Articles | Volume 7, issue 2
https://doi.org/10.5194/cp-7-425-2011
https://doi.org/10.5194/cp-7-425-2011
Research article
 | 
28 Apr 2011
Research article |  | 28 Apr 2011

Seasonal climate impacts on the grape harvest date in Burgundy (France)

M. Krieger, G. Lohmann, and T. Laepple

Abstract. In this study, we analyse the climatic impacts on the grape harvest date (GHD) in Burgundy (France) on interannual and decadal time scales. We affirm that the GHD is mainly influenced by the local April-to-August temperature (AAT) and provide the spatial expansion of this relationship. The spatial correlation pattern yields similar results for the instrumental and pre-instrumental period, indicating the consistency of the pre-instrumental field data with the instrumental GHD-spring/summer relationship. We find a previously undocumented second climate impact on the GHD. The winter temperature is significantly correlated with the GHD on decadal-to-multidecadal time scales and affects the GHD independently of the AAT. A multiple linear regression model, with AAT and decadal winter temperature as predictors, was found to be the best model to describe the GHD time series for the instrumental period. Stability tests of the correlations over time yield that both impacts on the GHD, AAT and decadal winter temperature, strengthen during the instrumental period. Using partial correlation analysis, we demonstrate that this is partly caused by a change in the winter–spring/summer temperature relationship. Summarising, the GHD is well suited to reconstruct interannual variations of the spring/summer temperature over large parts of Europe, even if the changing winter–spring/summer relation might affect the reconstruction in a second order. For decadal time scales, the December-to-August temperature shows the strongest relationship to the GHD and, therefore, proposes that the GHD can be used for European temperature reconstructions beyond the spring/summer season. Finally, we argue that our findings regarding the changed winter–spring/summer relation are relevant for physical and biological systems in several ways and should be analysed by other long-term proxy data and available model simulations.

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