Large-Scale Deep Learning-Based Hourly Storm Surge Modeling: Application Across the U.S. Gulf and East Coasts

No abstract is available for this paper.

• Publication year

  2026

• Venue

  Earth Systems and Environment

• Publication date

  2026-01-29

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1007/s41748-026-01039-0
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A dataset of storm surge reconstructions in the Western North Pacific using CNN

  2024cited by this paper
• A deep-learning model for rapid spatiotemporal prediction of coastal water levels

  2024cited by this paper
• Novel optimized deep learning algorithms and explainable artificial intelligence for storm surge susceptibility modeling and management in a flood-prone island

  2024cited by this paper
• Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process

  2024cited by this paper
• Developing a deep learning-based storm surge forecasting model

  2023cited by this paper
• Predicting Sea Level Rise Using Artificial Intelligence: A Review

  2023cited by this paper
• Storm surge hazard estimation along the US Gulf Coast: A Bayesian hierarchical approach

  2023cited by this paper
• Impact of changes in sea surface temperature due to climate change on hurricane wind and storm surge hazards across US Atlantic and Gulf coast regions

  2023cited by this paper
• A novel deep learning approach for typhoon-induced storm surge modeling through efficient emulation of wind and pressure fields

  2023cited by this paper
• High-resolution downscaling with interpretable deep learning: Rainfall extremes over New Zealand

  2022cited by this paper
• Machine learning-based assessment of storm surge in the New York metropolitan area

  2022cited by this paper
• Artificial intelligence for hurricane storm surge hazard assessment

  2022cited by this paper
• Exploring deep learning capabilities for surge predictions in coastal areas

  2021cited by this paper
• Multi-step ahead short-term predictions of storm surge level using CNN and LSTM network

  2021cited by this paper
• Storm Surge Prediction Based on Long Short-Term Memory Neural Network in the East China Sea

  2021cited by this paper
• GESLA Version 3: A major update to the global higher‐frequency sea‐level dataset

  2021cited by this paper
• A database of global storm surge reconstructions

  2021cited by this paper
• Extreme sea level variability dominates coastal flood risk changes at decadal time scales

  2020cited by this paper
• Probabilistic reanalysis of storm surge extremes in Europe

  2020cited by this paper
• Multi-model drought predictions using temporally aggregated climate indicators

  2020cited by this paper
• Data-Driven Modeling of Global Storm Surges

  2020cited by this paper
• A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections

  2020cited by this paper
• Estimation of global coastal sea level extremes using neural networks

  2020cited by this paper
• The ERA5 global reanalysis

  2020cited by this paper
• Multisite, multivariate weather generation based on generalised linear models

  2020cited by this paper
• Deep learning for multi-year ENSO forecasts

  2019cited by this paper
• Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions

  2019cited by this paper
• Deep learning and process understanding for data-driven Earth system science

  2019cited by this paper
• An extreme sea level indicator for the contiguous United States coastline

  2019cited by this paper
• Spatiotemporal patterns of extreme sea levels along the western North-Atlantic coasts

  2019cited by this paper
• Rainfall–runoff modelling using Long Short-Term Memory (LSTM) networks

  2018cited by this paper
• Global probabilistic projections of extreme sea levels show intensification of coastal flood hazard

  2018cited by this paper
• Regional coastal flood risk assessment for a tidally dominant, natural coastal setting: North Norfolk, southern North Sea

  2017cited by this paper
• The influence of sea surface temperature on the intensity and associated storm surge of tropical cyclone Yasi: a sensitivity study

  2017cited by this paper
• A novel companion objective function for regularization of deep convolutional neural networks

  2017cited by this paper
• Convolutional Neural Networks in Visual Computing: A Concise Guide

  2017cited by this paper
• Global reconstructed daily surge levels from the 20th Century Reanalysis (1871-2010)

  2017cited by this paper
• A global reanalysis of storm surges and extreme sea levels

  2016cited by this paper
• Projections of extreme storm surge levels along Europe

  2016cited by this paper
• On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

  2015cited by this paper
• Examination of extreme sea levels due to storm surges and tides over the northwest Pacific Ocean

  2015cited by this paper
• Weekly Prediction of Tides Using Neural Networks

  2015cited by this paper
• Statistical characteristics of rainfall in the Onkaparinga catchment in South Australia

  2015cited by this paper
• The ERA‐Interim reanalysis: configuration and performance of the data assimilation system

  2011cited by this paper
• Impacts of climate change and sea-level rise on cyclonic storm surge floods in Bangladesh

  2008cited by this paper
• Long Short-Term Memory

  1997cited by this paper

• No citing papers are available for this paper.