radiance data assimilation in wrf-var satellite data
Post on 18-Jan-2016
362 Views
Preview:
TRANSCRIPT
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
top related