The Data Assimilation Research Testbed: A Community Facility

The Data Assimilation Research Testbed: A Community Facility The Data Assimilation Research Testbed (DART) is an open-source community facility for data assimilation education, research, and development. DART's ensemble data assimilation algorithms, careful software engineering, and diagnostic tools allow atmospheric scientists, oceanographers, hydrologists, chemists, and other geophysicists to build state-of-the-art data assimilation systems with unprecedented ease. For global numerical weather prediction, DART produces ensemble-mean analyses comparable to analyses from major centers while also providing initial conditions for ensemble predictions. In addition, DART supports more novel assimilation applications like parameter estimation, sensitivity analysis, observing system design, and smoothing. Implementing basic systems for large models requires only a few person-weeks; comprehensive systems have been built in a few months. Incorporating new observation types is also straightforward, requiring only a forward operator mapping between a model's state and an observation's expected value. Forward operators for standard, in situ observations and novel types, like GPS radio occultation soundings, are available. DART algorithms scale well on a variety of parallel architectures, allowing large data assimilation problems to be studied. DART also includes many low-order models and an ensemble assimilation tutorial appropriate for undergraduate and graduate instruction. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

The Data Assimilation Research Testbed: A Community Facility

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
D.O.I.
10.1175/2009BAMS2618.1
Publisher site
See Article on Publisher Site

Abstract

The Data Assimilation Research Testbed (DART) is an open-source community facility for data assimilation education, research, and development. DART's ensemble data assimilation algorithms, careful software engineering, and diagnostic tools allow atmospheric scientists, oceanographers, hydrologists, chemists, and other geophysicists to build state-of-the-art data assimilation systems with unprecedented ease. For global numerical weather prediction, DART produces ensemble-mean analyses comparable to analyses from major centers while also providing initial conditions for ensemble predictions. In addition, DART supports more novel assimilation applications like parameter estimation, sensitivity analysis, observing system design, and smoothing. Implementing basic systems for large models requires only a few person-weeks; comprehensive systems have been built in a few months. Incorporating new observation types is also straightforward, requiring only a forward operator mapping between a model's state and an observation's expected value. Forward operators for standard, in situ observations and novel types, like GPS radio occultation soundings, are available. DART algorithms scale well on a variety of parallel architectures, allowing large data assimilation problems to be studied. DART also includes many low-order models and an ensemble assimilation tutorial appropriate for undergraduate and graduate instruction.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Sep 8, 2009

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