%0 Generic
%A Nederhoff, Kees
%A van Ormondt, Maarten
%A Veeramony, Jay
%A Van Dongeren, Ap
%A AntolĂ­nez,  Jose
%A Leijnse, Tim
%A Roelvink, Dano
%D 2024
%T Model Data for 'Accounting for Uncertainties in Forecasting Tropical Cyclone-Induced Compound Flooding' (TC-FF)
%U 
%R 10.4121/a5174397-3489-4f5d-b220-6749f3750942.v1
%K Tropical Cyclone Forecasting
%K Compound Flooding
%K SFINCS
%K TC-FF
%X <p>This dataset is an integral part of the research presented in the paper titled "Accounting for Uncertainties in Forecasting Tropical Cyclone-Induced Compound Flooding" (TC-FF). It encompasses a comprehensive collection of data and model setups used in our study, to facilitate further research and understanding in this area.</p><p></p><p>The contents of this dataset include:</p><ol><li><strong>SFINCS Model Setup</strong>: The SFINCS (Super-Fast INundation of CoastS) model is a critical component of our research. It was employed for simulating the hydrodynamic processes. More information about the SFINCS model can be found on Deltares' official website at <a href="https://www.deltares.nl/en/software-and-data/products/sfincs" target="_blank">Deltares SFINCS</a>.</li><li><strong>Tidal Validation Data</strong>: As illustrated in our paper, this section includes detailed tidal validation data, supporting the accuracy and reliability of our model predictions in tidal scenarios.</li><li><strong>Validation of Event Idai:</strong> This section contains specific validation data for Tropical Cyclone Idai, which is a key case study in our research. It demonstrates the model's effectiveness in predicting the impacts of this particular event.</li><li><strong>TC-FF Generated Ensemble Members</strong>: This critical component of our dataset includes the ensemble members generated for the TC-FF model, offering predictions from 1 to 5 days before landfall. These ensemble members are essential for understanding the range of potential outcomes and uncertainties associated with tropical cyclone-induced flooding.</li></ol><p></p><p>This dataset is intended to complement the findings and discussions presented in our paper, offering a deeper insight into the methodologies and analyses employed. We believe it will be a valuable resource for researchers and practitioners working in the field of meteorology, hydrology, and disaster risk management.</p>
%I 4TU.ResearchData