. "Why going from V3.3 to V4 is tampering, but going from 3.2 to 3.3 or the earlier steps is not, was never explained. "

    Sure. Does it really need an explanation?

    The plain-and-simple is that the skeptics cherry-pick whatever series tells them what they want to hear. They're either unaware of what they're doing, or they just don't care.

    A good scientist says "let's use the best methodology we can, and we'll accept the data that results".

    The "skeptics" are not good scientists. And you can't win an ideological war on the strength of your data -- not if the other person doesn't care about the data.

    If you find some magical way to make people be scientifically-minded, to examine all the evidence fairly and on its merits, let me know. =\

  2. Interesting work Nick, although I'm not too surprised based on what I have noticed subjectively over the last several years. To me it's a sign of larger uncertainty in the satellite global estimates of atmospheric temperature versus surface measurement based estimates of global surface temperature.

    1. Yes, I think the task of extracting temperatures from the microwave emissions is just very hard, and I think you can expect a wide range of results.

    2. So now RSS has the highest trend of any temperature series over the satellite era. Are the satellites still the Gold Standard. I think so!

  3. Time for amateurs to take over satellite monitoring LOL

    We could do just as good a job as old Roy-boy