[Met_help] [rt.rap.ucar.edu #42930] History for MET for WRF nested domains

RAL HelpDesk {for Paul Oldenburg} met_help at ucar.edu
Tue Dec 21 12:44:10 MST 2010


----------------------------------------------------------------
  Initial Request
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Hi,
I'm trying to use MET (2.0 and 3.0) to compare WRF-ARW results with measurements. I have three one-way nested domains (WRF namelist.input file is included), with 50, 10 and 2km grid. WRF results are postprocessed with WPP wrfpost.exe - there is no error message and I can plot postprocessed data with NCL - they look ok.
The problem is that when I try to run MET PoinStat (config file attached, I run it from sh script make_pointStatWIOS.sh), I got 0 pairs for domains 1 and 3. PointStat works well for domain 2. Could you please give me any hints what is wrong? The problem is for MET 2.0 and 3.0. Attached is also one nc file with measurements that I use to evaluate the WRF results.
Thanks in advance,
Maciek Kryza

-- 
#############################################################
Zakład Klimatologii i Ochrony Atmosfery
Uniwersytet Wrocławski
ul. Kosiby 6/8
 51-670 Wrocław


----------------------------------------------------------------
  Complete Ticket History
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Subject: Re: [rt.rap.ucar.edu #42930] MET for WRF nested domains
From: Paul Oldenburg
Time: Tue Dec 21 09:04:39 2010

Maciek,

Please send a WPP output file for which you are seeing zero matched
pairs.  I assume that you are using observations
contained in the NetCDF file that you already sent.  If the WPP output
file is too large for email, please upload it to
our FTP site using the following instructions:

http://www.dtcenter.org/met/users/support/met_help.php#ftp

Thanks,

Paul


On 12/20/2010 11:54 PM, RAL HelpDesk {for Maciej Kryza} wrote:
>
> Mon Dec 20 23:54:30 2010: Request 42930 was acted upon.
> Transaction: Ticket created by maciej.kryza at uni.wroc.pl
>        Queue: met_help
>      Subject: MET for WRF nested domains
>        Owner: Nobody
>   Requestors: maciej.kryza at uni.wroc.pl
>       Status: new
>  Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=42930 >
>
>
> Hi,
> I'm trying to use MET (2.0 and 3.0) to compare WRF-ARW results with
measurements. I have three one-way nested domains (WRF namelist.input
file is included), with 50, 10 and 2km grid. WRF results are
postprocessed with WPP wrfpost.exe - there is no error message and I
can plot postprocessed data with NCL - they look ok.
> The problem is that when I try to run MET PoinStat (config file
attached, I run it from sh script make_pointStatWIOS.sh), I got 0
pairs for domains 1 and 3. PointStat works well for domain 2. Could
you please give me any hints what is wrong? The problem is for MET 2.0
and 3.0. Attached is also one nc file with measurements that I use to
evaluate the WRF results.
> Thanks in advance,
> Maciek Kryza
>


------------------------------------------------
Subject: Re: [rt.rap.ucar.edu #42930] MET for WRF nested domains
From: Maciej Kryza
Time: Tue Dec 21 10:16:18 2010

Paul,
Thank you very much for quick reply. WPP files for one day are in
directory kryza_data (wppdata.zip). I also uploaded wrf file for this
day (wrfdata.zip). All files are for domain 3.
Best wishes,
Maciek

----- Oryginalna wiadomość -----
Od: "RAL HelpDesk {for Paul Oldenburg}" <met_help at ucar.edu>
Do: "maciej kryza" <maciej.kryza at uni.wroc.pl>
Wysłane: wtorek, 21 grudzień 2010 17:04:40
Temat: Re: [rt.rap.ucar.edu #42930] MET for WRF nested domains

Maciek,

Please send a WPP output file for which you are seeing zero matched
pairs.  I assume that you are using observations
contained in the NetCDF file that you already sent.  If the WPP output
file is too large for email, please upload it to
our FTP site using the following instructions:

http://www.dtcenter.org/met/users/support/met_help.php#ftp

Thanks,

Paul


On 12/20/2010 11:54 PM, RAL HelpDesk {for Maciej Kryza} wrote:
>
> Mon Dec 20 23:54:30 2010: Request 42930 was acted upon.
> Transaction: Ticket created by maciej.kryza at uni.wroc.pl
>        Queue: met_help
>      Subject: MET for WRF nested domains
>        Owner: Nobody
>   Requestors: maciej.kryza at uni.wroc.pl
>       Status: new
>  Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=42930 >
>
>
> Hi,
> I'm trying to use MET (2.0 and 3.0) to compare WRF-ARW results with
measurements. I have three one-way nested domains (WRF namelist.input
file is included), with 50, 10 and 2km grid. WRF results are
postprocessed with WPP wrfpost.exe - there is no error message and I
can plot postprocessed data with NCL - they look ok.
> The problem is that when I try to run MET PoinStat (config file
attached, I run it from sh script make_pointStatWIOS.sh), I got 0
pairs for domains 1 and 3. PointStat works well for domain 2. Could
you please give me any hints what is wrong? The problem is for MET 2.0
and 3.0. Attached is also one nc file with measurements that I use to
evaluate the WRF results.
> Thanks in advance,
> Maciek Kryza
>



--
#############################################################
Zakład Klimatologii i Ochrony Atmosfery
Uniwersytet Wrocławski
ul. Kosiby 6/8
 51-670 Wrocław

------------------------------------------------
Subject: MET for WRF nested domains
From: Paul Oldenburg
Time: Tue Dec 21 11:34:27 2010

Maciek,

I think the most important problem with your observation data is that
it is all located at a single point which lies
just to the north of your model data.  I used these commands to
determine the location of your observation data.  The
first command shows that (among other things) the location data for
the observations is contained in the NetCDF file
variable hdr_arr.  Then, I printed out all unique values of that
variable.

$ ncdump -h syn12415_legnica_2009.nc
...
        float hdr_arr(nhdr, hdr_arr_len) ;
                hdr_arr:long_name = "array of observation station
header values" ;
                hdr_arr:_fill_value = -9999.f ;
                hdr_arr:columns = "lat lon elv" ;
                hdr_arr:lat_long_name = "latitude" ;
...


$ ncdump -v hdr_arr syn12415_legnica_2009.nc | grep '^  [0-9]' | sort
-u
  51.83, 16.2, 122 ;
  51.83, 16.2, 122,

Then, I used the Unidata IDV viewer to look at your model data, and it
appears that your model data only extends north
to about latitude 51.80.  Also, I ran point_stat with the config file
that I attached.  In the places that I modified
your settings, I noted them using the string "orig:".  There are a
couple details that I want to mention:

1.  Setting beg_ds and end_ds to a non-zero value initially will help
you debug point_stat.  Once you see matched pairs,
you can reduce that window, but I would not advise going all the way
down to +/-0s immediately.

2.  We recommend using the fcst_field setting that corresponds to the
name of the GRIB field (see table
http://www.nco.ncep.noaa.gov/pmb/docs/on388/table2.html) with an
explicit level value.  In this case, it looked like you
were interested in surface temperature, so I used "TMP/Z2".  If you
leave the obs_field value blank, it will
automatically find all matching fields and levels.  I used the
following command to figure out the appropriate level
from the obs:

$ ncdump -v obs_arr syn12415_legnica_2009.nc | grep '^  [0-9]' | awk
-F', ' '{print $2, $4}' | sort -u
11 2
1 2
17 2
2 -9999
32 10
33 10
34 10
71 -9999

This command prints out all unique combinations of the observation
grib code along with the corresponding level, in
meters.  You can see that surface temperature (gc: 11) is taken at 2m.

Finally, set the point_stat verbosity level to 3 and look at the
output.  The output gives a report on why certain
points were rejected for observation.  You can see that there are 2880
temperature observations, with most being
rejected due to a mismatch in valid time.  However, the last one is
rejected because it does not fall within the model
domain.

% point_stat wpp_d03_20090420_000000.grb syn12415_legnica_2009.nc
PointStat_config -v 3
...
Processing TMP/Z2 versus TMP/Z2, for observation type SYNDAT, over
region FULL, for interpolation method UW_MEAN(1),
using 0 pairs.
Number of matched pairs  = 0
Observations processed   = 23040
Rejected: GRIB code      = 20160
Rejected: valid time     = 2879
Rejected: bad obs value  = 0
Rejected: off the grid   = 1
Rejected: level mismatch = 0
Rejected: message type   = 0
Rejected: masking region = 0
Rejected: bad fcst value = 0
...

If you have any questions, please let me know.

Thanks,

Paul



On 12/21/2010 10:16 AM, RAL HelpDesk {for Maciej Kryza} wrote:
>
> <URL: https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=42930 >
>
> Paul,
> Thank you very much for quick reply. WPP files for one day are in
directory kryza_data (wppdata.zip). I also uploaded wrf file for this
day (wrfdata.zip). All files are for domain 3.
> Best wishes,
> Maciek
>
> ----- Oryginalna wiadomość -----
> Od: "RAL HelpDesk {for Paul Oldenburg}" <met_help at ucar.edu>
> Do: "maciej kryza" <maciej.kryza at uni.wroc.pl>
> Wysłane: wtorek, 21 grudzień 2010 17:04:40
> Temat: Re: [rt.rap.ucar.edu #42930] MET for WRF nested domains
>
> Maciek,
>
> Please send a WPP output file for which you are seeing zero matched
pairs.  I assume that you are using observations
> contained in the NetCDF file that you already sent.  If the WPP
output file is too large for email, please upload it to
> our FTP site using the following instructions:
>
> http://www.dtcenter.org/met/users/support/met_help.php#ftp
>
> Thanks,
>
> Paul
>
>
> On 12/20/2010 11:54 PM, RAL HelpDesk {for Maciej Kryza} wrote:
>>
>> Mon Dec 20 23:54:30 2010: Request 42930 was acted upon.
>> Transaction: Ticket created by maciej.kryza at uni.wroc.pl
>>        Queue: met_help
>>      Subject: MET for WRF nested domains
>>        Owner: Nobody
>>   Requestors: maciej.kryza at uni.wroc.pl
>>       Status: new
>>  Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=42930 >
>>
>>
>> Hi,
>> I'm trying to use MET (2.0 and 3.0) to compare WRF-ARW results with
measurements. I have three one-way nested domains (WRF namelist.input
file is included), with 50, 10 and 2km grid. WRF results are
postprocessed with WPP wrfpost.exe - there is no error message and I
can plot postprocessed data with NCL - they look ok.
>> The problem is that when I try to run MET PoinStat (config file
attached, I run it from sh script make_pointStatWIOS.sh), I got 0
pairs for domains 1 and 3. PointStat works well for domain 2. Could
you please give me any hints what is wrong? The problem is for MET 2.0
and 3.0. Attached is also one nc file with measurements that I use to
evaluate the WRF results.
>> Thanks in advance,
>> Maciek Kryza
>>
>
>
>


------------------------------------------------
Subject: MET for WRF nested domains
From: Paul Oldenburg
Time: Tue Dec 21 11:34:27 2010

////////////////////////////////////////////////////////////////////////////////
//
// Default point_stat configuration file
//
////////////////////////////////////////////////////////////////////////////////

//
// Specify a name to designate the model being verified.  This name
will be
// written to the second column of the ASCII output generated.
//
model = "WRF";

//
// Beginning and ending time offset values in seconds for observations
// to be used.  These time offsets are defined in reference to the
// forecast valid time, v.  Observations with a valid time falling in
the
// window [v+beg_ds, v+end_ds] will be used.
// These selections are overridden by the command line arguments
// -valid_beg and -valid_end.
//
beg_ds = -3600;  // orig: 0
end_ds =  3600;  // orig: 0

//
// Specify a comma-separated list of fields to be verified.  The
forecast and
// observation fields may be specified separately.  If the obs_field
parameter
// is left blank, it will default to the contents of fcst_field.
//
// Each field is specified as a grib code or corresponding grib code
// abbreviation followed by an accumulation or vertical level
indicator.
//
// Each verification field is specified as one of the following:
//    GC/ANNN for accumulation interval NNN
//    GC/ZNNN for vertical level NNN
//    GC/PNNN for pressure level NNN in hPa
//    GC/PNNN-NNN for a range of pressure levels in hPa
//    GC/LNNN for a generic level type
//    GC/RNNN for a specific GRIB record number
//    Where GC is the number of or abbreviation for the grib code
//    to be verified.
// http://www.nco.ncep.noaa.gov/pmb/docs/on388/table2.html
//
//    NOTE: To verify winds as vectors rather than scalars,
//          specify UGRD (or 33) followd by VGRD (or 34) with the
//          same level values.
//
//    NOTE: To process a probability field, add "/PROB", such as
"POP/Z0/PROB".
//
// e.g. fcst_field[] = [ "SPFH/P500", "TMP/P500" ];
//
// fcst_field[] = [ "TMP/Z2", "UGRD/Z10", "VGRD/Z10", "WIND/Z10" ];
// obs_field[]  = [];

// fcst_field[] = [ "11/Z2", "UGRD/Z10", "VGRD/Z10" ];
// obs_field[]  = [ "11/R105", "UGRD/Z10", "VGRD/Z10" ];


//config setup for the 2009 synop data:
// TMP = 11; DPT=17; 1=station PRESSURE
//32 = wind speed; 33 = u component; 34 = v component
//71 = total cloudiness (TCDC)
// fcst_field[] = [ "11/Z2", "17/Z2", "1/L1", "32/Z10", "33/Z10",
"34/Z10" ];
// obs_field[]  = [ "11/R105", "17/R105", "1/R105", "32/R105",
"33/R105", "34/R105" ];
// orig:  fcst_field[] = [ "11/Z2" ];
// orig:  obs_field[]  = [ "11/R105" ];
fcst_field[] = [ "TMP/Z2" ];
obs_field[] = [ ];

//
// Specify a comma-separated list of groups of thresholds to be
applied to the
// fields listed above.  Thresholds for the forecast and observation
fields
// may be specified separately.  If the obs_thresh parameter is left
blank,
// it will default to the contents of fcst_thresh.
//
// At least one threshold must be provided for each field listed
above.  The
// lengths of the "fcst_field" and "fcst_thresh" arrays must match, as
must
// lengths of the "obs_field" and "obs_thresh" arrays.  To apply
multiple
// thresholds to a field, separate the threshold values with a space.
//
// Each threshold must be preceded by a two letter indicator for the
type of
// thresholding to be performed:
//    'lt' for less than     'le' for less than or equal to
//    'eq' for equal to      'ne' for not equal to
//    'gt' for greater than  'ge' for greater than or equal to
//
// NOTE: Thresholds for probabilities must be preceeded by "ge".
//
// e.g. fcst_thresh[] = [ "gt80", "gt273" ];
//
 fcst_thresh[] = [ "gt0.0" ];
//fcst_thresh[] = [ "gt0.0", "le100000.0", "le100000.0", "le100000.0",
"le100000.0", "le100000.0" ];
obs_thresh[]  = [];

//
// Specify a comma-separated list of thresholds to be used when
computing
// VL1L2 and VAL1L2 partial sums for winds.  The thresholds are
applied to the
// wind speed values derived from each U/V pair.  Only those U/V pairs
which meet
// the wind speed threshold criteria are retained.  If the
obs_wind_thresh
// parameter is left blank, it will default to the contents of
fcst_wind_thresh.
//
// To apply multiple wind speed thresholds, separate the threshold
values with a
// space.  Use "NA" to indicate that no wind speed threshold should be
applied.
//
// Each threshold must be preceded by a two letter indicator for the
type of
// thresholding to be performed:
//    'lt' for less than     'le' for less than or equal to
//    'eq' for equal to      'ne' for not equal to
//    'gt' for greater than  'ge' for greater than or equal to
//    'NA' for no threshold
//
// e.g. fcst_wind_thresh[] = [ "NA", "ge1.0" ];
//
fcst_wind_thresh[] = [ "NA" ];
obs_wind_thresh[]  = [];

//
// Specify a comma-separated list of PrepBufr message types with which
// to perform the verification.  Statistics will be computed
separately
// for each message type specified.  At least one PrepBufr message
type
// must be provided.
// List of valid message types:
//    ADPUPA AIRCAR AIRCFT ADPSFC ERS1DA GOESND GPSIPW
//    MSONET PROFLR QKSWND RASSDA SATEMP SATWND SFCBOG
//    SFCSHP SPSSMI SYNDAT VADWND
//    ANYAIR (= AIRCAR, AIRCFT)
//    ANYSFC (= ADPSFC, SFCSHP, ADPUPA, PROFLR)
//    ONLYSF (= ADPSFC, SFCSHP)
//
http://www.emc.ncep.noaa.gov/mmb/data_processing/prepbufr.doc/table_1.htm
//
// e.g. message_type[] = [ "ADPUPA", "AIRCAR" ];
//
message_type[] = [ "SYNDAT" ];

//
// Specify a comma-separated list of grids to be used in masking the
data over
// which to perform scoring.  An empty list indicates that no masking
grid
// should be performed.  The standard NCEP grids are named "GNNN"
where NNN
// indicates the three digit grid number.  Enter "FULL" to score over
the
// entire domain.
// http://www.nco.ncep.noaa.gov/pmb/docs/on388/tableb.html
//
// e.g. mask_grid[] = [ "FULL" ];
//
mask_grid[] = [ "FULL" ];

//
// Specify a comma-separated list of masking regions to be applied.
// An empty list indicates that no additional masks should be used.
// The masking regions may be defined in one of 4 ways:
//
// (1) An ASCII file containing a lat/lon polygon.
//     Latitude in degrees north and longitude in degrees east.
//     By default, the first and last polygon points are connected.
//     e.g. "MET_BASE/data/poly/EAST.poly" which consists of n points:
//          "poly_name lat1 lon1 lat2 lon2... latn lonn"
//
// (2) The NetCDF output of the gen_poly_mask tool.
//
// (3) A NetCDF data file, followed by the name of the NetCDF variable
//     to be used, and optionally, a threshold to be applied to the
field.
//     e.g. "sample.nc var_name gt0.00"
//
// (4) A GRIB data file, followed by a description of the field
//     to be used, and optionally, a threshold to be applied to the
field.
//     e.g. "sample.grb APCP/A3 gt0.00"
//
// Any NetCDF or GRIB file used must have the same grid dimensions as
the
// data being verified.
//
// MET_BASE may be used in the path for the files above.
//
// e.g. mask_poly[] = [ "MET_BASE/data/poly/EAST.poly",
//                      "poly_mask.ncf",
//                      "sample.nc APCP",
//                      "sample.grb HGT/Z0 gt100.0" ];
//
mask_poly[] = [ ];

//
// Specify the name of an ASCII file containing a space-separated list
of
// station ID's at which to perform verification.  Each station ID
specified
// is treated as an individual masking region.
//
// An empty list file name indicates that no station ID masks should
be used.
//
// MET_BASE may be used in the path for the station ID mask file name.
//
// e.g. mask_sid = "MET_BASE/data/stations/CONUS.stations";
//
mask_sid = "";

//
// Specify a comma-separated list of values for alpha to be used when
computing
// confidence intervals.  Values of alpha must be between 0 and 1.
//
// e.g. ci_alpha[] = [ 0.05, 0.10 ];
//
ci_alpha[] = [ 0.05 ];

//
// Specify the method to be used for computing bootstrap confidence
intervals.
// The value for this is interpreted as follows:
//    (0) Use the BCa interval method (computationally intensive)
//    (1) Use the percentile interval method
//
boot_interval = 1;

//
// Specify a proportion between 0 and 1 to define the replicate sample
size
// to be used when computing percentile intervals.  The replicate
sample
// size is set to boot_rep_prop * n, where n is the number of raw data
points.
//
// e.g boot_rep_prop = 0.80;
//
boot_rep_prop = 1.0;

//
// Specify the number of times each set of matched pair data should be
// resampled when computing bootstrap confidence intervals.  A value
of
// zero disables the computation of bootstrap condifence intervals.
//
// e.g. n_boot_rep = 1000;
//
n_boot_rep = 0;

//
// Specify the name of the random number generator to be used.  See
the MET
// Users Guide for a list of possible random number generators.
//
boot_rng = "mt19937";

//
// Specify the seed value to be used when computing bootstrap
confidence
// intervals.  If left unspecified, the seed will change for each run
and
// the computed bootstrap confidence intervals will not be
reproducable.
//
boot_seed = "";

//
// Specify a comma-separated list of interpolation method(s) to be
used
// for comparing the forecast grid to the observation points.  String
values
// are interpreted as follows:
//    MIN     = Minimum in the neighborhood
//    MAX     = Maximum in the neighborhood
//    MEDIAN  = Median in the neighborhood
//    UW_MEAN = Unweighted mean in the neighborhood
//    DW_MEAN = Distance-weighted mean in the neighborhood
//    LS_FIT  = Least-squares fit in the neighborhood
//
// In all cases, vertical interpolation is performed in the natural
log
// of pressure of the levels above and below the observation.
//
// e.g. interp_method[] = [ "UW_MEAN", "MEDIAN" ];
//
interp_method[] = [ "UW_MEAN" ];

//
// Specify a comma-separated list of box widths to be used by the
// interpolation techniques listed above.  A value of 1 indicates that
// the nearest neighbor approach should be used.  For a value of n
// greater than 1, the n*n grid points closest to the observation
define
// the neighborhood.
//
// e.g. interp_width = [ 1, 3, 5 ];
//
interp_width[] = [ 1 ];

//
// When interpolating, compute a ratio of the number of valid data
points
// to the total number of points in the neighborhood.  If that ratio
is
// less than this threshold, do not include the observation.  This
// threshold must be between 0 and 1.  Setting this threshold to 1
will
// require that each observation be surrounded by n*n valid forecast
// points.
//
// e.g. interp_thresh = 1.0;
//
interp_thresh = 1.0;

//
// Specify flags to indicate the type of data to be output:
//    (1) STAT and FHO Text Files, Forecast, Hit, Observation Rates:
//           Total (TOTAL),
//           Forecast Rate (F_RATE),
//           Hit Rate (H_RATE),
//           Observation Rate (O_RATE)
//
//    (2) STAT and CTC Text Files, Contingency Table Counts:
//           Total (TOTAL),
//           Forecast Yes and Observation Yes Count (FY_OY),
//           Forecast Yes and Observation No Count (FY_ON),
//           Forecast No and Observation Yes Count (FN_OY),
//           Forecast No and Observation No Count (FN_ON)
//
//    (3) STAT and CTS Text Files, Contingency Table Scores:
//           Total (TOTAL),
//           Base Rate (BASER), BASER_CL, BASER_CU,
//           Forecast Mean (FMEAN), FMEAN_CL, FMEAN_CU,
//           Accuracy (ACC), ACC_CL, ACC_CU,
//           Frequency Bias (FBIAS),
//           Probability of Detecting Yes (PODY), PODY_CL, PODY_CU,
//           Probability of Detecting No (PODN), PODN_CL, PODN_CU,
//           Probability of False Detection (POFD), POFD_CL, POFD_CU,
//           False Alarm Ratio (FAR), FAR_CL, FAR_CU,
//           Critical Success Index (CSI), CSI_CL, CSI_CU,
//           Gilbert Skill Score (GSS),
//           Hanssen and Kuipers Discriminant (HK), HK_CL, HK_CU,
//           Heidke Skill Score (HSS),
//           Odds Ratio (ODDS), ODDS_CL, ODDS_CU
//
//    (4) STAT and CNT Text Files, Statistics of Continuous Variables:
//           Total (TOTAL),
//           Forecast Mean (FBAR), FBAR_CL, FBAR_CU,
//           Forecast Standard Deviation (FSTDEV), FSTDEV_CL,
FSTDEV_CU
//           Observation Mean (OBAR), OBAR_CL, OBAR_CU,
//           Observation Standard Deviation (OSTDEV), OSTDEV_CL,
OSTDEV_CU,
//           Pearson's Correlation Coefficient (PR_CORR), PR_CORR_CL,
PR_CORR_CU,
//           Spearman's Rank Correlation Coefficient (SP_CORR),
//           Kendall Tau Rank Correlation Coefficient (KT_CORR),
//           Number of ranks compared (RANKS),
//           Number of tied ranks in the forecast field (FRANK_TIES),
//           Number of tied ranks in the observation field
(ORANK_TIES),
//           Mean Error (ME), ME_CL, ME_CU,
//           Standard Deviation of the Error (ESTDEV), ESTDEV_CL,
ESTDEV_CU,
//           Bias (BIAS = FBAR - OBAR),
//           Mean Absolute Error (MAE),
//           Mean Squared Error (MSE),
//           Bias-Corrected Mean Squared Error (BCMSE),
//           Root Mean Squared Error (RMSE),
//           Percentiles of the Error (E10, E25, E50, E75, E90)
//
//           NOTE: CL and CU values define lower and upper
//                 confidence interval limits.
//
//    (5) STAT and SL1L2 Text Files, Scalar Partial Sums:
//           Total (TOTAL),
//           Forecast Mean (FBAR),
//              = mean(f)
//           Observation Mean (OBAR),
//              = mean(o)
//           Forecast*Observation Product Mean (FOBAR),
//              = mean(f*o)
//           Forecast Squared Mean (FFBAR),
//              = mean(f^2)
//           Observation Squared Mean (OOBAR)
//              = mean(o^2)
//
//    (6) STAT and SAL1L2 Text Files, Scalar Anomaly Partial Sums:
//           Total (TOTAL),
//           Forecast Anomaly Mean (FABAR),
//              = mean(f-c)
//           Observation Anomaly Mean (OABAR),
//              = mean(o-c)
//           Product of Forecast and Observation Anomalies Mean
(FOABAR),
//              = mean((f-c)*(o-c))
//           Forecast Anomaly Squared Mean (FFABAR),
//              = mean((f-c)^2)
//           Observation Anomaly Squared Mean (OOABAR)
//              = mean((o-c)^2)
//
//    (7) STAT and VL1L2 Text Files, Vector Partial Sums:
//           Total (TOTAL),
//           U-Forecast Mean (UFBAR),
//              = mean(uf)
//           V-Forecast Mean (VFBAR),
//              = mean(vf)
//           U-Observation Mean (UOBAR),
//              = mean(uo)
//           V-Observation Mean (VOBAR),
//              = mean(vo)
//           U-Product Plus V-Product (UVFOBAR),
//              = mean(uf*uo+vf*vo)
//           U-Forecast Squared Plus V-Forecast Squared (UVFFBAR),
//              = mean(uf^2+vf^2)
//           U-Observation Squared Plus V-Observation Squared
(UVOOBAR)
//              = mean(uo^2+vo^2)
//
//    (8) STAT and VAL1L2 Text Files, Vector Anomaly Partial Sums:
//           U-Forecast Anomaly Mean (UFABAR),
//              = mean(uf-uc)
//           V-Forecast Anomaly Mean (VFABAR),
//              = mean(vf-vc)
//           U-Observation Anomaly Mean (UOABAR),
//              = mean(uo-uc)
//           V-Observation Anomaly Mean (VOABAR),
//              = mean(vo-vc)
//           U-Anomaly Product Plus V-Anomaly Product (UVFOABAR),
//              = mean((uf-uc)*(uo-uc)+(vf-vc)*(vo-vc))
//           U-Forecast Anomaly Squared Plus V-Forecast Anomaly
Squared (UVFFABAR),
//              = mean((uf-uc)^2+(vf-vc)^2)
//           U-Observation Anomaly Squared Plus V-Observation Anomaly
Squared (UVOOABAR)
//              = mean((uo-uc)^2+(vo-vc)^2)
//
//    (9) STAT and PCT Text Files, Nx2 Probability Contingency Table
Counts:
//           Total (TOTAL),
//           Number of Forecast Probability Thresholds (N_THRESH),
//           Probability Threshold Value (THRESH_i),
//           Row Observation Yes Count (OY_i),
//           Row Observation No Count (ON_i),
//           NOTE: Previous 3 columns repeated for each row in the
table
//           Last Probability Threshold Value (THRESH_n)
//
//   (10) STAT and PSTD Text Files, Nx2 Probability Contingency Table
Scores:
//           Total (TOTAL),
//           Number of Forecast Probability Thresholds (N_THRESH),
//           Reliability (RELIABILITY),
//           Resolution (RESOLUTION),
//           Uncertainty (UNCERTAINTY),
//           Area Under the ROC Curve (ROC_AUC),
//           Brier Score (BRIER), BRIER_NCL, BRIER_NCU,
//           Probability Threshold Value (THRESH_i)
//           NOTE: Previous column repeated for each probability
threshold
//
//   (11) STAT and PJC Text Files, Joint/Continuous Statistics of
//                                 Probabilistic Variables:
//           Total (TOTAL),
//           Number of Forecast Probability Thresholds (N_THRESH),
//           Probability Threshold Value (THRESH_i),
//           Observation Yes Count Divided by Total (OY_TP_i),
//           Observation No Count Divided by Total (ON_TP_i),
//           Calibration (CALIBRATION_i),
//           Refinement (REFINEMENT_i),
//           Likelikhood (LIKELIHOOD_i),
//           Base Rate (BASER_i),
//           NOTE: Previous 7 columns repeated for each row in the
table
//           Last Probability Threshold Value (THRESH_n)
//
//   (12) STAT and PRC Text Files, ROC Curve Points for
//                                 Probabilistic Variables:
//           Total (TOTAL),
//           Number of Forecast Probability Thresholds (N_THRESH),
//           Probability Threshold Value (THRESH_i),
//           Probability of Detecting Yes (PODY_i),
//           Probability of False Detection (POFD_i),
//           NOTE: Previous 3 columns repeated for each row in the
table
//           Last Probability Threshold Value (THRESH_n)
//
//   (13) STAT and MPR Text Files, Matched Pair Data:
//           Total (TOTAL),
//           Index (INDEX),
//           Latitude (LAT),
//           Longitude (LON),
//           Level (LEVEL),
//           Forecast Value (FCST),
//           Observation Value (OBS),
//           Climatological Value (CLIMO),
//           Interpolation Methold (INTERP_MTHD),
//           Interpolation Points (INTERP_PNTS)
//
//   In the expressions above, f are forecast values, o are observed
values,
//   and c are climatological values.
//
// Values for these flags are interpreted as follows:
//    (0) Do not generate output of this type
//    (1) Write output to a STAT file
//    (2) Write output to a STAT file and a text file
//
// orig: output_flag[] = [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2
];
output_flag[] = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];

//
// Flag to indicate whether Kendall's Tau and Spearman's Rank
Correlation
// Coefficients should be computed.  Computing them over large
datasets is
// computationally intensive and slows down the runtime execution
significantly.
//    (0) Do not compute these correlation coefficients
//    (1) Compute these correlation coefficients
//
rank_corr_flag = 1;

//
// Specify the GRIB Table 2 parameter table version number to be used
// for interpreting GRIB codes.
// http://www.nco.ncep.noaa.gov/pmb/docs/on388/table2.html
//
grib_ptv = 2;

//
// Directory where temporary files should be written.
//
tmp_dir = "/tmp";

//
// Prefix to be used for the output file names.
//
output_prefix = "";

//
// Indicate a version number for the contents of this configuration
file.
// The value should generally not be modified.
//
version = "V3.0";

------------------------------------------------
Subject: Re: [rt.rap.ucar.edu #42930] MET for WRF nested domains
From: Maciej Kryza
Time: Tue Dec 21 12:24:43 2010

Paul,
Thank you very much for help - you are absolutely right and I should
check my data more carefully before asking other people for help. The
site should be in my domain - that is why I sent these data as an
example. But I didn't check if the coordinates are correct - should
51.21, not 51.83. I also included all other suggestions - thank you
very much for all hints, it works nicely now. I'll check also the
domain 1, but it should be fine now.
Best wishes,
Maciek

----- Oryginalna wiadomość -----
Od: "RAL HelpDesk {for Paul Oldenburg}" <met_help at ucar.edu>
Do: "maciej kryza" <maciej.kryza at uni.wroc.pl>
Wysłane: wtorek, 21 grudzień 2010 19:34:28
Temat: Re: [rt.rap.ucar.edu #42930] MET for WRF nested domains

Maciek,

I think the most important problem with your observation data is that
it is all located at a single point which lies
just to the north of your model data.  I used these commands to
determine the location of your observation data.  The
first command shows that (among other things) the location data for
the observations is contained in the NetCDF file
variable hdr_arr.  Then, I printed out all unique values of that
variable.

$ ncdump -h syn12415_legnica_2009.nc
...
        float hdr_arr(nhdr, hdr_arr_len) ;
                hdr_arr:long_name = "array of observation station
header values" ;
                hdr_arr:_fill_value = -9999.f ;
                hdr_arr:columns = "lat lon elv" ;
                hdr_arr:lat_long_name = "latitude" ;
...


$ ncdump -v hdr_arr syn12415_legnica_2009.nc | grep '^  [0-9]' | sort
-u
  51.83, 16.2, 122 ;
  51.83, 16.2, 122,

Then, I used the Unidata IDV viewer to look at your model data, and it
appears that your model data only extends north
to about latitude 51.80.  Also, I ran point_stat with the config file
that I attached.  In the places that I modified
your settings, I noted them using the string "orig:".  There are a
couple details that I want to mention:

1.  Setting beg_ds and end_ds to a non-zero value initially will help
you debug point_stat.  Once you see matched pairs,
you can reduce that window, but I would not advise going all the way
down to +/-0s immediately.

2.  We recommend using the fcst_field setting that corresponds to the
name of the GRIB field (see table
http://www.nco.ncep.noaa.gov/pmb/docs/on388/table2.html) with an
explicit level value.  In this case, it looked like you
were interested in surface temperature, so I used "TMP/Z2".  If you
leave the obs_field value blank, it will
automatically find all matching fields and levels.  I used the
following command to figure out the appropriate level
from the obs:

$ ncdump -v obs_arr syn12415_legnica_2009.nc | grep '^  [0-9]' | awk
-F', ' '{print $2, $4}' | sort -u
11 2
1 2
17 2
2 -9999
32 10
33 10
34 10
71 -9999

This command prints out all unique combinations of the observation
grib code along with the corresponding level, in
meters.  You can see that surface temperature (gc: 11) is taken at 2m.

Finally, set the point_stat verbosity level to 3 and look at the
output.  The output gives a report on why certain
points were rejected for observation.  You can see that there are 2880
temperature observations, with most being
rejected due to a mismatch in valid time.  However, the last one is
rejected because it does not fall within the model
domain.

% point_stat wpp_d03_20090420_000000.grb syn12415_legnica_2009.nc
PointStat_config -v 3
...
Processing TMP/Z2 versus TMP/Z2, for observation type SYNDAT, over
region FULL, for interpolation method UW_MEAN(1),
using 0 pairs.
Number of matched pairs  = 0
Observations processed   = 23040
Rejected: GRIB code      = 20160
Rejected: valid time     = 2879
Rejected: bad obs value  = 0
Rejected: off the grid   = 1
Rejected: level mismatch = 0
Rejected: message type   = 0
Rejected: masking region = 0
Rejected: bad fcst value = 0
...

If you have any questions, please let me know.

Thanks,

Paul



On 12/21/2010 10:16 AM, RAL HelpDesk {for Maciej Kryza} wrote:
>
> <URL: https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=42930 >
>
> Paul,
> Thank you very much for quick reply. WPP files for one day are in
directory kryza_data (wppdata.zip). I also uploaded wrf file for this
day (wrfdata.zip). All files are for domain 3.
> Best wishes,
> Maciek
>
> ----- Oryginalna wiadomość -----
> Od: "RAL HelpDesk {for Paul Oldenburg}" <met_help at ucar.edu>
> Do: "maciej kryza" <maciej.kryza at uni.wroc.pl>
> Wysłane: wtorek, 21 grudzień 2010 17:04:40
> Temat: Re: [rt.rap.ucar.edu #42930] MET for WRF nested domains
>
> Maciek,
>
> Please send a WPP output file for which you are seeing zero matched
pairs.  I assume that you are using observations
> contained in the NetCDF file that you already sent.  If the WPP
output file is too large for email, please upload it to
> our FTP site using the following instructions:
>
> http://www.dtcenter.org/met/users/support/met_help.php#ftp
>
> Thanks,
>
> Paul
>
>
> On 12/20/2010 11:54 PM, RAL HelpDesk {for Maciej Kryza} wrote:
>>
>> Mon Dec 20 23:54:30 2010: Request 42930 was acted upon.
>> Transaction: Ticket created by maciej.kryza at uni.wroc.pl
>>        Queue: met_help
>>      Subject: MET for WRF nested domains
>>        Owner: Nobody
>>   Requestors: maciej.kryza at uni.wroc.pl
>>       Status: new
>>  Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=42930 >
>>
>>
>> Hi,
>> I'm trying to use MET (2.0 and 3.0) to compare WRF-ARW results with
measurements. I have three one-way nested domains (WRF namelist.input
file is included), with 50, 10 and 2km grid. WRF results are
postprocessed with WPP wrfpost.exe - there is no error message and I
can plot postprocessed data with NCL - they look ok.
>> The problem is that when I try to run MET PoinStat (config file
attached, I run it from sh script make_pointStatWIOS.sh), I got 0
pairs for domains 1 and 3. PointStat works well for domain 2. Could
you please give me any hints what is wrong? The problem is for MET 2.0
and 3.0. Attached is also one nc file with measurements that I use to
evaluate the WRF results.
>> Thanks in advance,
>> Maciek Kryza
>>
>
>
>




[Plik tekstowy:PointStat_config]

--
#############################################################
Zakład Klimatologii i Ochrony Atmosfery
Uniwersytet Wrocławski
ul. Kosiby 6/8
 51-670 Wrocław

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