Predicting Heat Stress in Cotton Using Probabilistic Canopy Temperature Forecasts

Heat stress can cause many adverse effects to exposed crops, most importantly reduced yield or total crop failure.  In this study, we define plant heat stress as those time periods during which the plant temperature, or canopy temperature, exceeds the upper limit on the Thermal Kinetic Window (TKW).  In cotton (Gossypium hirsutum L.), this upper limit has been determined to be 32^◦C.  A canopy temperature model was developed by linear regression and was verified using observed canopy temperature data recorded at Stripling Irrigation Research Park (SIRP) near Camilla, Georgia.  The European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) was used to predict cotton canopy temperature.  Probabilistic forecasts were generated and shown to be skillful out to 10 days. Medium term forecasts (10-day) as well as 24-hour forecasts were developed as part of a heat stress warning system.  Additionally, a short economic analysis was performed and suggests that it is financially responsible to protect against heat stress at very low probabilities during the reproductive phase, while it requires higher probabilities later in the growth cycle.