midas_genCoeff

link to source code

Dependency Diagrams:

Direct Dependency Diagram

program  midas_gencoeff

Purpose

Main program to compute radiance bias correction coefficients by linear regression.

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Algorithm

O-A are computed from input analysis fields resulting from a stand alone 3DVar analysis assimilating only anchoring observations (considered as “trials”) and bgckalt files.

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File I/O

The required input files and produced output files are listed as follows.

Input and Output Files (NWP application)	Description of file
flnml	In - Main namelist file with parameters user may modify
flnml_static	In - The “static” namelist that should not be modified
trlm_$NN (e.g. trlm_01)	In - Background state (a.k.a. trial) files for each timestep
analysisgrid	In - File defining grid for computing the analysis increment
obsfiles_$FAM/obs$FAM_$NNNN_$NNNN	In - Observation file for each “family” and MPI task
Remainder are files related to radiance obs:
stats_tovs	In - Observation error file for radiances
stats_tovs_symmetricObsErr	In - user-defined symmetric TOVS errors for all sky
Cmat_$PLATFORM_$SENSOR.dat	In - Inter-channel observation-error correlations
rtcoef_$PLATFORM_$SENSOR.H5	In - RTTOV coefficient file HDF-5 format
rtcoef_$PLATFORM_$SENSOR.dat	In - RTTOV coefficient file ASCII format
ozoneclim98	In - ozone climatology standard file (Fortuin and Kelder)

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Synopsis

Below is a summary of the genCoeff program calling sequence:

• Initial setups:

  • Setup time grid using initial time from trlm_01

  • Setup horizontal and vertical grid objects for “analysis grid” from analysisgrid file.

  • Setup obsSpaceData object and read observations from files: inn_setupObs.

  • Setup columnData and gridStateVector modules (read list of analysis variables from namelist) and allocate column object for storing trial on analysis levels.

  • Setup the observation error statistics in obsSpaceData object: oer_setObsErrors.

  • Allocate a stateVector object on the trial grid and then read the trials: gio_readTrials.

• Coefficients computation

  • Horizontally Interpolate “trial” fields to trial columns

  • if needed substract bias correction from ObsSpaceData to get raw O-F and obs.

  • Remove outliers

  • Compute innovation from “trial” fields

  • Refresh Bias Correction (probably useless)

  • Perform linear regression

  • write coefficients to output file.

  • if requested compute and output to file raw (.i.e without bias correction) O-F statistics

  • compute and apply bias coorection to obsSpace Data

  • if requested compute and output to file bias corrected O-F statistics

• Final step

  • deallocate memory (radiance bias correction module and obsSpaceData)

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Options

List of namelist blocks that can affect the genCoeff program.

Needed modules

• version_mod: MODULE version_mod (prefix=’ver’ category=’8. Low-level utilities and constants’)

• codeprecision_mod: MODULE codePrecision_mod (prefix=’pre’ category=’8. Low-level utilities and constants’)

• ramdisk_mod: MODULE ramDisk_mod (prefix=’ram’ category=’8. Low-level utilities and constants’)

• utilities_mod: MODULE utilities_mod (prefix=’utl’ category=’8. Low-level utilities and constants’)

• midasmpi_mod: MODULE midasMpi_mod (prefix=’mmpi’ category=’8. Low-level utilities and constants’)

• mathphysconstants_mod: MODULE mathPhysConstants_mod (prefix=’mpc’ category=’8. Low-level utilities and constants’)

• horizontalcoord_mod: MODULE horizontalCoord_mod (prefix=’hco’ category=’7. Low-level data objects’)

• verticalcoord_mod: MODULE verticalCoord_mod (prefix=’vco’ category=’7. Low-level data objects’)

• timecoord_mod: MODULE timeCoord_mod (prefix=’tim’ category=’7. Low-level data objects’)

• obsspacedata_mod: MODULE obsSpaceData_mod (prefix=’obs’ category=’6. High-level data objects’)

• columndata_mod: MODULE columnData_mod (prefix=’col’ category=’6. High-level data objects’)

• gridstatevector_mod: MODULE gridStateVector_mod (prefix=’gsv’ category=’6. High-level data objects’)

• gridstatevectorfileio_mod: MODULE gridStateVectorFileIO_mod (prefix=’gio’ category=’4. Data Object transformations’)

• obsfiles_mod: MODULE obsFiles_mod (prefix=’obsf’ category=’3. Observation input/output’)

• innovation_mod: MODULE innovation_mod (prefix=’inn’ category=’1. High-level functionality’)

• obserrors_mod: MODULE obsErrors_mod (prefix=’oer’ category=’2. B and R matrices’)

• biascorrectionsat_mod: MODULE biasCorrectionSat_mod (prefix=’bcs’ category=’1. High-level functionality’)

Routines called

ver_printnameandversion(), mmpi_initialize(), utl_tmg_start(), ram_setup(), inn_gethcovcofromtrlmfile(), gsv_allocate(), tim_getdatestamp(), gsv_zero(), gio_readtrials(), inn_setupcolumnsontrllev(), bcs_removebiascorrection(), bcs_removeoutliers(), utl_tmg_stop(), inn_computeinnovation(), bcs_refreshbiascorrection(), bcs_do_regression(), bcs_writebias(), bcs_computeresidualsstatistics(), bcs_calcbias(), bcs_finalize(), obs_finalize(), tim_setup(), obsf_setup(), tim_getdatestampfromfile(), tim_setdatestamp(), utl_abort(), mpc_printconstants(), pre_printprecisions(), gsv_setup(), hco_setupfromfile(), vco_setupfromfile(), col_setvco(), inn_setupobs(), col_setup(), oer_setobserrors()