[ncl-talk] mashing together multiple precip category variables into 1 variable

[Dennis Shea]

 Possibly:


  fgrb          = *addfiles(*...)
  prcType   = fgrb[:]->RAIN
  work        = fgrb[:]->FREEZE_RAIN
  prcType   = *where*
<http://www.ncl.ucar.edu/Document/Functions/Built-in/where.shtml>(work.ne.0,
2, prcType)
  work        = fgrb[:]->ICE
  prcType   = where(work.ne.0, 3, prcType)
  work        = fgrb[:]->SNOW
  prcType   = where(work.ne.0, 4, prcType)

Cheers


On Sat, Apr 4, 2020 at 8:53 AM Micah Sklut via ncl-talk <ncl-talk at ucar.edu>
wrote:

> Hi,
>
> Using GFS data, there are 4 different precipitation category variables:
> rain, freezing rain, ice, snow
>
> Each of these variables has a boolean 0 or 1 value for each grid point.
> I'd like to combine these 4 variables into 1 variable, such that each grid
> point has a value of:
> no precip = 0
> rain = 1
> freezing rain = 2
> ice = 3
> snow = 4
>
> Is looping through all of the grid points in space and time, the approach
> that needs to be taken here? Or is there a more efficient NCL function
> approach that can be taken?
>
> Thanks,
>
> --
> Micah Sklut
>
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