Improvement of Arctic Sea Ice Multi-Parameter Assimilation on Sea Ice Concentration Simulation

Based on the CICE sea ice model and the PDAF parallel data assimilation framework, this paper uses the local error subspace transform Kalman filter method (LESTKF) to assimilate the sea ice concentration, sea ice thickness and sea ice freeboard data into the model, and designs experiments to study t...

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Main Authors: ZHANG Sihan, ZHAO Jiechen, ZOU Wenfeng, WU Jie, WANG Yingzheng, CHEN Ziyi, ZHAO Dinglong, MU Fangru
Format: Article
Language:zho
Published: Editorial Office of Ocean Development and Management 2024-06-01
Series:Haiyang Kaifa yu guanli
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Online Access:http://www.haiyangkaifayuguanli.com/hykfyglen/ch/reader/view_abstract.aspx?file_no=20240601&flag=1
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author ZHANG Sihan
ZHAO Jiechen
ZOU Wenfeng
WU Jie
WANG Yingzheng
CHEN Ziyi
ZHAO Dinglong
MU Fangru
author_facet ZHANG Sihan
ZHAO Jiechen
ZOU Wenfeng
WU Jie
WANG Yingzheng
CHEN Ziyi
ZHAO Dinglong
MU Fangru
author_sort ZHANG Sihan
collection DOAJ
description Based on the CICE sea ice model and the PDAF parallel data assimilation framework, this paper uses the local error subspace transform Kalman filter method (LESTKF) to assimilate the sea ice concentration, sea ice thickness and sea ice freeboard data into the model, and designs experiments to study the improvement of multi-parameter assimilation on the simulation of Arctic sea ice concentration and range. The results show that data assimilation has a good improvement effect on the simulation of Arctic sea ice concentration and range. The average deviation, root mean square error and mean absolute error of the assimilation experiment are significantly reduced compared with the control experiment. The assimilation experiment improves the simulation of sea ice concentration and range most obviously in summer. Multi-parameter assimilation can improve the prediction accuracy and reliability of Arctic sea ice change.
format Article
id doaj-art-9e0701271c3d46b690de8e9d5f3fc239
institution OA Journals
issn 1005-9857
language zho
publishDate 2024-06-01
publisher Editorial Office of Ocean Development and Management
record_format Article
series Haiyang Kaifa yu guanli
spelling doaj-art-9e0701271c3d46b690de8e9d5f3fc2392025-08-20T02:14:35ZzhoEditorial Office of Ocean Development and ManagementHaiyang Kaifa yu guanli1005-98572024-06-014163141005-9857(2024)06-0003-12Improvement of Arctic Sea Ice Multi-Parameter Assimilation on Sea Ice Concentration SimulationZHANG Sihan0ZHAO Jiechen1ZOU Wenfeng2WU Jie3WANG Yingzheng4CHEN Ziyi5ZHAO Dinglong6MU Fangru7Qingdao Innovation Development Base of Harbin Engineering University, Qingdao 266000, ChinaQingdao Innovation Development Base of Harbin Engineering University, Qingdao 266000, ChinaCOSCO Shipping (Guangzhou) Co., Ltd., Guangzhou 510220, ChinaCOSCO Shipping Specialized Carriers Co., Ltd., Guangzhou 510220, ChinaCOSCO Shipping (Guangzhou) Co., Ltd., Guangzhou 510220, ChinaQingdao Innovation Development Base of Harbin Engineering University, Qingdao 266000, ChinaQingdao Innovation Development Base of Harbin Engineering University, Qingdao 266000, ChinaQingdao Innovation Development Base of Harbin Engineering University, Qingdao 266000, ChinaBased on the CICE sea ice model and the PDAF parallel data assimilation framework, this paper uses the local error subspace transform Kalman filter method (LESTKF) to assimilate the sea ice concentration, sea ice thickness and sea ice freeboard data into the model, and designs experiments to study the improvement of multi-parameter assimilation on the simulation of Arctic sea ice concentration and range. The results show that data assimilation has a good improvement effect on the simulation of Arctic sea ice concentration and range. The average deviation, root mean square error and mean absolute error of the assimilation experiment are significantly reduced compared with the control experiment. The assimilation experiment improves the simulation of sea ice concentration and range most obviously in summer. Multi-parameter assimilation can improve the prediction accuracy and reliability of Arctic sea ice change.http://www.haiyangkaifayuguanli.com/hykfyglen/ch/reader/view_abstract.aspx?file_no=20240601&flag=1arctic sea icedata assimilationcicepdafsea ice concentrationsea ice extent
spellingShingle ZHANG Sihan
ZHAO Jiechen
ZOU Wenfeng
WU Jie
WANG Yingzheng
CHEN Ziyi
ZHAO Dinglong
MU Fangru
Improvement of Arctic Sea Ice Multi-Parameter Assimilation on Sea Ice Concentration Simulation
Haiyang Kaifa yu guanli
arctic sea ice
data assimilation
cice
pdaf
sea ice concentration
sea ice extent
title Improvement of Arctic Sea Ice Multi-Parameter Assimilation on Sea Ice Concentration Simulation
title_full Improvement of Arctic Sea Ice Multi-Parameter Assimilation on Sea Ice Concentration Simulation
title_fullStr Improvement of Arctic Sea Ice Multi-Parameter Assimilation on Sea Ice Concentration Simulation
title_full_unstemmed Improvement of Arctic Sea Ice Multi-Parameter Assimilation on Sea Ice Concentration Simulation
title_short Improvement of Arctic Sea Ice Multi-Parameter Assimilation on Sea Ice Concentration Simulation
title_sort improvement of arctic sea ice multi parameter assimilation on sea ice concentration simulation
topic arctic sea ice
data assimilation
cice
pdaf
sea ice concentration
sea ice extent
url http://www.haiyangkaifayuguanli.com/hykfyglen/ch/reader/view_abstract.aspx?file_no=20240601&flag=1
work_keys_str_mv AT zhangsihan improvementofarcticseaicemultiparameterassimilationonseaiceconcentrationsimulation
AT zhaojiechen improvementofarcticseaicemultiparameterassimilationonseaiceconcentrationsimulation
AT zouwenfeng improvementofarcticseaicemultiparameterassimilationonseaiceconcentrationsimulation
AT wujie improvementofarcticseaicemultiparameterassimilationonseaiceconcentrationsimulation
AT wangyingzheng improvementofarcticseaicemultiparameterassimilationonseaiceconcentrationsimulation
AT chenziyi improvementofarcticseaicemultiparameterassimilationonseaiceconcentrationsimulation
AT zhaodinglong improvementofarcticseaicemultiparameterassimilationonseaiceconcentrationsimulation
AT mufangru improvementofarcticseaicemultiparameterassimilationonseaiceconcentrationsimulation