[ncl-talk] Interpolation for taylor diagram

Dennis Shea shea at ucar.edu
Fri Feb 24 08:28:11 MST 2017

```I started to look at your code. However, it has lots of commented
statements and, to me,  it is not clear what is happening. Really, you
should send only clean scripts. We like to help but we  don't have the time
to decipher codes.

The commented

;cor1 = dim_avg_n_Wrap(pattern_cor( t2mw, airw, clat, 0), 0)

contains
http://www.ncl.ucar.edu/Document/Functions/Contributed/pattern_cor.shtml

What is wrong with the following:

printVarSummary(t2mw)
printVarSummary(airw)

pcor = pattern_cor( t2mw, airw, clat, 0)
print(pcor)

On Thu, Feb 23, 2017 at 9:03 AM, Sri Nandini <snandini at marum.de> wrote:

> Dear NCL community,
> Greetings!
>
> I am trying to plot seasonal (DJF) Taylor diagrams and have errors in
> interpolation my datasets on same grid.
> (a) read 2 data sets with different resolutions and regrid  (modelled and
> obs temperature for a test)
> (b) calculate a pattern correlation
>
> My script is attached below ::
>
> ;=============================
> =====================================
> ;Taylor diagram calculations
> ;================================ interpolation onto common grid (of
> observational data)
> ;ncl pattern_cor between different size arrays
>  t2mw = f->t2mw(0,0,:,{0:360}); remove cyclic point
>   lon = f->lon({0:360})
> ;************************************************
> ; interpolate to new grid
> ;***********************************************
>   newlat = fspan(-60.,60,24)
>   newlon = fspan(0.,355.,72)
>
>  newt2mw = linint2_Wrap(lon,t2mw&lat,t2mw,True,newlon,newlat,0)
>
>   newt2mw!0   ="lat"
>   newt2mw!1   = "lon"
>   newt2mw&lat = newlat
>   newt2mw&lon = newlon
> ;=============================
> =========================================centered Pattern correlation
> (coslat weighting has been done previously above)
> re=escorc(airw,newt2mw)
>  ;cor1 = dim_avg_n_Wrap(pattern_cor( t2mw, airw, clat, 0), 0);rc =
> pattern_cor(x, y,gw, 0)      ; gaussian weighting, centered
>  mmd= (/cor1/)
>  printVarSummary(mmd)
> ;================================Standard deviation
> ;================================
>
> ;pre0_Std = dim_avg_n_Wrap( dim_stddev_n_Wrap( t2mw, (/1,2/)), 0)
>  ;std1 = dim_rmsd_Wrap(airw,t2mw, 0);computes rootmean square difference
> ;std1 = dim_rmsd_n(t2mw, airw, 0);
>     std1 = dim_rmsd( t2mw(lat|:,lon|:,time|:), airw(lat|:,lon|:,time|:)
> )    ; ==> rmsdTime(nlat,nlon)
>
>     ;rmsdTime = dim_rmsd_n( x, y, 0 )
> ; ==> no reordering needed
> ================================================================
> I had a look at other interpolation functions for correlations between
> different grids such a s:
>
> Assume *fi* is a 4D array dimensioned *ntim* x *nlvl* x *nlat* x *mlon* (
> *ntim*=50, *nlvl*=30, *nlat*=64, *mlon*=128), and that the rightmost
> dimension is to be treated as cyclic (the user should not add a cyclic
> point for the rightmost dimension).
>
> All times and levels will be interpolated and returned in a new array *fo*
> dimensioned *ntim* x *nlvl* x *73* x *144*:
>
>   lon = (0., 2.8125, .... , 357,0125)
>   lat = (-87.8638, ... ,87.8638)
>
>   LON = (0., 2.5, ... , 357.5)    ; length 144
>   LAT = (-90.,87.5,...90.)        ; length 73
>
>   fo = *linint2_Wrap* (lon,lat,fi, True, LON,LAT, 0)
>
> Error:
>
> Deeply appreciated
>
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