<div dir="ltr"><div>Try the _Wrap version. Generally, I would recommend using the _Wrap version of any function<br><br>regrid_f1=linint2_Wrap(lon2d(::<wbr>skip),lat2d(::-skip),f1_goes4(<wbr>::-skip,::skip),False,merge_<wbr>lon,merge_lat,0)<br></div>printVarSummary(regrid_f1)</div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Jan 3, 2017 at 10:49 AM, Ligia Bernardet - NOAA Affiliate <span dir="ltr"><<a href="mailto:ligia.bernardet@noaa.gov" target="_blank">ligia.bernardet@noaa.gov</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Hello,<div><br></div><div>I am trying to regrid a Hurricane WRF fost-processed forecast and then plot it, but I am getting the following error:<br><br></div><div>0) check_for_y_lat_coord: Warning: Data either does not contain a valid latitude coordinate array or doesn't contain one at all.<br>(0) A valid latitude coordinate array should have a 'units' attribute equal to one of the following values: <br>(0) 'degrees_north' 'degrees-north' 'degree_north' 'degrees north' 'degrees_N' 'Degrees_north' 'degree_N' 'degreeN' 'degreesN' 'deg north'<br>(0) check_for_lon_coord: Warning: Data either does not contain a valid longitude coordinate array or doesn't contain one at all.<br>(0) A valid longitude coordinate array should have a 'units' attribute equal to one of the following values: <br>(0) 'degrees_east' 'degrees-east' 'degree_east' 'degrees east' 'degrees_E' 'Degrees_east' 'degree_E' 'degreeE' 'degreesE' 'deg east</div><div><br></div><div>The original array is has 721 lat points (90 to -90, with 0.25 deg increments) and 1440 longitude points (0 to 275.75, with 0.25 increments). I am able to plot and print it correctly.</div><div><br></div><div>After linint2, I am able to print the interpolated field and it looks OK. But I cannot plot it.</div><div><br></div><div>Seems like attributes are missing?</div><div><br></div><div>Thanks for your help,</div><div>Ligia</div><div>ps: NCL script is below</div><div><br></div><div><div>load "$NCARG_ROOT/lib/ncarg/<wbr>nclscripts/csm/gsn_code.ncl"</div><div>load "$NCARG_ROOT/lib/ncarg/<wbr>nclscripts/csm/gsn_csm.ncl"</div><div>load "$NCARG_ROOT/lib/ncarg/<wbr>nclscripts/csm/contributed.<wbr>ncl"</div><div><br></div><div>; Read forecast file</div><div>f1 = addfile("/mnt/lfs2/projects/<wbr>dtc-hurr/Ligia.Bernardet/Sat_<wbr>verif/Ligia_sat_prep/<a href="http://gonzalo08l.2014101412.hwrfsat.global.0p25.f024.nc" target="_blank">gonzalo08<wbr>l.2014101412.hwrfsat.global.<wbr>0p25.f024.nc</a>","r")</div><div>vNames = getfilevarnames (f1)</div><div><br></div><div>; There is only one variable in the file, param7.5.0. GOES13 has 4 channels, then F17 SMIS had 7 channels, then SEVIRI has 7 channels, total 18 fields,</div><div>; NCL interprets as multiple times</div><div>; Read GOES_13 Channel 4, lat and lon</div><div>; Lat2d has 721 values, from 90 to -90, with 0.25 deg intervals</div><div>; Lon2d has 1440 values, from 0 to 359.75, with 0.25 deg intervals</div><div>vname = "param7.5.0" </div><div>f1_goes4 = f1->$vname$(2,:,:)</div><div>lat2d = f1->lat</div><div>lon2d = f1->lon</div><div><br></div><div>; Navigate forecast data so it is associated with 2D lat-lon arrays</div><div>f1_goes4@lon2d=conform_dims((/<wbr>721,1440/),lon2d,1)</div><div>f1_goes4@lat2d=conform_dims((/<wbr>721,1440/),lat2d,0)</div><div><br></div><div>; Replace NaN with -999</div><div>f1_goes4=where(isnan_ieee(f1_<wbr>goes4) .eq. True, -999., f1_goes4)</div><div><br></div><div>; ******************************<wbr>***********************8</div><div>; Find corners of forecast data - in this case it is a global dataset</div><div>f1_min_lat=min(lat2d)</div><div>f1_max_lat=max(lat2d)</div><div>f1_min_lon=min(lon2d)</div><div>f1_max_lon=max(lon2d)</div><div><br></div><div>; ******************************<wbr>******************************<wbr>**</div><div>; Create lat/lon arrays for output grid. Assign attributes</div><div>merge_lat=fspan(f1_min_lat+90,<wbr>f1_max_lat, 45)</div><div>merge_lon=fspan(f1_min_lon+<wbr>260,f1_min_lon+290,30)</div><div><br></div><div>merge_lat@units = "degrees_north"</div><div>merge_lat@standard_name = "latitude"</div><div>merge_lat@long_name = "latitude"</div><div>merge_lon@units = "degrees_east"</div><div>merge_lon@standard_name = "longitude"</div><div>merge_lon@long_name = "longitude"</div><div><br></div><div>;*****************************<wbr>******************************<wbr>****</div><div>; regrid forecast</div><div> print ("Start regridding of forecast")</div><div><br></div><div>skip=1</div><div>regrid_f1=linint2(lon2d(::<wbr>skip),lat2d(::-skip),f1_goes4(<wbr>::-skip,::skip),False,merge_<wbr>lon,merge_lat,0)</div><div><br></div><div>regrid_f1@merge_lat=merge_lat</div><div>regrid_f1@merge_lon=merge_lon</div><div><br></div><div><br></div><div>; ******************************<wbr>***********************8</div><div>;---Plot forecast regridded data</div><div> wks = gsn_open_wks("png","sat_hwrf_<wbr>regridded")</div><div> res = True</div><div> res@gsnMaximize = True ; maximize plot in frame</div><div> res@cnFillOn = True ; turn on contour fill</div><div> res@cnLinesOn = False ; turn off contour fill</div><div> res@tiMainString = "forecast"</div><div><br></div><div> plot = gsn_csm_contour_map(wks,<wbr>regrid_f1,res)</div><div><br></div></div><div><br></div><div><br></div><div><br></div></div>
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