INFERING THE RELATION OF HYDROMETEOROLOGICAL VARIABILITY ON THE DURANCE WATERSHED (SOUTHEASTERN FRANCE) TO LARGE SCALE CIRCULATION FROM ANATEM RECONSTRUCTED SERIES
Wednesday, 16 December 2015
Poster Hall (Moscone South)
Understanding large spatio-temporal hydrometeorological variabilities is critical in the present context of climate change. Large scale information analyses require long and numerous times series as input data. It is often met with difficulty because good quality time series are scarce and often not available over a large area. Reconstructions offer an interesting alternative to alleviate this problem. An original reconstruction method for rainfall and temperature called ANATEM has been developed by Electricité de France in 2013 (Kuentz et al., 2015) combining both a nearby time series (TEM) and a climate field (i.e: geopotential height)(ANA) as predictors. By using large scale information, this method should allow improving on the TEM regression model both in spatial and temporal dimensions. ANATEM was used to reconstruct daily rainfall time series from 25 stations of the Durance watershed in South of France, spanning 1883-2010. This study focused on extracting the large scale information contained in the reconstructed series. Wavelet analyses were used to break down the signal and extract its long-term component (out of 4 different time scales) while composite map analyses enabled to show the links between mean rainfall over the durance and climate fields in the Euro-Atlantic sector. The study showed that ANATEM reconstruction can indeed improve on long term/large scale reconstructions and thus that reconstructions can be used to infer climate processes. Wavelet Multiresolution analysis over the Durance watershed showed a dip in long-term rainfall from 1950 to the end of the 20th century. Composite analysis revealed that rainfall variation (from low to high rainfall) over the Durance watershed is mainly associated with transition from positive NAO-like pattern to negative NAO-like one. The spatial large scale information shows a strong variability with season. In summer, large scale forcings seem less apparent. Long term oscillations showed distinct spatio-temporal patterns compared to shorter term oscillations highlighting the role of local morphology such as relief. Future work should focus on important topics such as rainfall extremes evolution or non linearity/non stationarity in local-large scale relationship and many others.