P1.5
DART: A community facility for ensemble data assimilation
Jeffrey Anderson, NCAR, Boulder, CO; and T. Hoar, N. Collins, K. Raeder, and H. Liu
Data assimilation is the term used in geophysics for combining
information from observations with predictions from a numerical
model. Assimilation can be used to produce improved analyses and
forecasts of a geophysical system, to improve numerical models,
and to design and evaluate observing systems.
The Data Assimilation Research Testbed (DART) is a mature community
software facility providing researchers access to state-of-the-art
ensemble assimilation tools. The freely-available DART distribution
includes fully functional low-order and high-order models, support
for commonly available observations, hooks to easily add both new
models and observation types, diagnostic programs to interpret the
results, and a full tutorial suitable for self-study or teaching
data assimilation concepts, including exercises using the models
distributed with DART.
Recent applications of DART with both global and regional atmospheric
models are presented to provide an overview of capabilities. DART has
been used with the WRF regional atmospheric model to produce
ensemble analyses and predictions of Pacific and Atlantic tropical
storms. The impact of using radio occultation observations from the
COSMIC satellites has been evaluated in these cases. DART has also
been applied to global prediction with the CAM general circulation
model. Analysis of the assimilated fields has led to the discovery
of a significant coding error in the polar filtering in the CAM finite
volume core. Ensemble assimilation has also identified noise due to a
previously undocumented numerical instability that is found in the
finite volume cores that have been used for several major climate
models. DART was also used with the CAM/CHEM model to provide
operational support during the ARCTAS field campaign.
New tools to improve and simplify the use of ensemble assimilation
continue to be added to the DART facility. In the past year, improved
tools for automatically adapting to model error (adaptive damped
inflation) and a new nonlinear filtering variant have been introduced.
Examples of improvements to global analyses and forecasts are presented.
New models, both small and large continue to be added to the set
compatible with DART. For instance, During the past year, a version of
the MIT/OCEAN model was added by Ibrahim Hoteit and the Navy's COAMPS
model was added by Tim Whitcomb. An overview of requirements for adding
a new large model are presented.
Poster Session 1, Data Assimilation and Impact Studies
Monday, 12 January 2009, 2:30 PM-4:00 PM, Hall 5
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