obs_seq_coverage
queries a set of observation sequence files to determine which observation locations report frequently enough to be useful for a verification study. The big picture is to be able to pare down a large set of observations into a compact observation sequence file to run through ../filter/filter
with all of the intended observation types flagged as evaluate_only. DART's forward operators then get applied and all the forecasts are preserved in a standard obs_seq.final
file - perhaps more appropriately called obs_seq.forecast
! Paring down the input observation sequence file cuts down on the unnecessary application of the forward operator to create observation copies that will not be used anyway ...
obs_seq_coverage
results in two output files:
obsdef_mask.txt
contains the list of observation definitions (but not the observations themselves) that are desired. The observation definitions include the locations and times for each of the desired observation types. This file is read by../../../assimilation_code/programs/obs_selection/obs_selection
and combined with the raw observation sequence files to create the observation sequence file appropriate for use in a forecast.obsdef_mask.nc
contains information needed to be able to plot the times and locations of the observations in a manner to help explore the design of the verification locations/network.obsdef_mask.nc
is required by../../../assimilation_code/programs/obs_seq_verify/obs_seq_verify
, the program that reorders the observations into a structure that makes it easy to calculate statistics like ROC, etc.
The entire discussion about finding locations that are repeatedly observed through time boils down to the simple statement that if the observation is within about 500cm of a previous observation, they are treated as co-located observations. For some very high resolution applications, this may be insufficient, but there it is. For observations at pressure levels, see the Word about vertical levels.
The only complicated part of determining the verification network is the temporal component. The initial time (usually an analysis time from a previous assimilation), the verification interval, and the forecast length completely specify the temporal aspect of a forecast. The following example has a verification interval of 6 hours and a forecast length of 24 hours. We adopt the convention of also including the initial conditions (a "nowcast") in the "forecast", so there are 5 times of interest - which we will call verification times and are represented by . The candidate observation sequence files are scanned to select all the observations that are closest to the verification times. The difference in time between the "nowcast" and the "forecast" is the forecast lead.
So - that is simple enough if there is only one forecast, but this is rarely the case. Let's say we have a second forecast. Ideally, we'd like to verify at exactly the same locations and forecast leads - otherwise we're not really comparing the same things. If the second verification network happens to be at locations that are easy to predict, we're comparing apples and oranges. The fair way to proceed is to determine the verification network that is the same for all forecasts. This generally results in a pretty small set of observations - a problem we will deal with later.
The diagram below illustrates the logic behind determining the list of verification times for a pretty common scenario: a 24-hour forecast with a forecast lead of 6 hours, repeated the next day. The first_analysis is at VT1 - let's call it 00Z day 1. We need to have observations available at:
VT1 (00Z day1), VT2 (06Z day1), VT3 (12Z day1), VT4 (18Z day1), and VT5 (24Z day1 / 00Z day2). The last_analysis starts at VT5 00Z day 2 and must verify at
VT5 (00Z day2), VT6 (06Z day2), VT7 (12Z day2), VT8 (18Z day2), and VT9 (24Z day2 / 00Z day3).
Note that, if you wanted to, you could launch forecasts at VT2, VT3, and VT4 without adding extra constraints on the verification network.
obs_seq_coverage
simply provides these possible forecasts "for free", there is no assumption about needing them. We will use the variable verification_times to describe the complete set of times for all possible forecasts. In our example above, there are 5 possible forecasts, each forecast consisting of 5 verification times (the analysis time and the 4 forecast lead times). As such, there are 9 unique verification times.Note that no attempt is made at checking the QC value of the candidate observations. One of the common problems is that the region definition does not mesh particularly well with the model domain and the DART forward operator fails because it would have to extrapolate (which is not allowed). Without checking the QC value, this can mean there are a lot of 'false positives'; observations that seemingly could be used to validate, but are actually just outside the model domain. I'm working on that ....
The USAGE section has more on the actual use of
obs_seq_coverage
.This namelist is read from the file input.nml
. Namelists start with an ampersand '&' and terminate with a slash '/'. Character strings that contain a '/' must be enclosed in quotes to prevent them from prematurely terminating the namelist.
&obs_seq_coverage_nml
obs_sequences = ''
obs_sequence_list = ''
obs_of_interest = ''
textfile_out = 'obsdef_mask.txt'
netcdf_out = 'obsdef_mask.nc'
calendar = 'Gregorian'
first_analysis = 2003, 1, 1, 0, 0, 0
last_analysis = 2003, 1, 2, 0, 0, 0
forecast_length_days = 1
forecast_length_seconds = 0
verification_interval_seconds = 21600
temporal_coverage_percent = 100.0
lonlim1 = -888888.0
lonlim2 = -888888.0
latlim1 = -888888.0
latlim2 = -888888.0
verbose = .false.
debug = .false.
/
Note that -888888.0 is not a useful number. To use the defaults delete these lines from the namelist, or set them to 0.0, 360.0 and -90.0, 90.0.
The date-time integer arrays in this namelist have the form (YYYY, MM, DD, HR, MIN, SEC).
The allowable ranges for the region boundaries are: latitude [-90.,90], longitude [0.,Inf.]
You can specify either obs_sequences or obs_sequence_list -- not both. One of them has to be an empty string ... i.e. ''.
Item | Type | Description |
---|---|---|
obs_sequences | character(len=256) | Name of the observation sequence file(s). This may be a relative or absolute filename. If the filename contains a '/', the filename is considered to be comprised of everything to the right, and a directory structure to the left. The directory structure is then queried to see if it can be incremented to handle a sequence of observation files. The default behavior of obs_seq_coverage is to look for additional files to include until the files are exhausted or an obs_seq.final file is found that contains observations beyond the timeframe of interest. e.g. 'obsdir_001/obs_seq.final' will cause obs_seq_coverage to look for 'obsdir_002/obs_seq.final', and so on. If this is set, obs_sequence_list must be set to ' '. |
obs_sequence_list | character(len=256) | Name of an ascii text file which contains a list of one or more observation sequence files, one per line. If this is specified, obs_sequences must be set to ' '. Can be created by any method, including sending the output of the 'ls' command to a file, a text editor, or another program. |
obs_of_interest | character(len=32), dimension(:) | These are the observation types that will be verified. It is an array of character strings that must match the standard DART observation types. Simply add as many or as few observation types as you need. Could be 'METAR_U_10_METER_WIND', 'METAR_V_10_METER_WIND',..., for example. |
textfile_out | character(len=256) | The name of the file that will contain the observation definitions of the verfication observations. Only the metadata from the observations (location, time, obs_type) are preserved in this file. They are in no particular order. ../../../assimilation_code/programs/obs_selection/obs_selection will use this file as a 'mask' to extract the real observations from the candidate observation sequence files. |
netcdf_out | character(len=256) | The name of the file that will contain the observation definitions of the unique locations that match any of the verification times. This file is used in conjunction with ../../../assimilation_code/programs/obs_seq_verify/obs_seq_verify to reorder the obs_seq.forecast into a structure that will facilitate calculating the statistics and scores of the forecasts. |
calendar | character(len=129) | The type of the calendar used to interpret the dates. |
first_analysis | integer, dimension(6) | The start time of the first forecast. Also known as the analysis time of the first forecast. The six integers are: year, month, day, hour, hour, minute, second -- in that order. |
last_analysis | integer, dimension(6) | The start time of the last forecast. The six integers are: year, month, day, hour, hour, minute, second -- in that order. This needs to be a perfect multiple of the verification_interval_seconds from the start of first_analysis. |
forecast_length_days forecast_length_seconds | integer | both values are used to determine the total length of any single forecast. |
verification_interval_seconds | integer | The number of seconds between each verification.
|
temporal_coverage_percent | real | While it is possible to specify that you do not need an observation at every time, it makes the most sense. This is not actually required to be 100% but 100% results in the most robust comparison. |
lonlim1 | real | Westernmost longitude of desired region. |
lonlim2 | real | Easternmost longitude of desired region. If this value is less than the westernmost value, it defines a region that spans the prime meridian. It is perfectly acceptable to specify lonlim1 = 330 , lonlim2 = 50 to identify a region like "Africa". |
latlim1 | real | Southernmost latitude of desired region. |
latlim2 | real | Northernmost latitude of desired region. |
verbose | logical | Print extra run-time information. |
debug | logical | Enable debugging messages. May generate a lot of output. |
For example:
&obs_seq_coverage_nml
obs_sequences = ''
obs_sequence_list = 'obs_coverage_list.txt'
obs_of_interest = 'METAR_U_10_METER_WIND',
'METAR_V_10_METER_WIND'
textfile_out = 'obsdef_mask.txt'
netcdf_out = 'obsdef_mask.nc'
calendar = 'Gregorian'
first_analysis = 2003, 1, 1, 0, 0, 0
last_analysis = 2003, 1, 2, 0, 0, 0
forecast_length_days = 1
forecast_length_seconds = 0
verification_interval_seconds = 21600
temporal_coverage_percent = 100.0
lonlim1 = 0.0
lonlim2 = 360.0
latlim1 = -90.0
latlim2 = 90.0
verbose = .false.
/
assim_model_mod
types_mod
location_mod
model_mod
null_mpi_utilities_mod
obs_def_mod
obs_kind_mod
obs_sequence_mod
random_seq_mod
time_manager_mod
utilities_mod
input.nml
is used for obs_seq_coverage_nml- A text file containing the metadata for the observations to be used for forecast evaluation is created. This file is subsequently required by
../../../assimilation_code/programs/obs_selection/obs_selection
to subset the set of input observation sequence files into a single observation sequence file (obs_seq.evaluate
) for the forecast step. (obsdef_mask.txt
is the default name) - A netCDF file containing the metadata for a much larger set of observations that may be used is created. This file is subsequently required by
../../../assimilation_code/programs/obs_seq_coverage/obs_seq_coverage
to define the desired times and locations for the verification. (obsdef_mask.nc
is the default name)
obs_seq_coverage
is built in .../DART/models/your_model/work, in the same way as the other DART components.There is no requirement on the reporting time/frequence of the candidate voxels. Once the verification times have been defined, the observation closest in time to the verification time is selected, the others are ignored. Only observations within half the verification interval are eligible to be considered "close".
A word about vertical levels. If the desired observation type has UNDEFINED or SURFACE for the vertical coordinate system, there is no concern about trying to match the vertical. If the desired observation types use PRESSURE; the following 14 levels are used as the standard levels: 1000, 925, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 10 (all hPa). No other vertical coordinate system is supported.
In this example, we are generating an
obsdef_mask.txt
file for a single forecast. All the required input observation sequence filenames will be contained in a file referenced by the obs_sequence_list variable. We'll also restrict the observations to a specific rectangular (in Lat/Lon) region at a particular level. It is convenient to turn on the verbose option the first time to get a feel for the logic. Here are the namelist settings if you want to verify the METAR_U_10_METER_WIND and METAR_V_10_METER_WIND observations over the entire globe every 6 hours for 2 days starting 18Z 8 Jun 2008:&obs_seq_coverage_nml
obs_sequences = ''
obs_sequence_list = 'obs_file_list.txt'
obs_of_interest = 'METAR_U_10_METER_WIND',
'METAR_V_10_METER_WIND'
textfile_out = 'obsdef_mask.txt'
netcdf_out = 'obsdef_mask.nc'
calendar = 'Gregorian'
first_analysis = 2008, 6, 8, 18, 0, 0
last_analysis = 2008, 6, 8, 18, 0, 0
forecast_length_days = 2
forecast_length_seconds = 0
verification_interval_seconds = 21600
temporal_coverage_percent = 100.0
lonlim1 = 0.0
lonlim2 = 360.0
latlim1 = -90.0
latlim2 = 90.0
verbose = .true.
/
The first step is to create a file containing the list of observation sequence files you want to use. This can be done with the unix command 'ls' with the -1 option (that's a number one) to put one file per line, particularly if the files are organized in a nice fashion. If your observation sequence are organized like this:
/Exp1/Dir20080101/obs_seq.final
/Exp1/Dir20080102/obs_seq.final
/Exp1/Dir20080103/obs_seq.final
...
/Exp1/Dir20081231/obs_seq.final
then
ls -1 /Exp1/Dir*/obs_seq.final > obs_file_list.txt
creates the desired file. Then, simply run obs_seq_coverage
- you may want to save the run-time output to a file. It is convenient to turn on the verbose option the first time. Here is a portion of the run-time output:
[thoar@mirage2 work]$ ./obs_seq_coverage | & tee my.log
Starting program obs_seq_coverage
Initializing the utilities module.
Trying to log to unit 10
Trying to open file dart_log.out
--------------------------------------
Starting ... at YYYY MM DD HH MM SS =
2011 2 22 13 15 2
Program obs_seq_coverage
--------------------------------------
set_nml_output Echo NML values to log file only
Trying to open namelist log dart_log.nml
location_mod: Ignoring vertical when computing distances; horizontal only
------------------------------------------------------
-------------- ASSIMILATE_THESE_OBS_TYPES --------------
RADIOSONDE_TEMPERATURE
RADIOSONDE_U_WIND_COMPONENT
RADIOSONDE_V_WIND_COMPONENT
SAT_U_WIND_COMPONENT
SAT_V_WIND_COMPONENT
-------------- EVALUATE_THESE_OBS_TYPES --------------
RADIOSONDE_SPECIFIC_HUMIDITY
------------------------------------------------------
METAR_U_10_METER_WIND is type 36
METAR_V_10_METER_WIND is type 37
There are 9 verification times per forecast.
There are 1 supported forecasts.
There are 9 total times we need observations.
At least 9 observations times are required at:
verification # 1 at 2008 Jun 08 18:00:00
verification # 2 at 2008 Jun 09 00:00:00
verification # 3 at 2008 Jun 09 06:00:00
verification # 4 at 2008 Jun 09 12:00:00
verification # 5 at 2008 Jun 09 18:00:00
verification # 6 at 2008 Jun 10 00:00:00
verification # 7 at 2008 Jun 10 06:00:00
verification # 8 at 2008 Jun 10 12:00:00
verification # 9 at 2008 Jun 10 18:00:00
obs_seq_coverage opening obs_seq.final.2008060818
QC index 1 NCEP QC index
QC index 2 DART quality control
First observation time day=148812, sec=64380
First observation date 2008 Jun 08 17:53:00
Processing obs 10000 of 84691
Processing obs 20000 of 84691
Processing obs 30000 of 84691
Processing obs 40000 of 84691
Processing obs 50000 of 84691
Processing obs 60000 of 84691
Processing obs 70000 of 84691
Processing obs 80000 of 84691
obs_seq_coverage doneDONEdoneDONE does not exist. Finishing up.
There were 442 voxels matching the input criterion.
...
ASSIMILATE_THESE_OBS_TYPES
and EVALUATE_THESE_OBS_TYPES
are completely irrelevant - since we're not actually doing an assimilation. The BIG difference between the two output files is that obsdef_mask.txt
contains the metadata for just the matching observations while obsdef_mask.nc
contains the metadata for all candidate locations as well as a lot of information about the desired verification times. It is possible to explore obsdef_mask.nc
to review the selection criteria to include observations/"voxels" that do not perfectly match the original selection criteria.Now that you have the
obsdef_mask.nc
, you can explore it with ncdump.netcdf obsdef_mask {
dimensions:
voxel = UNLIMITED ; // (512 currently)
time = 9 ;
analysisT = 1 ;
forecast_lead = 9 ;
nlevels = 14 ;
linelen = 256 ;
nlines = 446 ;
stringlength = 32 ;
location = 3 ;
variables:
int voxel(voxel) ;
voxel:long_name = "desired voxel flag" ;
voxel:description = "1 == good voxel" ;
double time(time) ;
time:long_name = "verification time" ;
time:units = "days since 1601-1-1" ;
time:calendar = "GREGORIAN" ;
double analysisT(analysisT) ;
analysisT:long_name = "analysis (start) time of each forecast" ;
analysisT:units = "days since 1601-1-1" ;
analysisT:calendar = "GREGORIAN" ;
int forecast_lead(forecast_lead) ;
forecast_lead:long_name = "current forecast length" ;
forecast_lead:units = "seconds" ;
double verification_times(analysisT, forecast_lead) ;
verification_times:long_name = "verification times during each forecast run" ;
verification_times:units = "days since 1601-1-1" ;
verification_times:calendar = "GREGORIAN" ;
verification_times:rows = "each forecast" ;
verification_times:cols = "each verification time" ;
float mandatory_level(nlevels) ;
mandatory_level:long_name = "mandatory pressure levels" ;
mandatory_level:units = "Pa" ;
char namelist(nlines, linelen) ;
namelist:long_name = "input.nml contents" ;
char obs_type(voxel, stringlength) ;
obs_type:long_name = "observation type string at this voxel" ;
double location(voxel, location) ;
location:description = "location coordinates" ;
location:location_type = "loc3Dsphere" ;
location:long_name = "threed sphere locations: lon, lat, vertical" ;
location:storage_order = "Lon Lat Vertical" ;
location:units = "degrees degrees which_vert" ;
int which_vert(voxel) ;
which_vert:long_name = "vertical coordinate system code" ;
which_vert:VERTISUNDEF = -2 ;
which_vert:VERTISSURFACE = -1 ;
which_vert:VERTISLEVEL = 1 ;
which_vert:VERTISPRESSURE = 2 ;
which_vert:VERTISHEIGHT = 3 ;
which_vert:VERTISSCALEHEIGHT = 4 ;
int ntimes(voxel) ;
ntimes:long_name = "number of observation times at this voxel" ;
double first_time(voxel) ;
first_time:long_name = "first valid observation time at this voxel" ;
first_time:units = "days since 1601-1-1" ;
first_time:calendar = "GREGORIAN" ;
double last_time(voxel) ;
last_time:long_name = "last valid observation time at this voxel" ;
last_time:units = "days since 1601-1-1" ;
last_time:calendar = "GREGORIAN" ;
double ReportTime(voxel, time) ;
ReportTime:long_name = "time of observation" ;
ReportTime:units = "days since 1601-1-1" ;
ReportTime:calendar = "GREGORIAN" ;
ReportTime:missing_value = 0. ;
ReportTime:_FillValue = 0. ;
// global attributes:
:creation_date = "YYYY MM DD HH MM SS = 2011 03 01 09 28 40" ;
:obs_seq_coverage_source = "$URL$" ;
:obs_seq_coverage_revision = "$Revision$" ;
:obs_seq_coverage_revdate = "$Date$" ;
:min_steps_required = 9 ;
:forecast_length_days = 2 ;
:forecast_length_seconds = 0 ;
:verification_interval_seconds = 21600 ;
:obs_of_interest_001 = "METAR_U_10_METER_WIND" ;
:obs_of_interest_002 = "METAR_V_10_METER_WIND" ;
:obs_seq_file_001 = "obs_seq.final.2008060818" ;
data:
time = 148812.75, 148813, 148813.25, 148813.5, 148813.75, 148814, 148814.25,
148814.5, 148814.75 ;
forecast_lead = 0, 21600, 43200, 64800, 86400, 108000, 129600, 151200, 172800 ;
}
The voxel variable is fundamentally a flag that indicates if the station has all of the desired verification times. Combine that information with the obs_type and location to determine where your verifications of any particular observation type will take place.
Now that you have the
obsdef_mask.txt
, you can run ../../../assimilation_code/programs/obs_selection/obs_selection
to subset the observation sequence files into one compact file to use in your ensemble forecast.- none - but this seems like a good place to start: The Centre for Australian Weather and Climate Research - Forecast Verification Issues, Methods and FAQ