Exceptional Atmospheric and Hydrodynamic Processes and Events: Observations, Models, Forecasts, Response and Communication
Session Date: May 28th 2010
Session Time: 12:23
Session Lead: Elizabeth Smith
Session Co-Lead(s): Doug Wilson, Bill Boicourt, Kevin Sellner
Session Abstract: This session will highlight end-to-end modeling and forecasting of coastal processes that affect the Chesapeake Bay as extreme events or excursions from normal or typical processes and events. Discussions of supporting observations and observing systems, and user-driven event response and communication needs also are encouraged. Extreme event topics could include: coastal and estuarine storm driven inundation (or blow-out); waves; extreme precipitation or drought events; harmful algal blooms or toxic spills; seiches; or other similar, potentially catastrophic events. Diverse and novel approaches, especially those utilizing open-source or open-standards are welcomed. We also invite relevant presentations on observations and observing systems; atmospheric and hydrodynamic boundary conditions and forcing fields; data assimilation methods and requirements; model-data comparisons and validation studies; and model data management, visualization, and methods of communicating forecasts and results. This session builds upon recent experience in the Chesapeake Bay community in the development of the end-to-end process of the Chesapeake Inundation Prediction System (CIPS) prototype and invites perspectives on future collaborative research and development activities.
Presentations:
Post-Session Review: The goal of this session was to explore a myriad of forecasting and observing tools to aid decision-makers and planners in understanding, predicting, and communicating extreme events in the Chesapeake Bay. Two dominant themes emerged from this session. The first was that the importance of a strategic suite of atmospheric (especially measurements of wind and precipitation) and oceanographic observations in Chesapeake Bay to aid in model initialization and especially validation should not be underestimated. The second theme was that in order to be able to predict and/or respond to extreme events such as tropical storms or oil spills, the existing observational network must be very much more integrated and the data better aggregated to allow for a more rapid (real-time or nearly so) sharing of data and information across a robust network.
