An Efficient T-S Assimilation Strategy Based on the Developed Argo-Extending Algorithm
Data assimilation is an efficient technique in the estimation of ocean state, by introducing the benefit of in situ measurements. Considering the insufficiency of the observations, the performance of assimilation with few temperature and salinity (T-S) profiles is not satisfied. To modify the situat...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2017/6847343 |
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| author | Chaojie Zhou Xiaohua Ding Jie Zhang Jungang Yang Qiang Ma |
| author_facet | Chaojie Zhou Xiaohua Ding Jie Zhang Jungang Yang Qiang Ma |
| author_sort | Chaojie Zhou |
| collection | DOAJ |
| description | Data assimilation is an efficient technique in the estimation of ocean state, by introducing the benefit of in situ measurements. Considering the insufficiency of the observations, the performance of assimilation with few temperature and salinity (T-S) profiles is not satisfied. To modify the situation, an extending algorithm based on the Argo temperature profile is developed and applied to present more reconstructed information. Meanwhile, when the reconstructed information is assimilated into the ocean model, the accuracy of the outcomes would obtain a notable enhancement. To validate it, an experiment including four cases is conducted based on Regional Ocean Modeling System (ROMS) and 4-dimensional variational method (4DVAR). The comparison with the EN4 dataset shows that the cases assimilated the Argo and the reconstructed temperature profiles are both promoted; the addition of reconstructed temperature profiles does enhance the accuracy; the impact of SST introduced in the extending algorithm process is negligible; the net enhancement of reconstructed temperature profiles is comparable with Argo T-S observations. Finally, the positive impact of the developed algorithm on data assimilation is validated. |
| format | Article |
| id | doaj-art-be10cae7db87485289134e0a0609f1cd |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-be10cae7db87485289134e0a0609f1cd2025-02-03T05:51:18ZengWileyAdvances in Meteorology1687-93091687-93172017-01-01201710.1155/2017/68473436847343An Efficient T-S Assimilation Strategy Based on the Developed Argo-Extending AlgorithmChaojie Zhou0Xiaohua Ding1Jie Zhang2Jungang Yang3Qiang Ma4Department of Mathematics, Harbin Institute of Technology at Weihai, Weihai 264209, ChinaDepartment of Mathematics, Harbin Institute of Technology at Weihai, Weihai 264209, ChinaThe First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, ChinaThe First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, ChinaDepartment of Mathematics, Harbin Institute of Technology at Weihai, Weihai 264209, ChinaData assimilation is an efficient technique in the estimation of ocean state, by introducing the benefit of in situ measurements. Considering the insufficiency of the observations, the performance of assimilation with few temperature and salinity (T-S) profiles is not satisfied. To modify the situation, an extending algorithm based on the Argo temperature profile is developed and applied to present more reconstructed information. Meanwhile, when the reconstructed information is assimilated into the ocean model, the accuracy of the outcomes would obtain a notable enhancement. To validate it, an experiment including four cases is conducted based on Regional Ocean Modeling System (ROMS) and 4-dimensional variational method (4DVAR). The comparison with the EN4 dataset shows that the cases assimilated the Argo and the reconstructed temperature profiles are both promoted; the addition of reconstructed temperature profiles does enhance the accuracy; the impact of SST introduced in the extending algorithm process is negligible; the net enhancement of reconstructed temperature profiles is comparable with Argo T-S observations. Finally, the positive impact of the developed algorithm on data assimilation is validated.http://dx.doi.org/10.1155/2017/6847343 |
| spellingShingle | Chaojie Zhou Xiaohua Ding Jie Zhang Jungang Yang Qiang Ma An Efficient T-S Assimilation Strategy Based on the Developed Argo-Extending Algorithm Advances in Meteorology |
| title | An Efficient T-S Assimilation Strategy Based on the Developed Argo-Extending Algorithm |
| title_full | An Efficient T-S Assimilation Strategy Based on the Developed Argo-Extending Algorithm |
| title_fullStr | An Efficient T-S Assimilation Strategy Based on the Developed Argo-Extending Algorithm |
| title_full_unstemmed | An Efficient T-S Assimilation Strategy Based on the Developed Argo-Extending Algorithm |
| title_short | An Efficient T-S Assimilation Strategy Based on the Developed Argo-Extending Algorithm |
| title_sort | efficient t s assimilation strategy based on the developed argo extending algorithm |
| url | http://dx.doi.org/10.1155/2017/6847343 |
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