Integrated Research on TC Hazards and Risk
We aim to establish a physically-based probabilistic TC risk assessment framework that integrates the analysis of storm activity, hazards, and risk. Due to the limitation of historical records and the complexity of the problem, we apply Monte Carlo (MC) methods, based on numerous synthetic simulations. In such an approach, large numbers of synthetic but physically possible storms, characterized by their various track, intensity, and size, are simulated (with their annual frequencies estimated), under observed or climate-model projected future climate conditions. Hazard models are then used to estimate the wind, surge, and rainfall flooding associated with the simulated storms, with the probabilistic description of the hazards obtained. Given the estimated hazards and coastal exposure, vulnerability models can be applied to estimate the storm-induced consequences (e.g., damage and/or economic losses) and thus the risk. The risk assessment can inform risk management from various perspectives to achieve coastal resiliency. We continuously develop/improve the model components of this framework with disciplinary focus as well as interdisciplinary integration.
This framework was presented by Ning Lin at the United States Frontiers of Engineering (FOE) conference in September 2015, and published in the quarterly journal of National Academy of Engineering: Lin, N. (2015). An integrated approach to assess and manage hurricane risk in a changing climate. (NAE) The Bridge 45(4): 45–51.
Storm Surge Risk
We have developed a climatological-hydrodynamic approach to assess current storm surge threat, project future surge flood risk, and investigate the change of risk in the past. We first applied the approach to New York City (NYC), which was found to be highly vulnerable to hurricane storm surge due to its location at the vertex of the right angle made by Long Island and New Jersey (Lin et al. 2010, JGR-Atmos.). Looking forward, the probabilistic distribution of surge levels was found to shift to higher values under projected future climates by a magnitude comparable to the projected sea level rise, calling attention to the joint impact on coastal flooding of increasing storm activity and rising sea level (Lin et al. 2012, Nat. Clim. Change). Looking back, we found that the surge flooding risk for NYC has increased significantly during the last millennium due to both the change in storm activity and the rising of the sea level (Reed et al. 2015, PNAS). Recently, we combined probabilistic projections of the sea level and storm surge climatology to estimate the temporal evolution of flood hazard; we found that the frequency of Hurricane Sandy-like extreme flood events has increased significantly over the past two centuries and is very likely to increase more sharply over the 21st century, due to the compound effects of sea level rise and storm climatology change (Lin et al. 2016, PNAS).
To further evaluate the methodology regarding its capability to estimate extremes that are far beyond the history, we applied the approach to the northwest Florida region. Our numerical result agrees with a 4000-year paleorecord on that the region has a much higher risk of coastal inundation than that indicated by the limited (160-year) historical record (Lin et al. 2014, JGR-Atmos.). We then developed the notion of “grey swan tropical cyclones” as high-impact storms that would not be predicted based on history but may be foreseeable using physical knowledge together with historical data. We highlighted such extremes, with a focus on their storm surges, for three three highly vulnerable coastal cities, Tampa in Florida, Cairns in Australia, and Dubai in Persian Gulf (Lin and Emanuel 2015, Nat. Clim. Change).
We have applied our storm surge risk assessment to risk management. We estimated potential surge-induced losses for New York City (Aerts et al. 2013, Risk Anal.) and evaluated various risk mitigation strategies recently proposed for the City (Aerts et al. 2014, Science). We applied dynamic programing cost-benefit analysis to derive the optimal flood mitigation strategy and implementation time path under a changing climate (Lickley et al. 2015, Climate Risk Management). We have also applied the approach to support coastal resilience design for various sites in the Northeast U.S. that were affected by Hurricane Sandy (see our Structures of Coastal Resilience (SCR) project).
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We aim to develop a multi-hazard vulnerability model that describes the damage to residential areas under the joint forces of strong wind and storm surge. We previously established a probabilistic/deterministic model describing the cumulative wind damage to residential areas during storm passage. It fully couples the wind pressure effect on individual buildings and the interaction of the buildings due to windborne debris impact (Lin and Vanmarck 2008, Probabilist. Eng. Mech.; Lin and Vanmarck 2010, Wind. Struct.; Lin et al. 2010, Wind. Struct.).
Following Hurricane Sandy, we carried out a detailed damage survey and analysis for a heavily damaged residential area on the NJ coast. This study provides us with knowledge and data to develop a comprehensive surge damage model, considering the joint effects of flooding, wave impact, and waterborne debris damage (Hatzikyriakou et al. 2015, Nat. Hazards Rev.;Xian et al. 2015, Nat. Hazards). Eventually, we will integrate the wind and surge damage models, both component-based, into an advanced vulnerability model, which can be used to estimate the damage to residential areas due to the compound effects of joint hurricane hazards.