Directorate

• Contents
• EXECUTIVE SUMMARY
• 1. SCOPE OF THE PROGRAM
• 2. IMPROVING OUR UNDERSTANDING OF EARTH-SYSTEM PROCESSES
• 2.1 Scale Interactions Associated with Precipitating Convective Systems
• 2.2 Understanding the Dynamics and Predictability of Weather Systems on Time Scales of 0-48 h
• 2.3 Fundamental Research on Precipitation Processes, with an Emphasis on their Improved Representation in Numerical Models
• 2.4 Understanding the Dynamics, Physics and Chemistry of Multi-Scale Atmospheric Chemical Constituent and Particulate Transport, Dispersion and Transformations
• 2.5 Fundamental Research in Boundary Layers and their Interfacial Interactions
• 3. ADVANCING THE SCIENCE OF ATMOSPHERIC PREDICTION
• 3.1 Advancing Short-Range Weather Prediction
• 3.2Advancing Data Assimilation Research
• 3.3 Improving Forecasting of Pollutants and Hazardous Materials
• 4. ADVANCED COMMUNITY RESEARCH TOOLS
• 4.1 WRF Community Model
• 4.2 Community Data Assimilation Techniques
• 4.3 Nested Community Climate Model
• 5. SUMMARY
• Acronym List
• Print Version
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Mesoscale & Microscale Meteorology Division Science Plan:

4.2 Community Data Assimilation Techniques

Objective: To provide the Unified Data Assimilation System being developed for WRF to the community on a user-onus basis.
Data assimilation is already a central concern for NWP and, since it provides a direct, objective comparison of model simulations and observations, it will likely become increasingly important to other areas of mesoscale research. It thus crucial that ARW community modeling system include advanced data assimilation schemes for the WRF model.

Two data assimilation systems for WRF are available to the community at present: one based on the variational approach to assimilation and the other an ensemble filtering scheme. A third assimilation system, using nudging, is under development.
On the variational side, a WRF 3D-Var system has been developed, released to the community, and user tutorials provided. The 3D-Var scheme assimilates observations valid at single time (or close to a single time), using pre-specified background error covariances. A suite of background error covariance models have been developed, representing the different approaches adopted in current operational and research systems. These are available with the 3D-Var release. Numerous observation operators have also been developed, including conventional observations (surface, sonde, aircraft, and satellite temperature, moisture, and wind retrievals), radar reflectivity and radial velocity, scatterometer winds, microwave radiances, GPS refractivity, and total precipitable water observations. The WRF 3D-Var system is currently being extended to include a 4D-Var option. A basic version, based on dry versions of the linearized and adjoint models, is expected by summer 2005.

On the ensemble filtering side, an EnKF for WRF has been developed and is presently being tested with real observations at both convective and larger scales. The EnKF software is part of the Data Assimilation Research Testbed (DART) developed by NCAR’s Data Assimilation Initiative. Although the software is freely available, MMM provides very limited user support at this time. The EnKF also has numerous observation operators, including radar reflectivity and radial velocity, and GPS occulation operators of varying levels of complexity.

Since data assimilation schemes are much less mature than numerical models, we will be supporting the assimilation elements of the WRF community system differently to the support given to ARW. In particular, the WRF data assimilation system will not be usable as a ‘black box’; instead, users will need to tune (or even extend) the background and observation error specifications for specific applications. We will provide tools (e.g., observation error estimation algorithms, background error calculation codes) to assist the community, but it remains the responsibility of the user to perform this essential work for their own application.

We note that the EnKF approach has the additional benefit of providing a model ensemble for other activities. The adjoint model developed for the 4D-Var also can be used in forecast sensitivity studies.

By providing these tools at an early stage in their development, we aim to expand university expertise and education in data assimilation and to further the research goals of THORPEX and the USWRP.

Next section: Nested Community Climate Model

 

 

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