報告人：Renan Leroux

　　時間：時間：2017年12月20日 星期三 下午15:40

　　地點：遙感地球所奧運園區(qū) A503

　　主要內(nèi)容：At vineyard scale, climate variability can be significant in magnitude and play a key role in vine and wine characteristics. Adaptation of viticulture to climate change requires knowledge about future fine-scale climate evolution. This study aims to integrate local scale in future climate projections, coupling dynamic and statistical modelling. A first step consisted in producing temperature maps at 1 km resolution using WRF in a vineyard area (Marlborough, New-Zealand) and evaluating model uncertainties. It revealed that dynamical models do not represent well local climate variations. Using a high density temperature data logger network, the second part is dedicated to developing a non-linear statistical model to map temperature at very fine scale in famous sub-appellations of the Bordeaux vineyard area (Saint-émilion). Following, a method, coupling dynamical and statistical modelling, is proposed to integrate local scale in climate change projections. This study highlights that using simultaneously statistical and dynamical models can be an approach to reduce model uncertainties.

　　報告人簡介：PhD in climatology, my work focuses on the local scale variations of climate in the context of climate change and consequences on the wine industry. Coupling climate model at different spatial scale and resolution is a key issue to integrate local climate in the climate change prediction, so I developed methods to combine fine scale statistical model with dynamical regional scale model.