In an earlier essay this year, I used the useful maps prepared by Professor Ole Humlum of www.climate4you to ponder about how hot it actually was in Australia last year. I did so because of claims that the year was the hottest ever, as it was said to be for the world. When I wrote the piece I did not have access to the summary for the whole year, but I now have it, and it is displayed below.
These data are from the Goddard Institute of Space Studies, which is part of NASA, and they show the relative change between the average temperature for 2016 and the average for the preceding decade. I’ll deal with data questions later in the essay. But for now, you can eyeball the map with a glance at the colour chart and infer that there wasn’t much change in general, and nowhere (perhaps western Alaska excepted) was the change abrupt. Indeed, for a decent chunk of the globe there was no measurable change at all. To be fair, I think there is rather more green than blue, and that would accord with the actual data and estimates, which do show a small increase.
Very generally, eastern Siberia through Alaska (especially), Canada and the United States had a warmer year than the ten-year average, while Labrador and northern Quebec, central South America, southern Siberia and southern Western Australia all had a rather colder year. The oceans were generally cooler with the exception of the eastern Pacific, undergoing an el Nino episode.
Since my initial interest was in Australia, we can see that, very generally again, from the Ord River in northern Western Australia and going east and then south, right down to Tasmania, the coastal and contiguous inland areas were a bit warmer, while it was colder from Adelaide west. So any ‘average’ for Australia ignores two different and consistent temperature patterns.
Why did I use the GISS data? For two reasons. First, it is the one Ole Humlum used, and he provided the mapping, which is what I wanted. Second, the GISS data are the ones that have been most affected by ‘adjustments’ of various kinds, so I was using a dataset most unlikely to support my own general argument, which is that claims of increased temperature based on these data have to be put into some sort of context. Interested readers can compare the two maps in the two essays.
I probably should say again that the notion of an average global temperature is just that, a notion, a statistical construct, a number to serve other ends — in this case to provide a measurement baseline for the AGW theory that the world is heating up because of the activity of human beings in burning fossil fuels, making cement, and so on. What seems more important to me is the great variation around the world. During 2016 I read a few pieces referring to Alaska’s abnormally warm year, and that was news because we normally think of Alaska as a cold place, with polar bears, glaciers that drop into the sea, and roads that were a real problem to construct during the second world war. I don’t remember the ABC telling me of Perth’s unusually cool year, though I may have missed it.
The GISS data, or GISTEMP, are worth some consideration, and you can read about their history here. My summary is that until the late 1970s there really weren’t global temperatures of any consequence. Most of what was said to be known, was known about the northern hemisphere. In 1981 James Hansen, then the head of the Goddard Institute, was the first, with his colleagues, to try to systematically estimate global temperatures, and ‘global mean trends’, by combining northern hemisphere data with what southern hemisphere data there were. What follows comes from the history set out in the link above.
The methodology used then was relatively simple: Stations were grouped into 80 equal area boxes, the various anomaly series in a box were combined into a single anomaly series; these then were averaged across each of eight latitude belts. The global mean was estimated from an area weighing of the latitudinal means. From this beginning, estimates of global mean surface temperatures by scientists at GISS eventually morphed into the GISTEMP analysis that is available today.
Overt the years the estimates have been changed again and again, for two reasons. The first, the methodology changed, and second more data came to be available and was used. So 80 grid boxes, for example, became 8000. But here are some changes that rather make one’s eyebrows rise.
- Surface air temperature anomalies above the ocean were estimated using sea surface temperatures from ships and buoys starting in 1995 as documented in Hansen et al. (1996).
- Starting in the 1990s, the methodology took into account documented non-climatic biases in the raw data (e.g. station moves) and eliminated or corrected unrealistic outliers (Hansen et al., 1999).
- Areas with missing data were filled in — using means over large zonal bands — rather than restricting the averaging to areas with a defined temperature change (Hansen et al., 1999).
I guess that one can make an estimate for the temperature of the air above the surface of the sea by using the temperatures measured by engine intakes and buckets, and from the buoys. There’s got to be error there, and the summary doesn’t deal with it. As readers will know, my view is that, given the number of ships, the number of buoys, the great expanse of ocean where there are neither ships not buoys, not to mention the fact that we are discussing estimates here, not actual measurements, one cannot have much confidence in the outcome, unless it is used as a most general pointer to change. And I don’t like eliminating unrealistic outliers, for reasons discussed in the past, let alone ‘correcting’ them (oh dear). Finally, I don’t like providing data where there aren’t any, by using ‘means over large zonal bands’. All you are doing is providing more dodgy and uncertain data.