OK – here’s how I did it, so if anyone wants they can replicate…

The Tamworth temperatures can be obtained from:

http://www.bom.gov.au/climate/data/weather-data.shtml where you can select various meteorological data.

Select Temperature, and then in the new box download both the monthly Maximum Mean and the Minimum Mean (the monthly mean is not available). The Tamworth station IDs are Tamworth AP (station 055054) and Tamworth AP AWS (station 055325).

Create a monthly mean from the above data by adding the maximum and minimum mean temps for each month and divide by two. I cross checked this against the data at GISS:

http://data.giss.nasa.gov/work/gistemp/STATIONS//tmp.501957620000.1.1/station.txt which has what looks like the full Tamworth AP dataset. Note that the Tamworth AP data goes back to 1907 (as does the GISS data set) but there are a few gaps / missing months. Here is the difference between my mean and GISS:

Though there are a couple of downspikes, the vast majority is either the same or off by 0.05C attributable to rounding.

I then spliced the two datasets (the Tamworth AP and the Tamworth AP AWS) together without any adjustments. I guess that the temps should be identical as the AWS is basically at the same location as the screen that it replaces. There is a period of overlap and this is the difference.

The Airport AWS seems to run a bit cooler in the winter, and while purists may disagree as far as I’m concerned it’s negligible for this exercise.

The next step was to create a base from which an anomaly could be calculated. I decided to use the 1961-1990 period. (Note, if I used the same 10 year period as a base that Surly B used - the match may have been better…). To calculate the anomaly, I added every individual months means (i.e. added all the Jan’s, all the Feb’s etc) and divided by 30.

I then subtracted this monthly value from all the respective months to get the anomaly.

I then added the three months in each season (i.e. Mar, Apr & May for Autumn etc) and divided by three. This is the main (red) dataset in my graphs in my previous post.

I then did the 1:2:1 smoothing as follows (I think this is where you may have gone wrong Keith). The first value (Winter 1942) was:

(Autumn 1942 X 1 + Winter 1942 X 2 + Spring 1942 X 1) / 4,

and the next (Spring 1942) was:

(Winter 1942 X 1 + Spring 1942 X 2 + Summer 1943 X 1) / 4

This is the smoothed (blue) dataset in my graphs in my previous post.

And that’s it! If you have any questions let me know. I hope that this was usefull.