STORM (Synthetic Tropical cyclone generation Model) is designed to statistically extend any meteorological dataset to 10,000 years of tropical cyclone activity under the same climate conditions.
By doing so, we create a large enough dataset to properly assess tropical cyclone risk anywhere in the world, including an estimation of those low-probability events (e.g. the 1-in-1,000 or 1-in-10,000 year cyclone) that cannot be assessed using the currently available meteorological records. The STORM dataset is used as input dataset for the hydrodynamical model GTSM, to calculate high-resolution global tropical cyclone storm surge return periods.
This study was conducted in collaboration with University of Southampton, KNMI and Deltares
Contact information: Nadia Bloemendaal, Job Dullaart, Hans de Moel, Sanne Muis, Jeroen Aerts
For more information please visit the following site: https://data.4tu.nl/repository/uuid:82c1dc0d-5485-43d8-901a-ce7f26cda35d
Publications
- Bloemendaal, N., Haigh, I.D., de Moel, H., Muis, S., Haarsma, R.J. & Aerts, J.C.J.H. (2020). Generation of a global synthetic tropical cyclone hazard dataset using STORM. Scientific Data, 7(4). https://www.nature.com/articles/s41597-020-0381-2
- Dullaart, J.C.M., Muis, S., Bloemendaal, N. & Aerts, J.C.J.H. (2020). Advancing global storm surge modelling using the new ERA5 climate reanalysis. Climate Dynamics, 54, 1007–1021. https://link.springer.com/article/10.1007/s00382-019-05044-0