Preventing extrapolation

From: Chad Herman <chad.herman.us_at_nyahnyahspammersnyahnyah>
Date: Mon Jan 24 2011 - 14:46:01 MST

Hi everyone,

I've spent all of yesterday investigating this issue and haven't found
any satisfactory solution. I have a file containing land surface
temperature anomalies. The data is represented on an equal-area grid
with 8,000 grid boxes, so I have three arrays: one for longitude,
latitude and anomaly.

My task is to interpolate it into 5x5 resolution. I can't use any
interpolation functions that require the data present on a regular 2D
grid. I've used CSSGRID and NATGRID and they interpolate fine, but they
interpolate too much. It's completely infilling the oceans as well as
large land surfaces which must be missing. I've looked into the two
aforementioned interpolation routines and can't seem to find a way to
completely stop them from interpolating into data absent regions.

For NATGRID, I used nnsetp("ext", 0) and nnsetp("nul",
anomaly@_FillValue) which at least stopped excessive interpolation in
the Arctic. I tried to use bin_avg to find grid boxes where there is no
data whatsoever and use the results to mask out the interpolated grid.
While this solves the ocean data problem, it creates a new problem by
masking out too many grid boxes on land. If there are a couple of grid
boxes with non-missing data surrounding a grid box or two with no data,
it seems quite reasonable to interpolate into the missing region. But if
there is no data there, the interpolated values get masked.

Any suggestions?

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Received on Mon Jan 24 14:46:08 2011

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