<div dir="ltr"><div><div><div>A key is the 'level_type' attribute associated with the pressure variables (PRES_). There are numerous PRES_ variables. In particular,<br><br> float PRES_P0_L1_GLC0 ( ygrid_0, xgrid_0 )<br> center : US National Weather Service - NCEP (WMC)<br> production_status : Operational products<br> long_name : Pressure<br> units : Pa<br> _FillValue : 1e+20<br> coordinates : gridlat_0 gridlon_0<br> grid_type : Lambert Conformal can be secant or tangent, conical or bipolar<br> parameter_discipline_and_category : Meteorological products, Mass<br> parameter_template_discipline_category_number : ( 0, 0, 3, 0 )<br> level_type : Ground or water surface <*******************************************<br> level : 0<br> forecast_time : 0<br> forecast_time_units : hours<br> initial_time : 06/05/2009 (12:00)<br><br></div>It is a guess that this is the surface pressure (psfc). All pressure levels > psfc must be extrapolated. [ *Extrapolation is always dangerous!] <br><br></div>The 'ind' function can be used to get all 'valid' levels [ p<psfc ]. Try attached.<br><br></div>Cheers<br><div><div><div><div><br></div></div></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Jan 28, 2016 at 11:47 AM, Michelle Serino <span dir="ltr"><<a href="mailto:mmserino@tamu.edu" target="_blank">mmserino@tamu.edu</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"><div>Good afternoon,</div><div><br></div><div>I am plotting RUC2-Analysis data on a skew-T. Because this is analysis data, it seems that the data are always interpolated to the 1000-mb surface, regardless of the chosen location. For example, in a high elevation location like Denver, the data extend down to 1000 mb, which is unrealistic. This creates incorrect surface values, which results in a very incorrect value of surface CAPE.</div><div><br></div><div>I am wondering if, while still plotting on a skew-T, there is a way to specify the data that is plotted. Or, if there is another, more realistic, way around this. With a real sounding, I would not have this problem, so I am sure there is a way to fix this for the analysis data. I have attached the script I am using, along with its plot and an observed sounding for the same location (Denver). The direct link to the analysis data I am using is provided below. I appreciate any help!</div><div><br></div><div><a href="https://www.dropbox.com/s/qpe96hmhh9hsi0h/ruc2anl_130_20090605_1200_000.grb2?dl=0" target="_blank">https://www.dropbox.com/s/qpe96hmhh9hsi0h/ruc2anl_130_20090605_1200_000.grb2?dl=0</a><br></div><div><br></div><div>Best regards,</div><div><br></div><div>Michelle Serino</div><span class="HOEnZb"><font color="#888888"><div><br></div><div><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div dir="ltr">Michelle Serino<div>M.S. Candidate</div><div><span style="font-size:small">Texas A&M University</span><br></div><div>Atmospheric Sciences Dept.</div><div>Eller O&M, Suite 1017</div><div>College Station, TX 77843<br></div><div><a href="tel:%28484%29%20769-0949" value="+14847690949" target="_blank">(484) 769-0949</a></div></div></div></div></div></div></div></div></div></div>
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