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Radiance Data Assimilation in WRF-Var

Radiance Data Assimilation in WRF-Var. Please see other related detailed tutorial presentations available at. http://www.mmm.ucar.edu/wrf/users/tutorial/tutorial_presentation.htm. Satellite Data. http://www.mmm.ucar.edu/wrf/users/tutorial/200807/VAR/WRF_Tutorial_Radiances.pdf.

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Radiance Data Assimilation in WRF-Var

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  1. Radiance Data Assimilation in WRF-Var Please see other related detailed tutorial presentations available at http://www.mmm.ucar.edu/wrf/users/tutorial/tutorial_presentation.htm Satellite Data http://www.mmm.ucar.edu/wrf/users/tutorial/200807/VAR/WRF_Tutorial_Radiances.pdf

  2. Radiance codes are NOT included in the current V3.0.1.1 release. Radiance codes are expected to be released in the next coming release (April 2009). da/da_radiance] % ls adm_ehv2pem.inc da_predictor_rttov.inc da_sort_rad.inc da_allocate_rad_iv.inc da_print_stats_rad.inc da_transform_xtoy_crtm.inc da_ao_stats_rad.inc da_qc_airs.inc da_transform_xtoy_crtm_adj.inc da_biascorr.inc da_qc_amsua.inc da_transform_xtoy_rttov.inc da_biasprep.inc da_qc_amsub.inc da_transform_xtoy_rttov_adj.inc da_calculate_grady_rad.inc da_qc_crtm.inc da_write_biasprep.inc da_cld_eff_radius.inc da_qc_hirs.inc da_write_filtered_rad.inc da_cloud_detect_airs.inc da_qc_mhs.inc da_write_iv_rad_ascii.inc da_cloud_sim_airs.inc da_qc_rad.inc da_write_oa_rad_ascii.inc da_crtm.f90 da_qc_ssmis.inc ehv2pem.inc da_crtm_ad.inc da_radiance.f90 emiss_ssmi.inc da_crtm_direct.inc da_radiance1.f90 gsi_constants.f90 da_crtm_init.inc da_radiance_init.inc gsi_emiss.inc da_crtm_k.inc da_read_biascoef.inc gsi_kinds.f90 da_crtm_sensor_descriptor.inc da_read_filtered_rad.inc gsi_thinning.f90 da_crtm_tl.inc da_read_kma1dvar.inc iceem_amsu.inc da_detsurtyp.inc da_read_obs_bufrairs.inc init_constants_derived.inc da_get_innov_vector_crtm.inc da_read_obs_bufrssmis.inc inria_n2qn1.inc da_get_innov_vector_crtmk.inc da_read_obs_bufrtovs.inc landem.inc da_get_innov_vector_radiance.inc da_read_pseudo_rad.inc module_radiance.f90 da_get_innov_vector_rttov.inc da_residual_rad.inc ossmem.inc da_get_julian_time.inc da_rttov.f90 seaem.inc da_get_time_slots.inc da_rttov_ad.inc siem_ats.inc da_initialize_rad_iv.inc da_rttov_direct.inc siem_bts.inc da_jo_and_grady_rad.inc da_rttov_init.inc siem_interpolate.inc da_oi_stats_rad.inc da_rttov_tl.inc snwem_amsu.inc da_predictor_crtm.inc da_setup_radiance_structures.inc

  3. Basic Concepts: Radiative Transfer + + Surface Cloud/rain Emission/reflection Diffusion/scattering TOA radiance at frequency  Planck function Atmospheric absorption • Temperature information derived from well-mixed absorbents (CO2, …) • Channels sensitive to Humidity, Ozone, … • Surface channels: “window” parts of spectrum AMSUA

  4. Basic Concepts: Radiative Transfer + + Surface Cloud/rain Emission/reflection Diffusion/scattering TOA radiance at frequency  Planck function Atmospheric absorption CRTM, RTTOV, … T, Q, O3, … L() Forward model RT Inversion Regression, neural network, 1D-Var

  5. Practical issues: Quality Control • Specific QC for each sensorAMSU-A, AMSU-B, MHS, SSMIS, AIRS • Pixel-level QC • Reject limb observations • Reject pixels over land and sea-ice • Cloud/Precipitation detection • Synergy with imager (AIRS/VIS-NIR) • Channel-level QC • Grosscheck(innovations <15 K) • First-guess check(innovations < 3o). • Observation error tuning • Error factor tuned from objective method (Desrozier and Ivanov, 2001) AMSU-B 89GHz-150GHz Tb < 3K Katrina Location (2005/08/26/06Z) CLWP(mm) from Guess <0.2mm

  6. Parameters Predictors: • Offset • 1000-300mb thickness • 200-50mb thickness • Surface skin temperature • Total column water vapor • Scan Practical issues: Bias Correction Modeling of errors in satellite radiances: Air Mass Bias + Scan Bias Scan Bias = d(limb) - d(nadir) • d(.) is departure (omb or oma) • This is relative bias between limb and nadir

  7. Parameters Predictors: • Offset • 1000-300mb thickness • 200-50mb thickness • Surface skin temperature • Total column water vapor • Scan Practical issues: Variational Bias Correction Modeling of errors in satellite radiances: Bias parameters can be estimated within the variational assimilation, jointly with the atmospheric model state (Derber and Wu 1998) (Dee 2005) (Auligné et al. 2007) Inclusion of the bias parameters in the control vector : xT [x, ]T Jb: background term forx Jo: corrected observation term «Optimal » bias correction considering all available information J: background term for 

  8. Practical issues: Thinning No Thinning 120km Thinning Mesh

  9. Data Ingest (sources, instruments, Tb, Ta) • Radiative transfer model • Channel selection • Bias correction • Off-line bias correction statistics • Variational bias correction • Diagnostics and monitoring

  10. Data Ingest • NCEP global BUFR radiance data (Total: 14 sensors from 6 satellites) • HIRS from NOAA16, 17, 18 • AMSU-A from NOAA15, 16, 18, EOS-Aqua, METOP-2 • AMSU-B from NOAA15, 16, 17 • MHS from NOAA18, METOP-2 • AIRS from EOS-Aqua • NCAR processed AMSU-A, AMSU-B, MHS BUFR files. • NRL/AFWA/NESDIS produced DMSP-16 SSMI/S BUFR radiance data.

  11. Data Processing • Raw orbit-by-orbit level-1B radiance in binary format (including coefficients for radiance to temperature conversion) from NESDIS [ --> antenna temperature ] --> brightness temperature • Concatenate orbit-by-orbit files within desired time window into one BUFR file • Remove duplicate data

  12. NCEP BUFR ftp://ftp.ncep.noaa.gov/pub/data/nccf/com/gfs/prod/gdas.${yyyymmddhh} NCEP naming convention WRF-Var naming convention gdas1.t00z.1bamua.tm00.bufr_d gdas1.t00z.1bamub.tm00.bufr_d gdas1.t00z.1bhrs3.tm00.bufr_d gdas1.t00z.1bhrs4.tm00.bufr_d gdas1.t00z.1bmhs.tm00.bufr_d gdas1.t00z.airsev.tm00.bufr_d gdas1.t00z.airs.tm00.bufr_d amsua.bufr amsub.bufr hirs3.bufr hirs4.bufr mhs.bufr airs.bufr ssmis.bufr Direct input to WRF-Var, no pre-processing required. Quality control, thinning, time and domain check, bias correction are done inside WRF-Var • Namelist switches to decide if reading the data or not • Use_amsuaobs • Use_amsubobs • Use_hirs3obs • Use_hirs4obs • Use_mhsobs • Use_airsobs • Use_eos_amsuaobs • Use_ssmisobs

  13. Radiative Transfer Model For all the satellite sensors supported, given an atmospheric profile of temperature, water vapour and optionally ozone and carbon dioxide together with satellite zenith angle and surface temperature, pressure and optionally surface emissivity, RTTOV will compute the top of atmosphere radiances in each of the channels of the sensor being simulated. From http://www.metoffice.gov.uk/research/interproj/nwpsaf/rtm/rttov8_description.html

  14. Radiative Transfer Model • CRTM (Community Radiative Transfer Model) • JCSDA (Joint Center for Satellite Data Assimilation) ftp://ftp.emc.ncep.noaa.gov/jcsda/CRTM/ • Latest released version: CRTM REL-1.2_beta, September 2008 • Version used in WRF-Var: CRTM REL-1.1 Documentation still under development RTTOV (Radiative Transfer for TOVS) EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) http://www.metoffice.gov.uk/research/interproj/nwpsaf/rtm/index.html Latest released version: RTTOV_9_2, July 2008 Version used in WRF-Var: RTTOV_8_7 (with a small bug fix) in WRF-Var applications, CRTM and RTTOV produce similar resultswhile RTTOV is much faster than CRTM

  15. Channel selection Window Channels (1~3,15) not used Channels 10~14 above model top removed Ch4: 700mb Ch5: 500~700mb Ch6: 400~500mb Ch7: 200~300mb Sounding Channels (5~9) sensitive to Temperature. Ch8: 200mb Ch9: 100mb Ch10: 50mb Ch11: 30mb

  16. Channel selection WRFDA/var/run/radiance_info>ls -l total 160 -rw-r--r-- 1 hclin users 1588 Aug 22 17:01 dmsp-16-ssmis.info -rw-r--r-- 1 hclin users 17790 Aug 22 17:01 eos-2-airs.info -rw-r--r-- 1 hclin users 1033 Aug 22 17:01 eos-2-amsua.info -rw-r--r-- 1 hclin users 1036 Aug 22 17:01 metop-2-amsua.info -rw-r--r-- 1 hclin users 391 Aug 22 17:01 metop-2-mhs.info -rw-r--r-- 1 hclin users 1021 Aug 22 17:01 noaa-15-amsua.info -rw-r--r-- 1 hclin users 391 Aug 22 17:01 noaa-15-amsub.info -rw-r--r-- 1 hclin users 1277 Aug 22 17:01 noaa-15-hirs.info -rw-r--r-- 1 hclin users 1021 Aug 22 17:01 noaa-16-amsua.info -rw-r--r-- 1 hclin users 391 Aug 22 17:01 noaa-16-amsub.info -rw-r--r-- 1 hclin users 1275 Aug 22 17:01 noaa-16-hirs.info -rw-r--r-- 1 hclin users 391 Aug 22 17:01 noaa-17-amsub.info -rw-r--r-- 1 hclin users 1277 Aug 22 17:01 noaa-17-hirs.info -rw-r--r-- 1 hclin users 1036 Aug 22 17:01 noaa-18-amsua.info -rw-r--r-- 1 hclin users 1286 Aug 22 17:01 noaa-18-hirs.info -rw-r--r-- 1 hclin users 391 Aug 22 17:01 noaa-18-mhs.info metop-2-mhs.info sensor channel IR/MW use idum varch polarisation(0:vertical;1:horizontal) 203 1 1 -1 0 0.2500000000E+01 0.0000000000E+00 203 2 1 -1 0 0.2500000000E+01 0.0000000000E+00 203 3 1 1 0 0.2500000000E+01 0.1000000000E+01 203 4 1 1 0 0.2000000000E+01 0.1000000000E+01 203 5 1 1 0 0.2000000000E+01 0.0000000000E+00

  17. Setup and run - withradiances To run WRF-Var, first create a working directory, for example, WRFDA/var/test, then follow the steps below: cd WRFDA/var/test (go to the working directory) ln -sf WRFDA/run/LANDUSE.TBL ./LANDUSE.TBL ln -sf $DAT_DIR/rc/2007010200/wrfinput_d01 ./fg (link first guess file as fg) ln -sf WRFDA/var/obsproc/obs_gts_2007-01-02_00:00:00.3DVAR ./ob.ascii (link OBSPROC processed observation file as ob.ascii) ln -sf $DAT_DIR/be/be.dat ./be.dat (link background error statistics as be.dat) ln -sf WRFDA/var/da/da_wrfvar.exe ./da_wrfvar.exe (link executable) ln -sf $DAT_DIR/2007010200/gdas1.t00z.1bamua.tm00.bufr_d ./amsua.bufr ln -sf $RADIANCE_INFO_DIR ./radiance_info ln -sf $BIASCORR_DIR ./biascorr (CRTM only) ln -sf $CRTM_COEFFS_DIR ./crtm_coeffs (RTTOV only) ln -sf $RTTOV_COEFFS_DIR/rtcoef*.dat ./rtcoef*.dat (Variational Bias Correction only) vi VARBC.in vi namelist.input (&wrfvar4, &wrfvar14, &wrfvar12, &wrfvar22) da_wrfvar.exe >&! wrfda.log

  18. From RTTOV_8_7 Users Guide http://www.metoffice.gov.uk/research/interproj/nwpsaf/rtm/rttov8_ug.pdf sensor_id • Instrument triplets platform_id • satellite_id • sensor_id platform_id satellite_id

  19. namelist.input RTMINIT_NSENSOR = 12 RTMINIT_PLATFORM = 1, 1, 1, 9,10, 1, 1, 1, 1,10, 9, 2 RTMINIT_SATID = 15,16,18, 2, 2,15,16,17,18, 2, 2,16 RTMINIT_SENSOR = 3, 3, 3, 3, 3, 4, 4, 4,15,15,11,10 NOAA-15-AMSUA NOAA-16-AMSUA NOAA-18-AMSUA EOS-2-AMSUA METOP-2-AMSUA NOAA-15-AMSUB NOAA-16-AMSUB NOAA-17-AMSUB NOAA-18-MHS METOP-2-MHS EOS-2-AIRS DMSP-16-SSMIS

  20. RAD_MONITORING (30) • Integer array with dimension RTMINIT_NSENSER, where 0 for assimilating mode, 1 for monitoring mode (only calculate innovation). • THINNING • Logical, TRUE will perform thinning • THINNING_MESH (30) • Real array with dimension RTMINIT_NSENSOR, values indicate thinning mesh (in KM) for different sensors. • READ_BIASCOEF • Logical, control if reading bias correction coefficient files (Harris and Kelly scheme), always set to TRUE. • BIASCORR • Logical, control if perform bias correction (Harris and Kelly scheme). • BIASPREP • Logical, control if perform bias correction preparation (Harris and Kelly scheme). • QC_RAD • Logical, control if perform quality control, always set to TRUE. • WRITE_IV_RAD_ASCII • Logical, control if output Observation minus Background files, which are ASCII format and separated by sensors and processors. • WRITE_OA_RAD_ASCII • Logical, control if output Observation minus Analysis files (including also O minus B), which are ASCII format and separated by sensors and processors. • USE_ERROR_FACTOR_RAD • Logical, control if use a radiance error tuning factor file “radiance_error.factor”, which is created with empirical values or generated using variational tunning method (Desroziers and Ivannov, 1997) • ONLY_SEA_RAD • Logical, control if only assimilating radiance over water. • TIME_WINDOW_MIN • String, e.g., "2007-08-15_03:00:00.0000", start time of assimilation time window • TIME_WINDOW_MAX • String, e.g., "2007-08-15_09:00:00.0000", end time of assimilation time window

  21. RTTOV coefficients rttov_coefs>ls -l total 7488 -rw-r--r-- 1 hclin users 142117 Sep 27 2006 rtcoef_dmsp_10_ssmi.dat -rw-r--r-- 1 hclin users 142117 Sep 27 2006 rtcoef_dmsp_11_ssmi.dat -rw-r--r-- 1 hclin users 142117 Sep 27 2006 rtcoef_dmsp_12_ssmi.dat -rw-r--r-- 1 hclin users 142117 Sep 27 2006 rtcoef_dmsp_13_ssmi.dat -rw-r--r-- 1 hclin users 142117 Sep 27 2006 rtcoef_dmsp_14_ssmi.dat -rw-r--r-- 1 hclin users 142117 Sep 27 2006 rtcoef_dmsp_15_ssmi.dat -rw-r--r-- 1 hclin users 434642 Sep 27 2006 rtcoef_dmsp_16_ssmis.dat -rw-r--r-- 1 hclin users 142115 Sep 27 2006 rtcoef_dmsp_8_ssmi.dat -rw-r--r-- 1 hclin users 142115 Sep 27 2006 rtcoef_dmsp_9_ssmi.dat -rw-r--r-- 1 hclin users 282099 Oct 31 2006 rtcoef_eos_2_amsua.dat -rw-r--r-- 1 hclin users 282103 Oct 31 2006 rtcoef_metop_2_amsua.dat -rw-r--r-- 1 hclin users 107146 Oct 31 2006 rtcoef_metop_2_mhs.dat -rw-r--r-- 1 hclin users 282102 Oct 30 2006 rtcoef_noaa_15_amsua.dat -rw-r--r-- 1 hclin users 107091 Oct 31 2006 rtcoef_noaa_15_amsub.dat -rw-r--r-- 1 hclin users 282102 Oct 30 2006 rtcoef_noaa_16_amsua.dat -rw-r--r-- 1 hclin users 107091 Oct 31 2006 rtcoef_noaa_16_amsub.dat -rw-r--r-- 1 hclin users 282102 Oct 30 2006 rtcoef_noaa_17_amsua.dat -rw-r--r-- 1 hclin users 107091 Oct 31 2006 rtcoef_noaa_17_amsub.dat -rw-r--r-- 1 hclin users 282102 Oct 30 2006 rtcoef_noaa_18_amsua.dat -rw-r--r-- 1 hclin users 107145 Oct 31 2006 rtcoef_noaa_18_mhs.dat

  22. CRTM_02-29-08/CRTM_Coeffs>ls -l drwxr-xr-x 5 wrfhelp users 512 Mar 5 2008 AerosolCoeff drwxr-xr-x 5 wrfhelp users 512 Mar 5 2008 CloudCoeff drwxr-xr-x 5 wrfhelp users 512 Mar 5 2008 EmisCoeff drwxr-xr-x 4 wrfhelp users 512 Mar 5 2008 SpcCoeff drwxr-xr-x 5 wrfhelp users 512 Mar 5 2008 TauCoeff CRTM coefficients CRTM_02-29-08/CRTM_Coeffs/SpcCoeff>ls -l drwxr-xr-x 5 wrfhelp users 512 Dec 3 2007 Infrared drwxr-xr-x 5 wrfhelp users 512 Dec 3 2007 Microwave Link selected files from various source directories into single directory then link it ascrtm_coeffs in the WRF-Var working directory CRTM_02-29-08/CRTM_Coeffs/SpcCoeff/Microwave>ls -l drwxr-xr-x 5 wrfhelp users 512 Dec 3 2007 AAPP_AC drwxr-xr-x 5 wrfhelp users 512 Dec 3 2007 NESDIS_AC drwxr-xr-x 5 wrfhelp users 512 Feb 25 2008 No_AC CRTM_02-29-08/CRTM_Coeffs/SpcCoeff/Microwave/No_AC>ls -l drwxr-xr-x 2 wrfhelp users 1536 Dec 3 2007 Big_Endian drwxr-xr-x 2 wrfhelp users 1536 Dec 3 2007 Little_Endian drwxr-xr-x 2 wrfhelp users 1536 Feb 13 2008 netCDF CRTM_02-29-08/CRTM_Coeffs/SpcCoeff/Microwave/No_AC/Big_Endian>ls -l total 76 -rw-r--r-- 1 wrfhelp users 1232 Dec 3 2007 amsua_metop-a.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 1232 Dec 3 2007 amsua_metop-b.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 1232 Dec 3 2007 amsua_metop-c.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 1232 Dec 3 2007 amsua_n15.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 1232 Dec 3 2007 amsua_n16.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 1232 Dec 3 2007 amsua_n17.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 1232 Dec 3 2007 amsua_n18.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 1232 Dec 3 2007 amsua_n19.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 472 Dec 3 2007 amsub_n15.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 472 Dec 3 2007 amsub_n16.SpcCoeff.bin -rw-r--r-- 1 wrfhelp users 472 Dec 3 2007 amsub_n17.SpcCoeff.bin

  23. Bias Correction Satellite radiance is generally considered biased with respect to a reference (e.g., background or analysis field in NWP assimilation) due to system error of observation itself, reference field and RTM.

  24. Off-line bias correction statistics (Harris and Kelly, 2001) Step 1: generate 'biasprep' files by running WRF-Var • To generate “biasprep” files separated by sensors and processors which contains necessary information (obs, background, o minus b, predictors etc.) for used by the off-line statistics. • For statistical significance, month-long training dataset is preferred. • Running WRF-Var with radiance data to be used and appropriate background field (e.g., produced from GFSanalysis using WPS/REAL, or from a WRF 6h forecast in an existing assimilation experiment). • Note that the effect of bias correction can depend to some extent upon the reference field used for statistics. • BIASCORR=false • BIASPREP=true # control to generate biasprep* files (biasprep_noaa-15-amsua.*, biasprep_noaa-16-amsua.) • NTMAX=0 # no minimization needed since biasprep run just need to calculate innovation. • biasprep* files will be used for the off-line statistics described in step 2. Step 2: off-line statistics biascorr 139 > ls -l total 1280 -rw-r--r-- 1 hclin ncar 13433 Jul 03 12:29 dmsp-16-ssmis.bcor -rw-r--r-- 1 hclin ncar 5213 Jul 03 12:29 metop-2-amsua.bcor -rw-r--r-- 1 hclin ncar 4433 Jul 03 12:29 metop-2-mhs.bcor -rw-r--r-- 1 hclin ncar 5213 Jul 03 12:29 noaa-15-amsua.bcor -rw-r--r-- 1 hclin ncar 4433 Jul 03 12:29 noaa-15-amsub.bcor -rw-r--r-- 1 hclin ncar 5213 Jul 03 12:29 noaa-16-amsua.bcor -rw-r--r-- 1 hclin ncar 4433 Jul 03 12:29 noaa-16-amsub.bcor -rw-r--r-- 1 hclin ncar 4433 Jul 03 12:29 noaa-17-amsub.bcor -rw-r--r-- 1 hclin ncar 5213 Jul 03 12:29 noaa-18-amsua.bcor -rw-r--r-- 1 hclin ncar 4433 Jul 03 12:29 noaa-18-mhs.bcor

  25. biascorr 142 > more noaa-16-amsua.bcor 15 30 18 4 1 29557 213.78 18.76 -0.36 2.23 2 23627 181.56 13.65 -0.41 2.36 3 34047 246.38 13.24 -0.32 1.41 4 48092 265.92 4.83 0.07 3.28 5 48746 254.89 4.37 0.05 0.24 6 49495 237.05 4.69 0.02 0.14 7 49514 224.78 3.85 0.04 0.15 8 49709 215.52 2.93 -0.04 0.34 9 50068 210.00 3.08 -0.03 0.24 10 49411 216.04 3.01 -0.05 0.30 11 48618 225.41 2.58 -0.04 0.51 12 47858 235.08 2.39 0.00 1.04 13 47763 245.94 2.72 0.01 1.70 14 48232 257.77 2.80 -0.05 2.22 15 33583 259.48 13.30 -0.14 2.09 1 0.00062 0.00133 0.02410 0.16702 -32.43610 2 -0.00398 -0.00356 -0.09144 0.14316 87.68317 3 -0.00113 -0.00217 -0.19485 0.11985 85.22787 4 0.00117 0.00017 -0.04903 -0.00055 2.68755 5 -0.00024 -0.00023 -0.00172 -0.00533 4.77967 6 -0.00011 -0.00010 -0.00596 0.00008 2.67331 7 -0.00026 0.00014 -0.00557 0.00029 1.25566 8 -0.00038 0.00039 -0.00446 -0.00183 -0.07683 9 -0.00017 0.00004 -0.00267 -0.00113 0.85999 10 -0.00000 -0.00032 0.00024 0.00039 1.47647 11 0.00009 -0.00064 0.00415 -0.00129 2.07531 12 0.00018 -0.00065 0.00592 -0.00388 0.89372 13 -0.00003 -0.00035 0.03559 -0.00685 -8.74460 14 -0.00033 -0.00285 0.06766 -0.00396 3.14041 15 -0.00124 -0.00382 -0.23044 0.14527 109.53830 RELATIVE SCAN BIASES 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 1 -15.13 -14.84 -13.90 -10.91 -8.27 -5.86 -4.16 -2.59 -1.78 -1.14 -0.62 -0.63 -0.31 0.01 -0.10 0.10 -0.06 -0.15 -0.21 -0.50 -1.01 -1.83 -2.72 -4.10 -5.93 -8.46 -11.21 -13.78 -15.14 -15.36 2 -10.74 -10.11 -11.31 -13.20 -12.55 -8.79 -6.14 -3.91 -2.61 -1.63 -0.87 -0.78 -0.32 0.09 -0.10 0.10 -0.05 -0.20 -0.34 -0.61 -1.13 -2.08 -3.25 -5.07 -7.47 -10.84 -14.37 -12.72 -10.91 -10.20 3 -13.01 -11.37 -9.49 -7.44 -5.64 -4.11 -2.88 -1.90 -1.26 -0.66 -0.37 -0.33 -0.00 0.17 0.00 -0.00 -0.17 -0.49 -0.69 -0.94 -1.50 -2.10 -2.93 -3.90 -5.14 -6.64 -8.68 -10.66 -12.72 -14.38 4 -1.72 -1.70 -1.73 -1.53 -1.30 -1.12 -0.81 -0.66 -0.60 -0.13 -0.27 -0.12 0.09 -0.00 0.02 -0.02 -0.06 0.03 -0.00 0.11 -0.07 -0.30 -0.43 -0.71 -0.98 -1.06 -1.42 -1.63 -1.75 -1.72 5 -0.37 -0.52 -0.51 -0.42 -0.46 -0.38 -0.39 -0.31 -0.27 -0.21 -0.14 -0.11 -0.08 0.00 -0.02 0.02 0.02 -0.02 -0.03 -0.08 -0.12 -0.19 -0.23 -0.34 -0.35 -0.42 -0.45 -0.39 -0.43 -0.27 error standard deviation used asobservation errors in WRF-Var • Coefficients for air-mass bias correction column 1: 1000-300mb thickness column 2: 200-50mb thickness column 3: Surface skin temperature column 4: Total column water vapor column 5: offset

  26. Variational Bias Correction (VarBC) VARBC.in file is an ASCII file that controls all of what is going into the VarBC. Sample VARBC.in VARBC version 1.0 - Number of instruments: 2 ------------------------------------------------ Platform_id Sat_id Sensor_id Nchanl Npredmax ------------------------------------------------ 1 15 3 5 8 -----> Bias predictor statistics: Mean & Std & Nbgerr 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0 0 0 0 0 0 0 0 -----> Chanl_id Chanl_nb Pred_use(-1/0/1) Param 5 5 0 0 0 0 0 0 0 0 6 6 0 0 0 0 0 0 0 0 7 7 0 0 0 0 0 0 0 0 8 8 0 0 0 0 0 0 0 0 9 9 0 0 0 0 0 0 0 0 ------------------------------------------------ Platform_id Sat_id Sensor_id Nchanl Npredmax ------------------------------------------------ 1 16 4 3 8 -----> Bias predictor statistics: Mean & Std & Nbgerr 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0 0 0 0 0 0 0 0 -----> Chanl_id Chanl_nb Pred_use(-1/0/1) Param 3 3 0 0 0 0 0 0 0 0 4 4 0 0 0 0 0 0 0 0 5 5 0 0 0 0 0 0 0 0

  27. Sample VARBC.out (VARBC.in) VARBC version 1.0 - Number of instruments: 4 ------------------------------------------------ Platform_id Sat_id Sensor_id Nchanl Npredmax ------------------------------------------------ 1 15 4 5 8 -----> Bias predictor statistics: Mean & Std & Nbgerr 1.0 9273.1 8677.8 290.4 24.0 51.7 3502.8 260484.8 0.0 273.5 293.3 8.0 12.3 28.9 2827.2 252657.9 10000 10000 10000 10000 10000 10000 10000 10000 -----> Chanl_id Chanl_nb Pred_use(-1/0/1) Param 1 1 0 0 0 0 0 0 0 0 -3.400 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2 2 0 0 0 0 0 0 0 0 -0.200 0.000 0.000 0.000 0.000 0.000 0.000 0.000 3 3 1 1 1 1 1 1 1 1 1.213 -0.062 0.003 -0.070 0.008 -0.230 -0.111 -0.024 4 4 1 1 1 1 1 1 1 1 3.056 0.050 0.053 0.015 -0.059 0.304 0.241 0.203 5 5 1 1 1 1 1 1 1 1 0.869 0.034 -0.089 0.074 0.019 -0.118 -0.031 0.022 ------------------------------------------------ Platform_id Sat_id Sensor_id Nchanl Npredmax ------------------------------------------------ 1 16 4 5 8 -----> Bias predictor statistics: Mean & Std & Nbgerr 1.0 9280.2 8641.2 290.0 24.1 52.6 3568.9 264767.4 0.0 209.5 245.9 7.9 11.3 28.3 2792.1 249977.0 10000 10000 10000 10000 10000 10000 10000 10000 -----> Chanl_id Chanl_nb Pred_use(-1/0/1) Param 1 1 0 0 0 0 0 0 0 0 0.700 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2 2 0 0 0 0 0 0 0 0 -0.800 0.000 0.000 0.000 0.000 0.000 0.000 0.000 3 3 1 1 1 1 1 1 1 1 0.372 -0.028 0.010 0.060 0.025 0.117 0.023 -0.042 4 4 1 1 1 1 1 1 1 1 0.968 0.016 -0.003 -0.041 0.045 -0.018 -0.030 -0.028 5 5 1 1 1 1 1 1 1 1 -3.290 0.073 -0.093 0.096 0.018 0.011 0.010 0.004

  28. Evolution of VarBC parameters

  29. radiancemonitoring • Generally monitoring stage is necessary before new instruments enter into operational assimilation system • Two aspects • Assimilating/Monitoring mode switch on/off ability for different satellite instruments in WRF-Var for real time operation • Statistics/Visualization tool to monitor and assess observation quality

  30. radiancemonitoring - continue • namelist parameter: rad_monitoring • e.g., 10 instruments ingested into WRF-Var • rad_monitoring=0,0,0,0,0,1,1,1,1,1 • 0: assimilating mode, 5 sensors • calculate innovation (O minus B) and enter into minimization • 1: monitoring mode, 5 sensors • calculate innovation but NOT enter into minimization

  31. radiancemonitoring - continue • Radiance Post-Processing/Visualization • Output innovation and auxiliary information into ASCII files separated for CPUs • Convert ASCII files to one NETCDF file for each sensor (independent Fortran90 program), easy to manipulate with ncdump, nco, ncview tools • NCL script to plot various graphics • Channel TB, Histogram, scatter plot, time series etc. • Can be included in script to routinely produce graphics after WRF-Var runs • Users can control (by simple script parameter setup) to plot over smaller domain, only over land or sea, QCed or no-QCed observations

  32. ------ OMB before bias correction ------ OMB after bias correction

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