The Data Assimilation Research Testbed: A Community Facility

By Jeffrey L. Anderson, T. Hoar, K. Raeder, H. Liu, N. Collins, Ryan Torn, Avelino Avellano. 2009

291 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/e5cd94c5f94a1ede33fe59953777e3da60b61186

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In Atmospheric Science

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Citations in the corpus

Enhanced Adaptive Inflation Algorithm for Ensemble Filters (2018, methodology): “This is empirically shown to prevent collapse in the spread of the inflation pdf. d. Implementation The enhanced adaptive inflation algorithm is implemented in the Data Assimilation Research Testbed (DART) at NCAR (www.image.ucar.edu/DAReS/ DART/; Anderson et al. 2009).”
A Non-Gaussian Ensemble Filter Update for Data Assimilation (2010, methodology): “All temperature and wind observations from radiosondes, the Aircraft Communication, Ad-dressing, and Reporting System (ACARS), and other aircraft and satellite motion vector winds from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) re-analysis ”
Localization and Sampling Error Correction in Ensemble Kalman Filter Data Assimilation (2012, background): “These settings perform well in a variety of real data assimilations in large geophysical models (Anderson et al. 2009).”
The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty (2019, methodology): “Data Assimilation Capabilities The capabilities for conducting data assimilation with CLM5 using the Data Assimilation Research Testbed (DART, Anderson et al., 2009) continue to improve, particularly with respect to computational efficiency.”
A Localized Particle Filter for High-Dimensional Nonlinear Systems (2016, methodology): “The L96 model and EAKF data assimilation system used in this study are included in the open source NCAR DART software package (Anderson et al. 2009; available online at http://www. image.ucar.edu/DAReS/DART. b. Experiment setup Several data assimilation experiments are constructed to compare the PF…”
The Gaussian Approach to Adaptive Covariance Inflation and Its Implementation with the Local Ensemble Transform Kalman Filter (2011, methodology): “This A09 approach has been applied to the Data Assimilation Research Test bed (DART; Anderson et al. 2009) system, which has been used for realistic cases (e.g., Torn 2010a,b).”
Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations (2017, methodology): “This reduces the onus of correctly assimilating atmospheric initial conditions in parameter learning, which would be required if one were to match simulated and observed trajectories, as in approaches that assimilate model parameters jointly with the state of the system by augmenting state vectors w”