HR: 1340h
AN: IN33B-1183    [Abstracts]
TI: Facilitating Interdisciplinary Geosciences and Societal Impacts Research and Education via Dynamically Adaptive, Interoperable Data and Forecasting Systems
AU: * Weber, J
EM: jweber@unidata.ucar.edu
AF: Unidata/UCAR, P O Box 3000, Boulder, CO 80307-3000 United States
AU: Domenico, B
EM: ben@unidata.ucar.edu
AF: Unidata/UCAR, P O Box 3000, Boulder, CO 80307-3000 United States
AU: Chiswell, S
EM: chiz@unidata.ucar.edu
AF: Unidata/UCAR, P O Box 3000, Boulder, CO 80307-3000 United States
AU: Baltzer, T
EM: tbaltzer@unidata.ucar.edu
AF: Unidata/UCAR, P O Box 3000, Boulder, CO 80307-3000 United States
AB: The problems monitoring, predicting, and responding to coastal inundation and inland flooding situations are inherently multidisciplinary. Predicting precipitation and streamflow require expertise in meteorology and hydrology. Oceanography also enters the picture in the cases where the severe storm occurs in a coastal area. Appropriate responses to such natural hazards requires integration of infrastructure and demographics data systems associated with the societal impacts community. Building and disseminating a system that will address this problem in a comprehensive and coherent manner can only be done by a team with the a broad range of technological and scientific expertise and community connections. Efforts are underway to develop interoperable data systems among the atmospheric science, hydrology, coastal oceans, and societal impacts communities, so they may conveniently and rapidly share data among their systems in cases where hazardous events threaten infrastructure and human health. The basic approach is to build on a dynamically adaptive data access and high resolution, local forecasting system being developed for the LEAD (Linked Environments for Atmospheric Discovery) project. At present, the LEAD technology is confined to local weather forecasts automatically steered by algorithms analyzing data from national forecasts. But efforts are underway to develop an expanded team that would include expertise in coupling atmospheric forecast models with hydrological and storm surge forecast models and, in turn, to coordinate those data systems with those of the GIS (Geographic Information System) community which contain most of the demographic and infrastructure information related to societal impacts. The paper will provide an update on the status of these efforts and a demonstration of how such a dynamically adaptive forecasting system focused high resolution local forecast model runs on Hurricane Katrina.
DE: 0520 Data analysis: algorithms and implementation
DE: 0525 Data management
DE: 0850 Geoscience education research
DE: 1834 Human impacts
DE: 4564 Tsunamis and storm surges
SC: Earth and Space Science Informatics [IN]
MN: Fall Meeting 2005