Global Temperature Update
Posted on November 8, 2019 |
Update: This post has changed to correct a mistake I made with the ERA-5 data.
I keep hearing about such-and-such month being the “hottest such-and-such month on record.” October of this year, for example. For data sources like NASA and NOAA in the U.S. and HadCRU in the U.K., the time needed to do the computations (mainly waiting for all the observing stations to report) delayed such announcements until mid-month, but lately I’ve been hearing it early in such-and-such month, often based on announcements from the Copernicus Climate Change group in Europe. I think they base their announcments on the ERA-5 data, a re-analysis data set, which incorporates both observed data and computer simulation.
I looked at the ERA-5 data, which starts in 1979 (probably because that’s when the satellites really kick in). The interesting thing is that it doesn’t just show increase, it shows (statistically significant) acceleration.
I decided to apply my method of removing the influence of el Niño, volcanic eruptions, and solar variations. It still shows acceleration when adjusted for those factors:
I decided to look again for acceleration/deceleration in global temperature data sets, five for surface temperature (NASA, NOAA, HadCRUT4, Cowtan & Way, and Berkeley Earth) and two for lower-troposphere temperature (RSS and UAH), by fitting a quadratic polynomial to each for the data from 1979 to the present. Here are the quadratic coefficients with 2-sigma error bars (roughly the 95% confidence interval):
Except for the ERA-5 data, none of the confidence intervals excludes zero, so we don’t have significant evidence of acceleration (yet). NASA and NOAA data are close.
To make the test more sensitive, I also adjusted these data sets for el Niño, volcanic eruptions, and solar variations. All these factors are significant for all data sets (except ERA-5). Here are the quadratic coefficients for the adjusted data:
We now have statistical significance at 95% confidence for NOAA data, and almost so for NASA data. Their error bars are smaller, but their estimated quadratic coefficients are smaller too. Both HadCRUT4 and UAH data show signs of deceleration, but not even close to statistical significance.
I’m not ready to declare “acceleration” yet. But if the “hottest such-and-such month on record” reports keep piling up, that may change. I’ll keep you posted.
tamino.wordpress.com |
