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Initialized Earth System prediction from subseasonal to decadal timescales
Nature Reviews Earth & Environment ( IF 42.1 ) Pub Date : 2021-04-13 , DOI: 10.1038/s43017-021-00155-x
Gerald A. Meehl , Jadwiga H. Richter , Haiyan Teng , Antonietta Capotondi , Kim Cobb , Francisco Doblas-Reyes , Markus G. Donat , Matthew H. England , John C. Fyfe , Weiqing Han , Hyemi Kim , Ben P. Kirtman , Yochanan Kushnir , Nicole S. Lovenduski , Michael E. Mann , William J. Merryfield , Veronica Nieves , Kathy Pegion , Nan Rosenbloom , Sara C. Sanchez , Adam A. Scaife , Doug Smith , Aneesh C. Subramanian , Lantao Sun , Diane Thompson , Caroline C. Ummenhofer , Shang-Ping Xie

Initialized Earth System predictions are made by starting a numerical prediction model in a state as consistent as possible to observations and running it forward in time for up to 10 years. Skilful predictions at time slices from subseasonal to seasonal (S2S), seasonal to interannual (S2I) and seasonal to decadal (S2D) offer information useful for various stakeholders, ranging from agriculture to water resource management to human and infrastructure safety. In this Review, we examine the processes influencing predictability, and discuss estimates of skill across S2S, S2I and S2D timescales. There are encouraging signs that skilful predictions can be made: on S2S timescales, there has been some skill in predicting the Madden–Julian Oscillation and North Atlantic Oscillation; on S2I, in predicting the El Niño–Southern Oscillation; and on S2D, in predicting ocean and atmosphere variability in the North Atlantic region. However, challenges remain, and future work must prioritize reducing model error, more effectively communicating forecasts to users, and increasing process and mechanistic understanding that could enhance predictive skill and, in turn, confidence. As numerical models progress towards Earth System models, initialized predictions are expanding to include prediction of sea ice, air pollution, and terrestrial and ocean biochemistry that can bring clear benefit to society and various stakeholders.



中文翻译:

从次季节到十年时间尺度的初始化地球系统预测

通过在与观测尽可能一致的状态下启动数值预测模型并及时运行长达10年,来进行地球系统的初始预测。从亚季节到季节(S2S),季节到年际(S2I)和季节到十年(S2D)的时间段的熟练预测可以为各种利益相关者提供有用的信息,从农业到水资源管理再到人类和基础设施安全。在本评论中,我们检查了影响可预测性的过程,并讨论了跨S2S,S2I和S2D时标的技能估计。有令人鼓舞的迹象表明可以做出熟练的预测:在S2S时标上,有一些技巧可以预测Madden–Julian涛动和北大西洋涛动;在S2I上,预测厄尔尼诺-南方涛动;在S2D上,预测北大西洋地区海洋和大气的变化。但是,挑战仍然存在,未来的工作必须优先考虑减少模型错误,更有效地将预测传达给用户以及增加流程和机制的理解,从而增强预测技能,进而增强信心。随着数值模型向地球系统模型的发展,初始化的预测正在扩展,包括对海冰,空气污染以及可以为社会和各种利益相关者带来明显收益的海陆生化的预测。以及增加过程和机制的理解,可以增强预测技能,进而增强信心。随着数值模型向地球系统模型的发展,初始化的预测正在扩展,包括对海冰,空气污染以及可以为社会和各种利益相关者带来明显收益的海陆生化的预测。以及增加过程和机制的理解,可以增强预测技能,进而增强信心。随着数值模型向地球系统模型的发展,初始化的预测正在扩展,包括对海冰,空气污染以及可以为社会和各种利益相关者带来明显收益的海陆生化的预测。

更新日期:2021-04-13
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