Helping make agriculture sustainable and productive
AgriCast supports precision agriculture and helps minimize yield loss by providing data to help you determine the best times to plant, irrigate, spray, fertilize and harvest.
CFAN is partnering with trusted names in the agricultural industry such as Cotton, Inc. and USDA Extension in an effort to offer quality weather forecast products for growers. In developing AgriCast, CFAN scientists are collaborating with agricultural researchers at the University of Georgia, Auburn University, Mississippi State University, the University of Arkansas and North Carolina State University.
AgriCcast provides weather forecasts that are targeted at the needs of growers. AgriCcast brings weather data and forecasts directly to the grower via an interactive dashboard or your mobile device.
AgriCast distinguishes itself amidst competitors by improving upon the best weather forecast models in the world through the application of advanced calibration techniques and translating those improved forecasts into terms that growers can use to make on-farm decisions. CFAN’s products rely upon ensemble weather forecasts, providing the opportunity for users to more accurately calculate the probability and risk of weather events.
An example of AgriCast station precipitation forecast is provided below. Five different daily precipitation thresholds are specified, and the probability of exceeding each threshold is provided.
CFAN is developing new agricultural forecast products that are targeted at crop and dairy operations in the Southeast U.S. CFAN scientists are actively collaborating with crop scientists throughout the Southeast to develop relevant tools for weather-related on-farm challenges.
AgriCast provides forecasts at 244 locations in the southeast U.S. where high quality temperature and precipitation records are available, including the Weather Net stations in Florida and Georgia.
CFAN is now registering users for trial subscriptions of customized precipitation and temperature forecast products for the major agricultural regions throughout the southeastern United States. Forecasts are available for each station location identified on the map.
Subseasonal and Seasonal Forecasts
At extended time ranges (beyond two weeks), weather and climate forecasts can support strategic decisions regarding planting, harvesting and transportation, yield anticipation, storage and marketing . For commodities with futures markets, subseasonal weather forecasts (3-6 weeks) can support hedging strategies. Seasonal forecasts support strategic decisions regarding crop cultivar selection and intended acreage for planting. Such forecast information also has the potential to help various participants in the agriculture value chain to more intelligently join in the appropriate risk management markets via the extension of reliable outlooks beyond the current limited time scales.
CFAN has been awarded a grant from the NOAA Small Business Innovation Research (SBIR) program, entitled Probabilistic subseasonal weather forecasts for the energy and agriculture sectors. Under this project, CFAN is developing advanced solutions that address the challenges of providing probabilistic predictions on subseasonal (weeks 3 to 4) timescales. The expected outcomes are innovations in ensemble interpretation and calibration suitable for subseasonal time scales that provide the basis for web-based decision support tools for the agricultural sector.
Further information (link to pdf). We are seeking collaborators, partners and clients to help develop these products in a way that optimizes their utility for agricultural sector.
CFAN scientists are engaged in research to improve forecast products and applications in the agricultural sector. A particular focus of our research has been the application of probabilistic precipitation and weather forecasts. CFAN scientists are actively collaborating with crop scientists to develop relevant tools for weather-related on-farm challenges.
[Link] to our recent publications and presentations.
CFAN’s agrometeorology research is funded by grants from Cotton Inc. and NOAA
Heat stress can reduce crop yield or even cause total crop failure. The ability to predict heat stress in advance would allow growers time to implement protective measures that would help avoid such losses.
A recent paper published in the Agronomy Journal by CFAN team members Emily Christ, Peter Webster and Violeta Toma presents a strategy for producing probabilistic heat stress forecasts for well-watered cotton in Georgia. The 10-day forecast scheme integrates a cotton canopy temperature model with probabilistic forecasts of surface meteorology from the ECMWF Ensemble Prediction System. A heat stress warning system was then created using the forecasts. An economic model based on the variable cost of irrigation and the cost of yield loss was developed to guide decision making regarding irrigation as a strategy to protect from heat stress. The model identified thresholds of probability for heat stress occurrence that where it is financially beneficial to protect the crops with irrigation, depending on whether the farmer is more yield conscious or water conscious.