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Remap grid without losing data in coastal regions

Added by David Hoffmann almost 7 years ago

Hi,

I have a land dataset with a 1.0 degree resolution but need to remap it to 2.5 degree. It works fine so far with remain or remapbil. However I loose a good amount of data along the coastline as the adjacent grid cells contain NaN data. Consequently when remapping the first grid cell on land is NaN as well.
Is there a way to retain the data? Something like, that if half of the adjacent grid cells contain data, the calculations should be performed with them.
I've added plots of my data to make it better understandable. Remapnn is doing a bit better than remapbil in this case but still not satisfying.

This is the data in its original resolution

This is the data processed with remapbil to 2.5

This is the data processed with remapnn to 2.5

Thank you,
best regards,
David

Dataset_10degree.png (166 KB) Dataset_10degree.png This is the data in its original resolution
Dataset_25degree_remapbil.png (158 KB) Dataset_25degree_remapbil.png This is the data processed with remapbil to 2.5
Dataset_25degree_remapnn.png (161 KB) Dataset_25degree_remapnn.png This is the data processed with remapnn to 2.5

Replies (2)

RE: Remap grid without losing data in coastal regions - Added by Ralf Mueller almost 7 years ago

you could do some interpolation into the area of the missing values (NaN) with

  • fillmiss
  • fillmiss2
  • smooth
  • setmisstonn

have a look here for comparison

hth
ralf

RE: Remap grid without losing data in coastal regions - Added by David Hoffmann almost 7 years ago

Thank you Ralf!
That was very helpful! Exactly what I was looking for.

Cheers,
David

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