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.

本数据集是论文《热带气旋诱发复合型洪水预报中的不确定性考量》（简称TC-FF）所载研究的核心组成部分。本数据集囊括了本研究中使用的全套数据与模型配置，旨在助力该领域的后续研究与学术认知深化。

本数据集包含以下内容：
**SFINCS模型（Super-Fast INundation of CoastS）配置**：SFINCS模型是本研究的核心组件，被用于模拟水动力过程。有关该模型的更多信息可访问代尔夫特水利研究所（Deltares）官方网站的SFINCS专题页面。

**潮汐验证数据**：如本论文所述，本部分包含详细的潮汐验证数据集，用以佐证本研究模型在潮汐情景下的预测准确性与可靠性。

**伊代热带气旋验证数据集**：本部分包含针对热带气旋伊代（Tropical Cyclone Idai）的专属验证数据，该气旋亦是本研究的关键案例研究对象，可用于展示本模型对该极端事件影响的预测效能。

**TC-FF生成的集合预报成员**：本数据集的核心组件之一包含了针对TC-FF模型生成的集合预报成员，涵盖气旋登陆前1至5天的各类预测结果。此类集合成员是解析热带气旋诱发洪水的潜在影响范围与相关不确定性的关键依据。

本数据集旨在补充本论文所载的研究发现与讨论，帮助研究者更深入地理解本研究采用的方法论与分析流程。我们相信，本数据集将为气象学、水文学以及灾害风险管理领域的科研人员与从业者提供宝贵的研究资源。