Advances in Seasonal Predictions of Arctic Sea Ice With NOAA UFS. Issue 7 (30th March 2023)

• Record Type: Journal Article
• Authors: Zhu, Jieshun; Wang, Wanqiu; Liu, Yanyun; Kumar, Arun; DeWitt, David
• Is Part Of: Geophysical research letters. Volume 50:Issue 7(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-03-30
• Subjects: UFS -- seasonal prediction -- Arctic sea ice; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2022GL102392
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: The Unified Forecast System (UFS) is the next generation modeling infrastructure under development for NOAA's operational numerical weather/climate predictions. This study is the first attempt with UFS for seasonal predictions application. In particular, 9‐month hindcasts are performed starting from every month during 2007–2020. The UFS performance in predicting Arctic sea ice was compared to hindcasts by (a) the current operational Climate Forecast System version 2 (CFSv2) and (b) an experimental sea ice prediction system (CFSm5) at NOAA. Evaluations indicate that UFS demonstrates consistently improved skills than both CFSv2 and CFSm5 in seasonal sea ice predictions, together with more realistic climatological sea ice distributions. Diagnostics suggest that the better climatological sea ice distributions in UFS is related to its atmospheric states simulated with FV3, the atmospheric component of UFS, and reinforced by associated ocean circulations. In addition, applications of the multi‐model ensemble strategy do not present skill improvements over the UFS forecasts alone. Plain Language Summary: Arctic sea‐ice cover illustrates significant year‐to‐year fluctuations superimposed on the long‐term decline trend. Seasonal forecasts of the ice interannual fluctuations could play an important role in providing planning information for shipping industries, improving management of ocean and coastal resources in the Arctic, and better serving Northern communities. In this study, we evaluated the capability of the Unified Forecast System (UFS) in predicting the Arctic sea ice coverage. The UFS is the next generation modeling infrastructure under development for NOAA's operational numerical weather/climate predictions, which has not been tried with seasonal predictions application before. Evaluations suggested that UFS demonstrates consistently improved skills in seasonal sea ice predictions than two systems currently in operations at NOAA, together with more realistic climatological sea ice distributions. Our further diagnostics suggest that the improvement is mainly related to the atmospheric states simulated with UFS, but is also reinforced by associated ocean circulations. Key Points: This work is the first attempt with the Unified Forecast System (UFS) for seasonal predictions UFS presents better performance in seasonal prediction of Arctic sea ice than current operational systems at NOAA Better sea ice predictions with UFS are mainly related to its better representation of atmospheric states