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[ferret_users] masking out data but keep default values within



Dear all,

I want to mask a coarse resolution data (upper left plot) outside a region of interest. I can do that (upper right plot) but the probelm is: because of corase data resolution only portion of desired area is covered (and also some undesired area outside the boundary). I can solved the problem of coverage by first interpolating the coarse resolution data to a high resolution grid (lower left plot) but the problem is: data is now smoothened. 

What I want is: to keep the original magnitude at each location but also be able to mask out data outside region of interest. Someone suggested this could be done by resampling data but I have no idea how to do that. I would appreciate any suggestions.

Below is my script for generating those plots

sh d
     currently SET data sets:
    1> GPCPv2.2.precip.JJAS.mean.nc
 name     title                             I         J         K         L
 PRECIP   Average Monthly Rate of Precipi  1:144     1:72      ...       1:19
    2> NPL_adm0_box.nc  (default)
 name     title                             I         J         K         L
 MASK     IF PT_IN_POLY(TEMP[L=1,D=3],LON  1:455     1:300     1:1       1:1

! originial data
set vi ul
shade/nolab precip[d=1,l=1,x=79:89,y=25:31];go land 1,,1

! mask interpolated to the data grid of 2.5 deg resolution 
set vi ur
def grid/x=mask[d=2,gxy=precip[d=1]]/y=mask[d=2,gxy=precip[d=1]] gxy1
let dummy1=0*x[gx=gxy1]*y[gy=gxy1]
let N_NoTime1=reshape(mask[d=2,l=1,gxy=gxy1],dummy1); let Nmask1= if N_NoTime1 then 1
let prm1=precip[d=1]*nmask1
shade/nolab/lev prm1[l=1,x=79:89,y=25:31];go land 1,,1

! mask and data interpolated to a fine grid of 0.1 deg resolution
set vi ll
def axis/x=78E:91E:0.1 xax;  def axis/y=25N:31N:0.1 yax; def grid/x=xax/y=yax gxy2
let dummy2=0*x[gx=gxy2]*y[gy=gxy2]
let N_NoTime2=reshape(mask[d=2,l=1,gxy=gxy2],dummy2); let Nmask2= if N_NoTime2 then 1
let prm2=precip[d=1,gxy=nmask2]*nmask2
shade/nolab/lev prm2[l=1,x=79:89,y=25:31];go land 1,,1

Best regards,

Jagadish

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