Fast Ice Prediction System (FIPS) for land-fast sea ice at Prydz Bay, East Antarctica: an operational service for CHINARE
A Fast Ice Prediction System (FIPS) was constructed and is the first regional land-fast sea-ice forecasting system for the Antarctic. FIPS had two components: (1) near-real-time information on the ice-covered area from MODIS and SAR imagery that revealed, tidal cracks, ridged and rafted ice regions;...
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2020-12-01
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| Series: | Annals of Glaciology |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S0260305520000464/type/journal_article |
| _version_ | 1811157283596402688 |
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| author | Jiechen Zhao Bin Cheng Timo Vihma Petra Heil Fengming Hui Qi Shu Lin Zhang Qinghua Yang |
| author_facet | Jiechen Zhao Bin Cheng Timo Vihma Petra Heil Fengming Hui Qi Shu Lin Zhang Qinghua Yang |
| author_sort | Jiechen Zhao |
| collection | DOAJ |
| description | A Fast Ice Prediction System (FIPS) was constructed and is the first regional land-fast sea-ice forecasting system for the Antarctic. FIPS had two components: (1) near-real-time information on the ice-covered area from MODIS and SAR imagery that revealed, tidal cracks, ridged and rafted ice regions; (2) a high-resolution 1-D thermodynamic snow and ice model (HIGHTSI) that was extended to perform a 2-D simulation on snow and ice evolution using atmospheric forcing from ECMWF: either using ERA-Interim reanalysis (in hindcast mode) or HERS operational 10-day predictions (in forecast mode). A hindcast experiment for the 2015 season was in good agreement with field observations, with a mean bias of 0.14 ± 0.07 m and a correlation coefficient of 0.98 for modeled ice thickness. The errors are largely caused by a cold bias in the atmospheric forcing. The thick snow cover during the 2015 season led to modeled formation of extensive snow ice and superimposed ice. The first FIPS operational service was performed during the 2017/18 season. The system predicted a realistic ice thickness and onset of snow surface melt as well as the area of internal ice melt. The model results on the snow and ice properties were considered by the captain of R/V Xuelong when optimizing a low-risk route for on-ice transportation through fast ice to the coastal Zhongshan Station. |
| first_indexed | 2024-04-10T05:03:31Z |
| format | Article |
| id | doaj.art-4a1bb4db9d854bc8b3083634aaa86def |
| institution | Directory Open Access Journal |
| issn | 0260-3055 1727-5644 |
| language | English |
| last_indexed | 2024-04-10T05:03:31Z |
| publishDate | 2020-12-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Annals of Glaciology |
| spelling | doaj.art-4a1bb4db9d854bc8b3083634aaa86def2023-03-09T12:27:41ZengCambridge University PressAnnals of Glaciology0260-30551727-56442020-12-016127128310.1017/aog.2020.46Fast Ice Prediction System (FIPS) for land-fast sea ice at Prydz Bay, East Antarctica: an operational service for CHINAREJiechen Zhao0Bin Cheng1https://orcid.org/0000-0001-8156-8412Timo Vihma2Petra Heil3Fengming Hui4Qi Shu5https://orcid.org/0000-0003-4781-571XLin Zhang6Qinghua Yang7https://orcid.org/0000-0002-7114-2036Key Laboratory of Marine Hazards Forecasting, National Marine Environmental Forecasting Centre (NMEFC), Ministry of Natural Resources, Beijing 100081, China Laboratory for Regional Oceanography and Numerical Modelling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, ChinaFinnish Meteorological Institute (FMI), Helsinki 00101, FinlandFinnish Meteorological Institute (FMI), Helsinki 00101, FinlandAustralia Antarctic Division & Australian Antarctic Programmer Partnership, Private Bag 80, Hobart, TAS 7001, AustraliaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, ChinaLaboratory for Regional Oceanography and Numerical Modelling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, ChinaKey Laboratory of Marine Hazards Forecasting, National Marine Environmental Forecasting Centre (NMEFC), Ministry of Natural Resources, Beijing 100081, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China School of Atmospheric Sciences, and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai 519082, ChinaA Fast Ice Prediction System (FIPS) was constructed and is the first regional land-fast sea-ice forecasting system for the Antarctic. FIPS had two components: (1) near-real-time information on the ice-covered area from MODIS and SAR imagery that revealed, tidal cracks, ridged and rafted ice regions; (2) a high-resolution 1-D thermodynamic snow and ice model (HIGHTSI) that was extended to perform a 2-D simulation on snow and ice evolution using atmospheric forcing from ECMWF: either using ERA-Interim reanalysis (in hindcast mode) or HERS operational 10-day predictions (in forecast mode). A hindcast experiment for the 2015 season was in good agreement with field observations, with a mean bias of 0.14 ± 0.07 m and a correlation coefficient of 0.98 for modeled ice thickness. The errors are largely caused by a cold bias in the atmospheric forcing. The thick snow cover during the 2015 season led to modeled formation of extensive snow ice and superimposed ice. The first FIPS operational service was performed during the 2017/18 season. The system predicted a realistic ice thickness and onset of snow surface melt as well as the area of internal ice melt. The model results on the snow and ice properties were considered by the captain of R/V Xuelong when optimizing a low-risk route for on-ice transportation through fast ice to the coastal Zhongshan Station.https://www.cambridge.org/core/product/identifier/S0260305520000464/type/journal_articleAntarcticaland-fast sea iceoperational servicePrydz Baysnow and ice thicknessthermodynamic modeling |
| spellingShingle | Jiechen Zhao Bin Cheng Timo Vihma Petra Heil Fengming Hui Qi Shu Lin Zhang Qinghua Yang Fast Ice Prediction System (FIPS) for land-fast sea ice at Prydz Bay, East Antarctica: an operational service for CHINARE Annals of Glaciology Antarctica land-fast sea ice operational service Prydz Bay snow and ice thickness thermodynamic modeling |
| title | Fast Ice Prediction System (FIPS) for land-fast sea ice at Prydz Bay, East Antarctica: an operational service for CHINARE |
| title_full | Fast Ice Prediction System (FIPS) for land-fast sea ice at Prydz Bay, East Antarctica: an operational service for CHINARE |
| title_fullStr | Fast Ice Prediction System (FIPS) for land-fast sea ice at Prydz Bay, East Antarctica: an operational service for CHINARE |
| title_full_unstemmed | Fast Ice Prediction System (FIPS) for land-fast sea ice at Prydz Bay, East Antarctica: an operational service for CHINARE |
| title_short | Fast Ice Prediction System (FIPS) for land-fast sea ice at Prydz Bay, East Antarctica: an operational service for CHINARE |
| title_sort | fast ice prediction system fips for land fast sea ice at prydz bay east antarctica an operational service for chinare |
| topic | Antarctica land-fast sea ice operational service Prydz Bay snow and ice thickness thermodynamic modeling |
| url | https://www.cambridge.org/core/product/identifier/S0260305520000464/type/journal_article |
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