<p style="text-align: justify;"><strong>Aim</strong>: To improve knowledge of spatial climatic variability in viticultural region at fine scale</p><p style="text-align: justify;"><strong>Methods and results</strong>: Night temperatures recorded at 40 data loggers that were located in the vineyards of the Stellenbosch Wine of Origin District were monitored during different weather conditions during the 2009 grape ripening period (January-March). The daily maximum difference in minimum temperature between the coolest and warmest sites was, on average, 3.2 °C for the three-month period while it reached a difference of 14 °C under radiative conditions (a difference of 1 °C to 2 °C per km and 3 °C per 100 m elevation approximately). Numerical simulations of night temperatures, using a mesoscale atmospheric model, were performed for two weather events over this period. Night temperature fields at 200m resolution were generated, taking large scale weather conditions into account. Data from 16 automatic weather stations were used for validation. Temperature data from the data loggers that were located in the vineyards were used to produce maps of spatial distribution of the daily minimum temperature at a 90m scale by means of multicriteria statistical modelling, which concomitantly took environmental factors into account. Locations with optimum thermal conditions for color and flavor development and maintenance were identified based on average values for the three-month period and for specific weather conditions.</p><p style="text-align: justify;"><strong>Conclusion</strong>: The range of minimum temperatures varied as a function of geographical factors and synoptic weather conditions, which resulted in significant differences in night-time thermal conditions over the wine district, with possible implications for grape metabolism. The great spatial variability within short distances emphasized the difficulty of validating outputs of atmospheric modelling with accuracy. The study showed the importance and relevance of increasing resolution to refine studies on climate spatial variability and to perform climate modelling based on distinguished weather types.</p><p style="text-align: justify;"><strong>Significance and impact of the study</strong>: In the context of climate change, it is crucial to improve knowledge of current climatic conditions at fine scale during periods of grapevine growth and berry ripening in order to have a baseline from which to work when discussing and considering future local adaptations to accommodate to a warmer environnement.</p>
Permafrost causes unique fine‐scale spatial variability across tundra soils
