[ncl-talk] bias when there are missing values in one of the dataset
Dennis Shea
shea at ucar.edu
Mon Mar 13 08:02:42 MDT 2017
v_obs = obs->tmax(:,::-1,:) ;reverse latitudes min-max
v_rac =racmo->tmax ; <=== has missing values
; make both grids have the same _FillValue structure
vobs = where(ismissing(v_rac), v_obs at _FillValue, vobs)
===
Hopefully, the following gives a 'global' (overall) area weighted bias
; overall (global) bias; w are the weights: cos(rad*lat); gau(lat), ...
v_obs_mean = wgt_areaave_Wrap(v_obs, w, 1.0, 0)
v_rac_mean = wgt_areaave_Wrap(v_rac, w, 1.0, 0)
print(v_obs_mean)
print(v_rac_mean)
bias_global = v_rac - v_obs
bias_global at long_name = "Area weighted Bias: v_rac - v_obs"
bias_global at units = v_obs at units
copy_VarCoords(v_obs_mean, bias_global)
print(bias_global)
===
An alternative is to interpolate (fill-in) all the _FillValue. However, you
would have to proceed carefully.
Good Luck
On Mon, Mar 13, 2017 at 4:53 AM, Noelia otero <noeli1680 at gmail.com> wrote:
> Hi!
>
> I am having some problems when plotting biases between two datasets in
> those grids where one of the dataset has missing values. Here, a piece of
> my code:
>
> ;Get seasonal values for observ and mod.
> v_obs = obs->tmax(:,::-1,:) ;reverse latitudes min-max
> v_rac =racmo->tmax
> ; Seasonal average
> ;obs
> avgobs_seas=dim_avg_n(v_obs,0)
> avgobs_seas!0 = "lat"
> avgobs_seas!1 = "lon"
> avgobs_seas&lat = lat
> avgobs_seas&lon = lon
> ; model
> avgrac_seas =dim_avg_n(v_rac,0)
> copy_VarAtts(avgobs_seas,avgrac_seas)
> copy_VarCoords(avgobs_seas,avgrac_seas)
>
> ;Bias models
> brac=avgrac_seas -avgobs_seas ; bias between seasonal averages
> copy_VarAtts(avgobs_seas,brac)
> copy_VarCoords(avgobs_seas, brac)
>
> The variable avgrac_seas contains missing values in the last latitude, but
> not avgobs_seas.
> So, when I compute the bias (brac), I am seeing that brac has weird values
> for the last coordinate :
>
> print(brac(36,:))
>
> Variable: brac (subsection)
> Type: double
> Total Size: 384 bytes
> 48 values
> Number of Dimensions: 1
> Dimensions and sizes: [48]
> Coordinates:
> Number Of Attributes: 1
> _FillValue : -32767
> (0) -10271.61482711738
> (1) -10271.85755532229
> (2) -10272.11799386223
> (3) -10272.37392089582
> .......................................................
>
> and finally , my plot looks wrong ...
> Any suggestion to solve this? Should I filter the missing values before?
>
> Many thanks in advance,
>
> Noelia
>
>
>
>
>
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