Seasonal climate variability plays an important role in the production risks faced by producers. The majority of crop failures in the USA are associated with either a lack or excess of rainfall. Climate forecasts can be used to reduce risks faced by an agricultural enterprise, but simply providing better climate forecasts to potential users is not enough. Climate information only has value when there is a clearly defined adaptive response and a benefit once the content of the information is considered in the decision making process. AgClimate is a response to the need for information and tools on proactive adaptations to seasonal and interannual climate variability forecasts in the southeastern USA. Extension agents, agricultural producers, forest managers, crop consultants, and policy makers may use this decision support system to aid in decision making concerning management adjustments in light of climate forecasts. Adaptations include those that might mitigate potential losses as well those with the potential to produce optimal yields. AgClimate is a web-based climate forecast and information system that was designed and implemented in partnership with the Cooperative State Extension Service. It has two main components: the front-end interface and a set of dynamic tools. The main navigation menu includes the AgClimate tools, climate forecasts, and management options for crops, forestry, pasture, and livestock. It also includes a climate and El Niño section with background information. The tools section contains two applications that allow a user to examine the climate forecast for individual counties based on the ENSO phase and to evaluate yield potentials for certain crops. Applied outlooks for individual agricultural sectors are also provided on a quarterly basis. AgClimate is now operational under the Southeast Climate Consortium and several upgrades are under development and consideration.
Bibliographical noteFunding Information:
The authors acknowledge Oxana Uryasev (University of Florida) for her contribution developing prototype applications, and Melissa Griffin (Florida State University) for her contribution developing the climate database. We thank Larry Guerra (University of Georgia) for helping with the development of soil and crop parameters used in the crop modeling effort. Funding for this project was provided by the USDA-Risk Management Agency (USDA-RMA), the Office of Global Programs of the National Oceanic and Atmospheric Administration (NOAA), and the USDA-Cooperative State Research, Education and Extension Service (USDA-CSREES).
- Climate variability
- Crop models
- Decision making
- El Niño