Modeling and observations of North Atlantic cyclones: Implications for US Offshore wind energy

被引:0
|
作者
Wang, Jiali [1 ]
Hendricks, Eric [2 ]
Rozoff, Christopher M. [2 ]
Churchfield, Matt [3 ]
Zhu, Longhuan [4 ]
Feng, Sha [6 ]
Pringle, William J. [1 ]
Biswas, Mrinal [2 ]
Haupt, Sue Ellen [2 ]
Deskos, Georgios [3 ]
Jung, Chunyong [1 ]
Xue, Pengfei [1 ,4 ,5 ]
Berg, Larry K. [6 ]
Bryan, George [2 ]
Kosovic, Branko [2 ]
Kotamarthi, Rao [1 ]
机构
[1] Los Argonne Natl Lab, Environm Sci Div, Lemont, IL 60439 USA
[2] US Natl Sci Fdn Natl Ctr Atmospher Res, Boulder, CO 80307 USA
[3] Natl Renewable Energy Lab, Natl Wind Technol Ctr, Golden, CO 80401 USA
[4] Michigan Technol Univ, Great Lakes Res Ctr, Houghton, MI 49931 USA
[5] Michigan Technol Univ, Dept Civil Environm & Geospatial Engn, Houghton, MI 49931 USA
[6] Pacific Northwest Natl Lab, Atmospher Climate & Earth Sci ACES Div, Richland, WA 99352 USA
基金
美国国家科学基金会;
关键词
ATMOSPHERE-WAVE-OCEAN; HURRICANE RISK-ASSESSMENT; LARGE-EDDY SIMULATIONS; LEADING-EDGE EROSION; EXTRATROPICAL TRANSITION; TROPICAL CYCLONES; BOUNDARY-LAYER; SURFACE-WAVES; MIXED-LAYER; SEA-SURFACE;
D O I
10.1063/5.0214806
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. This paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere-ocean-wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.
引用
收藏
页数:24
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