In the present study, we performed a 53-year wave hindcast (1970-2022) for a significant portion of the South China Sea (SCS) with an unstructured mesh that reaches considerably high resolution along the coasts of the Guangdong province (China). The adopted modeling approach is based on the fully two-way coupled SCHISM-WWMIII numerical suite. The model was forced with ERA5 wind velocities that were compared to IFREMER altimeter wind velocities and then bias-corrected for a more accurate treatment of the wind component. Eight major tidal harmonics extracted from FES2014 were imposed to the open boundaries. After a preliminary mesh independence analysis, the model results have been validated against satellite altimeter observations retrieved from the European Space Agency database spanning the period from 1992 to 2019. Moreover, 28 year in-situ measurements from two coastal wave buoys and data from four tidal gauge stations (approximately 20 years) were used to test the nearshore skills of the model. Several statistical indicators have been used to evaluate the offshore and nearshore performance of the model results in terms of the main wave parameters (significant wave height, peak wave period, mean wave direction) and water levels. All statistical metrics suggest that the present hindcast improved the predictions of waves and water levels compared to previous datasets, especially in the coastal regions. The high spatial resolution together with a full coupling allowed the model to capture and simulate processes that are induced by the non-linear interactions between waves and currents, especially nearshore.
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））
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）
Spatiotemporal continuous estimates of daily 1-km PM2.5 from 2000 to present under the Tracking Air Pollution in China (TAP) framework
因此，迫切需要覆盖较长时间段的高空间分辨率PM2.5数据，以支持人口暴露评估和精细化空气质量管理。本文在TAP（Tracking Air Pollution in China，http：//tapdata.org.cn/）框架下，对2000年至今的PM2.5进行了空间分辨率为1 km的全覆盖预测。为了支持高空间分辨率建模，我们收集了来自国家和地方监测站的PM2.5测量值。为了正确反映影响PM2.5局部变化的土地覆盖特征的时间变化，我们构建了2000 - 2021年中国连续的年度地理信息数据集，包括道路图和集合网格人口图。我们还研究了各种模型结构和预测器组合，以平衡计算成本和模型性能。最终的模型融合了10公里TAP PM2.5预测从我们以前的工作，1公里卫星气溶胶光学深度反演和土地利用参数与随机森林模型。我们的年度模型的开箱R2范围在0.80和0.84之间，我们的后报模型的年度交叉验证R2为0.76。这一开放获取的1公里分辨率PM2.5数据产品覆盖面广，成功揭示了PM2.5在局地尺度上的空间变化，有利于环境研究和政策制定。
Bayesian Optimization for reanalysis and calibration of highly energetic sea state events simulated with a spectral third-generation wave model
EDF R&D, National Laboratory for Hydraulics and Environment (LNHE)（法国电力集团研发部，国家水力学与环境实验室（LNHE））；Saint-Venant Hydraulics Laboratory, LHSV, ENPC, Institut Polytechnique de Paris（圣维南水力学实验室，ENPC，巴黎理工学院）
Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China
Yunnan Key Laboratory of Complex Systems and Brain-Inspired Intelligence, Kunming University of Science and Technology（云南复杂系统与脑启发智能重点实验室，昆明理工大学）；Faculty of Science, Kunming University of Science and Technology（昆明理工大学理学院）
Generation of second-mode internal solitary waves during the winter by a shoaling internal tide in the northern South China Sea
Yang et al.（2009）报道了冬季在南海北部上大陆坡对第二模式内孤立波（模式-2 ISW）的现场测量结果，但其生成机制仍不清楚。我们研究了这个问题，多模态的演变模型和理论分析，这表明，所观察到的模式2 ISW所产生的浅滩模式2半日内潮（IT），从吕宋海峡。结果表明，两组模式2的ISW通常出现在一个半日潮周期内，先后骑在扩张和随后压缩的Pyceros线。波群的数量在很大程度上取决于IT的振幅;也就是说，较大的IT产生较大的模式2 ISW。此外，模间耦合占主导地位的模式-1 IT的演变，突出了考虑模式散射的传播中的低模式IT的重要性。
Formation and evolution of turbulence in convectively unstable internal solitary waves of depression shoaling over gentle slopes in the South China Sea
Cornell University（康奈尔大学）；University of Washington（华盛顿大学）；University of Waterloo（滑铁卢大学）；Wandering Wakhs Research（Wandering Wakhs 研究）
Courant Institute School of Mathematics, Computing and Data Science（库朗数学、计算与数据科学学院）；New York University（纽约大学）；Laboratoire d’Océanographie Physique et Spatiale (LOPS)（物理与空间海洋学实验室）；Ifremer
