High-resolution agroclimatic projections for assessing climate change impacts on French viticulture for the 2030, 2040, and 2050 horizons

Abstract

Agriculture is extremely vulnerable to climate change. Increases in air temperature, altered rainfall patterns, and more frequent extreme events are key climate impacts influencing crop yields, safety, and quality. Within this broader context, viticulture is particularly at risk due to its high sensitivity to climate variability and change, as grapevine development and grape quality are tightly controlled by temperature, water availability, and seasonal dynamics. French vineyards already show clear signs of climatic shifts affecting phenological timing and terroir suitability. Understanding and anticipating these changes at the local scale is crucial for sustaining productivity and resilience. However, standard climate projections operate at coarse spatial resolution (>50 km) and fail to capture the local heterogeneity that defines vineyard microclimates.

This study presents a comprehensive approach for generating and exploiting high-resolution daily weather series aligned with future climate projections while preserving the fine-scale spatial and temporal variability essential for viticultural impact assessment. The approach relies on two complementary high-resolution climate datasets covering metropolitan France at 1 km resolution and daily time step: (i) a historical reanalysis (1979–2021) derived from ERA5-Land using statistical downscaling followed by a bias-correction approach, and (ii) future projections for 2030, 2040, and 2050 based on CMIP6 models refined locally using the same methodology.
To move beyond aggregated statistical summaries and capture the sub-seasonal variability crucial to vine phenology, these projections were coupled with a stochastic weather generator that simulates multiple plausible daily weather trajectories for each location and time horizon. This probabilistic approach enables uncertainty quantification and exploration of adaptation pathways under different climate scenarios.

The resulting dataset allows computation of agroclimatic indicators critical for viticulture, including temperature sums, frost and drought risks, heat stress indices, disease pressure driven by humidity and temperature conditions, and climatic constraints on key phenological stages (budburst, flowering, etc.). A key advantage is the method’s capacity to adopt a phenological rather than calendar-based framework, which dynamically adjusts the timing of climatic exposure, offering a more biologically meaningful assessment of climate impacts on vine processes.

This work opens new perspectives for probabilistic risk assessment in viticulture, enabling fine-scale evaluation of climate-related risks for existing and alternative grape varieties under future conditions. Combined with phenological or water balance models, these data provide robust, actionable insights to support varietal selection, vineyard management, and the long-term adaptation of the French wine sector.

References

ER-RONDI, Mariam. (2025). Mieux évaluer l’impact du changement climatique sur l’agriculture en France : de la réanalyse historique à haute résolution à la projection d’indicateurs agro-climatiques aux horizons 2030/2040/2050. Université Clermont-Auvergne. PhD Dissertation.