Project Funding: 2009 - 2012

NRA: 2008 NASA: Decision Support through Earth Science Research Results   

Funded by NASA

Abstract:
This proposal addresses the theme of improving agricultural forecasts through a blend of downscaled climate models and observations in support of the Agriculture and Water Resources application areas/priority topics. The central objectives are to: 1) expand the usage of climate model and mission products for climate variability applications, 2) incorporate an end-to-end probabilistic approach linking key climate variables to yield projections and profit information from the Decision Support System for Agrotechnology Transfer (DSSAT), and 3) integrate projected changes in extreme climate events, as simulated by regional climate models and validated by mission products, into DSSAT for improved yield information and management options. The project is designed to ensure that results integrate seamlessly with DSSAT, which is widely used to merge crop, soil, and weather databases with management and application programs to allow simulation of multi-year crop outcomes. The work focuses on two regions: the Southeast United States and Central America. In the Southeast United States, the Southeast Climate Consortium (SECC) is a partnership of the United States Department of Agriculture (USDA) and the National Oceanic and Atmospheric Administration (NOAA) Regional Integrated Sciences and Assessments (RISA) program. In Central America, the Comite Regional de Recursos Hidraulicos de Istmo Centroamericano (CRRH) has a mandate to coordinate scientific observation of climate, hydrology, and water, focusing on integrated water management for the agriculture and water resource sectors. Climate variability and change projections from NASA global climate models (GCMs) and mission output can provide solutions for agricultural agencies in the United States and those with a mandate to promote agricultural efficiency abroad and to protect against climate risks. To date, integration of agricultural decision support tools with advanced climate change and variability output from climate models and mission output has been limited; this project addresses that gap.