TY - DATA
T1 - Model Data for 'Accounting for Uncertainties in Forecasting Tropical Cyclone-Induced Compound Flooding' (TC-FF)
PY - 2024/01/30
AU - Kees Nederhoff
AU - Maarten van Ormondt
AU - Jay Veeramony
AU - Ap Van Dongeren
AU -  Jose Antolínez
AU - Tim Leijnse
AU - Dano Roelvink
UR - 
DO - 10.4121/a5174397-3489-4f5d-b220-6749f3750942.v1
KW - Tropical Cyclone Forecasting
KW - Compound Flooding
KW - SFINCS
KW - TC-FF
N2 - <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>
ER -