The interplay between grape ripening and weather anomalies in Northern Italy – A modelling exercise

Current climate change is increasing inter- and intra-annual variability in atmospheric conditions leading to grapevine phenological shifts as well as altered grape ripening and composition at ripeness. This study aims to i) detect weather anomalies within a long-term time series, ii) model grape ripening revealing altered traits in time to target specific ripeness thresholds for four Vitis vinifera cultivars, and iii) establish empirical relationships between ripening and weather anomalies with forecasting purposes. The Day of the Year (DOY) to reach specific grape ripeness targets was determined from time series of sugar concentrations, total acidity and pH collected from a private company in the period 2009–2021 in North-Eastern Italy. Nonlinear regression models were fitted over a time series of ripening parameters on a calendar time basis and assessed for modelling efficiency (EF) and error of prediction (RMSE) in four grapevine cultivars (Merlot, Cabernet-Sauvignon, Glera and Garganega). For each vintage and cultivar, advances or delays in DOY to target specified ripeness thresholds were assessed with respect to the average ripening dynamics. A thirteen years’ long meteorological series monitored at a ground weather station using hourly air temperature and rainfall data was analysed. Climate statistics were obtained and for each time interval (month, bimester) weather anomalies were identified. A linear regression analysis was performed to assess correlations between ripening and weather anomalies. For each cultivar, ripeness advances or delays expressed in the number of days to target the specific ripening threshold were assessed in relation to registered weather anomalies and the specific reference time interval in the vintage. Precipitation of the warmest month and temperature anomalies during late spring (May–June) and during the warmest month (August) we found to be important to understanding the effect of climate change on sugar ripeness. Maximum and minimum temperatures of the May–June bimester and maximum temperatures of the warmest month best correlate with altered total acidity evolution and pH increment during the ripening process. A new modelling framework is presented using historical data that supports management decisions by better understanding past impacts and forecasting for the future.