Urgent computing of storm surge for North Carolina's coast

Abstract

Forecasting and prediction of natural events, such as tropical and extra-tropical cyclones, inland flooding, and severe winter weather, provide critical guidance to emergency managers and decision-makers from the local to the national level, with the goal of minimizing both human and economic losses. This guidance is used to facilitate evacuation route planning, post-disaster response and resource deployment, and critical infrastructure protection and securing, and it must be available within a time window in which decision makers can take appropriate action. This latter element is that which induces the need for urgency in this area. In this paper, we outline the North Carolina Forecasting System (NCFS) for storm surge and waves for coastal North Carolina, which is threatened by tropical cyclones about once every three years. We initially used advanced cyberinfrastructure techniques (e.g., opportunistic grid computing) in an effort to provide timely guidance for storm surge and wave impacts. However, our experience has been that a distributed computing approach is not robust enough to consistently produce the real-time results that end users expect. As a result, our technical approach has shifted so that the reliable and timely delivery of forecast products has been guaranteed by provisioning dedicated computational resources as opposed to relying on opportunistic availability of external resources. Our experiences with this forecasting effort is discussed in this paper, with a focus on Hurricane Irene (2011) that impacted a substantial portion of the US east coast from North Carolina, up along the eastern seaboard, and into New England