Re: [ferret_users] masking out data but keep default values within

[jagadish karmacharya <j_karmacharya@xxxxxxxxx>]

Dear Hein,

Thank you for your suggestions which is helpful for plotting.

But, what I actually wanted to do was compare the frequency distribution of the coarse resolution observation (e.g. GPCP) with a high resolution model ouput over a small and irregular region. The problem was: there was large difference in areal coverage of the coarse and hig resolution data when I applied the mask for the region. This problem could be corrected by regridding the coarse resolution data to the high resolution grid but this involved data interpolation. Since I was interested in frequency distribution, I wanted to avoid the data smoothening. Finally, I am able to get the desired result by regridding but applying @NRST trasformation at the same time as suggested by Steve.

Best regards,

 

Jagadish

On Tuesday, February 18, 2014 1:24 PM, Hein Zelle <hein.zelle@xxxxxxxxxxxxx> wrote:

Dear jagadish karmacharya,

glad you sorted it out with Steve's help.

One alternative method I use a lot for plotting charts is simply
overlaying different data sets on top of eachother, thus effectively
achieving the desired result (most of the time).  For example, if you
have coarse ocean data and want to overlay a fine land mask and a fine
sub-dataset:

1) shade coarse_model_data                ! ignore land problems
2) shade /overlay masked_fine_land_data    ! this fixes the coast line
3) shade /overlay fine_model_data

This approach doesn't always work (as you said, the coarse data leaves
gaps near the coast), but it can be a simpler approach sometimes than
getting all data on the same grid.  I use both methods depending on

the problem.

Kind regards,
    Hein

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BMT ARGOSS

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