series, the UCAR Quarterly profiles one or more of the NCAR strategic
initiatives each issue.
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
Contact: Jeffrey Anderson, 303-497-8991