{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:54:57Z","timestamp":1760147697391,"version":"build-2065373602"},"reference-count":46,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,25]],"date-time":"2023-02-25T00:00:00Z","timestamp":1677283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"],"award-info":[{"award-number":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Basic Scientific Fund for National Public Research Institute of China","award":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"],"award-info":[{"award-number":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"]}]},{"name":"National Natural Science Foundation of China","award":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"],"award-info":[{"award-number":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"]}]},{"name":"National Natural Science Foundation of China","award":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"],"award-info":[{"award-number":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"]}]},{"name":"Shandong Provincial Natural Science Foundation","award":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"],"award-info":[{"award-number":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"]}]},{"name":"Variation of Arctic Sea Ice Age and Its Relationship with Atmospheric Circulation Field","award":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"],"award-info":[{"award-number":["2017YFA0603102","2019S06","41821004","42175172","41975134","ZR2022QD070","PY112101"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To understand the Arctic environment, which is closely related to sea ice and to reduce potential risks, reliable sea ice forecasts are indispensable. A practical, lightweight yet effective assimilation scheme of sea ice concentration based on Optimal Interpolation is designed and adopted in an operational global 1\/10\u00b0 surface wave-tide-circulation coupled ocean model (FIO-COM10) forecasting system to improve Arctic sea ice forecasting. Twin numerical experiments with and without data assimilation are designed for the simulation of the year 2019, and 5-day real-time forecasts for 2021 are implemented to study the sea ice forecast ability. The results show that the large biases in the simulation and forecast of sea ice concentration are remarkably reduced due to satellite observation uncertainty levels by data assimilation, indicating the high efficiency of the data assimilation scheme. The most significant improvement occurs in the marginal ice zones. The sea surface temperature bias averaged over the marginal ice zones is also reduced by 0.9 \u00b0C. Sea ice concentration assimilation has a profound effect on improving forecasting ability. The Root Mean Square Error and Integrated Ice-Edge Error are reduced to the level of the independent satellite observation at least for 24-h forecast, and sea ice forecast by FIO-COM10 has better performance than the persistence forecasts in summer and autumn.<\/jats:p>","DOI":"10.3390\/rs15051274","type":"journal-article","created":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T01:59:10Z","timestamp":1677463150000},"page":"1274","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Arctic Sea Ice Concentration Assimilation in an Operational Global 1\/10\u00b0 Ocean Forecast System"],"prefix":"10.3390","volume":"15","author":[{"given":"Qiuli","family":"Shao","sequence":"first","affiliation":[{"name":"Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, China"},{"name":"Shandong Provincial Key Laboratory of Marine Monitoring Instrument Equipment Technology, Qingdao 266061, China"},{"name":"National Engineering and Technological Research Center of Marine Monitoring Equipment, Qingdao 266061, China"}]},{"given":"Qi","family":"Shu","sequence":"additional","affiliation":[{"name":"First Institute of Oceanography, and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Maine Science and Technology, Qingdao 266237, China"},{"name":"Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China"}]},{"given":"Bin","family":"Xiao","sequence":"additional","affiliation":[{"name":"First Institute of Oceanography, and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Maine Science and Technology, Qingdao 266237, China"},{"name":"Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6299-3357","authenticated-orcid":false,"given":"Lujun","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China"}]},{"given":"Xunqiang","family":"Yin","sequence":"additional","affiliation":[{"name":"First Institute of Oceanography, and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Maine Science and Technology, Qingdao 266237, China"},{"name":"Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China"}]},{"given":"Fangli","family":"Qiao","sequence":"additional","affiliation":[{"name":"First Institute of Oceanography, and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Maine Science and Technology, Qingdao 266237, China"},{"name":"Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"881","DOI":"10.5194\/tc-6-881-2012","article-title":"Arctic sea ice variability and trends, 1979\u20132010","volume":"6","author":"Cavalieri","year":"2012","journal-title":"Cryosphere"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"L01703","DOI":"10.1029\/2007GL031972","article-title":"Accelerated decline in the Arctic sea ice cover","volume":"35","author":"Comiso","year":"2008","journal-title":"Geophys. 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