Steps towards Modeling Community Resilience under Climate Change: Hazard Model Development

Journal of Marine Science and Engineering

Naiyu Wang¹  Humberto Vergara²  Xianwu Xue³  KevinM. Geoghegan⁴  ChristineM. Szpilka⁵  KendraM. Dresback⁵  RandallL. Kolar⁵  Jia Xu⁶ 

[1] College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China;Cooperative Institute of Mesoscale Meteorology, University of Oklahoma/National Weather Center, Norman, OK 73019, USA;Environmental Modeling Center, National Centers for Environmental Prediction/National Oceanic and Atmospheric Administration, College Park, MD 20740, USA;Northwest Hydraulic Consultants, Seattle, WA 98168, USA;School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73019, USA;School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024, China;

关键词: total water level;    tropical cyclones;    climate change;    coastal resilience;    coupled model system;   

DOI  :  10.3390/jmse7070225

来源: DOAJ

【 摘 要 】

With a growing population (over 40%) living in coastal counties within the U.S., there is an increasing risk that coastal communities will be significantly impacted by riverine/coastal flooding and high winds associated with tropical cyclones. Climate change could exacerbate these risks; thus, it would be prudent for coastal communities to plan for resilience in the face of these uncertainties. In order to address all of these risks, a coupled physics-based modeling system has been developed that simulates total water levels. This system uses parametric models for both rainfall and wind, which only require essential information (e.g., track and central pressure) generated by a hurricane model. The system is validated with Hurricane Isabel hindcasts: One using the parametric system and another using data assimilated fields. The results show a good agreement to the available data, indicating that the system is able to adequately capture the hazards using parametric models, as compared to optimized fields. The validated system was then utilized to simulate randomly generated scenarios that account for future uncertainty, i.e., amount of sea level rise and storm strength/track, as influenced by projected climate change scenarios. Results are then used in next step in the development of a system-wide, community resilience model.

【 授权许可】

Unknown