Skip to main content

Projected shifts of wine regions in response to climate change


This research simulates the impact of climate change on the distribution of the most important European wine regions using a comprehensive suite of spatially informative layers, including bioclimatic indices and water deficit, as predictor variables. More specifically, a machine learning approach (Random Forest, RF) was first calibrated for the present period and applied to future climate conditions as simulated by HadCM3 General Circulation Model (GCM) to predict the possible spatial expansion and/or shift in potential grapevine cultivated area in 2020 and 2050 under A2 and B2 SRES scenarios. Projected changes in climate depicted by the GCM and SRES scenarios results in a progressive warming in all bioclimatic indices as well as increasing water deficit over the European domain, altering the climatic profile of each of the grapevine cultivated areas. The two main responses to these warmer and drier conditions are 1) progressive shifts of existing grapevine cultivated area to the north–northwest of their original ranges, and 2) expansion or contraction of the wine regions due to changes in within region suitability for grapevine cultivation. Wine regions with climatic conditions from the Mediterranean basin today (e.g., the Languedoc, Provence, Côtes Rhône Méridionales, etc.) were shown to potentially shift the most over time. Overall the results show the potential for a dramatic change in the landscape for winegrape production in Europe due to changes in climate.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2


  • Allouche O, Tsoar A, Kadmon R (2006) Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J Appl Ecol 43:1223–1232

    Article  Google Scholar 

  • Amerine MA, Winkler AJ (1944) Composition and quality of musts and wines of California grapes. Hilgardia 15:493–673

    Google Scholar 

  • Bossard M, Feranec J, Otahel J (2000) Corine land cover technical guide — Addendum 2000. EEA Technical report No 40. Copenhagen (EEA)

  • Breiman L (2001) Random forests. Mach Learn 45:5–32

    Article  Google Scholar 

  • Diffenbaugh NS, White MA, Jones GV, Ashfaq M (2011) Climate adaptation wedges: a case study of premium wine in the western United States. Environ Res Lett 6:024024. doi:10.1088/1748-9326/6/2/024024

    Article  Google Scholar 

  • Duchêne E, Schneider C (2005) Grapevine and climatic changes: a glance at the situation in Alsace. Agron Sustain Dev 25:93–99

    Article  Google Scholar 

  • Evans JS, Murphy MA, Holden ZA, Cushman SA (2011) Modeling species distribution and change using random forest. In: Drew CA et al (eds) Predictive species and habitat modeling in landscape ecology: concepts and applications. doi:10.1007/978-1-4419-7390-0_8, Springer Science+Business Media, LLC 2011

  • Fraederick K, Gerstengarbe FW, Werner PC (2001) Climate shift during the last century. Clim Chang 50:405–417

    Article  Google Scholar 

  • Fregoni M (2003) L’indice bioclimatico di qualitá Fregoni. In: Fregoni M et al (eds) Terroir, Zonazione Viticoltura. Phytoline, Piacenza, pp 115–127

    Google Scholar 

  • Gaál M, Moriondo M, Bindi M (2012) Modelling the impact of climate change on the Hungarian wine regions using random forest. Appl Ecol Environ Res 10:121–140

    Google Scholar 

  • Gladstones J (1992) Viticulture and environment. Winetitles, Adelaide

    Google Scholar 

  • Godden P, Gishen M (2005) Trends in the composition of Australian wine. Aust N Z Wine Ind J 20:21–46

    Google Scholar 

  • Hall A, Jones GV (2010) Spatial analysis of climate in winegrape-growing regions in Australia. Aust J Grape Wine Res 16:389–404

    Article  Google Scholar 

  • Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978

    Article  Google Scholar 

  • Huglin P (1978) Nouveau mode d’évaluation des possibilités héliothermiques d’un milieu viticole. C R Acad Agric France 1117–1126

  • Jones GV, Webb LB (2010) Climate change, viticulture, and wine: challenges and opportunities. J Wine Res 21:103–106

    Article  Google Scholar 

  • Jones GV, White MA, Cooper OR, Storchmann K (2005a) Climate change and global wine quality. Clim Chang 73:319–343. doi:10.1007/s10584-005-4704-2

    Article  Google Scholar 

  • Jones GV, Duchene E, Tomasi D, Yuste J, Braslavksa O, Schultz H, Martinez C, Boso S, Langellier F, Perruchot C, Guimberteau G (2005b) Changes in European winegrape phenology and relationships with climate. GESCO 2005

  • Jones GV, Duff AA, Hall A, Myers JW (2010) Spatial analysis of climate in winegrape growing regions in the western United States. Am J Enol Vitic 61:313–326

    Google Scholar 

  • Keller M (2010) Managing grapevines to optimize fruit development in a challenging environment: a climate change primer for viticulturists. Aust J Grape Wine Res 16:56–69. doi:10.1111/j.1755-0238.2009.00077.x

    Article  Google Scholar 

  • Kenny GJ, Harrison PA (1992) The effects of climate variability and change on grape suitability in Europe. J Wine Res 3:163–183

    Article  Google Scholar 

  • Lavee S, May P (1997) Dormancy of grapevine buds—facts and speculation. Aust J Grape Wine Res 3:31–46

    Article  Google Scholar 

  • Malheiro AC, Santos JA, Fraga H, Pinto JG (2010) Climate change scenarios applied to viticultural zoning in Europe. Clim Res 43:163–177

    Article  Google Scholar 

  • Moriondo M, Bindi M, Fagarazzi C, Ferrise R, Trombi G (2011) Framework for high-resolution climate change impact assessment on grapevines at a regional scale. Reg Environ Change 11:553–567

    Article  Google Scholar 

  • Nakićenović N et al (2000) Special report on emissions scenarios: a special report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, 599 pp

    Google Scholar 

  • Pope VD, Gallani ML, Rowntree PR, Stratton RA (2000) The impact of new physical parameterizations in the Hadley Centre climate model — HadAM3. Clim Dyn 16:123–146

    Article  Google Scholar 

  • Santos JA, Malheiro AC, Pinto JG, Jones GV (2012) Macroclimate and viticultural zoning in Europe: observed trends and atmospheric forcing. Clim Res 51:89–103

    Article  Google Scholar 

  • Shultz HR, Jones GV (2010) Climate induced historic and future changes in viticulture. J Wine Res 21:137–145

    Article  Google Scholar 

  • Stock M, Gerstengarbe FW, Kartshall T, Werner PC (2005) Reliability of climate change impact assessment for viticulture. Proc. VII IS on Grapevine (Ed. LE Williams). Acta Hort 689, ISHS pp 29–39

  • Tonietto J, Carbonneau A (2004) A multicriteria climatic classification system for grape-growing regions worldwide. Agric For Meteorol 124:81–97

    Article  Google Scholar 

  • Urhausen S, Brienen S, Kapala A, Simmer C (2011) Climatic conditions and their impact on viticulture in the Upper Moselle region. Clim Chang 109:349–373

    Article  Google Scholar 

  • White MA, Diffenbaugh NS, Jones GV, Pal JS, Giorgi F (2006) Extreme heat reduces and shifts United States premium wine production in the 21st century. Proc Natl Acad Sci U S A 103(30):11217–11222

    Article  Google Scholar 

Download references


This research was supported by the Commission of EU (Project MEDIATION, project no. 244012). The authors would like to gratefully acknowledge the constructive comments provided by the two anonymous referees.

Author information

Authors and Affiliations


Corresponding author

Correspondence to M. Moriondo.

Electronic supplementary material

Below is the link to the electronic supplementary material.


Table describing climatic indices calculation (DOC 57.5 kb)


Table describing the spatial datasets used in this work (DOC 61 kb)


Description of the model of water balance (DOC 52 kb)


Description of Random Forest calibration strategy and relevant byproducts (Partial Plots) (DOC 3.59 MB)


Description of climatic structure of wine regions (DOC 323 kb)


Figures depicting the Random Forest accuracy in predicting grapevine cultivated area (Fig. 1, 2) and trend in wine regions shift in 2020 and 2050 (Fig. 3) (DOC 162 kb)


Tables showing Huglin index, Water deficit, minimum temperature of the coldest and maximum temperatures of warmest months of wine regions projected in 2020 and 2050 (A2 and B2 scenarios) (DOC 112 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Moriondo, M., Jones, G.V., Bois, B. et al. Projected shifts of wine regions in response to climate change. Climatic Change 119, 825–839 (2013).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • Random Forest
  • Random Forest Model
  • Random Forest Algorithm
  • Wine Region
  • Available Water Capacity