[ncl-talk] Problem on averaging variable

[Dennis Shea]

As previously noted, NCL recognizes "*_FillValue
<https://www.unidata.ucar.edu/software/netcdf/docs/attribute_conventions.html>*"


It is the user responsibility change NaNs to _FillValue

See: *replace_ieeenan*
<http://www.ncl.ucar.edu/Document/Functions/Built-in/replace_ieeenan.shtml>
It is easy to use:

  x = f->.....

 if (*any* <http://www.ncl.ucar.edu/Document/Functions/Built-in/any.shtml>(*isnan_ieee*
<http://www.ncl.ucar.edu/Document/Functions/Built-in/isnan_ieee.shtml>(x)))
then
    if(.not.*isatt*
<http://www.ncl.ucar.edu/Document/Functions/Built-in/isatt.shtml>(x,"_FillValue"))
then
      x at _FillValue = *default_fillvalue*
<http://www.ncl.ucar.edu/Document/Functions/Built-in/default_fillvalue.shtml>(*typeof*
<http://www.ncl.ucar.edu/Document/Functions/Built-in/typeof.shtml>(x))
    end if
    *replace_ieeenan* (x, x at _FillValue, 0)
  end if


On Tue, Jun 9, 2020 at 4:09 PM Dave Allured - NOAA Affiliate via ncl-talk <
ncl-talk at mailman.ucar.edu> wrote:

> It looks like your input data contains NaN's.  Otherwise you would
> probably never see this.
>
> > average_op_ncl :      dim_avg_n over dimension(s): lon
> > (0)     min=nan   max=nan
>
> In NCL, NaN's ara NaN's, not missing values.  Support for NaN's is not
> clean.  If it was, we would not be having this conversation.  ;-)
>
> There is more than one way to fix this.  Best practice IMO is to convert
> all NaN's to missing values after reading input data, and before any other
> calculations (except maybe for subsetting).  Please review NCL docs for
> detecting, counting, and replacing NaN's.  In particular, see the
> isnan_ieee function.
>
> Depending on how much you care, you might also want to take a quick look
> at the spatial and temporal distributions of NaN's in that model's file
> set.  NaN's are an anomaly.  They may or may not indicate a significant
> quality problem in that data, something you might want to know about before
> further efforts.
>
>
> On Tue, Jun 9, 2020 at 3:41 PM Giorgio Graffino via ncl-talk <
> ncl-talk at mailman.ucar.edu> wrote:
>
>> Dear NCL users,
>> I have a weird issue on computing a simple avarage of a variable.
>>
>> I'm analysing a large subset of CMIP models to obtain density plots.
>> However, there is a particular model I can't analyse: when I compute the
>> average, all values in the variable becomes missing values. Here is the
>> relevant snippet
>>
>> * printVarSummary(rho_9s_mask)*
>> * printMinMax(rho_9s_mask,False) *
>>
>> *;; Create cross sections*
>> * rho_9s_mask_ave = dim_avg_n_Wrap(rho_9s_mask,2)*
>> * copy_VarCoords_1(rho_9s_mask,rho_9s_mask_ave)*
>>
>> * printVarSummary(rho_9s_mask_ave)*
>> * printMinMax(rho_9s_mask_ave,False) *
>>
>> and here is what I obtain
>>
>> Variable: rho_9s_mask
>> Type: float
>> Total Size: 14493600 bytes
>>            3623400 values
>> Number of Dimensions: 3
>> Dimensions and sizes:   [time | 165] x [lev | 61] x [lon | 360]
>> Coordinates:
>>            time: [181.25..60081.25]
>>            lev: [   1..6525]
>>            lon: [ 0..358.9818]
>> Number Of Attributes: 1
>>  _FillValue :  1e+20
>> (0)     min=1020.5   max=1027.72
>>
>> Variable: rho_9s_mask_ave
>> Type: float
>> Total Size: 40260 bytes
>>            10065 values
>> Number of Dimensions: 2
>> Dimensions and sizes:   [time | 165] x [lev | 61]
>> Coordinates:
>>            time: [181.25..60081.25]
>>            lev: [   1..6525]
>> Number Of Attributes: 2
>>  _FillValue :  1e+20
>>  average_op_ncl :      dim_avg_n over dimension(s): lon
>> (0)     min=nan   max=nan
>>
>> This works for all models but one. I tried to use a different function
>> for the average, but nothing changes. I also tried to compute the average
>> on other dimensions: the problem occurs again when averaging on the lev
>> coordinate, but it doesn't when averaging on the time coordinate. It seems
>> that there is a problem in the coordinate, but everything looks alright in
>> the variable before the averaging.
>>
>> Do you have any guess of what's wrong or any suggestion to help me?
>>
>> Thanks a lot,
>> Giorgio
>>
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