Watts Up With That?

Jeff Id of the Air Vent has offered me this study he just completed for the consideration of WUWT readers. Given the wide audience we have here, I’m sure it will get a rigorous review and inspection.  Let’s see how well it stands up. – Anthony

In my last alternate reconstruction of Antarctic temperature I used the covariance of satellite information to weight surface stations. While the reconstruction is reasonable I found that it distributed the trends too far from the stations. This prompted me to think of a way to weight stations by area as best as I can. The algorithm I employed uses only surface station data laid on the 5509 grid cell locations of the Steig satellite reconstruction.

This new reconstruction was designed to provide as good a correlation vs distance as possible and the best possible area weighting of trend, it can’t make a good looking picture though but for the first time we can see the spatial limitations of the data. The idea was to manipulate the data as little as possible to make where the trend comes from as clear, simple and properly weighted as possible.

The algorithm I came up with works like this.

Calculate the distance from each of 42 surface stations to 5509 satellite points store them in a matrix 42 x 5509.

For each of 5509 points find the closest station and copy the data to that location. If there are missing values infill those from the next closest station looking farther and farther until all NA’s are infilled.

This is what the spatial distribution of trends looks like.

Figure 1

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