Methods and results:Window pane analysis showed that pre-bloom and bloom minimum temperatures and precipitation sums in the preceding year, winter temperatures, spring temperatures, and post-veraison minimum temperatures in the current year were positively correlated with annual yield; early spring and post-harvest temperatures in the preceding year, and, for Riesling, pre-bloom precipitation sums and post-bloom maximum temperatures in the current year were negatively correlated with annual yield. Models developed from these data simulated annual yield with high accuracy (R 2 adj = 0.88 for Riesling, and R 2 adj = 0.92 for Müller-Thurgau).
Conclusions:Meteorological conditions during distinct periods of yield formation are correlated with annual yield. Yield models can be used in practical viticulture as well as in climate change impact studies.Significance and impact of the study: Enhanced understanding of the effects of meteorological conditions during specific periods of yield formation supports growers' efforts to optimize viticultural measures aimed at achieving adequate yield levels.