The WRF Variational Data Assimilation System (WRF-Var)

1. Introduction

Data assimilation is the technique by which observations are combined with an NWP product (the first guess or background forecast) and their respective error statistics to provide an improved estimate (the analysis) of the atmospheric (or oceanic, Jovian, whatever) state. Variational (Var) data assimilation achieves this through the iterative minimization of a prescribed cost (or penalty) function. Differences between the analysis and observations/first guess are penalized (damped) according to their perceived error. The difference between three-dimensional (3D-Var) and four-dimensional (4D-Var) data assimilation is the use of a numerical forecast model in the latter.

MMM Division of NCAR supports a unified (global/regional, multi-model, 3/4D-Var) model-space variational data assimilation system (WRF-Var) for use by NCAR staff and collaborators, and is also freely available to the general community, together with further documentation, test results, plans etc., from the WRF-Var web-page http://www.mmm.ucar.edu/wrf/WG4/wrfvar/wrfvar.htm. The documentation you are reading is the "Users Guide" for those interested in downloaded and running the code. This text also forms the documentation for the online tutorial. The online WRF-Var tutorial is recommended for people who are

·       Potential users of WRF-Var who want to learn how to run WRF-Var by themselves;

 

·       New users who plan on coming to the NCAR WRF-Var tutorial - for you we recommend that you try this tutorial before you come to NCAR whether you are able or unable to register for practice sessions, and this will hopefully help you to understand the lectures a lot better;

 

·       Users who are looking for references to diagnostics, namelist options etc - look for 'Miscellanies' and 'Trouble Shooting' sections on each page.

If you are a new WRF-Var user, this tutorial is designed to take you through WRF-Var-related programs step by step. If you have familiar with 3/4D-Var systems, you may find useful information here too as the WRF-Var implementation of 3/4D-Var contains a number of unique capabilities (e.g. multiple background error models, WRF-framework based parallelism/IO, direct radar reflectivity assimilation). If you don't know anything about 3D-Var, you should first read the WRF-Var tutorial presentations available from the WRF-Var web-page http://www.mmm.ucar.edu/wrf/WG4/wrfvar/wrfvar.htm.

Goals Of This WRF-Var Tutorial

In this WRF-Var tutorial, you will learn how to run the various components of the WRF-Var system. In the online tutorial, you are supplied with a test case including the following input data: a) observation file, b) WRF NETCDF background file (previous forecast used as a first guess of the analysis), and c) Background error statistics (climatological estimate of errors in the background file). In your own work, you will need to create these two input files yourselves.

The components of the WRF-Var system are shown in blue in the sketch below, together with their relationship with rest of the WRF system.

Before using your own data, we suggest that you start by running through the WRF-Var related programs at least once using the supplied test case. This serves two purposes: First you can learn how to run the programs with data we have tested ourselves, and second you can test whether your computer is adequate to run the entire modeling system. After you have done this tutorial, you can try

 

 

 

As a professional courtesy, we request that you include the following reference in any publications that makes use of any component of the community WRF-Var system:

 

Barker, D. M., W. Huang, Y. R. Guo, and Q. N. Xiao., 2004: A Three-Dimensional (3DVAR) Data Assimilation System For Use With MM5: Implementation and Initial Results. Mon. Wea. Rev., 132, 897-914.

As you are going through the online tutorial, you will download program tar files and data to your local computer, compile and run on it. Do you know what machine you are going to use to run WRF-Var related programs? What compilers do you have on the machine?

Running WRF-Var requires a Fortran 90 compiler. We currently support the following platforms: IBM, DEC, SGI, PC/Linux (with Portland Group compiler), Cray-X1, and Apple G4/G5. Please let us know if this does not meet your requirements, and we will attempt to add other machines to our list of supported architectures as resources allow. Although we're interested to hear of your experiences modifying compile options, we do not yet recommend making changes to the configure file used to compile WRF-Var.

Tutorial Schedule

We recommend you follow the online tutorial in the order of the sections listed below. This tutorial does not cover parts of the larger WRF system, required if you wish to go beyond the test case supplied here, e.g. the WRF Standard Initialization (SI) and real pre-preprocessors are needed to create your own background field.

The online tutorial is broken down into the following sections.

a)             Download Test Data: This page describes how to access test datasets to run WRF-Var.

b)             The 3D-Var Observation Preprocessor (3DVAR_OBSPROC): Describes how to create an observation file for subsequent use in WRF-Var, and plot observation distributions.

c)             Setting up WRF-Var: In this part of the tutorial you will download and compile the codes that form the WRF-Var system (3DVAR_OBSPROC, WRF-Var, WRF_BC).

d)             Run WRF-Var CONUS Case Study: In this section, you will learn how to run WRF-Var for a test case.

e)             WRF-Var Diagnostics: WRF-Var produces a number of diagnostics file that contain useful information on how the assimilation has performed. This section will introduce you to some of these files, and what to look for.

f)               Updating WRF lateral boundary conditions: Before using the WRF-Var analysis as the initial conditions for a WRF forecast, the lateral boundary file must be modified to take account of the differences between first guess and analysis.


Once you are able to run all these programs successfully, and have spent some time looking at the variety of diagnostics output that is produced, we hope that you'll have some confidence in handling the WRF-Var system programs when you start your cases. Good luck!


For comments, send email to wrfhelp@wrf-model.org

Last Modified: January 25 2006