Abstract The SURA Coastal Ocean Observing and Prediction (SCOOP) program is using geographical information system (GIS) technologies to visualize and integrate distributed data sources from across the United States and Canada. Hydrodynamic models are run at different sites on a developing multi‐institutional computational Grid. Some of these predictive simulations of storm surge and wind waves are triggered by tropical and subtropical cyclones in the Atlantic and the Gulf of Mexico. Model predictions and observational data need to be merged and visualized in a geospatial context for a variety of analyses and applications. A data archive at LSU aggregates the model outputs from multiple sources, and a data‐driven workflow triggers remotely performed conversion of a subset of model predictions to georeferenced data sets, which are then delivered to a Web Map Service located at Texas A&M University. Other nodes in the distributed system aggregate the observational data. This paper describes the use of GIS within the SCOOP program for the 2005 hurricane season, along with details of the data‐driven distributed dataflow and workflow, which results in geospatial products. We also focus on future plans related to the complimentary use of GIS and Grid technologies in the SCOOP program, through which we hope to provide a wider range of tools that can enhance the tools and capabilities of earth science research and hazard planning. Copyright © 2008 John Wiley & Sons, Ltd.

The SURA Coastal Ocean Observing & Prediction (SCOOP) program is building cyberinfrastructure (CI) to enable advanced real-time ensemble forecasting of the coastal impacts from storms and hurricanes. This prototype of a reliable, flexible, grid-enabled forecast system integrates real-time distributed data and computer models for the coasts of the southeastern United States. The SCOOP system employs a service-oriented architecture with archive and transport services, metadata catalog, resource management, and portal interfaces. Currently, the SCOOP system uses distributed HPC machines (SCOOP, SURAgrid, others) to meet on-demand requirements. Geospatial web services disseminate the forecast results.We provide the architecture overview and describe the currently deployed system for Hurricane Season 2006 as an example in which a storm advisory automatically initiates a workflow that delivers timely forecasts. The system generates a wind-ensemble and then configures, deploys, and analyzes a variety of water level and wave models across distributed HPC resources to deliver timely forecasts.