Global warming is in the air, in the UAH lower troposphere

The UAH data for October is out. John Christy and Roy Spencer from the University of Arizona Huntsville have a contract with NOAA to analyse temperature changes in the atmosphere. Each month they publish the latest data.

Deniers dislike it less than other data sets, especially since John and Roy revised the latest version considerably downwards, making their data an anomaly!

I came across a chart I prepared a few years ago and thought I'd do it over again using the latest UAH data.

Anthony Watts makes a huge fuss about miniscule changes in atmospheric temperature data

A few days ago an astute reader wrote to me, asking if I knew why the RSS historical temperatures for the lower atmosphere varied month to month. I in turn asked Dr Carl Mears, who is the scientist behind the RSS temperature analysis (among other things).

To see what changes month to month, compare the charts for RSS TLT v3.3, which is just of the lower troposphere. The data is from that provided in November 2013, March 2016, July 2016 and October 2016:

Figure 1 | Lower troposphere temperature RSS v3.3. The chart shows data as reported in November 2013, March 2016, July 2016 and October 2016. Source: RSS

Do you see the big changes? No? So what is all the fuss about at WUWT (archived here) you might wonder.

101 conspiracy theories about troposphere temperature: the RSS love affair is over

Over at WUWT there have been three articles about the lower troposphere temperatures. The first (archived here) was a Guest Post by Werner Brozek and Nick Stokes, Edited by Just The Facts with the title: "Long Satellite Pauses Ending (Now Includes January Data)".  The second article was about the February data for UAH (archived here, latest here). It had the wistful wishful title: "Global Temperature Report: Warmest Ever February 2016 driven by El Niño". The third article is the real doozy (archived here). It's by Anthony Watts so could well have some awful blunders in it. He's called his article: "The ‘Karlization’ of global temperature continues – this time RSS makes a massive upwards adjustment."

This article is a few hours late, and I'm not satisfied that I've got everything right because this is a subject on which I am feeling distinctly out of depth. Science deniers will try to tell you that there are little thermometers on satellites sending raw data to Earth and miraculously drawing temperature charts - or something like that. That's a pile of hogwash. The real story is much more complicated. Satellites come and go. Instruments change. Orbits decay. Temperature isn't measured directly, it's estimated from measurements from microwave sounding instruments (MSUs). What's reported is the result of complex calculations after adjustments and conversion to temperature. What we get are temperature trends in very thick layers in the atmosphere (kilometers thick, looking upwards into space), not the temperature of a particular spot or distinct level in the sky. Then there is "diurnal drift" - which is largely what the new paper by Carl Mears and Frank J. Wentz is all about.

Warning: this article is rather long. It explains the new RSS paper in more detail than I did in the previous article.

About that tropical "hot spot"

A couple of days ago I wrote about the new paper by Steven Sherwood and Nidhi Nishant, which was reporting the release of an updated radiosonde dataset, and findings from an analysis of those data.

Data sources: Scripps and GISS/NASA

One of the things the authors reported was the "tropospheric hot spot" - though they didn't use that term in the paper itself (only the press release). I've never previously thoroughly looked into this myself. I knew about it in general terms, because some deniers point to what they regard as lack of evidence as evidence that global warming isn't happening. Which is really, really weird when you think about it. Or when you look at surface temperature data as in the chart on the right.

Anyway, I decided to go and learn more about this so-called "tropospheric hot spot".

Wondering Willis Eschenbach makes more mischief with volcanoes

Wondering Willis Eschenbach has a well-earned reputation for wandering off on a tangent and avoiding scientific research. He's done the same today at WUWT (archived here, latest here). He decided that two recent papers relating to volcanic forcing are "wrong". Not because he took any notice of the content of the papers - he didn't. Not because he took any notice of the observations reported. He didn't. He decided to reject the months of hard work by multiple scientists, on the basis of his own five minutes of "research".

Climate models and volcanic forcing

The two papers found evidence of volcanic forcing, coming from two different perspectives:

• Observed increase in Stratospheric Aerosol Optical Depth (SAOD) since 2005 (Ridley14)
• Multiple signals of volcanic forcing in sea surface temperature, atmospheric water vapour,  net clear-sky short-wave radiation, and elsewhere (Santer14)

One of the main points the scientists emphasised was that the CMIP5 models mostly assumed there was zero change in stratospheric volcanic forcing after 2000. They show that this assumption is not valid. Since 2005 in particular, there has been significant volcanic forcing, based on observations.

Christopher Monckton picks some cherries - plus RSS and the Southern Hemisphere

WUWT is starting to look like its old self again after something of a hiatus. There's been a cross-post at WUWT of the UAH temperature update on Roy Spencer's blog, which was missed last month. I've covered that one already.

Now Christopher Monckton is back with his RSS charts (archived here), trying to claim they prove that global warming is a hoax, or global warming has stopped, or something like that.

RSS has been an outlier since 2011. It's as though something crept into the algorithm in 2011 and got stuck there. RSS has the least coverage of all four data sets, only going from 82.5N to 70S.

Temperature data comparisons

Here are two charts comparing all the data sets, including 2014 year to date average. The top chart shows all the data available in all four datasets. You can see how closely aligned they all are by clicking on the chart to enlarge it.