Impacts of large-scale teleconnection indices on chill accumulation for specialty crops in California.

Although the impacts of teleconnection indices on climate metrics such as precipitation and temperature in California have been widely studied, less attention has been given to the impact on integrated climate indices such as chill accumulation. This study investigates the linkages between large-scale teleconnections and winter chill accumulation for specialty crops in California, which may enable more effective and dynamic adaptation to in-season climate variability. Three large-scale teleconnection indices were selected: Oceanic Nino Index (ONI), Pacific-North American teleconnection pattern (PNA), and Pacific Decadal Oscillation (PDO) index to assess their effects on chill accumulation. The Chill Hours Model and Dynamic Model are adopted to calculate chill accumulation in Chill Hours (CH) and Chill Portions (CP) from November to January. Three major crop-producing regions, including the Central Coast, Sacramento Valley, and San Joaquin Valley, are used as the focused regions. Our results suggest CP generally has a stronger response to teleconnection patterns than CH in California. The correlations between chill accumulation and teleconnections are generally weaker during the summer than other seasons, and significant correlation can be observed 2-10 months before the start of the chill accumulation period. Among the three teleconnection indices, ONI is most weakly correlated to chill accumulation in focused regions, while PDO shows the strongest positive correlation and explains up to 39% variability of CP. PNA presents the most widespread negative correlation with chill accumulation. When aggregated to different teleconnection modes, +3.6 above-average CP is expected during ONI positive mode; +2.3 above-average CP is expected during PDO positive mode, while +2.1 above-average CP is expected during PNA negative mode. This study provides insights on early-season chill prediction and feasible management and adaptation strategies, and the methodology presented here can be used to develop decision support tools of risk control for agricultural producers and policymakers.