An Improved Parameterization of Wind-Driven Turbulent Vertical Mixing Based on an Eddy-Resolving Climate Model

JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS(2021)

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摘要
Turbulent vertical mixing in the stratified ocean interior has a huge impact on global ocean circulations and the climate system. Although parameterizations of vertical mixing furnished by internal tides have been built into state-of-the-art coupled global climate models (CGCMs), efforts in parameterizing wind-driven vertical mixing in CGCMs are still limited. In this study, we apply a modified finescale parameterization (MFP) to an eddy-resolving Community Earth System Model (CESM) to represent the wind's contribution to vertical mixing in the stratified ocean interior. The spatial pattern of the MFP-parameterized wind-driven vertical mixing in the thermocline agrees with the observation derived from the finestructure measurements of Argo floats, reproducing the enhanced values in the Kuroshio, Gulf Stream extensions, and the Southern Ocean where the winds inject great amount of energy into the internal wave field. The MFP also captures the observed seasonal variation of wind-driven vertical mixing in the thermocline of these regions that exhibits enhancement and weakening in winter and summer, respectively. Application of the MFP to a non-eddy-resolving CESM fails to reproduce the observed wind-driven vertical mixing. Specifically, the magnitude of parameterized wind-driven vertical mixing in the thermocline of Kuroshio, Gulf Stream extensions, and the Southern Ocean is systemically smaller than those in the observation and eddy-resolving CESM; so is the case for the amplitude of seasonal cycle. The results highlight the benefit of eddy-resolving CESM compared to its standard-resolution counterpart in parameterizing the wind-driven vertical mixing and provide insight into developing parameterizations for wind-driven vertical mixing in eddy-resolving CGCMs.
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关键词
ocean modeling, turbulent mixing, finescale parameterization, near-inertial internal waves, coupled global climate model, high resolution
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