Radiance Data Assimilation in WRF-Var

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

Please see other related detailed tutorial presentations available at

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.incda_allocate_rad_iv.inc da_print_stats_rad.inc da_transform_xtoy_crtm.incda_ao_stats_rad.inc da_qc_airs.inc da_transform_xtoy_crtm_adj.incda_biascorr.inc da_qc_amsua.inc da_transform_xtoy_rttov.incda_biasprep.inc da_qc_amsub.inc da_transform_xtoy_rttov_adj.incda_calculate_grady_rad.inc da_qc_crtm.inc da_write_biasprep.incda_cld_eff_radius.inc da_qc_hirs.inc da_write_filtered_rad.incda_cloud_detect_airs.inc da_qc_mhs.inc da_write_iv_rad_ascii.incda_cloud_sim_airs.inc da_qc_rad.inc da_write_oa_rad_ascii.incda_crtm.f90 da_qc_ssmis.inc ehv2pem.incda_crtm_ad.inc da_radiance.f90 emiss_ssmi.incda_crtm_direct.inc da_radiance1.f90 gsi_constants.f90da_crtm_init.inc da_radiance_init.inc gsi_emiss.incda_crtm_k.inc da_read_biascoef.inc gsi_kinds.f90da_crtm_sensor_descriptor.inc da_read_filtered_rad.inc gsi_thinning.f90da_crtm_tl.inc da_read_kma1dvar.inc iceem_amsu.incda_detsurtyp.inc da_read_obs_bufrairs.inc init_constants_derived.incda_get_innov_vector_crtm.inc da_read_obs_bufrssmis.inc inria_n2qn1.incda_get_innov_vector_crtmk.inc da_read_obs_bufrtovs.inc landem.incda_get_innov_vector_radiance.inc da_read_pseudo_rad.inc module_radiance.f90da_get_innov_vector_rttov.inc da_residual_rad.inc ossmem.incda_get_julian_time.inc da_rttov.f90 seaem.incda_get_time_slots.inc da_rttov_ad.inc siem_ats.incda_initialize_rad_iv.inc da_rttov_direct.inc siem_bts.incda_jo_and_grady_rad.inc da_rttov_init.inc siem_interpolate.incda_oi_stats_rad.inc da_rttov_tl.inc snwem_amsu.incda_predictor_crtm.inc da_setup_radiance_structures.inc

Basic Concepts: Radiative Transfer

AMSUA

• Temperature information derived from

well-mixed absorbents (CO2, …)

• Channels sensitive to Humidity, Ozone, …

• Surface channels: “window” parts of spectrum

dzdz

dzTBL ∫

∞

⎥⎦

⎤⎢⎣

⎡=0

)())(,()(

ντνν + Surface + Cloud/rain

TOA radiance

at frequency ν

Planck function Atmospheric

absorption

Emission/reflection Diffusion/scattering

Basic Concepts: Radiative Transfer

dzdz

dzTBL ∫

∞

⎥⎦

⎤⎢⎣

⎡=0

)())(,()(

ντνν + Surface + Cloud/rain

TOA radiance

at frequency ν

Planck function Atmospheric

absorption

Emission/reflection Diffusion/scattering

RTRT

T, Q, O3, … Forward model

Inversion

L(ν)

CRTM, RTTOV, …

Regression, neural network, 1D-Var

AMSU-B 89GHz-150GHz Tb < 3K

CLWP(mm)from Guess<0.2mm

Katrina Location (2005/08/26/06Z)

• 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– Gross check (innovations <15 K)

– First-guess check (innovations < 3o).

• Observation error tuning– Error factor tuned from objective method

(Desrozier and Ivanov, 2001)

Practical issues: Quality Control

Modeling of errors in satellite radiances:

y =H(xt) + B(β) + εB(β) = βipi

i=1

N

∑

0=εPredictors:

• Offset• 1000-300mb thickness • 200-50mb thickness• Surface skin temperature• Total column water vapor• Scan

Parameters

Practical issues: Bias Correction

Scan Bias = d(limb) - d(nadir)– d(.) is departure (omb or oma)– This is relative bias between

limb and nadir

Air Mass Bias + Scan Bias

J(x,β) =(xb −x)TBx−1(xb −x) + y−H(x)−B(β)[ ]

T R−1 y−H(x)−B(β)[ ]

+ (βb −β)TBβ−1(βb −β)

Jb: background term for x

Jβ: background term for β

Jo: corrected observation term

«Optimal » bias correction considering all available information«Optimal » bias correction considering all available information

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, β]T

y =H(xt) + B(β) + εB(β) = βipi

i=1

N

∑

0=εPredictors:

• Offset• 1000-300mb thickness • 200-50mb thickness• Surface skin temperature• Total column water vapor• Scan

ParametersModeling of errors in satellite radiances:

Practical issues: Variational Bias Correction

No Thinning 120km Thinning Mesh

Practical issues: Thinning

• Data Ingest (sources, instruments, Tb, Ta)

• Radiative transfer model

• Channel selection

• Bias correction

— Off-line bias correction statistics

— Variational bias correction

• Diagnostics and monitoring

• 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.

Data Ingest

• 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

Data Processing

NCEP BUFRftp://ftp.ncep.noaa.gov/pub/data/nccf/com/gfs/prod/gdas.${yyyymmddhh}

gdas1.t00z.1bamua.tm00.bufr_dgdas1.t00z.1bamub.tm00.bufr_dgdas1.t00z.1bhrs3.tm00.bufr_dgdas1.t00z.1bhrs4.tm00.bufr_dgdas1.t00z.1bmhs.tm00.bufr_dgdas1.t00z.airsev.tm00.bufr_dgdas1.t00z.airs.tm00.bufr_d

amsua.buframsub.bufrhirs3.bufrhirs4.bufrmhs.bufrairs.bufrssmis.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 notUse_amsuaobsUse_amsubobsUse_hirs3obsUse_hirs4obsUse_mhsobsUse_airsobsUse_eos_amsuaobsUse_ssmisobs

NCEP naming convention WRF-Var naming convention

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.

Radiative Transfer Model

Fromhttp://www.metoffice.gov.uk/research/interproj/nwpsaf/rtm/rttov8_description.html

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

Channel selection

Channels 10~14 above model top removed

Window Channels(1~3,15) not used

Sounding Channels(5~9) sensitive toTemperature.

Ch4: 700mbCh5: 500~700mbCh6: 400~500mbCh7: 200~300mb

Ch8: 200mbCh9: 100mbCh10: 50mbCh11: 30mb

WRFDA/var/run/radiance_info>ls -ltotal 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

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

Channel selection

metop-2-mhs.info

Setup and run - with radiances

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.TBLln -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.bufrln -sf $RADIANCE_INFO_DIR ./radiance_infoln -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

From RTTOV_8_7 Users Guidehttp://www.metoffice.gov.uk/research/interproj/nwpsaf/rtm/rttov8_ug.pdf

platform_id satellite_id

sensor_idInstrument triplets platform_id

satellite_idsensor_id

RTMINIT_NSENSOR = 12RTMINIT_PLATFORM = 1, 1, 1, 9,10, 1, 1, 1, 1,10, 9, 2RTMINIT_SATID = 15,16,18, 2, 2,15,16,17,18, 2, 2,16RTMINIT_SENSOR = 3, 3, 3, 3, 3, 4, 4, 4,15,15,11,10

NOAA-15-AMSUANOAA-16-AMSUANOAA-18-AMSUAEOS-2-AMSUAMETOP-2-AMSUANOAA-15-AMSUBNOAA-16-AMSUBNOAA-17-AMSUBNOAA-18-MHSMETOP-2-MHSEOS-2-AIRSDMSP-16-SSMIS

namelist.input

RAD_MONITORING (30) Integer array with dimension RTMINIT_NSENSER, where 0 for assimilating mode, 1 for monitoring mode (only calculate innovation).

THINNINGLogical, TRUE will perform thinning

THINNING_MESH (30)Real array with dimension RTMINIT_NSENSOR, values indicate thinning mesh (in KM) for different sensors.

READ_BIASCOEFLogical, control if reading bias correction coefficient files (Harris and Kelly scheme), always set to TRUE.

BIASCORRLogical, control if perform bias correction (Harris and Kelly scheme).

BIASPREPLogical, control if perform bias correction preparation (Harris and Kelly scheme).

QC_RADLogical, control if perform quality control, always set to TRUE.

WRITE_IV_RAD_ASCIILogical, control if output Observation minus Background files, which are ASCII format and separated by sensors and processors.

WRITE_OA_RAD_ASCIILogical, 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_RADLogical, 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_RADLogical, control if only assimilating radiance over water.

TIME_WINDOW_MINString, e.g., "2007-08-15_03:00:00.0000", start time of assimilation time window

TIME_WINDOW_MAXString, e.g., "2007-08-15_09:00:00.0000", end time of assimilation time window

rttov_coefs>ls -ltotal 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

RTTOV coefficients

CRTM_02-29-08/CRTM_Coeffs>ls -ldrwxr-xr-x 5 wrfhelp users 512 Mar 5 2008 AerosolCoeffdrwxr-xr-x 5 wrfhelp users 512 Mar 5 2008 CloudCoeffdrwxr-xr-x 5 wrfhelp users 512 Mar 5 2008 EmisCoeffdrwxr-xr-x 4 wrfhelp users 512 Mar 5 2008 SpcCoeffdrwxr-xr-x 5 wrfhelp users 512 Mar 5 2008 TauCoeff

CRTM_02-29-08/CRTM_Coeffs/SpcCoeff>ls -ldrwxr-xr-x 5 wrfhelp users 512 Dec 3 2007 Infrareddrwxr-xr-x 5 wrfhelp users 512 Dec 3 2007 Microwave

CRTM_02-29-08/CRTM_Coeffs/SpcCoeff/Microwave>ls -ldrwxr-xr-x 5 wrfhelp users 512 Dec 3 2007 AAPP_ACdrwxr-xr-x 5 wrfhelp users 512 Dec 3 2007 NESDIS_ACdrwxr-xr-x 5 wrfhelp users 512 Feb 25 2008 No_AC

CRTM_02-29-08/CRTM_Coeffs/SpcCoeff/Microwave/No_AC>ls -ldrwxr-xr-x 2 wrfhelp users 1536 Dec 3 2007 Big_Endiandrwxr-xr-x 2 wrfhelp users 1536 Dec 3 2007 Little_Endiandrwxr-xr-x 2 wrfhelp users 1536 Feb 13 2008 netCDF

CRTM_02-29-08/CRTM_Coeffs/SpcCoeff/Microwave/No_AC/Big_Endian>ls -ltotal 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

CRTM coefficients

Link selected files from various source directories into single directory then link it ascrtm_coeffs in the WRF-Var working directory

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.

Off-line bias correction statistics (Harris and Kelly, 2001)

Step 1: generate 'biasprep' files by running WRF-Var

Step 2: off-line statistics

• 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 GFS

analysis 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.

biascorr 139 > ls -ltotal 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

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 109.53830RELATIVE 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 correctioncolumn 1: 1000-300mb thickness

column 2: 200-50mb thickness

column 3: Surface skin temperature

column 4: Total column water vapor

column 5: offset

Variational Bias Correction (VarBC)

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

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: 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

Sample VARBC.out (VARBC.in)

Evolution of VarBC parameters

radiance monitoring

• 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

• 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

radiance monitoring - 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

radiance monitoring - continue

------ OMB before bias correction------ OMB after bias correction