[Met_help] [rt.rap.ucar.edu #60133] History for MET Question

John Halley Gotway via RT met_help at ucar.edu
Mon Feb 4 09:09:02 MST 2013


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  Initial Request
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Hello,

My name is Andrew, and I am a meteorologist doing some statistical analysis with the MET system.  I would like to examine not only the statistical errors associated with model output (we'll see WRF for example), but also the results of a downscaling algorithm that I have applied to the WRF model output.  The problem (for MET purposes at least), is that my downscaling and interpolation algorithm makes forecasts exactly at the confirmation station points.  In other words, my confirmation points are the exact same as my forecast points, and the forecast points after downscaling and interpolation are no longer on a grid (they are dispersed throughout the country at the same location as the station models).  Is there any way for MET to compare point forecasts (not grid forecasts) with point observations?  If not, would you have any suggestions of programs that might be able to do this for me?  Thank you in advance...

Andrew


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  Complete Ticket History
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Subject: Re: [rt.rap.ucar.edu #60133] MET Question
From: John Halley Gotway
Time: Fri Feb 01 08:54:17 2013

Andrew,

Good question.  The basic answer to your question is no.  MET was
designed to verify gridded forecasts against gridded or point
observations.

But there are a couple of workarounds you could consider.

Here's one approach... If you have a bunch of point forecasts for
stations around the country, it shouldn't be too hard to "grid" them
by creating a NetCDF file who's values are bad data everywhere
except for the handful of grid points where you have computed a
downscaled value.  Then you could verify that gridded forecast against
point observations using the Point-Stat tool.

Here's a second approach... Your downscaling method is basically
producing a forecast value at stations for which you already know the
observation value.  So really, you already have forecast and
observation matched pair data.  (Often, that's the most difficult part
of verification!)  You could simply reformat that matched pair data to
look like the matched pair (MPR) output lines from the
Point-Stat tool.  Then just save them all in a file that ends with a
".stat" extension.  Then, run the STAT-Analysis tool too read in those
matched pairs and compute whatever verification statistics
you'd like.

In this case, you STAT-Analysis job might look something like this:
    stat_analysis -lookin my_data.stat -job aggregate_stat -line_type
MPR -out_line_type CNT

That'd read in all the matched pair lines and compute the
corresponding continuous statistics (like RMSE, for example).  STAT-
Analysis has the ability to filter your data down however you'd like
and
compute all the traditional types of continuous, categorical, and
probabilistic statistics.

Either route will require some work on your part - either creating a
gridded NetCDF file or reformatting your ASCII data.

There is a third alternative outside of MET.  If you happen to be
familiar with R, you could read your forecast and observation matched
pair values into R and use the "verification" package to compute
stats on them.

Hope that helps.

John Halley Gotway
met_help at ucar.edu


On 02/01/2013 04:58 AM, Andrew J. via RT wrote:
>
> Fri Feb 01 04:58:28 2013: Request 60133 was acted upon.
> Transaction: Ticket created by andrewwx at yahoo.com
>         Queue: met_help
>       Subject: MET Question
>         Owner: Nobody
>    Requestors: andrewwx at yahoo.com
>        Status: new
>   Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=60133 >
>
>
> Hello,
>
> My name is Andrew, and I am a meteorologist doing some statistical
analysis with the MET system.  I would like to examine not only the
statistical errors associated with model output (we'll see WRF for
example), but also the results of a downscaling algorithm that I have
applied to the WRF model output.  The problem (for MET purposes at
least), is that my downscaling and interpolation algorithm makes
forecasts exactly at the confirmation station points.  In other words,
my confirmation points are the exact same as my forecast points, and
the forecast points after downscaling and interpolation are no longer
on a grid (they are dispersed throughout the country at the same
location as the station models).  Is there any way for MET to compare
point forecasts (not grid forecasts) with point observations?  If not,
would you have any suggestions of programs that might be able to do
this for me?  Thank you in advance...
>
> Andrew
>

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