A. Fujisaki‐Manome, Haoguo Hu, Jia Wang, J. Westerink, D. Wirasaet, Guoming Ling, Mindo Choi, Saeed Moghimi, Edward Myers, Ali Abdolali, Clint Dawson, Carol Janzen
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引用次数: 0
Abstract
In Alaska’s coastal environment, accurate information of sea ice conditions is desired by operational forecasters, emergency managers, and responders. Complicated interactions among atmosphere, waves, ocean circulation, and sea ice collectively impact the ice conditions, intensity of storm surges and flooding, making accurate predictions challenging. A collaborative work to build the Alaska Coastal Ocean Forecast System established an integrated storm surge, wave, and sea ice model system for the coasts of Alaska, where the verified model components are linked using the Earth System Modeling Framework and the National Unified Operational Prediction Capability. We present the verification of the sea ice model component based on the Los Alamos Sea Ice model version 6. The regional, high resolution (3 km) configuration of the model was forced by operational atmospheric and ocean model outputs. Extensive numerical experiments were conducted for December 2018 to August 2020 to verify the model’s capability to represent detailed nearshore and offshore sea ice behavior, including landfast ice, ice thickness, and evolution of air-ice drag coefficient. Comparisons of the hindcast simulations with the observations of ice extent presented the model’s comparable performance with the Global Ocean Forecast System 3.1 (GOFS3.1). The model’s skill in reproducing landfast ice area significantly outperformed GOFS3.1. Comparison of the modeled sea ice freeboard with the Ice, Cloud and land Elevation Satellite-2 product showed a mean bias of -4.6 cm. Daily 5-day forecast simulations for October 2020-August 2021 presented the model’s promising performance for future implementation in the coupled model system.
期刊介绍:
Weather and Forecasting (WAF) (ISSN: 0882-8156; eISSN: 1520-0434) publishes research that is relevant to operational forecasting. This includes papers on significant weather events, forecasting techniques, forecast verification, model parameterizations, data assimilation, model ensembles, statistical postprocessing techniques, the transfer of research results to the forecasting community, and the societal use and value of forecasts. The scope of WAF includes research relevant to forecast lead times ranging from short-term “nowcasts” through seasonal time scales out to approximately two years.