CRUTEM4 is cooler than GHCN-V4

The October 2019 global temperature anomaly that I calculate based on the latest CRUTEM4 station data is 0.15C cooler than that using GHCN-V4 (0.79C as  compared to 0.96C). The temperature series are calculated in exactly the same way and both use HadSST3 for ocean temperatures. The only differences lie within the station data. CRU use 7280 stations and give similar results to GHCN-V3. V4 has many more stations (17378) but the data handling is different, even the station IDs have changed and mostly originate from GHCN-Daily.

If we look at the annual averages we can see a clear discrepancy.

Comparing annual temperatures for CRUTEM4 and GHCN-V4. 2019 is the averages of the 10 months Jan-Oct.

The HadCRUT4.6 official temperature is calculated on a 5deg (lat,lon) grid is 0.75C, whereas  I am instead Spherical Triangulation which gives results similar to Cowtan & Way. My 3D-H4 results given below.

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October temperatures rise 0.18C

October saw a large increase of 0.18C in the global average temperature (anomaly) since September.

NH Temperature anomaly distribution for October 2019

These results use a spherical triangulation of land (GHCN-V4) and ocean (HadSST3) temperature data with a baseline of 1961-1990. The methodology is described in this post

Here are the monthly trends since 1998.

Monthly global temperature anomalies since 1998

2019 is also set to be the second warmest year based on the partial average for the first 10 months.

Annual values of global temperature anomalies. 2019 is based on the first 10 months of data.

As remarked previously GHCN are no longer updating V3, which showed a significantly lower warming trend than V4.

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A comparison of HadCRUT4.6 using Icosahedral binning

The classic HadCRUT processing calculates average surface temperatures on a 5×5 grid in Latitude and Longitude. To calculate the global average a spatial weighting of cos(Lat) must be applied. The main advantage of using a more complex 3D Icosahedral grid is the resultant regular bin spacing over the earth’s surface. The global average is then simply the average over all occupied bins. In this post I look at differences between the two methods. First here are the monthly global temperature averages compared.

Figure 1. Monthly average temperatures from 1880 to September 2019 calculated by both methods. The two orange curves show the differences between the two against the right hand y-axis

In the early years there is no significant difference because there are less stations outside Europe/North America and very few stations at high latitudes. After 1970 however Icosahedral averaging gives slightly warmer global averages extending up to 0.05C warmer than classic result. This is because relatively more bins near the poles become occupied.

Figure 2. Detailed differences between Icosahedral grids and lat/lon grids after 1970

The global average is slightly larger for an Icosahedral grid, reaching 0.06C warmer by 2019 . Figure 3 shows an Arctic  view of the  spatial distribution for September 2019.

Figure 3: Spatial temperature distribution showing 2562 element Icosahedral grid.

This can be compared with  the classic (lat,lon) distribution (taken from Hadley’s website).

Figure 4. Spatial Distribution HadCRUT4.6 for September 2019

The same features are clearly present in both.

Finally we can compare icosahedral binning  to the Cowtan & Way (C&W) data. C&W use the same (lat,lon) binning as classic HadCRUT4 but in addition extrapolate the measured data into empty bins using a kriging technique. They justify this procedure  by arguing that it “corrects” a coverage bias in temperature anomalies,  particularly in the Arctic which is  warming relatively faster than elsewhere. My results show that this is not strictly even necessary. Using equal area icosahedral binning avoids this spatial bias without any need to extrapolate temperature measurements into empty cells. Figure 5 compares the 3 methods and shows that icosahedral binning inherently agrees with the C&W simply because it works in 3D.

Figure 5: Compare the 3 methods methods of averaging HadSST4 data. The deltas are differences relative to classic HadCRUT4. Click to expand.

We can see in figure 5. that there is hardly any difference between C&W and Icosahedral, whereas both diverge from HadCRUT4 by about 0.06C between  1998 and  2019. However I think  the most important  issue is that you can accurately use just the measured temperature values on a 3D surface, rather  than extrapolate into empty regions in 2D. Experimental results should only depend on the measured data. My only remaining problem  now is to speed up the algorithm because  to calculate all of H4 from scratch currently takes over 12 hours CPU!

The time series can be downloaded here


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