Initiatives in Brief: Data Assimilation Initiative (DAI)

In this series, the UCAR Quarterly profiles one or more of the NCAR strategic initiatives each issue. General background on the initiatives.

Left to right: Doug Nychka, Jeff Anderson, Chris Snyder, and Joe Tribbia. (Photo by Carlye Calvin.)

Leaders: Jeffrey Anderson, Doug Nychka, Chris Snyder, Joseph Tribbia. Other NCAR scientists include Dale Barker, Alain Caya, Timothy Hoar, Hui Liu, Tomoko Matsuo, Kevin Raeder

Initial university collaborators: James Hansen (Massachusetts Institute of Technology), Fuqing Zhang (Texas A&M University), Gregory Hakim (University of Washington)

Goals: Create and lead a research community for data assimilation where individuals benefit from sharing ideas, methodologies, and software tools as well as access to a data assimilation testbed.

Recent progress: DAI hosted the Advanced Study Program summer colloquium and used an initial release of the Data Assimilation Research Testbed (DART) to support student exercises. A variety of models, including the Weather Research and Forecasting Model (WRF) and the Community Atmosphere Model (CAM), can now be used in concert with DART data assimilation capabilities. DAI is using DART to establish collaborations with scientists in many NCAR divisions and with university researchers. DART is also facilitating fundamental research on data assimilation techniques, especially the newly emerging ensemble filters.

In the literature:

Snyder, C. and F. Zhang, 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Monthly Weather Review 131, 1663–1677.

Anderson, J., 2003: A local least squares framework for ensemble filtering. MWR 131, 634-642.

Bengtsson, T., C. Snyder and D. Nychka, 2003: A nonlinear filter that extends to high dimensional systems. Journal of Geophysical Research–Atmos. 108(D24), 8775–8785.

Zhang, F., C. Snyder and J. Sun, 2004: Impacts of initial estimate and observations on convective-scale data assimilation with an ensemble Kalman filter. MWR 132, 1238–1253.

Coming up: DART development will soon allow the use of a wide array of atmospheric observations with the models listed above and others. In collaboration with the National Centers for Environmental Prediction, the ensemble filtering methods being developed in DART are being tested on operational problems in global prediction and compared to NCEP’s more traditional assimilation methods. DAI will develop a coordinated global/regional model assimilation system that combines a global model with WRF. The group is looking for additional interesting assimilation applications within the NCAR community.

In recognition of the wide range of uses for assimliation across the geosciences, DAI will become a section in the new NCAR Institute for Mathematical Applications in the Geosciences (see article on page 7).

Contact: Jeffrey Anderson, 303-497-8991