title: Regional climate change scenarios applied to viticultural zoning in Mendoza, Argentina.
abstract: Due to the importance of the winemaking sector in Mendoza, Argentina, the assessment of future scenarios for viticulture is of foremost relevance. In this context, it is important to understand how temperature increase and precipitation changes will impact on grapes, because of changes in grapevine phenology and suitability wine-growing regions must be understood as an indicator of climate change. The general objective is to classify the suitable areas of viticulture in Argentina for the current and future climate using the MM5 regional climate change simulations. The spatial distribution of annual mean temperature, annual rainfall, and some bioclimatic indices has been analyzed for the present (1970-1989) and future (2080-2099) climate under SRES A2 emission scenario. In general, according to projected average growing season temperature and Winkler index classification, the regional model estimates (i) a reduction of cool areas, (ii) a westward and southward displacement of intermediate and warm suitability areas, and (iii) the arise of new suitability regions (hot and very hot areas) over Argentina. In addition, an increase of annual accumulated precipitation is projected over the center-west of Argentina. Similar pattern of change is modeled for growing season, but with lower intensity. Furthermore, the evaluation of projected seasonal precipitation shows a little precipitation increase over Cuyo and center of Argentina in summer and a little precipitation decrease over Cuyo and northern Patagonia in winter. Results show that Argentina has a great potential for expansion into new suitable vineyard areas by the end of twenty-first century, particularly due to projected displacement to higher latitudes for most present suitability winegrowing regions. Even though main conclusions are based on one global-regional model downscaling, this approach provides valuable information for implementing proper and diverse adaptation measures in the Argentinean viticultural regions. It has been concluded that regional climate change simulations are an adequate methodology, and indeed, the MM5 regional model is an appropriate tool to be applied in viticultural zoning in Mendoza, Argentina.
authors.affiliation: Centro de Investigaciones del Mar y la Atmósfera (CIMA/CONICET-UBA), Intendente Güiraldes 2160, Pabellón II, piso 2, Ciudad Universitaria, Buenos Aires, C1428EGA, Argentina. cabre@cima.fcen.uba.ar.|Instituto Franco Argentino de Estudios del Clima y sus Impactos (UMI IFAECI/CNRS), Buenos Aires, Argentina. cabre@cima.fcen.uba.ar.
authors.forename: María Fernanda
authors.initials: MF
authors.lastname: Cabré
authors.affiliation: Labotatoire LETG-Rennes-COSTEL, UMR6554 LETG du CNRS, Université Rennes 2, Place du Recteur Henri le Moal, 35000, Rennes, France.
authors.forename: Hervé
authors.initials: H
authors.lastname: Quénol
authors.affiliation: Centro de Investigaciones del Mar y la Atmósfera (CIMA/CONICET-UBA), Intendente Güiraldes 2160, Pabellón II, piso 2, Ciudad Universitaria, Buenos Aires, C1428EGA, Argentina.|Instituto Franco Argentino de Estudios del Clima y sus Impactos (UMI IFAECI/CNRS), Buenos Aires, Argentina.|Departamento de Ciencias de la Atmósfera y los Océanos, (DCAO/FCEN), Buenos Aires, Argentina.
authors.forename: Mario
authors.initials: M
authors.lastname: Nuñez
mesh_terms: D001118:Argentina; D057231:Climate Change; D008962:Models, Theoretical; D011891:Rain; D012621:Seasons; D013696:Temperature; D027843:Vitis
keywords: Argentinean viticultural zoning; Bioclimatic indices; MM5 regional model; Regional climate change scenarios
references.citation: Int J Biometeorol. 2016 Sep;60(9):1325-40
references.pmid: 26823161
references.citation: PLoS One. 2014 Sep 24;9(9):e108078
references.pmid: 25251495
references.citation: Int J Biometeorol. 2011 Mar;55(2):119-31
references.pmid: 20461417
references.citation: Proc Natl Acad Sci U S A. 2006 Jul 25;103(30):11217-22
references.pmid: 16840557
references.citation: Nature. 2002 Mar 28;416(6879):389-95
references.pmid: 11919621
references.citation: Nature. 2003 Jan 2;421(6918):57-60
references.pmid: 12511952
references.citation: PLoS One. 2013 Jul 23;8(7):e69015
references.pmid: 23894395
references.citation: Int J Biometeorol. 2001 Nov;45(4):184-90
references.pmid: 11769318
references.citation: Int J Biometeorol. 2012 Sep;56(5):853-64
references.pmid: 21909652
references.citation: Nature. 2004 Nov 18;432(7015):289-90
references.pmid: 15549085
references.citation: Int J Biometeorol. 2013 Nov;57(6):909-25
references.pmid: 23306774