Data assimilation research




		These two plots show 700 hPa concentration of CO from a DART/CAM assimilation using all standard observations for numerical weather prediction (top) and from a DART/CAM assimilation that included CO observations from the MOPITT instrument on the EOS Terra spacecraft (bottom). Comparison with aircraft observations (not shown) indicates that assimilating the MOPITT observations improves the analysis. These results, produced by Ave Arellano of ACD, demonstrate DART's abilities to facilitate innovative research involving assimilation of novel observations.

Data assimilation is the process of merging data from observations with computer models. It can transform diverse and incomplete observations to gridded estimates that can be easily used and interpreted. The assimilation process also produces quantitative information on model error, forecast skill, and observational errors, all of which allows us to improve the models. Data assimilation is providing rapid advances in geophysical studies. The Data Assimilation Research Section (DAReS) of IMAGe performs fundamental research on ensemble data assimilation methodologies for application across a wide range of geophysical problems. DAReS develops and maintains the Data Assimilation Research Testbed (DART), a software facility for doing ensemble data assimilation. DAReS also provides support to a growing community of NCAR, university, and government laboratory collaborators who are interested in applying ensemble data assimilation methods.

DAReS supports three of NCAR's strategic priorities: "Developing community models," "Developing and providing advanced services and tools," and "Enhancing science education." The DART user community includes members from many NCAR divisions, more than a dozen universities, and several government labs. Within NCAR:

Researchers in CGD are using DART/CAM (Community Atmosphere Model) to validate and improve climate models
MMM is using DART/WRF (Weather Research and Forecasting Model) to assimilate radar observations for convective-scale and hurricane prediction research
ACD will use DART as a central piece of a new satellite observing system testbed
COSMIC is using DART/WRF to assimilate GPS radio occultation observations
RAL is using DART/WRF to study boundary layer assimilation and modeling
HAO is exploring using DART for space weather and solar dynamo prediction

University groups are using both DART/WRF and DART/CAM, and several researchers have incorporated their own models including hydrological models, small-scale tracer transport models, and ocean/atmosphere GCMs. A DART/WRF system was tested during the NOAA/NSSL Spring Program to make predictions of severe weather over the central U.S. Researchers at the California Institute of Technology are preparing to use a DART/WRF system to assimilate observations of the Martian atmosphere. DAReS provides support for all these activities and uses feedback from users to develop more powerful and generic assimilation tools. DART has also been used to support graduate data assimilation classes at several universities. In July 2007, DART was used to provide six afternoons of computer exercises supporting an IMAGe workshop on assimilation of carbon dioxide observations.

The Jamaica release of DART was made available to the community in April using CISL's new subversion facility. Jamaica contains a number of enhanced assimilation algorithms and new parallel implementations that allow DART to run efficiently on a variety of parallel computing platforms.

Fundamental data assimilation research focuses on advancing ensemble methods to make them more powerful and generic, capable of being effectively applied to many problems as nearly "black-box" algorithms. Assimilation research will continue to focus on improving methods for dealing with sampling error (a major concern for generic filtering algorithms). New non-Gaussian ensemble filtering algorithms have been developed in the past year. These algorithms should facilitate the assimilation of discrete structures like thunderstorms and allow the use of observations with complex error characteristics. These algorithms will be tested in DART/WRF in FY2008.

This is the main page for DAReS and the DART facility.

The Data Assimilation Research Section is supported by NSF Core funding.