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  • 标题:Ensemble forecasting greatly expands the prediction horizon for ocean mesoscale variability
  • 本地全文:下载
  • 作者:Prasad G. Thoppil ; Sergey Frolov ; Clark D. Rowley
  • 期刊名称:Communications Earth & Environment
  • 电子版ISSN:2662-4435
  • 出版年度:2021
  • 卷号:2
  • 期号:1
  • 页码:1-9
  • DOI:10.1038/s43247-021-00151-5
  • 语种:English
  • 出版社:Nature Research
  • 摘要:Mesoscale eddies dominate energetics of the ocean, modify mass, heat and freshwater transport and primary production in the upper ocean. However, the forecast skill horizon for ocean mesoscales in current operational models is shorter than 10 days: eddy-resolving ocean models, with horizontal resolution finer than 10 km in mid-latitudes, represent mesoscale dynamics, but mesoscale initial conditions are hard to constrain with available observations. Here we analyze a suite of ocean model simulations at high (1/25) and lower (1/12.5) resolution and compare with an ensemble of lower-resolution simulations. We show that the ensemble forecast significantly extends the predictability of the ocean mesoscales to between 20 and 40 days. We find that the lack of predictive skill in data assimilative deterministic ocean models is due to high uncertainty in the initial location and forecast of mesoscale features. Ensemble simulations account for this uncertainty and filter-out unconstrained scales. We suggest that advancements in ensemble analysis and forecasting should complement the current focus on high-resolution modeling of the ocean. Forecasts of oceanic mesoscale variability, such as fronts and eddies, can be extended significantly by accounting for uncertainties in initial conditions, according to ensemble simulations of ocean models that filter out unconstrained scales.
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