Global Surface Temperature
Estimates of global surface temperatures [GST] from gridded dataset of historical near-surface air temperature anomalies over land and sea. At the moment I have applications to download and display data from the NOAA GISTEMP dataset, and the Met Office HadCRUT4 which is a collaborative product of the Met Office Hadley Centre and the Climatic Research Unit at the University of East Anglia.
The gridded data is a blend of CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature [SST] dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record given current understanding of non-climatic factors affecting near-surface temperature observations. This ensemble approach allows characterisation of spatially and temporally correlated uncertainty structure in the gridded data, for example arising from uncertainties in methods used to account for changes in SST measurement practices, homogenisation of land station records and the potential impacts of urbanisation. The HadCRUT4 data are neither interpolated nor variance adjusted.
Info courtesy of the Met Office.
12 UTC Mean Temperature Anomalies 1-14 August 2017 – courtesy of NCEP reanalysis
Fascinating anomaly chart for the first two weeks of August 2017. A band of cold anomalies more or less stretches from central north America, across the north Atlantic, to northwest Europe, with anomalies ranging from zero to -2°C. The recent heatwave across southeast Europe has left its mark there, with a belt of positive anomalies, as warm as +6°C over the Ukraine and eastern Black Sea, and curving down through Iraq, Saudi Arabia and into Sudan.
Figure 1 – Data courtesy of NCEP reanalysis
The extremely high temperature anomalies seem for the moment at least seem to have disappeared from the Arctic. This temperature anomaly chart (fig 1) is for the first 15 days of May 2017, and yes anomalies are still mainly positive in the Arctic, but in a range -2°C to +6°C, rather than in excess of +16°C that they were back in January and February. That might explain why Arctic sea ice has staged a bit of a recovery during late spring. There are a number of anomalous cold areas, one north of the Great lakes in Canada (-4°C) and another one over Scandinavia and northeast Russia (-6°C), the latter causing problems with heavy late spring snowfalls in places. Central North America, Greenland and large parts of central Asia have seen a very warm spring with anomalies typically +4°C above the 1948-2014 long-term average.
There are two key graphs central to the debate about climate change, one of them is arguably the primary reason why global temperatures are rising, and that’s a graph of monthly CO2 (fig 1) as recorded at Mauna Loa (I hope they’ve made allowances for any CO2 being vented by the volcano itself). The other is a graph of monthly global temperature anomalies (fig 2), either from the GISS data series produced by NASA, or maybe from the CRUTEM4 series produced by the Met Office and CRU. The latest GISS values are now in, and the anomaly for March is +1.12°C, which although slightly up on the February figure (+1.10°C), is down on the +1.28°C of March 2016. That drop might be expected, because last year in March the last El Niño event was just starting to wind down.
Depending on the range of the graph, and this one’s for the last 30 years (fig 2), you produce a different slope in the linear trend, but I think a period of 30 years is a fair length to sample, and I make the decadal rate from the GISS series is +0.181°C per decade. If you look at a linear trend for the last 10 years of global temperatures that decadal rise increases markedly to +0.383°C. I will admit now that in some screenshots in my earlier blogs I may have screwed this value up and I apologise, not that any of my readers seemed to notice it, or if they did they never commented, hopefully I’ve now got it right. Here’s a table of the recent monthly values of CRUTEM and GISS that I used to create the graph with (fig 3).
The latest data from Mauna Loa is ever upward it seems, and the first graph (fig 1) clearly shows the annual cyclical nature of CO2, and the obvious fact that CO2 has been rising inexorably by around 5% per decade since 1958, that’s a decadal increase of around 15.3 ppm if I’ve got that linear trend right, but I much prefer the following graph (fig 4) which shows the 12 month rate of change in CO2 levels. As you would expect the 12 month rate of change in CO2 has been increasing over the last almost 60 years and oscillates a fair bit – and yes I know the linear trend is probably not a good idea.
Figure 1 – Courtesy of NOAA/NCEP Reanalysis
You can see why the southeast of England had the highest regional temperatures in the UK during March, it was thanks to that warm anomalous area (+6°C) centred over Eastern Europe, but once again the central Atlantic was a little cooler than average. The central United States had another warm month (+6°C) but most parts of Russia were even warmer, with a massive +12°C anomaly over Novaya Zemlya.
Apart from a belt of negative anomalies (-2 or -3°C) stretching from the mid-western Atlantic to Sweden, the first eight days of March have been very warm in most areas across the rest of Europe. There is a large positive anomaly (+9°C) over Ukraine, and another one equally large over the Greenland sea.
The 12 month moving average of Global temperatures has fallen back in the last few months, after climbing quite sharply for the last four years or so. I’ve included a plot of both the CRUTEM4 and GISS monthly series as you can see (fig 1). I like to use a 12 month moving average because it’s a simple way of removing any seasonality, I’ve added a linear trend for both even though it’s probably not correct or in any way scientific. The linear trends are not aligned because the Americans use the 1961-1990 long-term averages to calculate their anomalies, whilst the British in their wisdom still use the 1951-1980 averages. The rate of increase in global warming is higher in the GISS series during the last 50 years at +0.292°C per decade, as opposed to the slightly lower +0.273°C using the CRUTEM4 series. For a bit of fun (yes I am weird), I thought that I would overlay the El Niño events of recent years (reddish vertical bands). I did read somewhere, that there was a strong correlation between global temperatures and ENSO, so I thought that I’d see if there was. Well that does seem to be true in some events, but not all. The 1991-1992 El Niño for instance, although the cooling that did occur then may have been due to the dust released in the Mount Pinatubo eruption at around that time. Talking of volcanic events the next chart (fig 2) is for the last 30 years and shows all volcanic events during that time, although I’ve only include the ones that scored 4 or higher on the VEI scale. You’ll also notice that the linear trend for both series is much lower during the last 30 years than it was in the last 50 years in the first chart. I have written about this before with regard to linear trends and the CET series, it can be misleading and I’m not going to bother to go into it all over again.
Figure 1 – Data courtesy of NCEP
Don’t look for much in the way of cold air from the north or Scandinavia this Winter, a far better bet is finding a thin conduit of air that stretches westward from the deep cold in the heart of central and northern Russia. Of course the cold anomaly of -10°C is in stark contrast to the +20°C warm anomaly in the Barents Sea between Spitsbergen and Franz Josef Land. It’s quite apparent to me that ‘bullseye’ anomalies like this one in the Arctic, are due to the fact that air temperatures over open sea are much higher than temperatures over pack ice, which of course is absent.
Image 2 – Courtesy of NSIDC
Mount Pinatubo June 1991 Courtesy of Wikipedia
I was just going to post the latest GISS global temperature anomalies for October 2016, and thought it might be a great idea to overlay the graphs with the volcanic activity of the last 136 years that would have impacted on global temperatures. Finding the source of the raw data on the internet was not easy, but there were some interesting Wikipedia articles about a term called the Volcanic Explosivity Index [VEI]. The VEI is a relative measure of the explosiveness of volcanic eruptions devised by Chris Newhall of the United States Geological Survey [USGS] and Stephen Self at the University of Hawaii in 1982. The scale runs from zero to eight, and there have only been 42 VEI 8 mega-colossal explosive eruption events in the last 36 million years. To give you an idea of the VEI scale Mount St Helen’s in 1980 was a type 5 event, Mount Pinatubo was a type 6 event in 1991, and Mount Tambora was a type 7 event in 1815. Anyway I finally tracked down the data to NOAA, and what’s now called the National Centers for Environmental Information [NCEI], they maintain a database they call ‘The Significant Volcanic Eruption Database‘ and I’m very grateful to them because I can now use the data in my global temperature application, and will add it to the graphs in my daily and monthly CET applications as time permits.
The caldera of Mount Tambora – courtesy of Jialiang Gao (peace-on-earth.org)
Here’s the full monthly GISS anomalies and a 12 month running average since 1880. The first event volcanic in 1883 was the eruption of Krakatoa, which may have resulted in some cold winters in the 1880’s, and undoubtedly some very colourful sunrises and sunsets.
And below is a zoom into the GISS global temperatures since 1980. As you probably know 2016 will undoubtedly be the warmest year in the series, although the 12 month running average has already peaked. The three volcanic events marked on the graph from left to right are Mount St Helens (1980), El Chichón (1982) and Mount Pinatubo (1991). I’ve placed a six month span on the volcanic event but this of course may have been much longer for Pinatubo. Looking at the graph there is no doubt about the obvious effect that Pinatubo had on global temperature, but it’s not obvious with the other two. I’ve tried drawing a left, right and a centre aligned 12 month moving average, and none of them synchronize well with any fall in global temperature, in fact the 1982 event almost appears to have caused a spike in global anomalies. Interestingly, although Wikipedia claims the Puyehue-Cordón Caulle event was a VEI 5 event in June 2011, the NOAA database lists it as a VEI 4. I suppose in reality even events with a VEI of less than 5 still emit a lot of dust, ash and gas into the atmosphere so they all must have some effect, looking at the graph there was a decrease in anomalies in 2011 which possibly had something to do with the 2011 eruption. I’ll have another think about the eruption data and maybe come up with some kind of annual index to overlay rather than specific events. It’s now been almost twenty-five years since we’ve had a type 5 VEI event on the planet, I wonder if 2017 will continue in the same vein?
I was just looking at the latest global temperatures from GISS and came across this interesting graphic on their website of October temperature anomalies.