Climatic Change

, Volume 119, Issue 3–4, pp 825–839 | Cite as

Projected shifts of wine regions in response to climate change

  • M. MoriondoEmail author
  • G. V. Jones
  • B. Bois
  • C. Dibari
  • R. Ferrise
  • G. Trombi
  • M. Bindi


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.


Random Forest Random Forest Model Random Forest Algorithm Wine Region Available Water Capacity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



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.

Supplementary material

10584_2013_739_MOESM1_ESM.doc (58 kb)
ESM 1 Table describing climatic indices calculation (DOC 57.5 kb)
10584_2013_739_MOESM2_ESM.doc (61 kb)
ESM 2 Table describing the spatial datasets used in this work (DOC 61 kb)
10584_2013_739_MOESM3_ESM.doc (52 kb)
ESM 3 Description of the model of water balance (DOC 52 kb)
10584_2013_739_MOESM4_ESM.doc (3.6 mb)
ESM 4 Description of Random Forest calibration strategy and relevant byproducts (Partial Plots) (DOC 3.59 MB)
10584_2013_739_MOESM5_ESM.doc (324 kb)
ESM 5 Description of climatic structure of wine regions (DOC 323 kb)
10584_2013_739_MOESM6_ESM.doc (162 kb)
ESM 6 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)
10584_2013_739_MOESM7_ESM.doc (112 kb)
ESM 7 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)


  1. 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 43:1223–1232CrossRefGoogle Scholar
  2. Amerine MA, Winkler AJ (1944) Composition and quality of musts and wines of California grapes. Hilgardia 15:493–673Google Scholar
  3. Bossard M, Feranec J, Otahel J (2000) Corine land cover technical guide — Addendum 2000. EEA Technical report No 40. Copenhagen (EEA)
  4. Breiman L (2001) Random forests. Mach Learn 45:5–32CrossRefGoogle Scholar
  5. 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 CrossRefGoogle Scholar
  6. Duchêne E, Schneider C (2005) Grapevine and climatic changes: a glance at the situation in Alsace. Agron Sustain Dev 25:93–99CrossRefGoogle Scholar
  7. 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
  8. Fraederick K, Gerstengarbe FW, Werner PC (2001) Climate shift during the last century. Clim Chang 50:405–417CrossRefGoogle Scholar
  9. Fregoni M (2003) L’indice bioclimatico di qualitá Fregoni. In: Fregoni M et al (eds) Terroir, Zonazione Viticoltura. Phytoline, Piacenza, pp 115–127Google Scholar
  10. 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 10:121–140Google Scholar
  11. Gladstones J (1992) Viticulture and environment. Winetitles, AdelaideGoogle Scholar
  12. Godden P, Gishen M (2005) Trends in the composition of Australian wine. Aust N Z Wine Ind J 20:21–46Google Scholar
  13. Hall A, Jones GV (2010) Spatial analysis of climate in winegrape-growing regions in Australia. Aust J Grape Wine Res 16:389–404CrossRefGoogle Scholar
  14. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978CrossRefGoogle Scholar
  15. Huglin P (1978) Nouveau mode d’évaluation des possibilités héliothermiques d’un milieu viticole. C R Acad Agric France 1117–1126Google Scholar
  16. Jones GV, Webb LB (2010) Climate change, viticulture, and wine: challenges and opportunities. J Wine Res 21:103–106CrossRefGoogle Scholar
  17. 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 CrossRefGoogle Scholar
  18. 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 2005Google Scholar
  19. 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 61:313–326Google Scholar
  20. 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 CrossRefGoogle Scholar
  21. Kenny GJ, Harrison PA (1992) The effects of climate variability and change on grape suitability in Europe. J Wine Res 3:163–183CrossRefGoogle Scholar
  22. Lavee S, May P (1997) Dormancy of grapevine buds—facts and speculation. Aust J Grape Wine Res 3:31–46CrossRefGoogle Scholar
  23. Malheiro AC, Santos JA, Fraga H, Pinto JG (2010) Climate change scenarios applied to viticultural zoning in Europe. Clim Res 43:163–177CrossRefGoogle Scholar
  24. 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 11:553–567CrossRefGoogle Scholar
  25. 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 ppGoogle Scholar
  26. Pope VD, Gallani ML, Rowntree PR, Stratton RA (2000) The impact of new physical parameterizations in the Hadley Centre climate model — HadAM3. Clim Dyn 16:123–146CrossRefGoogle Scholar
  27. Santos JA, Malheiro AC, Pinto JG, Jones GV (2012) Macroclimate and viticultural zoning in Europe: observed trends and atmospheric forcing. Clim Res 51:89–103CrossRefGoogle Scholar
  28. Shultz HR, Jones GV (2010) Climate induced historic and future changes in viticulture. J Wine Res 21:137–145CrossRefGoogle Scholar
  29. 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 29–39Google Scholar
  30. Tonietto J, Carbonneau A (2004) A multicriteria climatic classification system for grape-growing regions worldwide. Agric For Meteorol 124:81–97CrossRefGoogle Scholar
  31. Urhausen S, Brienen S, Kapala A, Simmer C (2011) Climatic conditions and their impact on viticulture in the Upper Moselle region. Clim Chang 109:349–373CrossRefGoogle Scholar
  32. 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):11217–11222CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • M. Moriondo
    • 1
    Email author
  • G. V. Jones
    • 2
  • B. Bois
    • 3
  • C. Dibari
    • 4
  • R. Ferrise
    • 4
  • G. Trombi
    • 4
  • M. Bindi
    • 4
  1. 1.CNR-IBIMETFlorenceItaly
  2. 2.Department of Environmental StudiesSouthern Oregon UniversityAshlandUSA
  3. 3.Institute of the Vine and Wine “J. Guyot”University of BurgundyDijon CedexFrance
  4. 4.Department of Agri-food Production and Environmental Sciences, University of FlorenceFlorenceItaly

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