Pascal Yiou

Understanding the relationship between mean temperature and its variance is essential for the prediction of temperature variability in the European region. Results on regional temperatures have been obtained for the climate of the 21st century but they mainly focused on monthly‐to‐seasonal variability. Since environmental variables such as plant phenology, net primary production or atmospheric pollution react on shorter timescales, it is necessary to investigate how daily variability is related to interannual temperature changes. Here, we assess the mean‐variance seasonal dependence of observed daily temperatures over Europe. We find that extreme mean temperatures in the summer and winter tend to be associated with more variance. This assessment allows us to test whether 11 climate model simulations used in the IPCC AR4 can reproduce this relationship in cold and warm seasons. Most models yield a fair performance in the winter, but apart from four models, the mean‐variance relationship is underestimated in the summer.

Extreme Value Theory (EVT) is a useful tool to describe the statistical properties of extreme events. Its underlying assumptions include some form of temporal stationarity in the data. Previous studies have been able to treat long-term trends in datasets, to obtain the time dependence of EVT parameters in a parametric form. Since there is also a dependence of surface temperature and precipitation to weather patterns obtained from pressure data, we determine the EVT parameters of those meteorological variables over France conditional to the occurrence of North Atlantic weather patterns in the summer. We use a clustering algorithm on geopotential height data over the North Atlantic to obtain those patterns. This approach refines the straightforward application of EVT on climate data by allowing us to assess the role of atmospheric variability on temperature and precipitation extreme parameters. This study also investigates the statistical robustness of this relation. Our results show how weather regimes can modulate the different behavior of mean climate variables and their extremes. Such a modulation can be very different for the mean and extreme precipitation.

Europe witnessed unprecedented warmth persisting throughout fall and winter 2006–2007, with only a few cold breaks. Whether this anomaly and recent warming in Europe can be linked to changes in atmospheric dynamics is a key question in the climate change prospective. We show that despite the fall/winter atmospheric flow was favorable to warmth, it cannot explain alone such an exceptional anomaly. Observed temperatures remained well above those found for analogue atmospheric circulations in other fall and winter seasons. Such an offset is also found during the last decade and culminates in 2006/2007. These observational results suggest that the main drivers of recent European warming are not changes in regional atmospheric flow and weather regimes frequencies, contrasting with observed changes before 1994.

This study focuses on two main rivers of Bohemia (Czech Republic): the Vltava and the Elbe. Flows are determined for the Elbe at Děčín (discharges) and Litoměřice (water stages), and for the Vltava... Cette étude traite des deux rivières principales de Bohême (République Tchèque): la Rivière Vltava et la Rivière Elbe. Les mesures sont effectuées à Děčín (débits) et à Litoměčice (niveaux d'eau) p...