Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation
Data assimilation experiments that aim at improving summer ice concentration and thickness forecasts in the Arctic are carried out. The data assimilation system used is based on the MIT general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter. The effect o...
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00013672 2023-05-15T15:11:49+02:00 Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation Yang, Qinghua Losch, Martin Losa, Svetlana N. Jung, Thomas Nerger, Lars Lavergne, Thomas 2016-04 electronic https://doi.org/10.5194/tc-10-761-2016 https://noa.gwlb.de/receive/cop_mods_00013672 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00013628/tc-10-761-2016.pdf https://tc.copernicus.org/articles/10/761/2016/tc-10-761-2016.pdf eng eng Copernicus Publications The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-10-761-2016 https://noa.gwlb.de/receive/cop_mods_00013672 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00013628/tc-10-761-2016.pdf https://tc.copernicus.org/articles/10/761/2016/tc-10-761-2016.pdf uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2016 ftnonlinearchiv https://doi.org/10.5194/tc-10-761-2016 2022-02-08T22:55:30Z Data assimilation experiments that aim at improving summer ice concentration and thickness forecasts in the Arctic are carried out. The data assimilation system used is based on the MIT general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter. The effect of using sea ice concentration satellite data products with appropriate uncertainty estimates is assessed by three different experiments using sea ice concentration data of the European Space Agency Sea Ice Climate Change Initiative (ESA SICCI) which are provided with a per-grid-cell physically based sea ice concentration uncertainty estimate. The first experiment uses the constant uncertainty, the second one imposes the provided SICCI uncertainty estimate, while the third experiment employs an elevated minimum uncertainty to account for a representation error. Using the observation uncertainties that are provided with the data improves the ensemble mean forecast of ice concentration compared to using constant data errors, but the thickness forecast, based on the sparsely available data, appears to be degraded. Further investigating this lack of positive impact on the sea ice thicknesses leads us to a fundamental mismatch between the satellite-based radiometric concentration and the modeled physical ice concentration in summer: the passive microwave sensors used for deriving the vast majority of the sea ice concentration satellite-based observations cannot distinguish ocean water (in leads) from melt water (in ponds). New data assimilation methodologies that fully account or mitigate this mismatch must be designed for successful assimilation of sea ice concentration satellite data in summer melt conditions. In our study, thickness forecasts can be slightly improved by adopting the pragmatic solution of raising the minimum observation uncertainty to inflate the data error and ensemble spread. Article in Journal/Newspaper Arctic Climate change Sea ice The Cryosphere Niedersächsisches Online-Archiv NOA Arctic The Cryosphere 10 2 761 774 |
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article Verlagsveröffentlichung Yang, Qinghua Losch, Martin Losa, Svetlana N. Jung, Thomas Nerger, Lars Lavergne, Thomas Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation |
topic_facet |
article Verlagsveröffentlichung |
description |
Data assimilation experiments that aim at improving summer ice concentration and thickness forecasts in the Arctic are carried out. The data assimilation system used is based on the MIT general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter. The effect of using sea ice concentration satellite data products with appropriate uncertainty estimates is assessed by three different experiments using sea ice concentration data of the European Space Agency Sea Ice Climate Change Initiative (ESA SICCI) which are provided with a per-grid-cell physically based sea ice concentration uncertainty estimate. The first experiment uses the constant uncertainty, the second one imposes the provided SICCI uncertainty estimate, while the third experiment employs an elevated minimum uncertainty to account for a representation error. Using the observation uncertainties that are provided with the data improves the ensemble mean forecast of ice concentration compared to using constant data errors, but the thickness forecast, based on the sparsely available data, appears to be degraded. Further investigating this lack of positive impact on the sea ice thicknesses leads us to a fundamental mismatch between the satellite-based radiometric concentration and the modeled physical ice concentration in summer: the passive microwave sensors used for deriving the vast majority of the sea ice concentration satellite-based observations cannot distinguish ocean water (in leads) from melt water (in ponds). New data assimilation methodologies that fully account or mitigate this mismatch must be designed for successful assimilation of sea ice concentration satellite data in summer melt conditions. In our study, thickness forecasts can be slightly improved by adopting the pragmatic solution of raising the minimum observation uncertainty to inflate the data error and ensemble spread. |
format |
Article in Journal/Newspaper |
author |
Yang, Qinghua Losch, Martin Losa, Svetlana N. Jung, Thomas Nerger, Lars Lavergne, Thomas |
author_facet |
Yang, Qinghua Losch, Martin Losa, Svetlana N. Jung, Thomas Nerger, Lars Lavergne, Thomas |
author_sort |
Yang, Qinghua |
title |
Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation |
title_short |
Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation |
title_full |
Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation |
title_fullStr |
Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation |
title_full_unstemmed |
Brief communication: The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation |
title_sort |
brief communication: the challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation |
publisher |
Copernicus Publications |
publishDate |
2016 |
url |
https://doi.org/10.5194/tc-10-761-2016 https://noa.gwlb.de/receive/cop_mods_00013672 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00013628/tc-10-761-2016.pdf https://tc.copernicus.org/articles/10/761/2016/tc-10-761-2016.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change Sea ice The Cryosphere |
genre_facet |
Arctic Climate change Sea ice The Cryosphere |
op_relation |
The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-10-761-2016 https://noa.gwlb.de/receive/cop_mods_00013672 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00013628/tc-10-761-2016.pdf https://tc.copernicus.org/articles/10/761/2016/tc-10-761-2016.pdf |
op_rights |
uneingeschränkt info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/tc-10-761-2016 |
container_title |
The Cryosphere |
container_volume |
10 |
container_issue |
2 |
container_start_page |
761 |
op_container_end_page |
774 |
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1766342609311105024 |