Advance the application of ensemble Data Assimilation

Data assimilation is providing rapid advances in geophysical studies. The Data Assimilation Research Section (DAReS) of IMAGe develops and maintains the Data Assimilation Research Testbed (DART), a software facility for ensemble data assimilation. DAReS also provides support to a growing community of NCAR, university, and government laboratory partners who apply ensemble data assimilation methods with DART. With DART, modelers and experimenters can use state-of-the-art DA algorithms to build forecasting systems and diagnose both models and observation systems with a minimum investment in software and algorithm development. DA experts can use DART as a framework for building and testing new algorithms with both simple and sophisticated models. Finally, DART fosters a community of users, supported by the DART development team, who collaborate scientifically and contribute important new capabilities to the facility.

SST anomaly correlation
This plot shows the anomaly correlation for sea surface temperature (SST) between a coupled DART/CESM reanalysis and the HADISST product for 1970-1981. Red colors indicate that the reanalysis agrees well with the independent estimates of SST (which were not assimilated by DART) from HADISST. Data from this reanalysis provides information for improved localization of observation impact in strongly coupled DART/CESM assimilations and could also act as initial conditions for CESM hindcasts.


Data assimilation is a key tool for Earth System science that allows models to be confronted with observations. DA is essential for making forecasts for all components of the Earth System at all space and time scales. DA also provides a tool for identifying deficiencies in models and observing systems. The ensemble DA tools provided by DART allow uncertainty quantification which is essential to many prediction and scientific goals. Facilitating the use of DART by scientists helps to achieve CISL’s strategic goal to “Advance Earth System science by expanding the productivity of researchers through high-performance computing and data services”.

Interfaces between DART and new models continue to be developed. During the past year, work began on interfaces for the CESM/CICE sea ice model, the WACCM-X high top atmosphere model, a second version of the ROMS ocean model, the OpenGGCM ionosphere-mesosphere-thermosphere model, and the PARFLOW watershed flow model. Interfaces were completed for the CM1 convection-resolving model, the FEOM ocean model, and a new version of the COSMO regional atmosphere model. Additional support for estimating sources and sinks of trace gases in both CAM and WRF/CHEM was developed in collaboration with ACOM and Berkeley. The real-time WRF/DART assimilation system continued to run, making use of the new memory-scalable version of DART. A number of enhancements were made to DART systems for CESM including a survey of DART optimization parameters with CAM in preparation for a decadal atmosphere reanalysis, and tuning of the localization of the impact of observations in coupled CAM/POP assimilations in collaboration with CGD.

Data assimilation research in IMAGe is supported by NSF Core funding plus Grant 16-013 from the University of New Hampshire’s Open Geospace General Circulation Model program, Grant N0014-15-1-2300 (subaward A15-0093-S001-P0567931) from the DOD Office of Naval Research’s National Oceanographic Partnership Program, and Grants OCE149559 and OCE1243015 from the National Science Foundation program Decadal and Regional Climate Prediction using Earth System Models.