Improved Arctic Ocean heat and freshwater transport and climate prediction by an interactive thin- and thick- ice data assimilation in an OGCM

2020 Fiscal Year Final Research Report

• Project/Area Number: 16K17805
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Meteorology/Physical oceanography/Hydrology
• Research Institution: Japan, Meteorological Research Institute
• Principal Investigator: Toyoda Takahiro 気象庁気象研究所, 全球大気海洋研究部, 主任研究官 (90450775)
• Project Period (FY): 2016-04-01 – 2021-03-31
• Keywords: 海氷 / 薄氷 / データ同化 / 北極海 / 水塊形成 / 再解析 / 南極海 / 予測

Outline of Final Research Achievements

A new method was introduced for constraining an ocean general circulation model by thin ice coverage and thickness retrievals from satellite observations. This approach impacted key parameters in the ocean-sea ice simulation, such as sea ice thickness, mixed layer depth, and surface salinity. In addition, schemes reflecting observational data were constructed: albedos of sea ice and snow on it in the melting season based on observations; adjoint system including sea ice dynamics which propagates sensitivities of model-observation misfits backward in time. These results were published in international peer-review journals. The enhanced ocean-sea ice reanalysis is now used in a coupled atmosphere-ocean-sea ice experiment and process study for enhancing our understanding and prediction of the Arctic Ocean climate.

Free Research Field

海洋物理学

Academic Significance and Societal Importance of the Research Achievements

まず、衛星観測から得られていた海氷形成域における薄氷情報が、海氷シミュレーションを大きく改善することを示すことが出来た。これは現状のモデルの改善の方向性を示すとともにデータ同化のアプローチの有効性を示唆し、初期値化・再解析に活用できる知見である。また本科研費の枠組みで更なる観測とモデルの融合的研究を進め、海氷データ同化の基盤を発展させることが出来た。成果は学会や国際誌での発表を通じて、世界の研究者と共有・議論を行った。現在、このシステムを用いて行っている大気・海洋・海氷結合予測実験やプロセス研究は北極海気候の理解・予測に更に貢献することが期待できる。