Application of seasonal climate forecasts in predicting winter chill for specialty crops.

Abstract

Abstract Many fruits and nuts crops in California require winter chill accumulation to break dormancy, and insufficient chill may result into delayed flowering and uneven budbreak which can impact quality and quantity of fruits. Early information on winter chill forecast can help growers prepare for a low chill year with management alternatives to alleviate some risks. This study assessed potential of state-of-the-art seasonal prediction systems to predict winter season (NDJF) chill anomaly and chill sufficiency for important specialty crops of California at different lead times. We found that it is possible to predict winter season Chill Portions category (above-normal, below-normal, normal) starting from October with 50–80% correct forecasts in the Central Valley and southern California. The anomaly correlation coefficients between model-predicted and reference winter season CP in the UKMO and ECMWF ranged from 0.5 to 0.8 in the Central Valley and above 0.7 in most of the southern California. All models were able to predict crop-specific winter season chill sufficiency from October with more than 90% accuracy for all the crops, except for the plums which was correctly predicted more than 60% of time. Results from this study might help growers to minimize risks associated with low chill.