November 21 st 2002 Summer 2009 WRFDA Tutorial WRF-Var System Overview Xin Zhang, Yong-Run Guo, Syed R-H Rizvi, and Michael Duda.

Slides:



Advertisements
Similar presentations
Assimilation of radar data - research plan
Advertisements

Page 1 of 26 A PV control variable Ross Bannister* Mike Cullen *Data Assimilation Research Centre, Univ. Reading, UK Met Office, Exeter, UK.
Weather Research & Forecasting: A General Overview
SOFTWARE TESTING. INTRODUCTION  Software Testing is the process of executing a program or system with the intent of finding errors.  It involves any.
Assimilation Algorithms: Tangent Linear and Adjoint models Yannick Trémolet ECMWF Data Assimilation Training Course March 2006.
Y.-R. Guo WRFVar code development Tangent Linear and Adjoint Code Development Yong-Run Guo 1 National Center for Atmospheric Research.
© Crown copyright Met Office Does the order of the horizontal and vertical transforms matter in the representation of an operational static covariance.
The Climate Prediction Center Rainfall Estimation Algorithm Version 2 Tim Love -- RSIS/CPC.
5/22/201563rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL Experiments of Hurricane Initialization with Airborne Doppler.
WRFDA 2012 Overview and Recent Adjoint-based Observation Impact Studies Hans Huang National Center for Atmospheric Research (NCAR is sponsored by.
1/20 Accelerating minimizations in ensemble variational assimilation G. Desroziers, L. Berre Météo-France/CNRS (CNRM/GAME)
Advanced data assimilation methods with evolving forecast error covariance Four-dimensional variational analysis (4D-Var) Shu-Chih Yang (with EK)
Bill Campbell and Liz Satterfield Naval Research Laboratory, Monterey CA Presented at the AMS Annual Meeting 4-8 January 2015 Phoenix, AZ Accounting for.
This is the footer Running WRF on HECToR Ralph Burton, NCAS (Leeds) Alan Gadian, NCAS (Leeds) With thanks to Paul Connolly, Hector.
A comparison of hybrid ensemble transform Kalman filter(ETKF)-3DVAR and ensemble square root filter (EnSRF) analysis schemes Xuguang Wang NOAA/ESRL/PSD,
- differences between V2.2-beta and V3 - setup and run
Implementation of 2D FDTD
Understanding the 3DVAR in a Practical Way
Introduction to the WRF Modeling System Wei Wang NCAR/MMM.
3D-Var Revisited and Quality Control of Surface Temperature Data Xiaolei Zou Department of Meteorology Florida State University June 11,
Multimodal Interaction Dr. Mike Spann
MIIDAPS Status – 13 th JCSDA Technical Review and Science Workshop, College Park, MD Quality Control-Consistent algorithm for all sensors to determine.
Different options for the assimilation of GPS Radio Occultation data within GSI Lidia Cucurull NOAA/NWS/NCEP/EMC GSI workshop, Boulder CO, 28 June 2011.
Computational Issues: An EnKF Perspective Jeff Whitaker NOAA Earth System Research Lab ENIAC 1948“Roadrunner” 2008.
Potential benefits from data assimilation of carbon observations for modellers and observers - prerequisites and current state J. Segschneider, Max-Planck-Institute.
The recent developments of WRFDA (WRF-Var) Hans Huang, NCAR WRFDA: WRF Data Assimilation WRF-Var: WRF Variational data assimilation Acknowledge: NCAR/ESSL/MMM/DAG,
Resources applied to WRF 3DVAR NCAR0.75 FTE, split among 1-3 people FSL0.50 FTE, mostly Devenyi CAPS0.80 FTE, 1-2 people NCEP1.30 FTE, Wan-shu Wu (1.0)
Hybrid Variational/Ensemble Data Assimilation
Ming Hu Developmental Testbed Center Introduction to Practice Session 2011 GSI Community Tutorial June 29-July 1, 2011, Boulder, CO.
DoD Center for Geosciences/Atmospheric Research at Colorado State University WSMR November 19-20, 2003 ARMY Research Lab and CIRA/CSU Collaboration on.
University of Colorado Boulder ASEN 5070: Statistical Orbit Determination I Fall 2014 Professor Brandon A. Jones Lecture 18: Minimum Variance Estimator.
Ensemble Kalman Filters for WRF-ARW Chris Snyder MMM and IMAGe National Center for Atmospheric Research Presented by So-Young Ha (MMM/NCAR)
Installing and Running the WPS Michael Duda 2006 WRF-ARW Summer Tutorial.
Potential Benefits of Multiple-Doppler Radar Data to Quantitative Precipitation Forecasting: Assimilation of Simulated Data Using WRF-3DVAR System Soichiro.
240-Current Research Easily Extensible Systems, Octave, Input Formats, SOA.
Data assimilation and forecasting the weather (!) Eugenia Kalnay and many friends University of Maryland.
WRF Four-Dimensional Data Assimilation (FDDA) Jimy Dudhia.
6/29/2010 Wan-Shu Wu1 GSI Tutorial 2010 Background and Observation Error Estimation and Tuning.
Oct WRF 4D-Var System Xiang-Yu Huang, Xin Zhang Qingnong Xiao, Zaizhong Ma, John Michalakes, Tom henderson and Wei Huang MMM Division National.
© Crown copyright Met Office The EN4 dataset of quality controlled ocean temperature and salinity profiles and monthly objective analyses Simon Good.
Introduction on WRF-Var Regression Test Ruifang Li MMM Phone:
NCEP ESMF GFS Global Spectral Forecast Model Weiyu Yang, Mike Young and Joe Sela ESMF Community Meeting MIT, Cambridge, MA July 21, 2005.
BE, gen_be and Single ob experiments Syed RH Rizvi National Center For Atmospheric Research NCAR/MMM, Boulder, CO-80307, USA Syed.
July, 2009 WRF-Var Tutorial Syed RH Rizvi 0 WRFDA Background Error Estimation Syed RH Rizvi National Center For Atmospheric Research NCAR/ESSL/MMM, Boulder,
PROGRAMMING TESTING B MODULE 2: SOFTWARE SYSTEMS 22 NOVEMBER 2013.
MIIDAPS Application to GSI for QC and Dynamic Emissivity in Passive Microwave Data Assimilation.
NCAR April 1 st 2003 Mesoscale and Microscale Meteorology Data Assimilation in AMPS Dale Barker S. Rizvi, and M. Duda MMM Division, NCAR
0 0 July, 2009 WRF-Var Tutorial Syed RH Rizvi WRFDA Analysis/Forecast Verification Syed RH Rizvi National Center For Atmospheric Research NCAR/ESSL/MMM,
Installing and Running the WPS Michael Duda 2006 WRF-ARW Summer Tutorial.
Slide 1 NEMOVAR-LEFE Workshop 22/ Slide 1 Current status of NEMOVAR Kristian Mogensen.
Ligia Bernardet NOAA ESRL Global Systems Division, Boulder CO University of Colorado CIRES, Boulder CO HWRF Initialization Overview 1 HWRF v3.5a Tutorial.
Ensemble forecasting/data assimilation and model error estimation algorithm Prepared by Dusanka Zupanski and Milija Zupanski CIRA/CSU Denning group meeting.
École Doctorale des Sciences de l'Environnement d’ Î le-de-France Année Modélisation Numérique de l’Écoulement Atmosphérique et Assimilation.
1 Data assimilation developments for NEMO  A working group was created at the 2006 Developers Meeting with the objective of standardizing for NEMO certain.
Hernán García CeCalcULA Universidad de los Andes.
June 20, 2005Workshop on Chemical data assimilation and data needs Data Assimilation Methods Experience from operational meteorological assimilation John.
Recent data assimilation activities at the Hungarian Meteorological Service Gergely Bölöni, Edit Adamcsek, Alena Trojáková, László Szabó ALADIN WS /
ECMWF/EUMETSAT NWP-SAF Satellite data assimilation Training Course
WRF Four-Dimensional Data Assimilation (FDDA)
In-situ Visualization using VisIt
Run WRF 3D-VAR Shu-hua Chen1 and Dale Barker2
HWRF Initialization Overview
Winter storm forecast at 1-12 h range
Assimilating Tropospheric Emission Spectrometer profiles in GEOS-Chem
Local Analysis and Prediction System (LAPS)
Initialization of Numerical Forecast Models with Satellite data
EnKF Fundamentail 2a: Diagnostics
Impact of Assimilating AMSU-A Radiances on forecasts of 2008 Atlantic TCs Initialized with a limited-area EnKF Zhiquan Liu, Craig Schwartz, Chris Snyder,
Sarah Dance DARC/University of Reading
EnKF Fundamentail 2a: Diagnostics
Presentation transcript:

November 21 st 2002 Summer 2009 WRFDA Tutorial WRF-Var System Overview Xin Zhang, Yong-Run Guo, Syed R-H Rizvi, and Michael Duda

November 21 st 2002 Summer 2009 WRFDA Tutorial1 Outline 1. WRF-Var in the WRF Modeling System 2. WRF-Var Software 3. WRF-Var Implementation

November 21 st 2002 Summer 2009 WRFDA Tutorial2 WRF-Var in the WRF Modeling System

November 21 st 2002 Summer 2009 WRFDA Tutorial3 WRF-Var in the WRF Modeling System Blue --> Supported by WRF-Var Team WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial4 Blue --> Supported by WRF-Var Team 1. Prepare BE data WRF-Var in the WRF Modeling System Background Error (gen_be) B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial5 Prepare BE statistics J(x) = (x - x b ) T B -1 (x - x b ) + (y o - Hx) T R -1 (y o - Hx)  For initial testing, default background error statistics may be used  be.dat file (CV option 5) from test case tar file can only be used with the domain from online tutorial  be.dat.cv3 (CV option 3) from source code tar file can be used for general test domains  Ultimately, these should be specific to the particular model domain (and season)

November 21 st 2002 Summer 2009 WRFDA Tutorial6 2. Prepare background (WPS and real) WRF-Var in the WRF Modeling System Background Error (gen_be) xbxb Background Preprocessing (WPS, real) x lbc B0B0 Cold-Start Background WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial7 Prepare background J(x) = (x - x b ) T B -1 (x - x b ) + (y o - Hx) T R -1 (y o - Hx)  In “cold-start” mode: accomplished by running the WPS and real programs  The background is essentially the wrfinput_d01 file  In “cycling” mode: the output of the WRF model  WRF can output wrfinput-formatted files used for cycling

November 21 st 2002 Summer 2009 WRFDA Tutorial8 Blue --> Supported by WRF-Var Team 3. Prepare observations (run OBSPROC) WRF-Var in the WRF Modeling System Background Error (gen_be) xbxb Background Preprocessing (WPS, real) x lbc B0B0 y o, R Cold-Start Background Radar in ASCII Radiance in BUFR Observation Preprocessing (OBSPROC) WRF-Var Note: Radar and radiance data do not pass through the OBSPROC program!

November 21 st 2002 Summer 2009 WRFDA Tutorial9  Observation input for WRF-Var is supplied through observation preprocessor, OBSPROC  Except radar and satellite radiances  Observation error covariance also provided by OBSPROC (R is a diagonal matrix)  Separate input file (ASCII) for radar, both reflectivity and radial velocity.  Separate input file for satellite radiances Prepare observations (y 0 ) J(x) = (x - x b ) T B -1 (x - x b ) + ( y o - Hx) T R -1 ( y o - Hx)

November 21 st 2002 Summer 2009 WRFDA Tutorial10 Blue --> Supported by WRF-Var Team 4. Run WRF-Var WRF-Var in the WRF Modeling System Background Error (gen_be) xbxb xaxa Background Preprocessing (WPS, real) x lbc B0B0 y o, R Cold-Start Background Radar in ASCII Radiance in BUFR Observation Preprocessing (OBSPROC) WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial11 Blue --> Supported by WRF-Var Team 5. Update boundary conditions (UPDATE_BC) WRF-Var in the WRF Modeling System Background Error (gen_be) xbxb xaxa Update Lateral & Lower BCs (UPDATE_BC) Background Preprocessing (WPS, real) x lbc B0B0 y o, R Cold-Start Background Radar in ASCII Radiance in BUFR Observation Preprocessing (OBSPROC) WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial12 Update boundary conditions  After creating an analysis, x a, we have changed the initial conditions for the model  However, tendencies in wrfbdy_d01 (and possibly wrflbdy ) file are valid for background, x b  The update_bc program adjusts these tendencies based on the difference x a - x b  Of course, if x a was produced for reasons other than running WRF, there is probably not a need to update boundary conditions

November 21 st 2002 Summer 2009 WRFDA Tutorial13 Blue --> Supported by WRF-Var Team 6a. Run forecast (cold-start mode) WRF-Var in the WRF Modeling System Background Error (gen_be) Forecast (WRF) xbxb xaxa Update Lateral & Lower BCs (UPDATE_BC) Background Preprocessing (WPS, real) x lbc B0B0 y o, R Cold-Start Background Radar in ASCII Radiance in BUFR Observation Preprocessing (OBSPROC) WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial14 WRF-Var in the WRF Modeling System Note the arrow from ARW MODEL to WRF-Var!

November 21 st 2002 Summer 2009 WRFDA Tutorial15 Blue --> Supported by WRF-Var Team 6b. Run forecast (cycling mode) WRF-Var in the WRF Modeling System Background Error (gen_be) Forecast (WRF) xbxb xaxa Update Lateral & Lower BCs (UPDATE_BC) Background Preprocessing (WPS, real) x lbc Cycled Background B0B0 y o, R Radar in ASCII Radiance in BUFR xfxf Observation Preprocessing (OBSPROC) WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial16 Background Error (BE) for WRF-Var One important question from WRF-Var users is “What background errors are best for my application?” Create your own once you have run your system for a few weeks to a month Implement, tune, and iterate The utility gen_be has been developed at NCAR for use in calculating these BEs

November 21 st 2002 Summer 2009 WRFDA Tutorial17 Blue --> Supported by WRF-Var Team 7. WRF-Var/WRF Ultimate Configuration WRF-Var in the WRF Modeling System Background Error (gen_be) Forecast (WRF) xbxb xaxa Update Lateral & Lower BCs (UPDATE_BC) Background Preprocessing (WPS, real) x lbc Cycled Background B0B0 y o, R Cold-Start Background Radar in ASCII Radiance in BUFR xfxf Observation Preprocessing (OBSPROC) WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial18 WRF-Var Software

November 21 st 2002 Summer 2009 WRFDA Tutorial19 Use of the WRF Software Framework WRF-Var relies on the WRF Software framework for – Distributed memory parallelism (halo exchanges, etc.) – Input/Output of first guess and analysis files – Parallel transposes WRF-Var also uses – The WRF Registry mechanism to handle definitions of fields, halos, and transposes – The WRF build system (clean, configure, compile)

November 21 st 2002 Summer 2009 WRFDA Tutorial20 WRF-Var Code Organization Besides the directories for WRF, the WRFDA tar file contains a “var” directory, which holds all of the WRF-Var code

November 21 st 2002 Summer 2009 WRFDA Tutorial21 WRF-Var Code Organization Generally, each subdirectory of “da” contains a Fortran module with the same name

November 21 st 2002 Summer 2009 WRFDA Tutorial22 WRF-Var Code Organization da_metar.f90 contains a Fortran module Each.inc file corresponds to a subroutine within the module

November 21 st 2002 Summer 2009 WRFDA Tutorial23 WRF-Var Implementation

November 21 st 2002 Summer 2009 WRFDA Tutorial24 WRF-Var Formulation  WRF-Var actually uses an incremental formulation of the 3DVAR problem  Define the increment x’ = x - x b  Also, if x’ is small, H(x) = H(x b + x’) ≈ H(x b ) + Hx’ where H is the linearization of H  Then, the problem becomes with y o’ = y o - H(x b ) J(x) = (x - x b ) T B -1 (x - x b ) + (y o - H(x)) T R -1 (y o - H(x)) J(x’) = (x’) T B -1 (x’) + (y o ’ - Hx’) T R -1 (y o ’ - Hx’)

November 21 st 2002 Summer 2009 WRFDA Tutorial25 WRF-Var Formulation  Next, define the control variable transform U such that x’ = Uv.  v is the analysis increment in control variable space  B is approximated by UU T  WRF-Var actually minimizes  After minimization, the analysis, x a, is given by J(v) = v T v + (y o ’ - HUv) T R -1 (y o ’ - HUv) x a = x b + Uv

November 21 st 2002 Summer 2009 WRFDA Tutorial26 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial27 Reads grid dimensions from “namelist.input” file. Use WRF framework’s distributed memory capability to initialize tile, memory, patch dimensions, etc. Setup Frame

November 21 st 2002 Summer 2009 WRFDA Tutorial28 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial29 Reads WRF-Var data assimilation options from “namelist.input” file. Performs consistency checks between namelist options. Read Namelist

November 21 st 2002 Summer 2009 WRFDA Tutorial30 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial31 Reads in the first-guess field. Format depends on namelist option : “fg_format” ; 1= WRF, etc. Extracts necessary fields. Creates background FORTRAN 90 derived data type “xb” e.g. xb % mix, xb % u(:,:,:), …. Setup Background (First-guess)

November 21 st 2002 Summer 2009 WRFDA Tutorial32 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial33 Reads in background error statistics. Extracts necessary quantities – eigenvectors, eigenvalues, lengthscales, regression coefficients, etc (see “WRF-Var Background Error Estimation”). Creates background error FORTRAN 90 derived data type “be” – e.g. be % v1 % evec(:,:), be % v2 % eval(:), etc, …. Setup Background Errors (BE)

November 21 st 2002 Summer 2009 WRFDA Tutorial34 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial35 Reads in observations. Format depends on namelist variable “ob_format” 1 = BUFR, 2 = ASCII “WRF-Var” format. Creates observation FORTRAN 90 derived data type “ob” – e.g. ob % metar(:), ob % sound(:) % u(:), etc, …. Identifies Obs outside/inside the domain Setup Observations

November 21 st 2002 Summer 2009 WRFDA Tutorial36 Obs. on one processor’s halo Obs. on neighboring processor * Observations in Distributed Memory Halo Region Observation For global option obs. on East and West boundaries are duplicated

November 21 st 2002 Summer 2009 WRFDA Tutorial37 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial38 Calculates “model equivalent” B of observation O through interpolation and change of variable. Computes observation minus first guess (O-B) value. Creates innovation vector FORTRAN 90 derived data type “iv” – e.g. iv % metar(:), iv % qscat(:) % u, iv % sound(:) % u(:), etc …. Calculate Innovation Vector (O-B)

November 21 st 2002 Summer 2009 WRFDA Tutorial39 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial40 Use conjugate gradient method (a) Initializes analysis increments to zero. (b) Computes cost function (if desired). (c) Computes gradient of cost function. (d) Uses cost function and gradient to calculate new value of analysis control variable, v Iterate (b) to (d) Minimize Cost Function

November 21 st 2002 Summer 2009 WRFDA Tutorial41 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial42 Once WRF-Var has found a converged control variable, convert control variable to model space analysis increments Calculate: analysis = first-guess + analysis increment Performs consistency checks, e.g., remove negative humidity etc. Compute Analysis

November 21 st 2002 Summer 2009 WRFDA Tutorial43 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial44 Compute O-B, O-A statistics for all observation types and variables. Compute A-B (analysis increment) statistics for all model variables and levels. Statistics include minimum, maximum (and their locations), mean and standard deviation. Compute Diagnostics

November 21 st 2002 Summer 2009 WRFDA Tutorial45 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial46 Outputs analysis in native model format. Choice is made through namelist option “fg_format” 1 = WRF, etc. Also output analysis increments (for diagnostic purposes) in native model format. Switch off by setting WRITE_INCREMENTS =.FALSE. in namelist.input. Output Analysis

November 21 st 2002 Summer 2009 WRFDA Tutorial47 Read Namelist xbxb xaxa yoyo Compute Analysis Calculate O-B Setup Frame Setup Background Setup Background Errors Minimize Cost Function Setup Observations Calculate Diagnostics Output Analysis Diagnostics File Namelist File Tidy Up WRF-Var START WRF-Var END “Outer Loop” B0B0 WRF-Var

November 21 st 2002 Summer 2009 WRFDA Tutorial48 Deallocate dynamically-allocated arrays, structures, etc. Timing information. Clean end to WRF-Var. Tidy Up

November 21 st 2002 Summer 2009 WRFDA Tutorial49 WRFDA has a dedicated page, similar to the ARW Users’ page: Online WRFDA Resources

November 21 st 2002 Summer 2009 WRFDA Tutorial50 From the WRFDA page, one can access: Online WRFDA Resources

November 21 st 2002 Summer 2009 WRFDA Tutorial51 Online WRF-Var Tutorial – WRF-Var chapter of Users’ Guide – uide_chap6.htm If further help is needed, try the WRF Users’ Forum or ask questions via Other WRFDA Resources

November 21 st 2002 Summer 2009 WRFDA Tutorial52 Questions?