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Aim: While it is well recognised that climate can vary spatially so that grapevine phenology significantly varies within a winegrowing region, the magnitude of temporal variability in climate determining factors to engender a significant difference in phenology over time can only currently be described in general terms. This study’s aim was to quantify and compare the temporal variability, and its interaction with spatial variability, in grapevine phenology and three derived viticulture climate indexes for three viticulture regions in eastern Australia with varying topographies, latitudes and continentalities. Methods and Results: Maximum and minimum temperature data were spatially interpolated to produce fine scale topoclimate maps at 30 m resolution for every day of a 20 year period from 1998 to 2018 for the three viticulture regions. Grapevine phenology modelling using a heat accumulation methodology was then applied to estimate growing season temperature, cool night index and post-harvest growing degree days (GDD) for every 30 m map pixel of the three regions in each of the 20 growing seasons. Conclusions: Summary statistics that quantify the spatial and year-to-year temporal variability and the interaction of spatial and temporal variability (i.e. spatiotemporal variability) demonstrated significant differences in grapevine phenology between each of three regions. The key conclusion was that within-region temporal variability in growing season temperature, cool night index and post-harvest GDD exceeded within-region spatial variability. Significance and impact of the study: This is the first study to quantify temporal variability in modelled grapevine phenology, compare this with the level of spatial variability and also consider the interaction of spatial and temporal variability in grapevine phenology within viticultural regions. This study opens many potential lines of further investigation into the effect of temporal variability on wine production and the cultural terroir factors that develop within a wine region as a result, particularly in the context of forecast future increases in inter-annual temperature variability.

Modelling within-region spatiotemporal variability in grapevine phenology with high resolution temperature data