In Search of Cooling Trends

by Verity Jones and Tony Brown (Tonyb)

Back in October Tony asked me to help with a big idea.  Searching Norwegian climate site Rimfrost (www.rimfrost.no) Tony had found many climate stations all over the world with a cooling trend in temperatures over at least the last thirty years – which is significant in climate terms.  You see Tony had a grand vision of a website with blue dots on a map representing these “cooling stations”, where clicking on the dots brought up a graph of the data and the wonderful cooling trend.  Would this not persuade people to look again at the notion of worldwide global warming?

Figure 1. Map showing stations on Tony's "Cooling List" - stations which appear to have a cooling trend (>30 years) to present (data source: http://www.rimfrost.no Oct-Dec 2009; Earth image source: Dave Pape)

I asked Tony how many stations he had in mind. “Oh two hundred or so…”  He suggested breaking it down into bite-sized chunks and sending me sets of ten at a time.  I was to compare the data with that on the GISS site and/or those of national met agencies where available to verify the source, and produce graphs to a standard template.

We were concerned that this could be seen as ‘cherrypicking’ nonetheless it was an attractive idea.  In many cases it was not just cherrypicking the stations, but also the start dates of each cooling trend.  Despite these reservations we decided to go ahead, although ultimately we have not completed the project, partly for these reasons, but also because it is a case where the journey became more important than the destination and it is worth sharing.

The first 10 (Set 1) of Tony’s target stations, which at this point I should say seemed to be a randomly chosen set, were:

• Brazil – Curitiba (1885 to 2009) Cooling 1955 to 2009
• Canada – Edmonton (1881-2009) Cooling from 1886 to 2009
• Chile – Puerto Montt (1951-2009) Cooling from 1955
• China – Jiuquan (1934-2009) Cooling all years
• Russia – Kandalaska (1913-2009) Cooling 1933-2009
• Iceland – Haell (1931-2009) Cooling all years
• India – Amritsar (1948-2009) Cooling all years
• Morocco – Casablanca (1925-2009) Cooling all years
• Adelaide – Australia (1881-2008) Cooling all years
• Abilene, Texas – USA (1886-2009) Cooling 1933-2009

The comparisons in many cases were not straightforward.  While many matched GISS data, some of the graphs in Rimfrost used unadjusted data, others homogenised data.  For some such as Kandalaska, there was a close but not exact match to either GISS data set.  The data for Haell was clearly from the Icelandic Met Office, but I could find no match for Edmonton to any GISS series or data from Environment Canada (although having looked at Canadian data further since I am not entirely surprised). The first set took much longer than we had anticipated; however, I drew the graphs to a template and prepared to start on Set 2.

Tony also wanted a ‘spaghetti’ graph for the anomaly data of the first set, and this is where it got most interesting.  In fact we were blown away by what the graph looked like.  Taking these ten locations from across the globe and superimposing the anomaly data produced a sine wave-like pattern (Figure 2) with distinct cooling from the early 1940s to mid-1970s followed by warming to present; for many of the locations the older data was warmer, or at least as warm as present.  Now I had seen this before with many individual stations, but it really impressed me to see the pattern matching from such far-flung locations.

Figure 2. "Spaghetti graph" of anomalies for the ten stations in Set 1.

But in the meantime there were other developments.  Tony knew I was interested in putting the GHCN v2.mean temperature data from stations all over the world into a database.  As usual, this exceeded my own knowledge and capabilities, but I had made a start and was learning as I went along.  Tony, whose contacts and connections never cease to amaze me, put me in touch with a computer professional, database, web and mapping expert who was well known to commenters on The Air Vent, Climate Audit and WUWT as KevinUK”.  Kevin was also keen to put climate data into a database.

By now this was the end of November.  Kevin and I rapidly established a good rapport by email and voip and, with really only a few pointers to GHCN and GISS datafiles from me (and probably lots of hindrance), he rapidly built a fully functional database.  Not only that but he set about writing software to plot graphs and calculate trends from the data and put the whole lot on an interactive map – and all this in a period of about 6 weeks.  It is still a work in progress, fixing glitches and preparing Version 2.0; for more information see blog post Mapping Global Warming and the website itself: www.climateapplications.com.

I did deliver 40 graphs for Tony in the end, but I was quite slow about it (and that “sine wave” pattern kept showing up again and again and stuck in my mind). Tony had moved on to researching other climate projects and Kevin’s maps meanwhile showed so much more than we ever could.  With the “sine wave” climatic pattern in mind, the following maps (focussing on North America and Europe) show how climate has cooled, warmed, cooled and warmed again since 1880.

Figure 3. Maps showing temperature trends at weather stations for defined periods. Cooling trends are shown by blue colours: dark blue>blue>light blue>turquoise>pale turquoise. Warming trends are shown by reds: dark red>red>light red>orange>light orange. For full legend see: https://diggingintheclay.wordpress.com/2010/01/18/mapping-global-warming/

So is this “sine wave” the true climate signal?  It would seem so, although we can’t expect it always to be so regular.  Choosing stations that are more closely geographically located does give a more homogeneous shape to the wave.

Figure 4a (left) Anomaly data for a subset of Arctic stations ; Figure 4b (right) Anomaly data for a four US stations.

Figure 5. Anomalies of unadjusted data for stations in Madagascar

It is most extreme in the high Arctic – Figure 4a shows the graph for six stations above 64N where the magnitude of change is +/- several degrees Celsius.  Further south (e.g. Figure 4b – four stations in the US) the magnitude is smaller, and close to the equator (Figure 5, Madagascar) the magnitude is less still.

A final point – with the exception of the Madagascar graph, which was prepared for a blog post (link), all these graphs were part of different sets (the first 40 stations for which data was examined). Although the original data was chosen for its cooling trend this, in many cases, results from warmer temperatures in the period 1930-1940 than present.

The wave pattern is still present in many data sets worldwide, no matter what the overall trend.  In some the date of the onset of warming or cooling is later or earlier, depending on location – as would be expected with the oceans moving warmth around the globe.  In others however the wave pattern is not present or is obliterated by something – in these sets should it be present or not? Is it wiped out by anthropogenic effects on the temperature record such as growth of cities and even small rural communities though the otherwise cooling 40s, 50s and 60s?

For us the take-home message of this study was simply how widespread and consistent the wave pattern is, and this, ultimately is very convincing of the veracity of the arguments against CO2 as a primary cause of current warming.  From the physics I don’t doubt it has a role in warming, but its role needs to be disentangled from the large magnitude natural climate swings that are clearly present all over the world – a pattern that is not widely disseminated.