GSI Data Assimilation System WRF-DA Tutorial, 20-22 July, 2009, Boulder, CO Acknowledgement: NOAA, AFWA, NCAR Hui Shao, Ming Hu, Laurie Carson, Louisa Nance, Xiang-Yu Huang, Bill Kuo Developmental Testbed Center John Derber, Russ Treadon NOAA/NCEP/Environmental Modeling Center
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GSI Data Assimilation System WRF-DA Tutorial, 20-22 July, 2009, Boulder, CO Acknowledgement: NOAA, AFWA, NCAR Hui Shao, Ming Hu, Laurie Carson, Louisa.
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GSI Data Assimilation System
WRF-DA Tutorial, 20-22 July, 2009, Boulder, CO
Acknowledgement: NOAA, AFWA, NCAR
Hui Shao, Ming Hu, Laurie Carson, Louisa Nance, Xiang-Yu Huang, Bill Kuo
Developmental Testbed Center
John Derber, Russ TreadonNOAA/NCEP/Environmental Modeling Center
• NOAA/NCEP/EMC– John Derber, Jim Purser, Russ Treadon, Wan-Shu
Wu, Dave Parrish, Lidia Cucurull, Dave Parrish, Manuel Pondeca, Paul van Delst, Daryl Kleist, Xiujuan Su, Yanqiu Zhu, and others
• NASA/GMAO– Ricardo Todling, Ron Errico, Runhua Yang, Ron
Gelaro, Wei Gu, and others
• And NOAA/GSD, NCAR/MMM,…
Primary Developers
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• GSI System and Community Support (30 minutes, presented by Hui Shao)
• Installation, Running, and Diagnostics (30 minutes, presented by Ming Hu)
• To use observation, GSI simulates observation using analysis variables – observation operator (H) Can be simple interpolation to ob location/time. Can be more complex (e.g., radiation transfer).
For radiances, GSI uses CRTM.
Observation Operator (H)
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• Space correlation computed using recursive filters in horizontal and vertical
• Multivariate relation• Flow dependent variability in background error
– Background error variances modified based on 9 and 3 hour forecast differences:
• Variance increased in regions of rapid change• Variance decreased in “calm” regions • Global mean variance ~ preserved
– Being used for regional (US) surface analysis operationally.
Background Errors (B)
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Surface pressure backgrounderror standard deviation fields
Valid at 00Z November 06, 2007
HPC Surface Analysis
a) without re-scaling
b) with flow dependent re-scaling
rescaled
“as is”
L
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Option 1: univariate
• Temperature (blue) increment forces large increment in RH (shaded).
Option 2: multivariate
• Temperature (blue) increment
forces increment in q (red).
• much smaller RH (shaded)
increment.
Moisture analysis
• Improved specification of observational errors– Adaptive Tuning
Observation Errors
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After tuning
Before tuning
After tuning and smoothing
• External platform specific QC• Some gross checking in PREPBUFR file creation• Optimal interpolation quality control (OIQC) – on its way out• Analysis QC
– Gross checks – specified in input data files– Variational quality control (VarQC) – implemented
operationally in Feb 2009
Observation Quality Control
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Number of data rejected by OIQC VarQC weight (W)
• NCEP uses a two step process for Tb
– Scan angle correction – based on position– Air mass correction – based on predictors
• Predictors– mean– path length (local zenith angle determined)– integrated lapse rate– integrated lapse rate ** 2– cloud liquid water
Bias Correction of Radiance Data
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DMSP15 July2004 : 1month before bias correction after bias correction
19V
22V
19H
37V
37H
85H
85V
B-O Histogram
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Community Support
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System Implementation date
Mode
Physical SST retrieval
9/27/2005 CRTM + analytical solution
NAM (regional) 6/20/2006 3D-VAR
RTMA 8/22/2006 2D-VAR
Global 5/1/2007 3D-VAR
HWRF 6/19/2007 3D-VAR
RR Early 2010
AFWA operational
2010 or early 2011
Research Community
Goals:•Provide current operational GSI capability to the research community (O2R)•Provide a framework for distributed development of new capabilities & advances in data assimilation (R2O)
DTC
Community GSI Code
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• Free and shared resource• Ongoing distributed development by both
research and operational communities• Maintained under version control• Periodic releases made available to the
community• Includes latest developments of new
capabilities and techniques• Centralized support• Provided in collaboration with developers
Definition of Community Codes
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Tasks Timeline Note
Beta release (Q1FY09)
Jun, 2009 Friendly user only (through the GSI website)
First release (Q1FY09)
Sep, 2009
Tutorial Jun, 2010
With user support
Residential tutorial and hand-on practical session
GSI Community Release Timetable
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Success of this structure will depend on communication and collaboration among all GSI developers, users, and DTC.
User’s Guide will be updated to be consistent with each new release to the community.
GSI User’s Guide
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On-line Tutorial (Beta Release)
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On-line Documents (Beta Release)
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GSI Web Brower
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O2R2O2R2O2R2O2R2O …
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GSI: Compile
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• System required libraries – FORTRAN 90/95 compiler
– C compiler
– Perl
– netCDF
• GSI system– Download GSI system tar files (GSIbeta.tar.gz ) from
http://www.dtcenter.org/com-GSI/users/index.php
– gunzip and untar
tar –zxvf GSIbeta.tar.gz (Should see GSI/. directory )
– cd to GSI directory
cd GSI
Requirements
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makefile Top-level makefile README General information about GSI code arch/ Directory where compile options are gathered clean script to clean created files and executables compile script for compiling WRF code configure script to configure the configure.wrf file for compile sorc Directory for GSI and library source code fix/ Directory containing static/fixed data files lib/ Directory created for libraries include/ Directory created for include/module files run/ Directory for executable, and example script
• WRF_DIRWRF needs to be compiled prior to compiling GSI
GSI uses WRF I/O API libraries to do file input and output
WRF directory specified:
setenv WRF_DIR /home/user/WRFV3
• netCDFIf netCDF libraries are not located in the standard
/usr/local , thensetenv NETCDF “path for netCDF”
For LINUX systems, make sure the netCDF libraries are installed using the same compiler (PGI, Intel, g95) that will be used to compile GSI.
Set environment
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• To create a GSI configuration file for your computer:
./configure
• This script checks the system hardware and software (mostly netCDF), and then offers the user choices for configuring GSI:
Choices for 32-bit LINUX operated machines are: 1. Linux i486 i586 i686, PGI compiler 2. Linux i486 i586 i686, Intel compiler 3. Linux i486 i586 i686, gfortran compiler
Choices for IBM machines are: 1. AIX xlf compiler with xlc
Configuring GSI
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• configure.gsi – Created by the ./configure command
– contains compilation options, rules, etc.
– specific to your computer
– can be edited to change compile options, if desired.
• At this time, the IBM option is well tested. Working on Linux option test.
• The arch/configure.defaults file can be edited to add a new option if needed.
Configuring GSI, cont.
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• To compile:./compile >& compile_gsi.log
• To get compile help message:./compile -h
• If the compilation is successful, it will create one executable under bin/:
gsi.exe
Compiling GSI
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• To remove all object files and executables./clean
• To remove all built files, including configure.gsi./clean –a
Clean is recommended if compilation failed want to change configuration file
Clean Compilation
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Running GSIUser’s Guide: Chapter 3
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• GSI Executable
• Background (first guess) file
• Observations– Not needed for single observation experiment
• Fixed files (within GSI package)
• Run script (namelist included)
To run GSI, you need:
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• GSI can use– WRF NMM input file in binary format– WRF NMM input file in netcdf format– WRF ARW input file in binary format– WRF ARW input file in netcdf format– GFS input file in binary format– GMAO global model input file in binary format
• DTC has only tested regional analysis with WRF input– On IBM: both binary and nedcdf format– On Linux: netcdf format only
Background
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• All observations have to be in BUFR format
• prepbufr: NCEP flavor BUFR – Need NCEP BUFR library
Observation
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• Collection of statistic and control files under fix directory– Background and observation errors
• berror_stats, errtable
– Observation data control file (info files)• convinfo , satinfo
– Bias correction used by radiance analysis • satbias_angle, satbias_in
– Radiance coefficient used by CRTM • EmisCoeff.bin, CloudCoeff.bin
Fixed files
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– Ask for computer resources to run GSI– Set environment variables for the machine
– Set experiments variables (experiment name, analysis time, background and observation)
– Check the definition of required variables
– Generate a run directory for GSI (working or temp directory)
– Copy GSI executable to run directory– Copy background file to run directory– Copy or link observations to run directory– Copy fixed files to run directory– Generate namelist for GSI
– Run the GSI executable
– Save the GSI analysis results
Run script - structure
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# analysis time (YYYYMMDDHH)
ANAL_TIME=2008051112
# working direcotry, where GSI runs
WORK_ROOT=./gsi/case
# path and name of background file BK_FILE=./2008051112/bkARW/wrfout_d01_2008-05-11_12:00:00
• First place to look after any GSI run– If successful
• Data distribution• Optimal iteration• Maximum and minimum of analysis fields
– If fails, • which part of GSI has problem• what is the possible reason for failure
Standard out file - stdout
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• read in all data and prepare analysis:– read in configuration (namelist)– read in background– read in constant file (fixed file)– read in observation– partition background and observation data for