Chen (2026) The ensembles forecast data for the Stevens Flood Advisory System

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-01-08
• Authors: Ziyu Chen
• DOI: 10.17632/7mx8npghk9.1

Research Groups

• Stevens Institute of Technology

Short Summary

This paper describes and makes available the ensemble forecast data generated by the Stevens Flood Advisory System, an operational total water level forecast system, which is utilized for research into mid-latitude super-ensemble coastal water level forecasting.

Objective

• To describe and provide access to the ensemble forecast data produced by the Stevens Flood Advisory System for coastal total water level forecasting applications and research.

Study Configuration

• Spatial Scale: Coastal regions, specifically mid-latitude areas.
• Temporal Scale: Ongoing forecasting since 2016; the described dataset was published in 2026.

Methodology and Data

• Models used: Stevens Flood Advisory System (SFAS) ensemble model for total water level forecasting.
• Data sources: Model-generated ensemble forecast data for total water level, including components related to storm surge and tropical cyclones.

Main Results

• The provision of a comprehensive dataset of ensemble total water level forecasts from the Stevens Flood Advisory System, an operational system since 2016.
• This dataset serves as foundational data for subsequent research, such as studies on the advantages and challenges of mid-latitude super-ensemble coastal water level forecasting.

Contributions

• Offers a publicly accessible and well-documented dataset of ensemble total water level forecasts from a long-standing operational system, thereby facilitating further research, validation, and development in coastal flood forecasting, particularly for mid-latitude regions.

Funding

• Not specified in the provided text.

Citation

@article{Chen2026ensembles,
  author = {Chen, Ziyu},
  title = {The ensembles forecast data for the Stevens Flood Advisory System},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/7mx8npghk9.1},
  url = {https://doi.org/10.17632/7mx8npghk9.1}
}