WRFDA System Overview

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, etc.) 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.

The MMM Division of NCAR supports a unified (global/regional, multi-model, 3/4D-Var) model-space data assimilation system (WRFDA) for use by the NCAR staff and collaborators, and is also freely available to the general community, together with further documentation, test results, plans etc.

Various components of the WRFDA system are shown in blue in the sketch below, together with their relationship with the rest of the WRF system.

System overview

x^b first guess, either from a previous WRF forecast or from WPS/REAL output

x^lbc lateral boundary from WPS/REAL output

x^a analysis from the WRFDA system

x^f WRF forecast output

y^o observations processed by OBSPROC (NOTE: PREPBUFR input, radar, radiance, and rainfall data are not processed through OBSPROC)

B₀ background error statistics from generic BE data (CV3) or gen_be

R observational and representative error statistics

Before using your own data, we suggest that you start by running through the WRFDA-related programs using the supplied test case (can be downloaded here). 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 capable of running the entire modeling system. After you have done the tutorial, you can try running other, more computationally intensive, case studies and experimenting with some of the many namelist variables.

Platforms capable of running WRFDA

Running WRFDA requires a Fortran 90 compiler. We have tested the WRFDA on the following platforms: IBM (XLF), SGI Altix (INTEL), PC/Linux (PGI, INTEL, GFORTRAN), and Apple (G95/PGI). 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 are interested in hearing about your experiences in modifying compiler options, we do not recommend making changes to the configure file used to compile WRFDA.

WARNING: It is impossible to test every permutation of computer, compiler, number of processors, case, namelist option, etc. for every WRFDA release. The namelist options that are supported are indicated in the WRFDA/var/README.namelist file of the source code, and these are the default options.

We hope our test cases will prepare you for the variety of ways in which you may wish to run your own WRFDA experiments. Please inform us about your experiences.

As a professional courtesy, we request that you include the following references in any publication that uses any component of the community WRFDA 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.

Huang, X.Y., Q. Xiao, D.M. Barker, X. Zhang, J. Michalakes, W. Huang, T. Henderson, J. Bray, Y. Chen, Z. Ma, J. Dudhia, Y. Guo, X. Zhang, D.J. Won, H.C. Lin, and Y.H. Kuo, 2009: Four-Dimensional Variational Data Assimilation for WRF: Formulation and Preliminary Results. Mon. Wea. Rev., 137, 299–314.

A more complete introduction to WRFDA, along with instructions on how to compile and run the various components, can be found in the WRFDA User Guide.