A climatic classification of the world’s wine regions

Abstract

Using a dataset with 16 climate variables for locations representing 813 wine regions that cover 99 % of the world’s winegrape area, we employ principal component analysis (PCA) for data reduction and cluster analysis for grouping similar regions. The PCA resulted in three components explaining 89 % of the variation in the data, with loadings that differentiate between locations that are warm/dry from cool/wet, low from high diurnal temperature ranges, low from high nighttime temperatures during ripening, and low from high vapour pressure deficits. The cluster analysis, based on these three principal components, resulted in three clusters defining wine regions globally, with the results showing that premium wine regions can be found across each of the climate types. This is, to our knowledge, the first such classification of virtually all of the world’s wine regions. However, with both climate change and an increasing preference for premium relative to non-premium wines, many of the world’s winegrowers may need to change their mixes of varieties, or source more of their grapes from more appropriate climates.

Climate Change Impacts on Vineyards in Warm and Dry Areas: Challenges and Opportunities

“…A global phenology network could help to confirm whether, or to what extent, cultivars differ in their phenological response to diverse climates, and identify the genetic basis for such variability. Additionally, the correlation between the veraison ranking in Figure 5 and that for average growing season temperature by cultivar across the world (Puga et al 2022) is relatively weak (r s = 0.58, p = 0.02, n = 17 common cultivars). Thus, while cultivars with a later veraison date tend to be grown in warmer climates, some cultivars might perform well in diverse climates.…”

Winegrape Yield and Revenue Variability in Australia

“…Climate data on growing season average temperature (GST) and growing season precipitation (GSP) from Anderson and Puga [8] were also used for the study. GST is one of the most-used climate indexes to represent temperature in viticulture [10,11], and GSP is another commonly used index that has a high correlation with other precipitation-related variables [12].…”