A multi-model Python wrapper for operational oil spill transport forecasts. (12th June 2015)

• Record Type: Journal Article
• Authors: Hou, X; Hodges, B R; Negusse, S; Barker, C
• Is Part Of: Computational science & discovery. Volume 8:Number 1(2015)
• Publication Date: 2015-06-12
• Subjects: Python wrapper -- hydrodynamic model -- oil spill model -- oil spill forecast; 93A13 -- 93A30 -- 93C83 -- 68U20; Science -- Computer simulation -- Periodicals; Technology -- Computer simulation -- Periodicals; Science -- Data processing -- Periodicals; Technology -- Data processing -- Periodicals; Research -- Methodology -- Periodicals; Research -- Periodicals; Periodicals; 501.13
• DOI: 10.1088/1749-4699/8/1/014004
• Languages: English
• ISSNs: 1749-4699

Abstract

Abstract: The Hydrodynamic and oil spill modeling system for Python (HyosPy) is presented as an example of a multi-model wrapper that ties together existing models, web access to forecast data and visualization techniques as part of an adaptable operational forecast system. The system is designed to automatically run a continual sequence of hindcast/forecast hydrodynamic models so that multiple predictions of the time-and-space-varying velocity fields are already available when a spill is reported. Once the user provides the estimated spill parameters, the system runs multiple oil spill prediction models using the output from the hydrodynamic models. As new wind and tide data become available, they are downloaded from the web, used as forcing conditions for a new instance of the hydrodynamic model and then applied to a new instance of the oil spill model. The predicted spill trajectories from multiple oil spill models are visualized through Python methods invoking Google Map TM and Google Earth TM functions. HyosPy is designed in modules that allow easy future adaptation to new models, new data sources or new visualization tools.