Projecting Future Coastal Hazards for Evaluating the Performance of Mangrove NNBF Systems under Changing Climate
Authors: Yan Grace , Abellera Marriah , Tomiczek Tori , Ritchie Liesel 
Published: February 2023

&lt;p&gt;Warmer sea temperatures will cause hurricane winds to be intensified (leading to more severe storm surge) and cause hurricanes to be wetter, increasing the chance of compound flooding due to storm surge, tides, rainfall, and sea-level rise. Mangrove forests have demonstrated significant potential to attenuate waves and reduce structural loads and resulting damage during extreme coastal events. However, these natural and nature-based features (NNBF) are underutilized due to 1) a lack of understanding of stakeholders about mangroves&amp;#8217; effectiveness for mitigating coastal flooding impacts and 2) a lack of knowledge about mangroves&amp;#8217; performance under nonstationary environments (changing climate and rising sea levels). To fully leverage mangrove forests to enhance coastal resilience, the overarching goal of this study is to investigate the wave attenuation efficiency of mangroves under the changing climate. To understand future conditions associated with climate change, this study will project the occurrence frequency and genesis locations of future hurricanes in the Atlantic Ocean. The following combined representative concentration pathway (RCP) scenario will be considered in this study: RCP8.5+SSP5.&lt;/p&gt;
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&lt;p&gt;The historical TC activities datasets for the Atlantic Ocean used in this study will be obtained from the National Hurricane Center and Central Pacific Hurricane Center named HURDAT2, which provide the information on the observed TC events (from 1851 to 2021). The dataset provides the location (longitude and latitude), time of TC genesis, track, and intensity peak in terms of wind speed at the time of 0am, 6am, 12pm and 6pm each day. The time instant when the TC center&amp;#160;crosses a coastline (makes landfall) is also provided. In this study, the 171 years (1851-2021) of record data are selected from the HURDAT2 as the period of current climate. During this period, a total number of 1707 TC records.&amp;#160;Kernel Density Estimation (KDE) will be applied in this study to determine the probability function&amp;#160;of two variables, annual occurrence number and genesis location/time of tropical cyclones in Synthetic TC modeling. KDE is a non-parametric method to estimate the probability density function of a random variable based on Kernels as weights. It is data-driven, which statistically estimates the probability density function of the random variable from a finite number of data samples. It can be taken as a kind of continuous replacement for the discrete histogram.&amp;#160;&lt;/p&gt;
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&lt;p&gt;For the future climate, the data from eight different global climate models of Coupled Model Inter-comparison Project Phase 6 (CMIP6) will be used, including Geophysical Fluid Dynamics Laboratory Climate Mode. A Genesis Index will be developed based on the projected environmental factors from the global climate modeling data. The genesis index (GI) proposed by Tippett will be used to estimate the annual occurrence number of TC under future climate. This index is based on the Poisson regression equation expressed in terms of the annual occurrence of TCs obtained from historical data and oceanic-atmospheric environmental parameters. This GI will be weighted using the ratio of the GI obtained from future climate to the GI obtained from current climate, in order to remove the bias and properly obtained the annual occurrence probability. &amp;#160;&lt;/p&gt;