Remap grid without losing data in coastal regions
Added by David Hoffmann almost 8 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 over 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 over 7 years ago
Thank you Ralf!
That was very helpful! Exactly what I was looking for.
Cheers,
David