对巴西南部沿海和海洋地区的风浪进行集合后向预报

IF 4.2 2区 地球科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Gustavo Souza Correia , Leandro Farina , Claudia Klose Parise , Gabriel Bonow Münchow , Rita de Cássia M. Alves
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引用次数: 0

摘要

在使用波浪模式后向预报风暴事件波场时,结果的质量在很大程度上取决于几个因素,如计算网格的分辨率和大气强迫的精度。为了尽量减少这一过程中的不确定性,我们利用模拟近岸波浪(SWAN)模式和天气研究与预报模式(WRF)以及ERA5数据同化集合(ERA5 Ensemble of Data Assimilation,EDA)和确定性高分辨率系统的大气数据,建立了三个海洋波浪和海面风集合后报系统。为此,我们建立了三个集合系统:SWN-ERA5EDA 使用 ERA5-EDA 全球再分析风,SWN-WRFERA5 使用 WRF 对 ERA5-EDA 进行降尺度,SWN-WRFPPar 结合 WRF 多物理场运行进行动态降尺度。这项研究的重点是巴西南部在澳大利亚冬季发生的极端事件,强调了提高海洋波浪和海面风数据分辨率的重要性,以便为沿海和海洋活动提供更准确、更可靠的预报。我们的分析表明,与仅基于ERA5 EDA的波浪集合后报相比,利用WRF进行的大气降尺度不仅显著增加了集合传播,还提高了波浪集合后报的清晰度。具体而言,在格兰德河浮标位置,SWN-WRFERA5 系统的显著波高(Hs)比 SWN-ERA5 增加了 0.5,SWN-WRFPPar 系统的显著波高增加了 0.6。此外,SWN-WRFERA5 和 SWN-WRFPPar 系统的波峰周期(Tp)比 SWN-ERA5 增加了 1.2。此外,用 WRF 多物理场方法生成的集合捕捉到了浮标记录的显著波高的峰值,而其他集合系统无法再现这些峰值,这表明预测精度有所提高,尽管扩散和局部强波变化之间的相关性较小。除了量化后报误差,这项工作中提出的方法还提供了一种生成替代和改进的过去极端事件表征的方法。这种方法大大提高了我们对近期气候条件进行采样和扩大数据集进行统计分析的能力,这对海洋和海岸工程项目尤其有价值。这项研究强调了加强波浪建模中的计算和方法对更好地理解和减轻极端天气事件对沿海和海洋地区的影响的重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ensemble hindcasting of winds and waves for the coastal and oceanic region of Southern Brazil

When hindcasting wave fields of storm events with wave models, the quality of the results strongly depends on several factors such as the computational grid resolution and the accuracy of the atmospheric forcing. In an effort to minimize the uncertainties involved in this process, three ocean wave and surface wind ensemble hindcast systems were established using the Simulating WAves Nearshore (SWAN) model and Weather Research and Forecasting Model (WRF) with atmospheric data from ERA5 Ensemble of Data Assimilation (EDA) as well as deterministic high-resolution systems. We established three ensemble systems to tackle this: SWN-ERA5EDA using ERA5-EDA global reanalyses winds, SWN-WRFERA5 employing WRF downscaling of ERA5-EDA, and SWN-WRFPPar incorporating WRF multi-physics runs for dynamical downscaling. This study focuses on extreme events in southern Brazil during an austral winter, highlighting the importance of increasing the resolution of ocean wave and surface wind data to provide more accurate and reliable forecasts for coastal and marine activities. Our analyses revealed that atmospheric downscaling performed with WRF not only increased the ensemble spread by significant amounts but also enhanced the sharpness of the wave ensemble hindcast compared with those based solely on the ERA5 EDA. Specifically, for the Rio Grande buoy location, the significant wave height (Hs) from the SWN-WRFERA5 system showed an increase of 0.5 over SWN-ERA5, and Hs from the SWN-WRFPPar system increased by 0.6. Additionally, the wave peak period (Tp) for both SWN-WRFERA5 and SWN-WRFPPar systems experienced an increase of 1.2 compared to SWN-ERA5. Additionally, the ensemble produced with the WRF multi-physics approach captured peaks in the significant wave height registered by the buoy that were not reproduced by other ensemble systems, demonstrating an improvement in predictive accuracy, despite presenting a smaller correlation between spread and strong localized wave variations. Besides quantifying the hindcast error, the methodology presented in this work also offers a way to generate alternative and improved representations of past extreme events. This approach significantly contributes to our ability to sample recent climatic conditions and expand the dataset for statistical analyses, which is especially valuable for ocean and coastal engineering projects. This study underscores the critical role of enhancing computational and methodological approaches in wave modeling for better understanding and mitigating the impacts of extreme weather events on coastal and oceanic regions.

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来源期刊
Computers & Geosciences
Computers & Geosciences 地学-地球科学综合
CiteScore
9.30
自引率
6.80%
发文量
164
审稿时长
3.4 months
期刊介绍: Computers & Geosciences publishes high impact, original research at the interface between Computer Sciences and Geosciences. Publications should apply modern computer science paradigms, whether computational or informatics-based, to address problems in the geosciences.
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