## 2 Materials and Methods
### Crop Model Description  
The STICS (_Simulateur mulTIdsciplinaire pour les Cultures Standard_) crop model, version 121, was used herein to simulate grapevine yields [31]. This model is currently one of the few crop models that incorporates the necessary parameterizations for perennial crops and, more specifically, for grapevine simulations [32; 33; 34]. In a study by [PERSON] et al. [35], the STICS model was used to simulate yield, phenology and abiotic (water) stress conditions throughout Europe, showing a high agreement with observational data [35; 36]. Subsequently, this model was used in assessing the potential impacts of climate change on viticulture and the effectiveness of different adaptation strategies, like irrigation or mulching [37; 38]. The current study follows the same guidelines and parameterizations as in [PERSON], et al. [35].  
Regarding the model runs, the model operates on a daily time-step, simulating grapevine growth driven by daily weather data. Grapevine budburst is simulated by using the BRIN model [39], whereas flowering and veraison are simulated by using growing degree-days, with a base temperature of 10 \({}^{\circ}\)C. To simulate biomass growth, nitrogen and carbon reserves are considered, also taking into account competition between vegetative and generative organs. CO\({}_{2}\) effects on plant physiology and radiation use efficiency are also simulated [31]. Fruit growth is described by the dynamics of dry-matter accumulation and water content [40]. Temperature thresholds (i.e., frost and heat shock) are also taken into consideration for growth and development, which is critical for the objectives of the present study.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**COUNTRY** & **REGION** & **LON (\({}^{\circ}\))** & **LAT (\({}^{\circ}\))** & **T (\({}^{\circ}\)C)** & **P (mm)** \\ \hline \multirow{4}{*}{**France**} & \multicolumn{1}{c}{Alsace} & 7.38 & 48.20 & 10.6 & 605 \\  & Bordeaux & 0.55 & 44.50 & 13.2 & 807 \\  & Champagne & 4.00 & 49.16 & **10.5** & 664 \\  & Loire Valley & 0.13 & 47.12 & 12.3 & 684 \\  & Rhone & 4.83 & 44.06 & **14.7** & 733 \\ \hline \multirow{2}{*}{**Germany**} & \multicolumn{1}{c}{Mosel} & 6.87 & 49.28 & **10.4** & 766 \\  & Rheinlessen & 8.13 & 49.92 & 10.6 & 579 \\ \hline \multirow{4}{*}{**Italy**} & Emilia-Romagna & 10.93 & 44.50 & 13.1 & **840** \\  & Piedmont & 8.67 & 44.66 & 13.3 & **988** \\  & Sicily & 13.99 & 37.64 & **15.9** & 482 \\  & Tuscany & 11.77 & 43.08 & 13.6 & 723 \\ \hline \multirow{2}{*}{**Luxembourg**} & \multicolumn{1}{c}{Moselle} & 6.35 & 49.55 & **10.3** & 743 \\ \hline \multirow{2}{*}{**Portugal**} & \multicolumn{1}{c}{Alentejo} & \(-\)7.56 & 38.38 & **17.2** & 562 \\  & Douro & \(-\)7.55 & 41.17 & 13.3 & 830 \\  & Minho & \(-\)8.41 & 41.82 & 14.1 & **956** \\ \hline \multirow{2}{*}{**Spain**} & \multicolumn{1}{c}{La Mancha} & \(-\)2.69 & 39.65 & 14.2 & **455** \\  & La Rioja & \(-\)2.40 & 41.57 & 11.5 & 523 \\  & Ribera del Duero & \(-\)4.36 & 41.63 & 12.3 & **423** \\ \hline \end{tabular}
\end{table}
Table 1: Targeted winemaking regions (18 in total), with country and region designation, along with their centroid longitude and latitude, and area-means of annual mean temperature (T) and precipitation sum (P), calculated from the E-OBS dataset, version 19.0e, over the baseline period of 1986–2015. The three highest and lowest values are highlighted in bold.