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 |
---|---|
Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Stockholm University Press
2020
|
Subjects: | |
Online Access: | https://doi.org/10.1080/16000870.2019.1697166 https://doaj.org/article/677cfefb01c740ff81ec5550263a2507 |
id |
ftdoajarticles:oai:doaj.org/article:677cfefb01c740ff81ec5550263a2507 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:677cfefb01c740ff81ec5550263a2507 2023-05-15T15:07:36+02:00 Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: a twin experiment Abhishek Shah Laurent Bertino François Counillon Mohamad El Gharamti Jiping Xie 2020-01-01T00:00:00Z https://doi.org/10.1080/16000870.2019.1697166 https://doaj.org/article/677cfefb01c740ff81ec5550263a2507 EN eng Stockholm University Press http://dx.doi.org/10.1080/16000870.2019.1697166 https://doaj.org/toc/1600-0870 1600-0870 doi:10.1080/16000870.2019.1697166 https://doaj.org/article/677cfefb01c740ff81ec5550263a2507 Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 72, Iss 1, Pp 1-15 (2020) semi-qualitative observations range limitation smos ice thickness topaz4 enkf-sq Oceanography GC1-1581 Meteorology. Climatology QC851-999 article 2020 ftdoajarticles https://doi.org/10.1080/16000870.2019.1697166 2022-12-30T23:26:48Z 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 Directory of Open Access Journals: DOAJ Articles Arctic Tellus A: Dynamic Meteorology and Oceanography 72 1 1 15 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
semi-qualitative observations range limitation smos ice thickness topaz4 enkf-sq Oceanography GC1-1581 Meteorology. Climatology QC851-999 |
spellingShingle |
semi-qualitative observations range limitation smos ice thickness topaz4 enkf-sq Oceanography GC1-1581 Meteorology. Climatology QC851-999 Abhishek Shah Laurent Bertino François Counillon Mohamad El Gharamti Jiping Xie Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: a twin experiment |
topic_facet |
semi-qualitative observations range limitation smos ice thickness topaz4 enkf-sq Oceanography GC1-1581 Meteorology. Climatology QC851-999 |
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. |
format |
Article in Journal/Newspaper |
author |
Abhishek Shah Laurent Bertino François Counillon Mohamad El Gharamti Jiping Xie |
author_facet |
Abhishek Shah Laurent Bertino François Counillon Mohamad El Gharamti Jiping Xie |
author_sort |
Abhishek Shah |
title |
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 |
publisher |
Stockholm University Press |
publishDate |
2020 |
url |
https://doi.org/10.1080/16000870.2019.1697166 https://doaj.org/article/677cfefb01c740ff81ec5550263a2507 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 72, Iss 1, Pp 1-15 (2020) |
op_relation |
http://dx.doi.org/10.1080/16000870.2019.1697166 https://doaj.org/toc/1600-0870 1600-0870 doi:10.1080/16000870.2019.1697166 https://doaj.org/article/677cfefb01c740ff81ec5550263a2507 |
op_doi |
https://doi.org/10.1080/16000870.2019.1697166 |
container_title |
Tellus A: Dynamic Meteorology and Oceanography |
container_volume |
72 |
container_issue |
1 |
container_start_page |
1 |
op_container_end_page |
15 |
_version_ |
1766339074887516160 |