On Wed, Nov 18, 2009 at 10:16 PM, Andrew Revering <span dir="ltr"><<a href="mailto:andy@f5data.com">andy@f5data.com</a>></span> wrote:<br><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
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<p class="MsoNormal"><font size="2" face="Arial"><span style="font-size:10.0pt;font-family:Arial">I am loading 142 radar sites into one graphic in GrADS from
NetCDF files.</span></font></p>
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<p class="MsoNormal"><font size="2" face="Arial"><span style="font-size:10.0pt;font-family:Arial">I want to do a smoothed shaded contour of the data. When I
do this, each radar site is contoured using the smth9() function and it works
well..</span></font></p>
<p class="MsoNormal"><font size="2" face="Arial"><span style="font-size:10.0pt;font-family:Arial"> </span></font></p></div></div></blockquote><div>I've been looking at your data. Why would you want to use smoothed contouring to display your data? This is supposed to represent precipitation, a notoriously discontinuous parameter. </div>
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<p class="MsoNormal"><font size="2" face="Arial"><span style="font-size:10.0pt;font-family:Arial">The problem I have is it looks goofy when you smooth each
radar site. I need all of the data to be plotted and then it all smoothed
together.</span></font></p>
<p class="MsoNormal"><font size="2" face="Arial"><span style="font-size:10.0pt;font-family:Arial"></span></font></p></div></div></blockquote><div>These smoothing algorithms assume the function have a certain number of continuous derivatives. They are not designed for discontinuous data. Results are unlikely to be physical.</div>
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<p class="MsoNormal"><font size="2" face="Arial"><span style="font-size:10.0pt;font-family:Arial">This would be accomplished if the 142 individual data
sources were in one file, but I don’t know if they can be combined
because they are of different locations.</span></font></p>
<p class="MsoNormal"><font size="2" face="Arial"><span style="font-size:10.0pt;font-family:Arial"></span></font></p></div></div></blockquote><div> Regardless, it is fair to want to combine these individual radar reports into a single grid. Now, the data resolution is dlon ~ dlat ~ 0.013599 degrees, way too fine for visualization at a continental scale. You should be able to get away with dlon = dlat ~ 0.1 deg. I used 0.05 deg in the attached plot.</div>
<div><br></div><div>The data you sent me in a separate e-mail had individual files in a subdirectory out/, e. g., </div><div><br></div><div> out/</div><div> <a href="http://n.kabr.nc">n.kabr.nc</a></div><div><div> <a href="http://sn.kabx.nc">sn.kabx.nc</a></div>
<div> <a href="http://sn.kakq.nc">sn.kakq.nc</a></div><div> <a href="http://sn.kama.nc">sn.kama.nc</a></div><div> <a href="http://sn.kamx.nc">sn.kamx.nc</a></div><div> <a href="http://sn.kapx.nc">sn.kapx.nc</a></div>
</div><div> ...</div><div><br></div><div>The attached <a href="http://radar_composite.gs">radar_composite.gs</a> script goes over these individual files, use re() to place them on a common grid, and combine them, taking care for not double count pixels. This script requires the function if() and command gxyat, both available with the opengrads extensions; you should be able to replace these with maskout and printim. Command sdfwrite is used to save the composite grid.</div>
<div><br></div><div> Could you go over the script and make sure it is correct? We should include this in a recipe.</div><div><br></div><div> Arlindo</div><div> </div><div><br></div><div><br></div><div><br></div><div>
<br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div></div>-- <br>Arlindo da Silva<br><a href="mailto:dasilva@alum.mit.edu">dasilva@alum.mit.edu</a><br>