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北极海冰短期预报和中长期预估模式研究进展

Study of short term forecast and medium-long term prediction of Arctic sea ice:A review
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摘要 在全球气候变暖的背景下,北极海冰的快速变化对北冰洋的自然环境、水文状况、生态系统等均产生显著的影响。作为全球气候变化的重要指示器,加强对北极海冰未来变化的精确预估将增进对北极乃至全球气候变化趋势的理解和认识。当前,数值模式是有效预估海冰未来变化的主要手段之一,然而由于影响模式准确度的因素众多,模式之间的结果差异较大。因此,本文梳理了目前国内外有关北冰洋短期预报以及中长期预估模式的研究进展,着重对各类模式在北极海冰的密集度、覆盖范围和面积、厚度以及漂移速度等关键要素的模拟精度进行研究,分析了当前模式对北极海冰未来变化趋势的预估,并展望了数值模式在北极海冰预估方面的研究与应用前景。 In the current global warming context,rapid changes in Arctic sea ice have a significant impact on the environment,the hydrological conditions and ecosystems of the Arctic Ocean.As an important indicator of global climate change,accurate predictions of future changes in Arctic sea ice contribute to the understanding and awareness of climate change trends in the Arctic and even globally.At present,numerical models are one of the most important means to effectively estimate future changes in sea ice,but due to the many factors affecting the accuracy of the patterns,the estimated results between the models vary greatly.Therefore,this paper sorted out the current research progress on short term forecast and medium-long term prediction models of the Arctic Ocean at home and abroad,focusing on the simulation accuracy of the key elements in the Arctic sea ice such as the concentration,extent and area,thickness and drift speed of various models.It analyzed the prediction of the future change trend of Arctic sea ice in the current stage of the model.In addition,on the basis of previous research,the research and application of future numerical models in the prediction of Arctic Ocean sea ice are prospected.
作者 查宇凡 张瑜 陈长胜 徐丹亚 Zha Yufan;Zhang Yu;Chen Changsheng;Xu Danya(College of Marine Sciences,Shanghai Ocean University,Shanghai 201306,China;Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China;School for Marine Science and Technology,University of Massachusetts Dartmouth,New Bedford,Massachusetts 02744,USA)
出处 《极地研究》 CAS CSCD 北大核心 2023年第3期440-459,共20页 Chinese Journal of Polar Research
基金 国家重点研发计划(2019YFA0607001) 上海市自然科学基金(22ZR1427400) 国家自然科学基金(42130402,41706210) 南方海洋科学与工程广东省实验室(珠海)创新团队建设项目(311021009)资助。
关键词 北极 海冰 预报 预估 模式 Arctic sea ice forecast prediction model
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