Collection of Python modules for pre- and postprocessing XBeach models and output files

Statistical extreme value analysis of storm surges with Python

This open-source research application provides an application that can be used to predict the response of communities subjected to water-borne hazard events like tsunami and storm surge.

Storm Surge Prediction Using Different Machine Learning Methods

Web-Map + Database - Global Storm Surge Reconstructions (GSSR)

Extension of GeoClaw storm surge simulation

A collection of scripts used for modeling global daily maximum surges

ParaTC: Python functions and classes for generating parametric tropical cyclone models.

A pipeline for estimating and characterizing uncertainty in coastal storm surge levels

7-member ensemble-based, real-time, operational coastal circulation, wind and wave forecast system

Soontiens, N., Allen, S., Latornell, D., Le Souef, K., Machuca, I., Paquin, J.-P., Lu, Y., Thompson, K., Korabel, V. (2015). Storm surges in the Strait of Georgia simulated with a regional model. Atmosphere-Ocean, 54: 1-21 (2016).

This repository will contain all the updated information in the shared project between GeoOcean-MetService

Contributions of Storm Drivers to Compound Flooding in New York City: Insights from Coupled Modeling and Machine Learning Approaches

MATLAB package for developing and analyzing storm surge climatology (SSC) indicator.

This is a collection of analyses of the results of the Salish Sea MEOPAR NEMO model. Most of the files are IPython Notebooks. See the README.md files in each directory for links to read-only renderings of the notebooks.

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