The Data Assimilation Research Testbed: A Community FacilitySource: Bulletin of the American Meteorological Society:;2009:;volume( 090 ):;issue: 009::page 1283Author:Anderson, Jeffrey
,
Hoar, Tim
,
Raeder, Kevin
,
Liu, Hui
,
Collins, Nancy
,
Torn, Ryan
,
Avellano, Avelino
DOI: 10.1175/2009BAMS2618.1Publisher: American Meteorological Society
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.
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contributor author | Anderson, Jeffrey | |
contributor author | Hoar, Tim | |
contributor author | Raeder, Kevin | |
contributor author | Liu, Hui | |
contributor author | Collins, Nancy | |
contributor author | Torn, Ryan | |
contributor author | Avellano, Avelino | |
date accessioned | 2017-06-09T16:27:13Z | |
date available | 2017-06-09T16:27:13Z | |
date copyright | 2009/09/01 | |
date issued | 2009 | |
identifier issn | 0003-0007 | |
identifier other | ams-68122.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4209646 | |
description 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. | |
publisher | American Meteorological Society | |
title | The Data Assimilation Research Testbed: A Community Facility | |
type | Journal Paper | |
journal volume | 90 | |
journal issue | 9 | |
journal title | Bulletin of the American Meteorological Society | |
identifier doi | 10.1175/2009BAMS2618.1 | |
journal fristpage | 1283 | |
journal lastpage | 1296 | |
tree | Bulletin of the American Meteorological Society:;2009:;volume( 090 ):;issue: 009 | |
contenttype | Fulltext |