Рет қаралды 135
The SECOORA Coastal Observing In Your Community Webinar Series is hosted monthly. To view our upcoming and past webinars, please visit our website (secoora.org/webinar-series/). This month, Dr. Joseph Zhang from the Virginia Institute of Marine Science gave a presentation on the development of a new Southeast Coastal Operational Forecast System (SECOFS) and provided progress updates and preliminary results.
Abstract:
Dr. Zhang and his team are working with NOAA (CO-OPS, OCS, IOOS) and regional organizations (SECOORA) to develop a new operational Southeast Coastal Operational Forecast System (SECOFS) based on the work they have done on the Surge and Tide Operational Forecast System (STOFS). SECOFS will include enhancement of the coupling infrastructure itself to be compliant with the Unified Forecast System (UFS). SECOFS will also comply with NOAA efforts to develop a generic coastal flood modeling skill assessment and evaluation infrastructure for operational models. Zhang’s team is also supporting the development of coupling capability for remapping 2D/3D fields for conversion of ocean model results to UFS downstream applications, such as safe and efficient navigation, risk reduction, and total water level.
About the Presenter:
Dr. Joseph Zhang is a professor at the Virginia Institute of Marine Science and leads the development of the cross-scale modeling system, SCHISM. Trained in theoretical and computational fluid dynamics, he has successfully built an open community for the past 20 years for the advancement of hydrodynamic and hydrologic processes using cross-scale simulation approaches. At the moment his team is working with NOAA/OCS on total water prediction using a novel cross-scale platform known as STOFS3D, which has been successfully implemented for the Atlantic and Pacific. He’s also working with IOOS and CO-OPS to develop a regional application (SECOFS) focused on flood hazard and safe navigation in the southeastern US coast, and with NWC on the development of the next-generation National Water Model.