Developing Spatially Populated Weather Data for Applications In Environmental Modeling and Monitoring.

Technological advances in remote sensing and geographical information system (GIS) have increased the spatial and temporal resolution of meteorological (climate and weather) data which is an integral part of in environmental and pesticide transport modeling.  However, considerable computing resources may be required as the spatial resolution of the simulation increases. Techniques have been developed to coordinate enterprise-level data collection and dissemination of advanced weather and climate information in order to prepare agriculturally relevant climate datasets for environmental modeling. This presentation will describe data collection and integration methodologies for combining these climate surfaces with soil data and other environmental information.  In addition, similar methodologies to employ near real-time meteorological information for predictive agricultural and environmental applications will be discussed. This presentation will demonstrate additional approaches for preparation of daily gridded climate data estimates, applicable to water quality monitoring, environmental fate and agronomic modeling, and development of regional climate change scenarios.