Many fruit and nut crops in California require sufficient winter chill to break dormancy, and insufficient chill can harm fruit quantity and quality. Early information on winter chill forecast can help growers prepare for a low chill year. This study evaluates the use of dynamic climate models for chill accumulation forecasts in California. Using temperature forecasts from seasonal prediction systems, the study found that multimodel forecasts can predict chill, with anomaly correlation coefficients exceeding 0.5 for most California regions. The forecasts correctly identified chill categories in over 50% of instances in more than 40% of the Central Valley and southern California. However, forecasts beyond a one-month lead time showed reduced skill.

Prakash Kumar Jha, Tapan B. Pathak