Abstract:

This dataset is associated with the publication: Hou, X., Hodges, B.R., Feng, D., & Liu, Q. 2017. Uncertainty quantification and reliability assessment in operational oil spill forecast modeling system. Mar. Pollut. Bull. 116(1-2): 420-433. https://doi.org/10.1016/j.marpolbul.2017.01.038. The dataset contains the simulation result of Hyospy system of all the case studies as indicated in the publication. The running period of the system is from 7/26/2014-4/11/2015, while the oil spill model runs a 48 hours simulation at each date during this period. The data is distributed into several folders with each under the name of the running date. In each folder, there includes the setup information of the Hyospy system, the input and output of the hydrodynamic model (SELFE), the input and output of the oil spill model (GNOME). For example, in the folder 1_29_2015, there are scripts of the Hyospy system, among which hydro.py defines the setup information and parameters. In each folder, there are 17 sub-folders, each of which represents the input and output of the hydrodynamic model with various weightings of forecast and hindcast boundary conditions. In the folder GNOME, the hydrodynamic outputs are transformed to those can be read by GNOME. More details of the structure of this dataset can be found on Github: https://github.com/utcivil/HyosPy.

Suggested Citation:

Xianlong Hou, Ben R. Hodges, Dongyu Feng. 2017. Simulation result of the Hyospy oil spill operational system for uncertainty quantification and reliability assessment in oil spill forecasting system. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7BP016H

Publications:

Hou, X., Hodges, B. R., Feng, D., & Liu, Q. (2017). Uncertainty quantification and reliability assessment in operational oil spill forecast modeling system. Marine Pollution Bulletin. doi:10.1016/j.marpolbul.2017.01.038

Purpose:

This dataset is supposed to provide forecast/hindcast data series for the input forecast error εk assessment based on Monte Carlo simulation and quantify the uncertainty in an operational oil spill forecast modeling system.

Data Parameters and Units:

surface flow velocity (m/s), oil spill particle locations (latitude, longitude), depth (m), x (m), y (m)

Individual Files: