Climate Decision Support in the Gulf States: Assessing the Impacts of Key Uncertainties in End-to-End Assessments
DESCRIPTION: The overall objective of this project is to evaluate the impacts of uncertainty throughout the climate impacts assessment process to identify the most crucial options and provide more robust analysis for climate change decision support, thereby improving risk management and the development of sustainable adaptation strategies in the agricultural sector. We investigate the assessment uncertainties associated with peanut modeling in the Gulf Coast regions of Florida and Alabama. NASA remote sensing tools (including several high-resolution precipitation products and surface insolation estimates) and modeling systems (including the Modern Era Retrospective Analysis; MERRA) are also introduced into the impacts assessment process and their impacts on final decision support estimated.
OUTCOMES: Experiments have been completed for a series of locations in Southern Alabama and Northwestern Florida, allowing for a full investigation of propagating uncertainties involving more than a dozen historical climate datasets, more than 30 future climate models, and a variety of climate scenario methods. Project activities led to a paper in Global Change Biology and work has led directly to several major global initiatives within the the Agricultural Model Intercomparison and Improvement Project (AgMIP). These include the Coordinated Climate-Crop Modeling Project (C3MP), which aligned 100+ researchers to follow similar protocols for temperature, precipitation, and CO2 sensitivity tests enabling crop model emulation to understand core climate factor responses. In the end there were 1000+ sites evaluated including 50+ countries, 20+ crop models, and 15+ crop species. A similar approach was also applied to the AgMIP Global Gridded Crop Model Intercomparison (GGCMI), which produced global climate factor responses (adding nitrogen and application dimensions) enabling global emulators and impacts response surfaces. A similar approach was also applied by AgMIP's European partners at sites across Europe in their MACSUR project. This work also led to the development of two climate forcing datasets (AgMERRA and AgCFSR) that combines satellite remote sensing, gridded station datasets, and NASA MERRA to create a bias-adjusted historical climate dataset designed for agricultural model applications. AgMERRA and AgCFSR play an integral role in many agricultural impact studies within AgMIP and beyond, as they dramatically increase the consistency and accuracy of climate information in regions where local observations are not reliable.