2017 Temperature Summary

RealClimate did a brief post about the latest global temperature data, just released. A reader comment says, “I think it would be a good idea to publish graphs with the influence of El Nino, etc, removed, if this is possible.

Happy to oblige.


Here’s the original graph comparing many data sets, from the RealClimate post:

They’ve set all data sets to a common baseline: 1979 through 1988. It’s an uncommon choice, but makes sense for two reasons. First, satellite data sets don’t even start until 1979; second, by aligning them to the first 10 years of the satellite era we get a clearer picture of how the various data sets have diverged since then.

In response to the reader comment, Gavin posted an adjusted set for NASA GISS data:

It accounts for el Niño, but doesn’t remove the influence of volcanic eruptions or solar variations. Also, I think my method of accounting for el Niño is better (but I certainly haven’t proved that). In any case, I applied my adjustment method (an improved version of Foster & Rahmstorf). I also included two additional data sets: those from NOAA (National Oceanic and Atmospheric Administration) and HadCRU (Hadley Centre/Climate Research Unit in the U.K.). I don’t have December 2017 data for all of the data sets yet, so those are only based on 11 months out of last year, but I reckon that’ll be enough to inform but not mislead. Here are the adjusted data (annual averages, 1979 through 2017):

Two interesting facts become clear. First, the hottest year on record after removing the influence of fluctuation factors was 2017, in all seven data sets. Second, the “odd man out” is clearly the data from UAH.


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6 responses to “2017 Temperature Summary

  1. Excellent work. Very helpful!

  2. Is UAH 6 still in beta/not peer-reviewed?

    [Response: I believe it’s no longer in beta, and a peer-reviewed publication about it has appeared.]

  3. Everett F Sargent

    “Second, the “odd man out” is clearly the data from UAH.”

    Exactly!

  4. Tamino, thanks for another excellent post.
    I was wondering: Could your regression methodology be used to directly examine the rate of global temperature change – the difference between T(t) and T(t-1)? Or should a different approach be used for first difference time series?

  5. Shoulded the satellite data be lower then the surface data? The warming of Earth seems to be greatest for the surface and lower for the Lower Troposphere Layer and even much lower for the Middle Troposphere Layer and zero warming some where between Middle Troposphere Layer and Lower Stratosphere Layer wich is cooling.

    [Response: The stratosphere is indeed cooling as we expect. But for the lower troposphere the issue isn’t settled. Perhaps your belief is unduly influenced by past versions of the satellite data (esp. those from UAH); the truth is, the satellite data are not nearly as reliable as the surface data, and updates from one version to the next can be substantial.]