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Special Issues
Real-Time Forecasting of Waves and Storm Surge
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Real-Time Forecasting of Waves and Storm Surge

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Coastal Engineering".

Deadline for manuscript submissions: 15 August 2024 | Viewed by 865

Special Issue Editor

Dr. Robert J. Weaver

E-Mail Website
Guest Editor
Florida Institute of Technology, Department of Ocean Engineering and Marine Sciences, Melbourne, FL, USA
Interests: coastal engineering; living shorelines; storm surge; hurricane; ADCIRC; 3D numerical modeling; hydrodynamic; SWAN; Indian River Lagoon
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Severe weather events such as tropical cyclones, hurricanes, and typhoons are dynamic and powerful forces of nature that significantly impact coastal regions worldwide. Storm surge flooding and the accompanying waves and currents produced by these events can cause catastrophic damage including loss of human life and destruction of infrastructure.  

Real-time forecasting plays a pivotal role in predicting and mitigating the potentially devastating consequences of these extreme weather phenomena. In recent years, technological advancements have significantly improved the precision and lead time of real-time forecasts for waves and storm surges. 

This Special Issue welcomes submissions of papers that underscore the challenges in forecasting waves, storm surge inundations, and other coastal phenomena, as well as their solutions, providing crucial information for disaster preparedness and response in coastal regions susceptible to extreme weather events. 

Key forecasting technologies include, but are not limited to, the following:  

  1. Data Collection and Observation: Technologies that facilitate data collection and observation, including buoys, sensors, satellite remote sensing, ocean radar, and tide gauges.  
  2. Models: Numerical weather prediction (NWP) models, wave and circulation models, storm surge models, and coupled hydrologic/hydrodynamic models. 
  3. Data Assimilation: Advanced techniques that harness high-performance computing (HPC), machine learning, and artificial intelligence to enhance forecast accuracy. Such visualization and communication tools help to ensure effective dissemination of vital information. 

Dr. Robert J. Weaver
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • data collection and observation
  • data assimilation
  • numerical modeling

Published Papers (1 paper)

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Research

20 pages, 7251 KiB  
Article
Four Storm Surge Cases on the Coast of São Paulo, Brazil: Weather Analyses and High-Resolution Forecasts
by Sin Chan Chou, Marcely Sondermann, Diego José Chagas, Jorge Luís Gomes, Celia Regina de Gouveia Souza, Matheus Souza Ruiz, Alexandra F. P. Sampaio, Renan Braga Ribeiro, Regina Souza Ferreira, Priscila Linhares da Silva and Joseph Harari
J. Mar. Sci. Eng. 2024, 12(5), 771; https://doi.org/10.3390/jmse12050771 - 3 May 2024
Viewed by 518
Abstract
The coast of São Paulo, Brazil, is exposed to storm surges that can cause damage and floods. These storm surges are produced by slowly traveling cyclone–anticyclone systems. The motivation behind this work was the need to evaluate high-resolution forecasts of the mean sea-level [...] Read more.
The coast of São Paulo, Brazil, is exposed to storm surges that can cause damage and floods. These storm surges are produced by slowly traveling cyclone–anticyclone systems. The motivation behind this work was the need to evaluate high-resolution forecasts of the mean sea-level pressure and 10 m winds, which are the major drivers of the wave model. This work is part of the activity in devising an early warning system for São Paulo coastal storm surges. For the evaluation, four case studies that had a major impact on the coast of São Paulo in 2020 were selected. Because storm surges that reach the coast may cause coastal flooding, precipitation forecasts were also evaluated. The mesoscale Eta model produces forecasts with a 5 km resolution for up to an 84 h lead time. The model was set up in a region that covers part of southeast and south Brazil. The ERA5 reanalysis was used to describe the large-scale synoptic conditions and to evaluate the weather forecasts. The cases showed a region in common between 35° S, 40° S and 35° W, 45° W where the low-pressure center deepened rapidly on the day before the highest waves reached the coast of São Paulo, with a mostly eastward, rather than northeastward, displacement of the associated surface cyclone and minimal or no tilt with height. The winds on the coast were the strongest on the day before the surge reached the coast of São Paulo, and then the winds weakened on the day of the maximum wave height. The pattern of the mean sea-level pressure and 10 m wind in the 36 h, 60 h, and 84 h forecasts agreed with the ERA5 reanalysis, but the pressure was slightly underestimated. In contrast, the winds along the coast were slightly overestimated. The 24 h accumulated precipitation pattern was also captured by the forecast, but was overestimated, especially at high precipitation rates. The 36 h forecasts showed the smallest error, but the growth in the error for longer lead times was small, which made the 84 h forecasts useful for driving wave models and other local applications, such as an early warning system. Full article
(This article belongs to the Special Issue Real-Time Forecasting of Waves and Storm Surge)
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