Advanced sea ice modeling for short-term forecasting for Alaska’s coasts

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Weather and Forecasting Pub Date : 2024-03-06 DOI:10.1175/waf-d-23-0178.1
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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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.
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用于阿拉斯加沿岸短期预测的先进海冰模型
在阿拉斯加的沿海环境中,业务预报员、应急管理人员和救灾人员都希望获得准确的海冰状况信息。大气、波浪、海洋环流和海冰之间复杂的相互作用共同影响着冰的状况、风暴潮和洪水的强度,使得准确预测具有挑战性。建立阿拉斯加沿海海洋预报系统的合作工作为阿拉斯加沿海建立了一个风暴潮、海浪和海冰综合模型系统,其中经过验证的模型组件利用地球系统建模框架和国家统一业务预测能力连接起来。我们介绍了基于洛斯阿拉莫斯海冰模型第 6 版的海冰模型组件的验证情况。该模式的区域性高分辨率(3 公里)配置是由大气和海洋模式的运行输出所驱动的。在 2018 年 12 月至 2020 年 8 月期间进行了广泛的数值实验,以验证该模型表现近岸和离岸海冰详细行为的能力,包括陆冰、冰厚度和气冰阻力系数的演变。后报模拟结果与冰面观测结果的比较表明,该模式的性能与全球海洋预报系统 3.1(GOFS3.1)相当。该模式在再现陆冰面积方面的能力明显优于 GOFS3.1。将模拟的海冰自由板与冰云陆地高程卫星-2 产品进行比较,结果显示平均偏差为-4.6 厘米。2020 年 10 月至 2021 年 8 月的每日 5 天预报模拟显示,该模式的性能很有希望在未来的耦合模式系统中得到应用。
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来源期刊
Weather and Forecasting
Weather and Forecasting 地学-气象与大气科学
CiteScore
5.20
自引率
17.20%
发文量
131
审稿时长
6-12 weeks
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.
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