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This study investigated the temporal variability and changes in snow cover duration and the average snow depth from December to April in the Pyrenees at 1,500 and 2,100 m a.s.l. for the period 1958–2017. This is the first such analysis for the entire mountain range using SAFRAN‐Crocus simulations run for this specific purpose. The SAFRAN‐Crocus simulations were evaluated for the period 1980–2016 using 28 in situ snow depth data time series, and for the period 2000–2017 using MODIS observations of the snow cover duration. Following confirmation that the simulated snow series satisfactorily reproduced the observed evolution of the snowpack, the Mann–Kendall test showed that snow cover duration and average depth decreased during the full study period, but this was only statistically significant at 2,100 m a.s.l. The temporal evolution in the snow series indicated marked differences among massifs, elevations, and snow variables. In general, the most western massifs of the French Pyrenees underwent a greater decrease in the snowpack, while in some eastern massifs the snowpack did not decrease, and in some cases increased at 1,500 m a.s.l. The results suggest that the trends were consistent over time, as they were little affected by the start and end year of the study period, except if trends are computed only starting after 1980, when no significant trends were apparent. Most of the observed negative trends were not correlated with changes in the atmospheric circulation patterns during the snow season. This suggests that the continuous warming in the Pyrenees since the beginning of the industrial period, and particularly the sharp increase since 1955, is a major driver explaining the snow cover decline in the Pyrenees. [ABSTRACT FROM AUTHOR]

The FP7 project EUPORIAS was a great opportunity for the climate community to co-design with stakeholders some original and innovative climate services at seasonal time scales. In this framework, Météo- France proposed a prototype that aimed to provide to water resource managers some tailored information to better anticipate the coming season. It is based on a forecasting system, built on a refined hydrological suite, forced by a coupled seasonal forecast model. It particularly delivers probabilistic river flow prediction on river basins all over the French territory. This paper presents the work we have done with "EPTB Seine Grands Lacs" (EPTB SGL), an institutional stakeholder in charge of the management of 4 great reservoirs on the upper Seine Basin. First, we present the codesign phase, which means the translation of classical climate outputs into several indices, relevant to influence the stakeholder's decision making process (DMP). And second, we detail the evaluation of the impact of the forecast on the DMP. This evaluation is based on an experiment realised in collaboration with the stakeholder. Concretely EPTB SGL has replayed some past decisions, in three different contexts: without any forecast, with a forecast A and with a forecast B. One of forecast A and B really contained seasonal forecast, the other only contained random forecasts taken from past climate. This placebo experiment, realised in a blind test, allowed us to calculate promising skill scores of the DMP based on seasonal forecast in comparison to a classical approach based on climatology, and to EPTG SGL current practice. [ABSTRACT FROM AUTHOR]

In the autumn, the French Mediterranean area is frequently exposed to heavy precipitation events whose daily accumulation can exceed 300 mm. One of the key processes contributing to these precipitation amounts is deep convection, which can be explicitly resolved by state-of-the-art convection-permitting models to reproduce heavy rainfall events that are comparable to observations. This approach has been tested and performed at climate scale in several studies in recent decades for different areas. In this research, we investigate the added value of using an ensemble of three climate simulations at convection-permitting resolution (approx. 3 km) to replicate extreme precipitation events at both daily and shorter timescales over the south of France. These three convection-permitting simulations are performed with the Weather Research and Forecasting (WRF) Model. They are forced by three EURO-CORDEX simulations, which are also run with WRF at the resolution of 0.11 ∘ (approx. 12 km). We found that a convection-permitting approach provides a more realistic representation of extreme daily and 3-hourly rainfall in comparison with EURO-CORDEX simulations. Their similarity to observations allows use for climate change studies and its impacts. [ABSTRACT FROM AUTHOR]

In the autumn, the French Mediterranean area is frequently exposed to heavy precipitation events whose daily accumulation can exceed 300 mm. One of the key processes contributing to these precipitation amounts is the deep convection, which can be resolved explicitly by state-or-the-art convection-permitting model to reproduce heavy rainfall events that are comparable to observations. However, this approach has never been used in climate simulation for the Mediterranean coastal region. In this research, we investigate the added values of using three ensembles of climate simulations at convection-permitting resolution (approx. 3 km) in replicating extreme precipitation events in both daily and shorter time scale over the South of France. These three convection-permitting simulations are performed with the Weather Research and Forecasting Model (WRF). They are forced by three EURO-CORDEX simulations, which are also downscaled with WRF at the resolution of 0.11° (approx. 12 km). We found that a convection-permitting approach provides a more realistic representation of extreme daily and 3-hourly rainfall simulations in comparison with EURO-CORDEX simulations. Their similarity with observations allows a use for climate change studies and its impacts. [ABSTRACT FROM AUTHOR]

Several major storms pounded western Europe in January 2018, generating large damages and casualties. The two most impactful ones, Eleanor and Friederike, are analysed here in the context of climate change. Near surface wind speed station observations exhibit a decreasing trend in the frequency of strong winds associated with such storms. High-resolution regional climate models, on the other hand, show no trend up to now and a small increase in storminess in future due to climate change. This shows that factors other than climate change, which are not in the climate models, caused the observed decline in storminess over land. A large part is probably due to increases in surface roughness, as shown for a small set of stations covering the Netherlands and in previous studies. This observed trend could therefore be independent from climate evolution. We concluded that human-induced climate change has had so far no significant influence on storms like the two mentioned. However, all simulations indicate that global warming could lead to a marginal increase (0 %–20 %) in the probability of extreme hourly winds until the middle of the century, consistent with previous modelling studies. This excludes other factors, such as surface roughness, aerosols, and decadal variability, which have up to now caused a much larger negative trend. Until these factors are correctly simulated by climate models, we cannot give credible projections of future storminess over land in Europe. [ABSTRACT FROM AUTHOR]

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 10.5281/zenodo.1299760 for precipitation, 10.5281/zenodo.1299712 for temperature, and 10.5281/zenodo.1251843 for reference evapotranspiration. [ABSTRACT FROM AUTHOR]

We examine long-term trends in the historical record of extreme precipitation events occurring over the French Mediterranean area. Extreme events are considered in terms of their intensity, frequency, extent and precipitated volume. Changes in intensity are analysed via an original statistical approach where the annual maximum rainfall amounts observed at each measurement station are aggregated into a univariate time-series according to their dependence. The mean intensity increase is significant and estimated at + 22% (+ 7 to + 39% at the 90% confidence level) over the 1961-2015 period. Given the observed warming over the considered area, this increase is consistent with a rate of about one to three times that implied by the Clausius-Clapeyron relationship. Changes in frequency and other spatial features are investigated through a Generalised Linear Model. Changes in frequency for events exceeding high thresholds (about 200 mm in 1 day) are found to be significant, typically near a doubling of the frequency, but with large uncertainties in this change ratio. The area affected by severe events and the water volume precipitated during those events also exhibit significant trends, with an increase by a factor of about 4 for a 200 mm threshold, again with large uncertainties. All diagnoses consistently point toward an intensification of the most extreme events over the last decades. We argue that it is difficult to explain the diagnosed trends without invoking the human influence on climate. [ABSTRACT FROM AUTHOR]

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 (Spatially COherent Probabilistic Extended 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 paves the way for improving the knowledge on specific past meteorological events or for improving the 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 ttp://doi.org/10.5281/zenodo.1299760 for precipitation, ttp://doi.org/10.5281/zenodo.1299712 for temperature, and ttp://doi.org/10.5281/zenodo.1251843 for reference evapotranspiration. [ABSTRACT FROM AUTHOR]

Several major storms pounded Western Europe in January 2018, generating large damages and casualties. The two most impactful ones, Eleanor and Friederike, are analyzed here in the context of climate change. Near surface wind speed station observations exhibit a decreasing trend of the frequency of strong winds associated with such storms. High-resolution regional climate models on the other hand show no trend up to now and a small increase in the future due to climate change. This shows that that factors other than climate change, which are not represented (well) in the climate models, caused the observed decline in storminess over land. A large part is probably due to increases in surface roughness, as shown for a small set of stations covering The Netherlands and in previous studies. This trend could therefore be independent from climate evolution. We concluded that human-induced climate change has had so far no significant influence on storms like the two studied. However, all simulations indicate that global warming could lead to a marginal increase (0-20%) of the probability of extreme hourly winds until the middle of the century, consistent with previous modelling studies. However, this excludes other factors, such as roughness, aerosols, and decadal variability, which have up to now caused a much larger negative trend. Until these factors are simulated well by climate models they cannot give credible projections of future storminess over land in Europe. [ABSTRACT FROM AUTHOR]

Summary A Hydrological Ensemble Forecasting System (HEFS) known as SIMPE has been run over France in real time by Météo-France since 2004. The system combines the 51-member, 10-day ECMWF EPS atmospheric forcing at a 1.5° resolution with the ISBA-MODCOU physically-based distributed hydrological model to provide streamflow forecasts over France. The initial conditions for all the HEFS runs are provided by SIM; i.e., the ISBA-MODCOU model forced by the outputs of the mesoscale meteorological analysis system SAFRAN. A previous study introduced and tested two improvements of this system over a past period. These modifications consisted of an improved representation of the profile of hydraulic conductivity and the implementation of a data assimilation subsystem. The purpose of the present study was to test the HEFS and its two modifications in operational mode, with the new higher-resolution ECMWF EPS atmospheric forcing at 0.25° resolution, available in real time on the Météo-France database, and with less observed discharge available for the data assimilation subsystem. The new ISBA physics scheme led to a notable improvement in the discharge simulation in western and northeastern France, where no aquifers were simulated by the MODCOU model. This improvement was not impacted by real-time conditions. Likewise, the improvement resulting from the data assimilation system applied over France was not significantly affected by real-time conditions. The propagation of the data assimilation correction to gauging stations located upstream or downstream of the assimilated stations limited the deterioration of forecasted streamflow due to real-time conditions. Finally, the ECMWF EPS high-resolution atmospheric forcing had a significant impact on the streamflow forecasts for small catchments, which increased with lead time. [ABSTRACT FROM AUTHOR]

The article presents an atmospheric reanalysis over France performed with the Safran-gauge-based analysis system for the period 1958-2008. It states that long-term mean values, inter-annual and seasonal variability of the Safran 50-year analysis were presented for all computed variables including rainfall, snowfall, and mean air temperature. It notes that researchers assess the reanalysis through various validation experiments with both dependent and independent data.

Ski tourism plays a major role in European mountain areas such as the Alps, Pyrenees, Scandinavia, Turkey, Eastern European Mountains etc. Meteorological conditions govern the operating conditions of ski resorts, due to their reliance on natural snow fall and favorable conditions for snowmaking. However, there is currently a major lack of assessment of past and future operating conditions of ski resorts at the pan-European scale in the context of climate change. The presented work aims at filling this gap, as part of the ongoing development of "European Tourism" Sectoral Information System (SIS) of the Copernicus Climate Change Services (C3S). C3S is run by the European Center for Medium-range Weather Forecast (ECMWF) on behalf of the European Commission. The Mountain Tourism Meteorological and Snow Indi-cators (MTMSI) are derived using statistical adjustment of EURO-CORDEX climate projections (multiple GCM/RCM pairs for several RCP) using the UERRA 5.5 km resolution surface reanalysis as a reference, followed by snowpack models runs using the Crocus multi-layer model, with and without snow manage-ment options (grooming, snowmaking). Results are generated by 100 m elevation bands for NUTS-3 geographical areas spanning all mountainous areas in Europe. The resulting data can be aggregated in time and space in various ways, depending on the use case. The presentation quickly introduces the un-derpinning elements for the generation of this product, and illustrates results at the pan-European scale as well as for smaller scale case studies, for past and future climate conditions. The data will be made available freely through the Copernicus Data Store starting in 2019. It is expected that the data and the tools developed within this project will not only make it possible to analyze the climate sensitivity of ski tourism in Europe as a topical yet academic research question, but would also help third-parties in devel-oping climate services specifically targeting the ski tourism industry in Europe. [ABSTRACT FROM AUTHOR]

The SIM hydro-meteorological model is used in operation at Météo-France since 2003 for real time hydro-meteorological monitoring. It is also part of a real-time ensemble mid term prediction system and allows climate change impact studies as well as seasonnal forecast experiments. An hydro-meteorological system based on SIM, called SIM-PS, was first developped for demonstration in the frame of the European FP7 EUPORIAS project. It was then improved to provide real time seasonnal prediction over France each month. The Météo-France-system6 meteorological forecasts presently drive SIM model. A quantile-quantile correction of temperature and precipitation forecasts is previously applied. SIM predicts streamflows and soil moisture fields among other variables. A quantile-quantile adaptation of streamflow is also applied. Finally, SIM-PS forecasts are made available on a french website dedicated to seasonnal forecasts. An evaluation of those forecasts using a 24-year hindcast will be presented. The forecasted streamflows will be compared to the SIM reanalysis through statistical scores. A focus will be made on the low flows forecasts. SIM-PS is also used to produce so-called « climatological seasonnal forecasts ». The hydrological SIM simulation starts from the current initial soil moisture state and is driven by meteorological forcings from the past climatology. This kind of approach provides end-users with scenarii that happened previously but taking the current soil moisture situation into account. This system allows to assess the impact of the initial hydrological state (soil moisture, snow cover) on the hydrological forecasts. This is of high interest in some cases, such as a particularly dry period like the 2017 summer and autumn over France. The performances of both systems, Météo-France-system6 based seasonnal forecasts and climatological seasonnal forecasts, will be compared, particularly for low flow forecasts. Moreover, in the frame-work of the french AQUI-FR project, a new hydro-geological modelisation plateform is being developped. This platform aims at performing detailed hydro-geological analysis and forecasts over France. It gathers existing groundwater modeling tools, developped by the partners of the project. Within the next few months, the AQUI-FR platform is expected to replace the hydro-geological model MODCOU in the SIM system. In this context, the AQUI-FR platform was run to produce seasonnal hydro-geological forecasts, using the water fluxes derivated from SIM-PS. The streamflow forecasts performed with AQUI-FR for a 24-year hindcast will be compared to the one performed with the MODCOU model within SIM-PS. A focus will be made on the forecasts issued on the 1st of May for low flow prediction. [ABSTRACT FROM AUTHOR]

Many studies have investigated the climate variability of specific areas in the Pyrenees. However, due to the complexity of obtaining data from three different countries, a study of the Pyrenees as a whole was still missing. Here, for the first time and under the framework of the CLIM'PY project, scientists from Spain, France and Andorra are working together to create a common temperature and precipitation database. We collected 1,495 precipitation and 1,331 temperature series of both sides of the mountain range to create: 1) a high-resolution gridded dataset (1x1 km) including daily data for the period 1981-2015; and 2) a long-term monthly dataset based on 61 temperature and 119 precipitation homogenized series for the period 1950-2015. Then, we calculated the annual, seasonal and monthly trends. Likewise, we computed a set of 27 extreme precipitation and temperature indices from the World Meteorological Organization, as well as their trends, to assess the spatial distribution and long-term variability of the climate in the Pyrenees.Overall, we discovered an increase of both annual (0.2 ºC/decade) and seasonal temperature, especially in spring and summer (0.3 ºC/decade), and a slight decrease in precipitation (-1.8 %/decade), although in general not significant and including a high spatial variability. This decrease is significant, however, in the southernmost side and can be seen in the spatial distribution of all daily and extreme indices of precipitation. This study represents the first step to assess the impacts of climate change in the whole Pyrenees, helping achieve a better management of a territory that highly depends on climate (tourism, agriculture, etc.) and with a great ecological diversity. [ABSTRACT FROM AUTHOR]