<div dir="ltr"><div><div><div><div><div>As suggested by Andrew, the ESMF approach is the way to go.<br><br></div>[1] Save the weight file. Note: generating the weight file may be slow but it is done once.<br></div>[2] Regrid using the weight file generated in [1]. This should be VERY FAST! It is basically a sparse matrix multiply.<br> <a href="http://www.ncl.ucar.edu/Document/Functions/ESMF/ESMF_regrid_with_weights.shtml">http://www.ncl.ucar.edu/Document/Functions/ESMF/ESMF_regrid_with_weights.shtml</a><br></div>[3] See<br><br><a href="http://www.ncl.ucar.edu/Applications/ESMF.shtml">http://www.ncl.ucar.edu/Applications/ESMF.shtml</a><br></div>EXample 4 + numerous others.<br><br></div>Good luck<br><br><div><div><div><br></div></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Dec 1, 2016 at 2:17 PM, debasish mazumder <span dir="ltr"><<a href="mailto:debasish@ucar.edu" target="_blank">debasish@ucar.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">I tried with ESMF regridding but it is still slow. Any other suggestion?<br>
-Deb<br>
<span class=""><br>
On 12/1/16 1:14 PM, Andrew Kren - NOAA Affiliate wrote:<br>
> I would try to use the NCL ESMF regridding tools, much faster and more<br>
> options<br>
><br>
> On Thu, Dec 1, 2016 at 1:12 PM, debasish mazumder <<a href="mailto:debasish@ucar.edu">debasish@ucar.edu</a><br>
</span><span class="">> <mailto:<a href="mailto:debasish@ucar.edu">debasish@ucar.edu</a>>> wrote:<br>
><br>
> Hi All,<br>
><br>
> I am trying to interpolates data on a curvilinear grid to to a<br>
> rectilinear grid using rcm2rgrid.<br>
> Input data dimension is tmax(time = 12 months, y = 8075, x = 7814) and<br>
> lat2d(y = 8075, x = 7814), lon2d(y = 8075, x = 7814)<br>
><br>
> output lat(192) and lon(288)<br>
><br>
> tmaxi = rcm2rgrid(lat2d,lon2d,tmax,<wbr>lat,lon,0)<br>
><br>
> It took forever to perform the interpolation. Is there any faster way do<br>
> that.<br>
><br>
> with regards<br>
> -Deb<br>
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> Andrew Kren, PhD<br>
> Research Scientist I, Global Observing Systems Analysis (GOSA) Group<br>
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