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Choosing the optimal numerical precision for data assimilation in the presence of model error

Abstract:

The use of reduced numerical precision within an atmospheric data assimilation system is investigated. An atmospheric model with a spectral dynamical core is used to generate synthetic observations, which are then assimilated back into the same model using an ensemble Kalman filter. The effect on the analysis error of reducing precision from 64 bits to only 22 bits is measured and found to depend strongly on the degree of model uncertainty within the system. When the model used to generate th...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's Version

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Publisher copy:
10.1029/2018MS001341

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Atmospheric Oceanic and Planetary Physics
ORCID:
0000-0001-7235-6450
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Atmospheric Oceanic and Planetary Physics
Miyoshi, T More by this author
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Publisher:
American Geophysical Union Publisher's website
Journal:
Journal of Advances in Modeling Earth Systems Journal website
Volume:
10
Issue:
9
Pages:
2177-2191
Publication date:
2018-08-13
Acceptance date:
2018-08-07
DOI:
EISSN:
1942-2466
ISSN:
1942-2466
Pubs id:
pubs:912172
URN:
uri:f38223cc-1a2b-4b0e-834d-9d2837bd0d75
UUID:
uuid:f38223cc-1a2b-4b0e-834d-9d2837bd0d75
Local pid:
pubs:912172

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