Physically-based data assimilation
Ideally, a validation and assimilation scheme should maintain the physical principles embodied in the model and be able to evaluate and assimilate lower dimensional features (e.g., discontinuities) contained within a bulk simulation, even when these features are not directly observed or represented...
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ftunivadelaidedl:oai:digital.library.adelaide.edu.au:2440/83111 2023-12-17T10:49:52+01:00 Physically-based data assimilation Levy, G. Coon, M. Nguyen, G. Sulsky, D. 2010 application/pdf http://hdl.handle.net/2440/83111 https://doi.org/10.5194/gmdd-3-517-2010 en eng Copernicus GmbH Geoscientific Model Development, 2010; 3:669-677 1991-959X http://hdl.handle.net/2440/83111 doi:10.5194/gmdd-3-517-2010 © Author(s) 2010. This work is distributed under the Creative Commons Attribution 3.0 License. http://dx.doi.org/10.5194/gmdd-3-517-2010 Journal article 2010 ftunivadelaidedl https://doi.org/10.5194/gmdd-3-517-2010 2023-11-20T23:31:25Z Ideally, a validation and assimilation scheme should maintain the physical principles embodied in the model and be able to evaluate and assimilate lower dimensional features (e.g., discontinuities) contained within a bulk simulation, even when these features are not directly observed or represented by model variables. We present such a scheme and suggest its potential to resolve or alleviate some outstanding problems that stem from making and applying required, yet often non-physical, assumptions and procedures in common operational data assimilation. As proof of concept, we use a sea-ice model with remotely sensed observations of leads in a one-step assimilation cycle. Using the new scheme in a sixteen day simulation experiment introduces model skill (against persistence) several days earlier than in the control run, improves the overall model skill and delays its drop off at later stages of the simulation. The potential and requirements to extend this scheme to different applications, and to both empirical and statistical multivariate and full cycle data assimilation schemes, are discussed. G. Levy, M. Coon, G. Nguyen, and D. Sulsky Article in Journal/Newspaper Sea ice The University of Adelaide: Digital Library Levy ENVELOPE(-66.567,-66.567,-66.320,-66.320) |
institution |
Open Polar |
collection |
The University of Adelaide: Digital Library |
op_collection_id |
ftunivadelaidedl |
language |
English |
description |
Ideally, a validation and assimilation scheme should maintain the physical principles embodied in the model and be able to evaluate and assimilate lower dimensional features (e.g., discontinuities) contained within a bulk simulation, even when these features are not directly observed or represented by model variables. We present such a scheme and suggest its potential to resolve or alleviate some outstanding problems that stem from making and applying required, yet often non-physical, assumptions and procedures in common operational data assimilation. As proof of concept, we use a sea-ice model with remotely sensed observations of leads in a one-step assimilation cycle. Using the new scheme in a sixteen day simulation experiment introduces model skill (against persistence) several days earlier than in the control run, improves the overall model skill and delays its drop off at later stages of the simulation. The potential and requirements to extend this scheme to different applications, and to both empirical and statistical multivariate and full cycle data assimilation schemes, are discussed. G. Levy, M. Coon, G. Nguyen, and D. Sulsky |
format |
Article in Journal/Newspaper |
author |
Levy, G. Coon, M. Nguyen, G. Sulsky, D. |
spellingShingle |
Levy, G. Coon, M. Nguyen, G. Sulsky, D. Physically-based data assimilation |
author_facet |
Levy, G. Coon, M. Nguyen, G. Sulsky, D. |
author_sort |
Levy, G. |
title |
Physically-based data assimilation |
title_short |
Physically-based data assimilation |
title_full |
Physically-based data assimilation |
title_fullStr |
Physically-based data assimilation |
title_full_unstemmed |
Physically-based data assimilation |
title_sort |
physically-based data assimilation |
publisher |
Copernicus GmbH |
publishDate |
2010 |
url |
http://hdl.handle.net/2440/83111 https://doi.org/10.5194/gmdd-3-517-2010 |
long_lat |
ENVELOPE(-66.567,-66.567,-66.320,-66.320) |
geographic |
Levy |
geographic_facet |
Levy |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
http://dx.doi.org/10.5194/gmdd-3-517-2010 |
op_relation |
Geoscientific Model Development, 2010; 3:669-677 1991-959X http://hdl.handle.net/2440/83111 doi:10.5194/gmdd-3-517-2010 |
op_rights |
© Author(s) 2010. This work is distributed under the Creative Commons Attribution 3.0 License. |
op_doi |
https://doi.org/10.5194/gmdd-3-517-2010 |
_version_ |
1785574468487217152 |