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 Southeastern Universities Research Association (SURA) coastal ocean observing and prediction (SCOOP) program is a SURA Coastal Research initiative that is deploying cutting edge information technology to advance the science of environmental prediction and hazard planning for our nation's coasts. SCOOP is a distributed program, incorporating heterogeneous data, software and hardware; thus the use of standards to enable interoperability is key to SCOOP's success. Standards activities range from internal coordination among SCOOP partners to participation in national standards efforts. As the lead partner in the SCOOP program for both data management and data translation, the University of Alabama in Huntsville (UAH) is developing a suite of advanced technologies to provide core data and information management services for scientific data, including the SCOOP Catalog and a suite of standards-based web services providing Catalog access. Currently under development is a web service that will export information on SCOOP data collections in a schema compliant with the Federal Geographic Data Committee's Content Standard for Digital Geospatial Metadata. SCOOP is also a participant in the OpenlOOS Interoperability Demonstration, which leverages open geospatial consortium (OGQ standards such as the Web map service (WMS) and Web Feature Service (WFS) protocols to display near real time coastal observations together with water level, wave, and surge forecasts. SCOOP partners are also active participants in several data and metadata standards efforts, including the national ocean sciences data management and communications metadata studies and the marine metadata interoperability project. Continued close cooperation between the IT and coastal science modeling communities is producing positive results toward a real-time modeling environment that will benefit coastal stakeholders through better predictive capabilities.

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.