On a non-climate note, I congratulate the New Orleans Saints for their victory in Super Bowl XLIV. It was a well-deserved victory for the underdogs, and is a source of pride for a city which still shows massive scars from the ravages of Hurricane Katrina.Read the rest of the post at the source…
We’ve already looked at a way to combine data from different locations to obtain a grid-wide average of station anomalies. In that post, I computed anomalies for each location then combined the anomalies. It’s also possible to combine raw temperature data, then compute anomalies for the grid averages. I also combined station records in a simple way, by starting with a “reference station” then adding one new location at a time, computing an offset to align it with existing data and then incorporating it into the average. But I’ve noted that this is not the “optimal” way, that optimally (in a least-squares sense) one would compute the offsets which give the minimum sum of squared differences between all stations.
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