The internal-wave (IW) continuum of a regional ocean model is studied in terms of the vertical spectral kinetic-energy (KE) fluxes and transfers at high vertical wavenumbers. Previous work has shown that this model permits a partial representation of the IW cascade. In this work, vertical spectral KE flux is decomposed into catalyst, source, and destination frequency bands of nonlinear scattering, a framework that allows for the discernment of different types of nonlinear interactions involving both waves and eddies. Energy transfer within the supertidal IW continuum is found to be strongly dependent on horizontal resolution. Specifically, at a horizontal grid spacing of 1/48-degrees, the vast majority of KE in the supertidal continuum arrives there from lower frequency modes through a single nonlinear interaction, while at 1/384-degrees KE transfers within the supertidal IW continuum are comparable in size to KE transfer from lower-frequency modes. Additionally, comparisons are made with existing theoretical and observational work on energy pathways in the IW continuum. Induced diffusion (ID) is found to be associated with a weak forward frequency transfer within the supertidal IW continuum. Spectrally local interactions are found to play an insignificant role within the model evolution. At the same time, ID-like processes involving high vertical-wavenumber near-inertial and tidal waves as well as low-vertical-wavenumber eddy fields are substantial, suggesting that the processes giving rise to a Garrett-Munk-like spectra in the present numerical simulation and perhaps the real ocean may be more varied than in idealized or wave-only frameworks.
Borey: A High-Resolution Regional Atmosphere-Ocean-Sea Ice-Wave Forecasting System and Hindcast Dataset for the Barents and Kara Seas
Skolkovo Institute of Science and Technology（斯科尔科沃科学技术学院）；Shirshov Institute of Oceanology, Russian Academy of Sciences（俄罗斯科学院谢尔肖夫海洋研究所）；Moscow Institute of Physics and Technology（莫斯科物理技术学院）；Autonomous Non-Profit Organization Artificial Intelligence Research Institute (AIRI)（人工智能研究院（AIRI））
Wind, wave and current interactions appear key for quantifying cross-shelf transport and carbon export; new knowledge and the potential of SKIM to enable monitoring
Exascale Hybrid Numerical-AI Ensembles for Operational Flood-Season Forecasting in East Asia: 15-km Decadal Hindcasts and 1-km High-Resolution Capability
Tsinghua University（清华大学）；Sun Yat-Sen University（中山大学）；Jiangsu Provincial Meteorol. Bureau（江苏省气象局）；Beijing Normal University（北京师范大学）；Qinghai University（青海大学）；National Supercomputing Center in Wuxi（无锡国家超级计算中心）；National Supercomputing Center in Shenzhen（深圳国家超级计算中心）；CMA Earth System Modeling and Prediction Center（中国气象局地球系统模式与预报中心）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）
