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Methodologies for climate variability analysis of winegrowing regions. A case study of Bordeaux winegrowing area. Benjamin BOIS Centre de Recherches de Climatologie Université de Bourgogne
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Spatial analysis of climate for viticulture Risk management –Pest management (models) –Frost, hail, wind, excessive drought risks Terroir comprehension and characterization –Vineyard management –Site selection Source : RSVAH (2007), Sandoz Bindi & Maselli (2001)
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1 cm 10 cm1 m10 m100 m1 km10 km100 km1000 km Micro-scale Macro-scale LeafCanopyPlotVineyard Climate differences > Uncertainty From Oke (1978) Climate differences Uncertainty ? Local scale Meso-scale Spatial scale in climatology RegionCountry
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Climate spatialization 11,5°C 12°C 14°C 13°C ? Interpolation Meteorological models Remote sensing
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Bordeaux winegrowing region Normals (1976-2005) Villenave dOrnon 0 5 10 15 20 25 30 Jan. Mar. Mai Jul. Sept. Nov. Temperature (°C) 0 20 40 60 80 100 120 Rainfall (mm) RR Tmin Tmax Tmoy
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Rainfall ET 0 RsRs MODELS ET AGRO- CLIMATIC INDICES at daily time step Soil water balance Degree-days Stations T min T max Radar CORINE DEM Sat Zoning
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Zoning relevance Is the spatialization uncertainty sufficiently low to draw reliable analysis of the spatial structure of climate ?
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Spatialization accuracy Variable Spatialization technique Available period Evaluation period RMSE (Apr.-Sept.) Rainfall Ordinary kriging1994-2005 5.6 mm/month (11%) T min Multiple regression + kriging 2001-2005 0.86°C T max Multiple regression + kriging 2001-2005 0.6°C RsRs Satellite sensing + DEM 1985-20052001-2005 3.3 MJ/m²/day (17%) ET 0 Turc method2001-2005 0.57 mm/day (16%)
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Spatialization accuracy TEMPERATURE Half-véraison (DD prediction vs. field observations) Predicted values vs. grapevine phenology Spatialization residuals (errors) vs. Measured spatial variability RAINFALL Comparison of several interpolation methods
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Zoning relevance Is the spatialization uncertainty sufficiently low to draw reliable analysis of the spatial structure of climate ? Is the spatial structure redundant ?
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Rainfall year-to-year variability 2004 1994
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64% 21% 12% 1% Degree.days Zoning 2001-2005 period Cool zones ( +5 to +15 days): Early cultivars (Merlot, white cultivars,…) Warm zones ( -5 to -15 days): Late cultivars (Cabernet-Sauvignon, Petit Verdot) Climate change consideration Interclass interval : 42 to 79 DD 5 to 11 days
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Conclusions New technologies (remote sensing, GIS, increasing computing potentialities) More accurate interpolations, reduction of the cost / scale dilemma
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Conclusions The need for climate spatial analysis recommendations Numerous methods and data Ergonomic simple !
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Thanks ! …Work in progress… TERVICLIM (Very large scale climate analysis and modelling) Large scale climate analysis (Jones et al.) World classification of winegrowing regions Bois (unpublished)
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Résultats RMSE = 0.86°C RMSE = 0.59°C
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Temperature 2001-2005 period Strong inter-annual variations ST Jan.-Sept. 2002 (DD) ST Jan.-Sept. 2003 (DD)
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0.5 0.6 0.7 0.8 0.9 1 YearApr. - Sept. RMSE (°C) OK IDWA MRK T min Daily temperature spatialization 0.5 0.6 0.7 0.8 0.9 1 YearApr. - Sept. RMSE (°C) T max Minimal temperature vs. distance to Gironde estuary
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Rayonnement global RMSE annuelle de 2,7 MJ.m -2 par jour (19,8%) Sous-estimation : biais de -11,1% Climatologie de la Gironde –Gradient Ouest-Est de temps clair décroissant. –Jusquà 20% décart max. en hiver, 16% en été (8% en Gironde viticole) –Effet notable du relief N
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R s HelioClim-1 (MJ.m -2 ) R s pyranometer (MJ.m -2 ) Solar radiation spatilization 2001-2005 (1826 days) Annual RMSE = 2.7 MJ.m -2 (19.8%) RMSE Aug.-Sept. =2.9 MJ.m -2 (16.6%) 10 to 6% 6 to 1% 3 to -3% -3 to -8% -8 to -13% Urban areas Saint-Émilion village
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ET 0 RsRs T min T max Potential Evapotranspiration : Turc Method with local re-adjustement Annual RMSE= 0.51 (21%) Apr.-Sept. RMSE= 0.57 (15.9%)
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Saint-emilion – zoom – moy. Ver mat 20 ans N
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ETP RMSE = 0.25 mm (11%)RMSE = 0.41 mm (17%)
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ETP (prop. Interpolation T) Données de validation croisée du processus dinterpolation des températures (MRK) Faible propagation des erreurs dinterpolation de la température quotidienne RMSE ~ 0.05 mm
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Radar (Hydram Method) RMSE = 4.4 mm Ordinary kriging RMSE = 2.5 mm RADAR Rainfall spatialization Numerous artifacts with radar rainfall estimates Ordinary kriging at different time steps 114 days – 51 raingauges location
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