Monday, 13 January 2025
New Orleans Ernest N. Morial Convention Center
Society's ability to make wise decisions leading to a thriving planet depends on an accurate understanding of the state of Earth and an ability to predict future states. Data Assimilation (DA) enables this through the combination of observations and our theoretical understanding embodied in forecast models. The Data Assimilation Research Testbed (DART) is a community facility for ensemble DA developed by the NSF National Center for Atmospheric Research (NSF NCAR). DART's products include a "best estimate" of the state of a system, and a description of the uncertainties associated with it,for a wide variety of Earth system models. The DART development community continues to enhance the DA capabilities of the Earth sciences community with ground-breaking algorithms, interfaces to new models and observations, increases in efficiency and capacity, thorough documentation, and educational materials. This poster focuses on a few of the recent advances:
+ Nonlinear and non-Gaussian DA capabilities (Quantile-Conserving Ensemble Filter Framework; QCEFF) leading to improved reanalyses for weather, atmospheric chemistry and space weather in NCAR’s CESM models.
+ Hybrid ensemble Kalman filters applied to Hurricane Ian with the WRF-Hydro streamflow model.
+ Improved representation of land surface processes in CLM.
+ The ability to assimilate Fluxnet observations.
+ Assimilation for the SEIR model of infectious disease spread.
+ An updated and improved tutorial for WRF-DART.
+ Numerous software enhancements including grid compression algorithms for efficient assimilation on masked grids (e.g. land areas in ocean models).
- Indicates paper has been withdrawn from meeting
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