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Coastal Risk Assessment in Central America: from Deep Waters to Nearshore Regions

EasyChair Preprint no. 8062

4 pagesDate: May 24, 2022

Abstract

Wave climate and atmospheric behaviour in the Pacific Ocean is quite different from that of the Mediterranean sea, and the phenomena which occur along the Pacific Basin influence the state of other oceans around it. The waves that reach the coasts of the American continent are mainly influenced by events such as storm surges, ENSO phenomena, low pressure systems and climate change.

On the other hand, studies have revealed that the wave estimated by numerical models arriving on the Pacific coast of Central America is underestimated and the wave statistics need to be recalibrated, or a recalibration of the global wave model to handle this deficiency must to be carried out (Alfaro, et. al., 2019). One of the main reasons of the accuracy shortcoming of the numerical models in this region is partly due to the lack of field-recorded wave data, or the low temporal resolution with which these models work. Recently, Acoustic Doppler Current Profilers have gone into operation in the region, which combined with satellite data, it has been used in this investigation.

In this study the configuration, calibration and validation of the an unstructured wave numerical model were developed by using Wavewatch III (The WAVEWATCH III ® Development Group, 2019) from the Pacific basin to the Central American shoreline. Then, the Storm Power Index, Costal Vulnerability Index and Risk Index have been estimated for several coastal regions in the Central American Pacific coast.

Keyphrases: Coastal Risk Assessment, unstructured mesh, Wave hindcast, wave model, wave storm power

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:8062,
  author = {Manuel Corrales and Andrea Lira-Loarca and Giovanni Besio},
  title = {Coastal Risk Assessment in Central America: from Deep Waters to Nearshore Regions},
  howpublished = {EasyChair Preprint no. 8062},

  year = {EasyChair, 2022}}
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