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Abstract. In 2015 large parts of Europe were affected by drought. In this paper, we analyze the hydrological footprint (dynamic development over space and time) of the drought of 2015 in terms of both severity (magnitude) and spatial extent and compare it to the extreme drought of 2003. Analyses are based on a range of low flow and hydrological drought indices derived for about 800 streamflow records across Europe, collected in a community effort based on a common protocol. We compare the hydrological footprints of both events with the meteorological footprints, in order to learn from similarities and differences of both perspectives and to draw conclusions for drought management. The region affected by hydrological drought in 2015 differed somewhat from the drought of 2003, with its center located more towards eastern Europe. In terms of low flow magnitude, a region surrounding the Czech Republic was the most affected, with summer low flows that exhibited return intervals of 100 years and more. In terms of deficit volumes, the geographical center of the event was in southern Germany, where the drought lasted a particularly long time. A detailed spatial and temporal assessment of the 2015 event showed that the particular behavior in these regions was partly a result of diverging wetness preconditions in the studied catchments. Extreme droughts emerged where preconditions were particularly dry. In regions with wet preconditions, low flow events developed later and tended to be less severe. For both the 2003 and 2015 events, the onset of the hydrological drought was well correlated with the lowest flow recorded during the event (low flow magnitude), pointing towards a potential for early warning of the severity of streamflow drought. Time series of monthly drought indices (both streamflow- and climate-based indices) showed that meteorological and hydrological events developed differently in space and time, both in terms of extent and severity (magnitude). These results emphasize that drought is a hazard which leaves different footprints on the various components of the water cycle at different spatial and temporal scales. The difference in the dynamic development of meteorological and hydrological drought also implies that impacts on various water-use sectors and river ecology cannot be informed by climate indices alone. Thus, an assessment of drought impacts on water resources requires hydrological data in addition to drought indices based solely on climate data. The transboundary scale of the event also suggests that additional efforts need to be undertaken to make timely pan-European hydrological assessments more operational in the future.

Abstract. This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871-2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards.The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis, available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871-2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over-and under-estimated over the whole of France.Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature (T ). Comparisons to the Safran reanalysis over 1959-2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in a quantitative precipitation forecast context, the stepwise subselection method allows for potential season shifts and SST trends and is therefore better suited for climate reconstructions and climate change studies.The probabilistic downscaling of 20CR over the period 1871-2012 with the SANDHY probabilistic downscaling method combined with the stepwise subselection thus constitutes a perfect framework for assessing the recent observed meteorological events but also future events projected by climate change impact studies and putting them in a historical perspective.

Abstract. The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatiotemporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

Abstract. SCOPE Climate (Spatially COherent Probabilistic Extended Climate dataset) is a 25-member ensemble of 142-year daily high-resolution reconstructions of precipitation, temperature, and Penman–Monteith reference evapotranspiration over France, from 1 January 1871 to 29 December 2012. SCOPE Climate provides an ensemble of 25 spatially coherent gridded multivariate time series. It is derived from the statistical downscaling of the Twentieth Century Reanalysis (20CR) by the SCOPE method, which is based on the analogue approach. SCOPE Climate performs well in comparison to both dependent and independent data for precipitation and temperature. The ensemble aspect corresponds to the uncertainty related to the SCOPE method. SCOPE Climate is the first century-long gridded high-resolution homogeneous dataset available over France and thus has paved the way for improving knowledge on specific past meteorological events or for improving knowledge on climate variability, since the end of the 19th century. This dataset has also been designed as a forcing dataset for long-term hydrological applications and studies of the hydrological consequences of climate variability over France. SCOPE Climate is freely available for any non-commercial use and can be downloaded as NetCDF files from https://doi.org/10.5281/zenodo.1299760 for precipitation, https://doi.org/10.5281/zenodo.1299712 for temperature, and https://doi.org/10.5281/zenodo.1251843 for reference evapotranspiration.