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