Cowtan & Way airbrushing

The Cowtan & Way version of Hadcrut4 uses a kriging technique to extrapolate values into those parts of the world where there are no direct measurements. Originally I had assumed that this fit was guided by the use of UAH satellite tropospheric temperature data and therefore more valid than that say used by GISS. However this is not really true as kriging has been used on all Hadcrut4 gridded data back to 1850, and the difference between the Hybrid (satellite) and kriging only results since 1979 is minimal. The net effect of this is to airbrush away regional variability. This can be seen by comparing the meridional temperature profiles of the original Hadcrut4.5 data with those of Cowtan & Way.

Figure 1. All 117 meridional H4 temperature anomaly profiles from 1990 to 2016. They are coloured blue if the annual global anomalies < -0.2C, Blue,-0.2<grey<0.2, 0.2<yellow<0.4, red > 0.4. Traces are 80% transparent to view them all.

Figure2: Same as above but with Cowtan & Way regional profiles plotted with latitude (meridional)

All profiles have been nicely smoothed out with warming concentrated at the North Pole and the Antarctic. The Antarctic profiles are all sorted so that the warmest also agree with those at the North Pole. What a tidy picture – but is it true or just a by-product of the fit?

Here are the  annual averaged anomalies calculated using the above profiles.

Figure 3: Comparison of the Hadcrut4.5 annual temperature anomalies with those calculated using the profiles in Figure 2.

The boost in warming from 2000 onwards is because the high latitude temperature profiles have been untangled by the algorithm. Kriging forces a smoothed spline dependence with latitude all the way to 90N.

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Temperature data averaged 3 ways

How should you calculate annual global temperature data? We start with Hadcrut4.5 gridded monthly data defined on a 5×5 degree grid and then form the global area weighted average in 3 different ways.

  1. Integrate the annual anomaly  over month,lat & lon all in one go, weighting by cos(lat)
  2. First calculate the yearly averaged grid.  Then integrate this over lat, lon grid points weighted by cos(lat)
  3. As 2. but first calculate the NH average and the SH average.  Then calculate for GL = (SH+NH)/2

This is what I get

3 ways to calculate the global annual average from monthly data compared to the official 0) is H4 published annual series.

There is a systematic difference between the 3 methods. Hadcrut4.5 seems to be using the single pass average as this gives almost identical results to mine – but not quite. Most   differences in the 3 methods are concentrated in the years before 1950, when the distribution of measurements was sparser, and mostly concentrated in the Northern hemisphere.

The Land only temperatures CRUTEM3 used the (NH+SH)/2 method until about 2011, but then switched to (2NH+SH)/3 for CRUTEM4, the argument being that the NH contains about twice the land surface of the southern hemisphere. If we now also apply second method  to the latest GCHN V3C station data, then this is the result.

Comparison of V3C temperature anomalies calculated using CRU’s gridding and averging software to CRUTEM4 annual values.

Again before 1920 there are systematic differences between the two datasets. In my opinion this difference simply represents an underlying systematic error when calculating net warming from preindustrial times. This error is about ±0.15C and is in addition to statistical sampling errors. So I estimate that the earth has warmed by 0.85±0.25 C since 1850.

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Meridional warming

Update (7/2): I made a silly mistake with normalising the averages. The text and figures have been updated with the correct results.

In this post I am going to present global temperature data in a different way to highlight how the earth cools by transporting heat from the tropics to the poles. This shows that enhanced CO2 warming is mainly concentrated in northern latitudes. To do this I use the latest monthly Hadcrut4 gridded data from 1900 to 2016 and integrate it over longitude and seasons to form yearly meridional temperature profiles.  Here are the results.

Figure 1. All 117 meridional temperature anomaly profiles from 1990 to 2016. They are coloured blue if the annual global anomalies < -0.2C, Blue,-0.2<grey<0.2, 0.2<yellow<0.4, red > 0.4. Traces are 80% transparent to view them all.

There has essentially been hardly any warming (within measurement errors (0.1C)) less warming  between -50 < lat < 50 than at the poles. Much of the  significant warming is concentrated  at latitudes > 50.

Of course it is  real temperatures that  actually affect our lives rather than temperature ‘anomalies’.  So in order to plot the actual temperatures I have used a standard meridional temperature profile based on long term measurements of our climate – see Scotese (Paleomap Project). Here are the resultant temperature profiles relative to the normal, offset by the measured anomalies over  the last 116 years.

Figure 2. Average temperature profiles from 1900 to 2016 calculated relative to a standard profile. Colour scheme is the same as Figure 1.

One sees on this scale just how tiny any relative increase in temperature really is. In a previous post we saw  how most warming actually occurs in winter, when temperatures fall to -40C in the Arctic and to -50C in the Antarctic. Compared to such extreme temperatures, a relative  increase of just 0.5C is tiny. We can see this by looking at more detail in the Arctic region.

Figure 3. Detailed look at changes in absolute temperatures at high latitudes.

The use of anomalies to present global temperatures is confusing because it assumes that all measurement locations are warming by the same amount globally. Instead warming is concentrated towards the Arctic, reflected an increase in heat transport away from the tropics. An increase of 1C at the equator would be far more serious than a 1C rise in the Arctic winter from -50C to -49C.

Over the last 500 million years the earth has been through extreme hot house to severe Icehouse climates. This is what the meridional temperature profiles looked like under extreme climates.

Figure 4. Credits: Christopher R. Scotese. Palemap Project 2015

Such changes as we observe in the Hadcrut4 temperature are totally insignificance when compared to these far larger changes in the past. Warming is concentrated in the coldest places on earth because heat transport by the atmosphere and oceans has increased slightly. Sea levels are rising linearly since 1850 at about 1.3 mm/year probably as a result. However, even at this rate it would still take 1000 years to rise by 1-2 meters.

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