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I'm interested in extrapolating measured horizontal wind data of a vehicle into a forecast horizontal wind grid. Given the flight path you have a series of points that are "more accurate" than the forecast data. What would be the best way to extrapolate those deltas out into the neighboring points (especially in front of the vehicle), assuming the trends in the forecast data are likely to persist?

I hope that was clear. I have a general idea of how I would do this, but I'm sure there's a name/algorithm for what I'm trying to do. Thanks!

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The process of combining forecasts and measurements is called "data assimilation." There are a variety of ways to do this, but most methods fit into two general approaches (1) variational methods that use some kind of weighted least squares approach or (2) Kalman filtering approaches. –  Brian Borchers Oct 14 '11 at 3:04
    
"Data assimilation" was the keyword(s). I found all the information I needed from that, your approaches were point on also. Thanks! –  Anthony Oct 17 '11 at 13:13
    
If you want to put this in the answer so I can accept I'll do so. Thanks. –  Anthony Oct 17 '11 at 13:14
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