The ACORN2 average December temperature for Australia is 25.9 C

I claimed in the last post that average temperatures in Australia for December  was 24C and not the 27C as stated by BOM, even though everyone else seems to agrees with them (CRU,GHCN,Berkeley) – See for example  this graphic. So apparently I must be wrong and should beg for forgiveness on twitter. However if  you actually use just the 112 quality controlled ACORN2 station data to calculate the average temperatures in exactly the same way as CRU (rather than triangulation) then you get 25.9C, provided you first exclude off-shore stations.  The result therefore depends on your definition of the average.  I calculated  the spatial distribution for ACORN2 stations binned and averaged in exactly the same way as CRU (5 degree bins).

Fig1. ACORN2 average December temperatures (1961-1990). Stars show station locations. Values shown are the average temperature within each 5×5 bin.

Figure 1  shows the 30y average temperatures for December using just ACORN2 stations. The station normals that I calculated for each month and for overlapping ACORN station agree exactly with those calculated by CRU. For instance the Merredin 12 monthly normals are:

CRU: 25.8 25.5 23.1 18.9 14.5 12.1 10.8 11.2 13.6 16.9 20.6 23.9

Clive: 25.8 25.5 23.2 19.0 14.6 12.2 10.8 11.2 13.6 16.9 20.7 24.0

So why do others find even warmer temperatures? Well one difference to the ACORN analysis is  that CRU, GHCN and Berkeley Earth are using about 400 Australian weather stations, three quarters of which do not directly appear in ACORN2 although some overlap. Perhaps including these extra stations then boosts the resultant spatial average to 27.1 C, or does it?

This paper describes how BOM selected the stations for ACORN. To quote:

Only some of the stations in a network are suitable for use in long term climate change analyses. Most have too little data (less than 30 years), and some have excessive missing data, poor site or observation quality, or are otherwise unsuitable.

So the Australian average temperature depends on whether you include these “unsuitable” stations in the calculation for Australia, including those rejected from the ACORN series for data quality reasons. Apparently BOM itself then quotes the CRU average temperature (27.1C for December)  resulting from using all stations and not those just those from the quality controlled ACORN set.

None of this makes any difference to the temperature anomaly results which are fine, but it demonstrates just how tricky it can be to convert these anomalies to absolute temperatures.

I then looked at the CRUTEM4 results themselves. I simply used the CRU calculated normals from all the station files within Australia. These have the Country codes  94 and 95. There are 360 of them with normals defined between 1961 and 1990. I likewise also restricted all these to be lie within the continental land mass of Australia  (one is actually located in Antarctica).  Here is the result.

The average December temperature now works out at 26.1C, which is a bit nearer to the quoted 27.1 but still not quite there. If you now exclude Tasmania then we reach a value of 26.4C. This is the highest value I can get using CRUs explicit 1961-1990 normalised values, but this is still 0.8C short of ACORN2’s quoted average December temperature.

All  data and results can be found here:



P.S. I am actually in Katoomba, Australia  right now (6 Feb). The temperature today reached just 14C but at least brought some much needed rain!


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What is the mean temperature of Australia ?

ACORN2 is the latest BOM version of station data in Australia. You can plot the average temperature anomaly data for December using their trend tracker. Shown below the graph is the average temperature for the baseline period 1961-1990. The value is 27.2C. Ed Hawkins used the anomaly  data and simply added on this average temperature to produce this plot.

Ed’s alarmist plot

I have analysed ACORN1 data before so I downloaded the latest ACORN2 version and expected to be able to use the same software to check the result. However the format has changed dramatically. ACORN1 had daily Tmax and Tmin values in a single file, one for each station covering the full measurement period. These have now been split into two separate files Tmax and Tmin and the metadata is no longer directly available ( I found it in their Javascript!). Other changes which caused me difficulties were:

  1. Different timescales for Tmax and Tmin
  2. Missing values are now simply left blank whereas in ACORN1 they were set to -9999.9
  3. Sometimes ( eg. Merriden) there are up to 17 days of consecutive data simply missing .
  4. The start dates for the two files are quite often different which means for example we have only a tmin and a missing tmax .

Having resolved all these problems I then calculated the anomalies for December and the area averaged temperatures for Australia. I got good agreement for the temperature anomalies.

Compare ACORN2 with my calculation

However I got wildly different values for the Average December temperature. I got 23.8C as the area averaged temperature for Australia between for 1961-1990 instead of their 27.2C.

So obviously I must be wrong – or am I? I take the daily average  temperature to be (Tmax+Tmin)/2 and then average this value in each of the 12 months between 1961 and 1990 and for each of the 112 stations. My values then agree almost perfectly with various travel/tourist website averages for expected monthly temperatures. For example my monthly average values for Sydney are:

22.965, 23.093,  21.857,  19.548,  16.531,  14.016,  13.068,  14.176,  16.347,  18.671,  20.297,  22.175

Compared with

My area averaged value for Australia uses a triangulation method so I thought that maybe I had screwed that up, so to check I recalculated everything using the CRU 5×5 grid method, and I basically  got exactly the same result. So I think the difference is instead the following.

Everyone uses monthly average temperatures  – GHCN, Berkeley, CRU etc to calculate anomalies whereas I am using the daily values. So my 1961-1990 averages are based on the 30 year average daily temperature for each station during any particular month. These are then spatially integrated to give the normal  climatology. So why are they not the same as ACORN or GHCN?

My suspicion is that ACORN, GHCN, Berkeley etc. uses the monthly values over the 30 years period. So the minimum temperature is the lowest Average  temperature and NOT the lowest Minimum (night-time) temperature for a given month. This could explain why they get higher values.


My average of daily (Tmax+Tmin)/2
ACORN2 monthly averages

Finally here are my trends for December. The increased temperatures in December are mostly because the minimum (night-time) temperatures have been rising much faster. There is not much change in the average maximum temperatures up until 2018.

December temperatures from 1910 to 2018. Note how the minimum night-time temperatures have has risen fastest,

P.S. I have no time to check all this as I will soon be on a plane to Australia !

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Differences in 2019 temperatures

HadCRUT4.6 has released their annual temperature result for 2019 as 0.74C. They grid the station data (CRUTEM4) with SST data (HADSST3) in 5×5 degree bins and perform an area weighted: \cos (lat) global average. CRUTEM4 has 7680 stations which contribute to calculating this average. Although GHCN-V4 has more stations (17280) it is not clear to me that the coverage is really all that much better. CRUTEM4 is similar to the coverage of V3 but with some additional stations.

I downloaded the CRUTEM4 station data and calculated the global average with HadSST3 using my 3D averaging method (Spherical Triangulation). This is exactly the same data as that used by HadCRUT4.  Both results are compared below together with those using GHCN-V4 and HadSST3..

Comparison of methodology and station data used to calculate annual global temperatures.

The largest difference is that between spatial integration techniques. Exactly the same data produces a difference of 0.07C in the result for 2019. The reason for this is simply because spherical triangulation makes an implicit interpolation over both poles, whereas the traditional 5×5 lat/lon grid averages over just the occupied cells. This difference will  depend from year by year on just how much warmer high latitude stations warm as compared to those at lower latitudes. So in 2004 and 2015 there was little difference between the two as compared to say 2016.

Here is the 3D grid used to calculate the anomaly for December 2019.

The spherical triangulation grid for December 2019.

This shows how the triangulation connects together all station locations covering all the earth’s surface and as a result interpolates the average temperature from the 3 vertices across each triangular area. The coloured triangles show the relative increase in temperature anomalies relative to 1961-1990..

This procedure also gives very similar results to those of Cowtan & Way who instead use a kriging technique to interpolate into polar regions.

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