Wednesday, January 4, 2017

UAH - first index with record warm 2016

if you don't count NCEP/NCAR. But UAH just scraped in, due to a drop of 0.21°C in December. I see Roy Spencer has now adopted the line "not statistically warmer". I guess we'll hear a lot of this. There will be indices that will never be "statistically warmer" while the temperatures go up and up.

Anyway, in previous years I have shown progressive record plots to show how the record has crept (or, sometimes recently, leapt) upward over the years. This year I wanted to take an advance peek. So I did a range of indices, infilling missing months with the minimum month for 2016. That is pretty conservative, although it would have overestimated UAH. I show the plots below. There is more explanation of the style here. This time I have headed the plots with an "Incomplete" and superimposed a pink cross if there was infilling. I'll maintain it, so when the results are all in, this will go away. Use the arrow buttons to flick through the datasets. I'll try to keep the most recent finalised showing first. With conservative infilling, all indices currently show a record, though some are close. Often, the margin is high if that for 2015 was low, and vice versa.

For the meaning of the headings, see the glossary here.


  1. Time to drain the swamp of these atmospheric scientists such as Spencer, Curry, and Lindzen. In terms of metrology, these satellite readings have been suspect all along. I have never seen a decent explanation for the calibration approach. From what I understand, a detected signal is all they receive and this detected signal has no automatic calibration or reference value that something like a mercury bulb thermometer has. So if the sensor amplification has changed over the course of time, there is no verifiable way of ever making sense of the trend.

    Yet, the intriguing element in the satellite time-series is the almost exaggerated way that the readings pick up the ENSO signal. ENSO is partly a differential effect and so is sensitive to relative changes. So that if keepers of the data ever tried to calibrate the satellite trend to match the surface records, the differential ENSO changes would go through the roof. Which means the ENSO signal would be even more exaggerated than it is now.

    Whatever calibration dance these guys have been doing all these years revolves around trying to make the magnitude of the ENSO signal look reasonable in comparison to the trend. I could probably take the raw satellite readings and do as good a calibration with much fewer lines of code by minimizing the ENSO errors. That's a standard approach in EE signal processing.

    And what would make it great is to incorporate my model for ENSO into the mix. It will still be a while before the consensus picks up the rather obvious Mathieu sloshing modulation that governs the ENSO cycles. As in Kalman filtering, having a good model for the noise allows the desired signal -- in this case the trend -- to be extracted much more readily.

    1. It's amazing that satellite-borne microwave soundings and their host of corrections and deconvolutions work even as well as they do to estimate atmospheric temperatures.

      But to persist year after year in claiming that they are more accurate/superior to ground-based methods shows that one is either wearing blinders or peddling disinformation.

  2. You should include RSS TTT v4. Carl Mears suggests that it is a better proxy for surface temperatures than TLT due to the removal of stratospheric contamination.

  3. An interesting perspective that I have not seen graphed before for so many indices. However, the differing time scales makes it more difficult to interpret and tends to exaggerate the flatness in the UAH plot.

    I'm curious if anyone has tried to develop something like TLT, TMT, TUT, TLS using the reanalysis data? And if so, how does it compare to the UAH and RSS satellite derived estimates?

    That would seem to be another of the advantages of the reanalysis approach.

  4. Zeke,
    Done. I've included UAH 5.6 too, though Dec results aren't out yet.

  5. Not "statistically warmer" ... at the 95% level.

    At what level would it be warmer?

    If anyone feels like satisfying my whims how about a table or graph showing length of time vs. confidence that the latest period is the warmest in the record.

    maybe the last 12 months are warmest at the 80% level
    maybe the last 13 months are warmest at the 82% level
    maybe the last 48 months are warmest at the 99% level

    Obviously, I'm wanting the real numbers...