Spatio-Temporal Variability and Model Parameter Sensitivity Analysis of Ice Production in Ross Ice Shelf Polynya from 2003 to 2015

Antarctic sea ice formation is strongly influenced by polynyas occurring in austral winter. The sea ice production of Ross Ice Shelf Polynya (RISP) located in the Ross Sea is the highest among coastal polynyas around the Southern Ocean. In this paper, daily sea ice production distribution of RISP in...

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Published in:Remote Sensing
Main Authors: Zian Cheng, Xiaoping Pang, Xi Zhao, Cheng Tan
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2017
Subjects:
Q
Online Access:https://doi.org/10.3390/rs9090934
https://doaj.org/article/e2346538c05e46b4b60f960ee8190ed0
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spelling ftdoajarticles:oai:doaj.org/article:e2346538c05e46b4b60f960ee8190ed0 2023-05-15T13:55:36+02:00 Spatio-Temporal Variability and Model Parameter Sensitivity Analysis of Ice Production in Ross Ice Shelf Polynya from 2003 to 2015 Zian Cheng Xiaoping Pang Xi Zhao Cheng Tan 2017-09-01T00:00:00Z https://doi.org/10.3390/rs9090934 https://doaj.org/article/e2346538c05e46b4b60f960ee8190ed0 EN eng MDPI AG https://www.mdpi.com/2072-4292/9/9/934 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs9090934 https://doaj.org/article/e2346538c05e46b4b60f960ee8190ed0 Remote Sensing, Vol 9, Iss 9, p 934 (2017) polynya thermodynamic model ice production Ross Sea sensitivity test Science Q article 2017 ftdoajarticles https://doi.org/10.3390/rs9090934 2022-12-31T15:24:36Z Antarctic sea ice formation is strongly influenced by polynyas occurring in austral winter. The sea ice production of Ross Ice Shelf Polynya (RISP) located in the Ross Sea is the highest among coastal polynyas around the Southern Ocean. In this paper, daily sea ice production distribution of RISP in wintertime is estimated during 2003–2015, and the spatial and temporal trends of ice production are explored. Moreover, the sensitivity of the ice production model to parameterization is tested. To define the extent of RISP, this study uses sea ice concentration (SIC) maps mainly derived from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSRE) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) by ARTIST (Arctic Radiation and Turbulence Interaction Study) sea ice algorithm (ASI) and constrains the ice production estimation to areas with SIC less than 75%. ERA-Interim reanalysis meteorological data are applied to a thermodynamic model to estimate daily ice production distribution between April and October during 2003–2015 for the open water fractions within the polynya. This estimation is conducted under the assumption that the meteorological data represent the reality. We further analyzed the spatial variability, monthly trend, and interannual trend for wintertime of the total RISP sea ice production. The results show that the ocean surface produces ice at a high rate within the distance of 20–30 km from the ice shelf front. In most high production areas, the ice production significantly increases. Some local regions show a contrarily significant decreasing trend as a result of ice shelf expansion and iceberg events. The monthly total RISP ice production ranges from 14 to 76 km3, showing substantial fluctuations in each month during 2003–2015. The seasonal variation of each year also shows substantial fluctuations. The wintertime total ice productions of RISP for 2003–2015 range 164–313 km3 with an average of 219 km3, showing no obvious temporal trend. More importantly, we conducted ten ... Article in Journal/Newspaper Antarc* Antarctic Arctic Ice Shelf Iceberg* Iceberg* Ross Ice Shelf Ross Sea Sea ice Southern Ocean Directory of Open Access Journals: DOAJ Articles Antarctic Arctic Austral Ross Ice Shelf Ross Sea Southern Ocean Remote Sensing 9 9 934
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic polynya
thermodynamic model
ice production
Ross Sea
sensitivity test
Science
Q
spellingShingle polynya
thermodynamic model
ice production
Ross Sea
sensitivity test
Science
Q
Zian Cheng
Xiaoping Pang
Xi Zhao
Cheng Tan
Spatio-Temporal Variability and Model Parameter Sensitivity Analysis of Ice Production in Ross Ice Shelf Polynya from 2003 to 2015
topic_facet polynya
thermodynamic model
ice production
Ross Sea
sensitivity test
Science
Q
description Antarctic sea ice formation is strongly influenced by polynyas occurring in austral winter. The sea ice production of Ross Ice Shelf Polynya (RISP) located in the Ross Sea is the highest among coastal polynyas around the Southern Ocean. In this paper, daily sea ice production distribution of RISP in wintertime is estimated during 2003–2015, and the spatial and temporal trends of ice production are explored. Moreover, the sensitivity of the ice production model to parameterization is tested. To define the extent of RISP, this study uses sea ice concentration (SIC) maps mainly derived from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSRE) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) by ARTIST (Arctic Radiation and Turbulence Interaction Study) sea ice algorithm (ASI) and constrains the ice production estimation to areas with SIC less than 75%. ERA-Interim reanalysis meteorological data are applied to a thermodynamic model to estimate daily ice production distribution between April and October during 2003–2015 for the open water fractions within the polynya. This estimation is conducted under the assumption that the meteorological data represent the reality. We further analyzed the spatial variability, monthly trend, and interannual trend for wintertime of the total RISP sea ice production. The results show that the ocean surface produces ice at a high rate within the distance of 20–30 km from the ice shelf front. In most high production areas, the ice production significantly increases. Some local regions show a contrarily significant decreasing trend as a result of ice shelf expansion and iceberg events. The monthly total RISP ice production ranges from 14 to 76 km3, showing substantial fluctuations in each month during 2003–2015. The seasonal variation of each year also shows substantial fluctuations. The wintertime total ice productions of RISP for 2003–2015 range 164–313 km3 with an average of 219 km3, showing no obvious temporal trend. More importantly, we conducted ten ...
format Article in Journal/Newspaper
author Zian Cheng
Xiaoping Pang
Xi Zhao
Cheng Tan
author_facet Zian Cheng
Xiaoping Pang
Xi Zhao
Cheng Tan
author_sort Zian Cheng
title Spatio-Temporal Variability and Model Parameter Sensitivity Analysis of Ice Production in Ross Ice Shelf Polynya from 2003 to 2015
title_short Spatio-Temporal Variability and Model Parameter Sensitivity Analysis of Ice Production in Ross Ice Shelf Polynya from 2003 to 2015
title_full Spatio-Temporal Variability and Model Parameter Sensitivity Analysis of Ice Production in Ross Ice Shelf Polynya from 2003 to 2015
title_fullStr Spatio-Temporal Variability and Model Parameter Sensitivity Analysis of Ice Production in Ross Ice Shelf Polynya from 2003 to 2015
title_full_unstemmed Spatio-Temporal Variability and Model Parameter Sensitivity Analysis of Ice Production in Ross Ice Shelf Polynya from 2003 to 2015
title_sort spatio-temporal variability and model parameter sensitivity analysis of ice production in ross ice shelf polynya from 2003 to 2015
publisher MDPI AG
publishDate 2017
url https://doi.org/10.3390/rs9090934
https://doaj.org/article/e2346538c05e46b4b60f960ee8190ed0
geographic Antarctic
Arctic
Austral
Ross Ice Shelf
Ross Sea
Southern Ocean
geographic_facet Antarctic
Arctic
Austral
Ross Ice Shelf
Ross Sea
Southern Ocean
genre Antarc*
Antarctic
Arctic
Ice Shelf
Iceberg*
Iceberg*
Ross Ice Shelf
Ross Sea
Sea ice
Southern Ocean
genre_facet Antarc*
Antarctic
Arctic
Ice Shelf
Iceberg*
Iceberg*
Ross Ice Shelf
Ross Sea
Sea ice
Southern Ocean
op_source Remote Sensing, Vol 9, Iss 9, p 934 (2017)
op_relation https://www.mdpi.com/2072-4292/9/9/934
https://doaj.org/toc/2072-4292
2072-4292
doi:10.3390/rs9090934
https://doaj.org/article/e2346538c05e46b4b60f960ee8190ed0
op_doi https://doi.org/10.3390/rs9090934
container_title Remote Sensing
container_volume 9
container_issue 9
container_start_page 934
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