Model Data for 'Accounting for Uncertainties in Forecasting Tropical Cyclone-Induced Compound Flooding' (TC-FF)

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.<br>The contents of this dataset include:<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 Deltares SFINCS.<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.<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.<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.<br>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.