Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: A twin experiment
A newly introduced stochastic data assimilation method, the Ensemble Kalman Filter Semi-Qualitative (EnKF-SQ) is applied to a realistic coupled ice-ocean model of the Arctic, the TOPAZ4 configuration, in a twin experiment framework. The method is shown to add value to range-limited thin ice thicknes...
Published in: | Tellus A: Dynamic Meteorology and Oceanography |
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Online Access: | https://doi.org/10.1080/16000870.2019.1697166 |
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ftncar:oai:drupal-site.org:articles_24101 2024-04-28T08:10:43+00:00 Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: A twin experiment Shah, Abhishek (author) Bertino, Laurent (author) Counillon, François (author) El Gharamti, Mohamad (author) Xie, Jiping (author) 2020-01-01 https://doi.org/10.1080/16000870.2019.1697166 en eng Tellus A: Dynamic Meteorology and Oceanography--Tellus A: Dynamic Meteorology and Oceanography--1600-0870 articles:24101 ark:/85065/d7s46wb5 doi:10.1080/16000870.2019.1697166 Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. article Text 2020 ftncar https://doi.org/10.1080/16000870.2019.1697166 2024-04-04T17:33:50Z A newly introduced stochastic data assimilation method, the Ensemble Kalman Filter Semi-Qualitative (EnKF-SQ) is applied to a realistic coupled ice-ocean model of the Arctic, the TOPAZ4 configuration, in a twin experiment framework. The method is shown to add value to range-limited thin ice thickness measurements, as obtained from passive microwave remote sensing, with respect to more trivial solutions like neglecting the out-of-range values or assimilating climatology instead. Some known properties inherent to the EnKF-SQ are evaluated: the tendency to draw the solution closer to the thickness threshold, the skewness of the resulting analysis ensemble and the potential appearance of outliers. The experiments show that none of these properties prove deleterious in light of the other sub-optimal characters of the sea ice data assimilation system used here (non-linearities, non-Gaussian variables, lack of strong coupling). The EnKF-SQ has a single tuning parameter that is adjusted for best performance of the system at hand. The sensitivity tests reveal that the tuning parameter does not critically influence the results. The EnKF-SQ makes overall a valid approach for assimilating semi-qualitative observations into high-dimensional nonlinear systems. Article in Journal/Newspaper Arctic Sea ice OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) Tellus A: Dynamic Meteorology and Oceanography 72 1 1 15 |
institution |
Open Polar |
collection |
OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) |
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ftncar |
language |
English |
description |
A newly introduced stochastic data assimilation method, the Ensemble Kalman Filter Semi-Qualitative (EnKF-SQ) is applied to a realistic coupled ice-ocean model of the Arctic, the TOPAZ4 configuration, in a twin experiment framework. The method is shown to add value to range-limited thin ice thickness measurements, as obtained from passive microwave remote sensing, with respect to more trivial solutions like neglecting the out-of-range values or assimilating climatology instead. Some known properties inherent to the EnKF-SQ are evaluated: the tendency to draw the solution closer to the thickness threshold, the skewness of the resulting analysis ensemble and the potential appearance of outliers. The experiments show that none of these properties prove deleterious in light of the other sub-optimal characters of the sea ice data assimilation system used here (non-linearities, non-Gaussian variables, lack of strong coupling). The EnKF-SQ has a single tuning parameter that is adjusted for best performance of the system at hand. The sensitivity tests reveal that the tuning parameter does not critically influence the results. The EnKF-SQ makes overall a valid approach for assimilating semi-qualitative observations into high-dimensional nonlinear systems. |
author2 |
Shah, Abhishek (author) Bertino, Laurent (author) Counillon, François (author) El Gharamti, Mohamad (author) Xie, Jiping (author) |
format |
Article in Journal/Newspaper |
title |
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: A twin experiment |
spellingShingle |
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: A twin experiment |
title_short |
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: A twin experiment |
title_full |
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: A twin experiment |
title_fullStr |
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: A twin experiment |
title_full_unstemmed |
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: A twin experiment |
title_sort |
assimilation of semi-qualitative sea ice thickness data with the enkf-sq: a twin experiment |
publishDate |
2020 |
url |
https://doi.org/10.1080/16000870.2019.1697166 |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_relation |
Tellus A: Dynamic Meteorology and Oceanography--Tellus A: Dynamic Meteorology and Oceanography--1600-0870 articles:24101 ark:/85065/d7s46wb5 doi:10.1080/16000870.2019.1697166 |
op_rights |
Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
op_doi |
https://doi.org/10.1080/16000870.2019.1697166 |
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Tellus A: Dynamic Meteorology and Oceanography |
container_volume |
72 |
container_issue |
1 |
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1 |
op_container_end_page |
15 |
_version_ |
1797578466189639680 |