Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite

Physically-based droughts can be defined as a water deficit in at least one component of the land surface hydrological cycle. The reliance of different activity domains (water supply, irrigation, hydropower, etc.) on specific components of this cycle requires drought monitoring to be based on indices related to meteorological, agricultural, and hydrological droughts. This paper describes a high-resolution retrospective analysis of such droughts in France over the last fifty years, based on the Safran-Isba-Modcou (SIM) hydrometeorological suite. The high-resolution 1958–2008 Safran atmospheric reanalysis was used to force the Isba land surface scheme and the hydrogeological model Modcou. Meteorological droughts are characterized with the Standardized Precipitation Index (SPI) at time scales varying from 1 to 24 months. Similar standardizing methods were applied to soil moisture and streamflow for identifying multiscale agricultural droughts – through the Standardized Soil Wetness Index (SSWI) – and multiscale hydrological droughts, through the Standardized Flow Index (SFI). Based on a common threshold level for all indices, drought event statistics over the 50-yr period – number of events, duration, severity and magnitude – have been derived locally in order to highlight regional differences at multiple time scales and at multiple levels of the hydrological cycle (precipitation, soil moisture, streamflow). Results show a substantial variety of temporal drought patterns over the country that are highly dependent on both the variable and time scale considered. Independent spatio-temporal drought events have then been identified and described by combining local characteristics with the evolution of area under drought. Summary statistics have finally been used to compare past severe drought events, from multi-year precipitation deficits (1989–1990) to short hot and dry periods (2003). Results show that the ranking of drought events depends highly on both the time scale and the variable considered. This multilevel and multiscale drought climatology will serve as a basis for assessing the impacts of climate change on droughts in France

Changements sur les caractéristiques des sécheresses en France au cours du 21e siècle

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Uncertainties in the Safran 50-year atmospheric reanalysis over France

International audienceLong-term retrospective meteorological datasets at high spatial and temporal resolution are of critical use in regional climate change assessment. Safran is a gauge-based analysis system that combines atmospheric profiles from ECMWF global scale reanalyses with ground observations to provide time series of seven variables - solid and liquid precipitation, air temperature, specific humidity, wind speed, visible and infrared radiation - for climatically homogenous zones. Within the ClimSec project, Safran has here been applied over France to build a 50-year meteorological dataset with a 8 km spatial resolution (Vidal et al., 2010). This study focuses on the uncertainties identified in this long-term reanalysis. Several tests were conducted in order to investigate three different sources of uncertainty. The intrinsic uncertainty of the analysis system, due to the spatial and temporal interpolation steps, is first assessed over the whole period 1958-2008 by comparing Safran outputs with observations at 83 high-quality validation stations included in the analysis (dependent data). The second source of uncertainty is related to the significance of the ground network density and its evolution over the 50-year period. This type of uncertainty has been studied throughout three experiments: (1) four years sampling the rise in available observations were selected for running the Safran analysis after having discarded observations from the validation stations (independent data); (2) the Safran analysis has been run again for a recent year by considering only stations available in the early 1960s; and (3) the analysis was finally run for the same recent year by considering no ground observation at all. The last studied source of uncertainty results from the non-homogeneity in time series of surface observations and is here assessed by comparing long-term trends computed from reanalysis outputs and from homogenized time series. Results first show that Safran intrinsic bias and error are relatively low and fairly constant over the 50-year period. The dramatic rise in the number of observations that occurred in the 1990s results in a large decrease of the uncertainty between the late 1950s and the early 2000s for all variables expect precipitation for which a dense network of observations was already available at the beginning of the period. Large-scale information only appears not to be sufficient for adequately representing spatial patterns of visible and infrared radiation and wind speed fields. Adding observations from stations available in the early 1960s improves significantly the results for all variables except visible radiation and wind speed, whose field correlation remain low. Finally, trend estimates from the Safran reanalysis compare well to homogenized series for precipitation, but show very scattered values for minimum and maximum temperature that are not found in trends from homogenized series

Typologie des sécheresses sur la France et outils de suivi de la ressource en eau utilisés à Météo-France

La France a subi des sécheresses en 2003, 2005 et 2006, dont les conséquences notamment sur les bâtiments ont mis en lumière l’importance de ce risque naturel. En raison de ses missions, Météo-France suit l’ensemble des phénomènes météorologiques, dont les sécheresses, via la quantification des déficits pluviométriques observés par un important réseau de mesure de précipitations et des systèmes d’analyse atmosphérique. Dans cet article, on présente les différents types de sécheresse et la comparaison des sécheresses récentes par rapport aux sécheresses connues dans le passé. De plus, Météo-France utilise des modèles de suivi du bilan en eau comme le modèle Safran Isba Modcou (SIM) pour mieux appréhender les conséquences des déficits pluviométriques et de la demande évaporative sur l’extension et l’intensité de la sécheresse. SIM permet de calculer des bilans d’eau spatialisés et en particulier un indice d’humidité du sol et un stock de neige sur les montagnes. Ces données sont utilisées dans le suivi hydrologique en France. Les caractéristiques et quelques résultats en terme de contenu en eau du sol de deux de ces modèles sont présentés

Assessing changes in drought characteristics with standardized indices

International audienceStandardized drought indices like the Standardized Precipitation Index (SPI) are more and more frequently adopted for drought reconstruction, monitoring and forecasting, and the SPI has been recently recommended by the World Meteorological Organization to characterize meteorological droughts. Such indices are based on the statistical distribution of a hydrometeorological variable (e.g., precipitation) in a given reference climate, and a drought event is defined as a period with continuously negative index values. Because of the way these indices are constructed, some issues may arise when using them in a non-stationnary climate. This work thus aims at highlighting such issues and demonstrating the different ways these indices may -- or may not -- be applied and interpreted in the context of an anthropogenic climate change. Three major points are detailed through examples taken from both a high-resolution gridded reanalysis dataset over France and transient projections from the Arpege general circulation model downscaled over France. The first point deals with the choice of the reference climate, and more specifically its type (from observations/reanalysis or from present-day modelled climate) and its record period. Second, the interpretation of actual changes are closely linked with the type of the selected drought feature over a future period: mean index value, under-threshold frequency, or drought event characteristics (number, mean duration and magnitude, seasonality, etc.). Finally, applicable approaches as well as related uncertainties depend on the availability of data from a future climate, whether in the form of a fully transient time series from present-day or only a future time slice. The projected evolution of drought characteristics under climate change must inform present decisions on long-term water resources planning. An assessment of changes in drought characteristics should therefore provide water managers with appropriate information that can help building effective adaptation strategies. This work thus aims at showing the potential of standardized indices to describe changes in drought characteristics, but also possible pitfalls and potentially misleading interpretations

Changes in drought characteristics in France during the 21st century

International audienceStandardized drought indices such as the Standardized Precipitation Index (SPI) have been shown to be highly relevant for drought reconstruction and drought monitoring. Such indices can be built to deal with different types of drought (meteorological, agricultural and hydrological) and to study droughts at different time and spatial scales. In this study, a 50-year multilevel and multiscale drought reanalysis over France recently built with Safran-Isba-Modcou hydrometeorological suite will serve as a basis for assessing the impact of climate change on droughts. An ensemble of climate projections have been statistically downscaled in order to force the Isba and Modcou hydrological models over France and generate 8-km gridded soil moisture time series as well as streamflow time series at more than 900 locations. Two different statistical downscaling methods have been applied using the Safran high resolution atmospheric reanalysis dataset over France: a method based on weather types and regressions, and a quantile-quantile method. As a first step, transient runs from only one general circulation model have been used under different climate scenarios. Three different standardized indices previously applied for the drought reanalysis are here used to estimate the evolution of droughts in the future: the commonly used SPI, the Standardized SoilWetness Index (SSWI) based on soil moisture simulated by Isba and the Standardized Flow Index (SFI) based on streamflow computed by Modcou. Changes in the characteristics (occurrence, intensity, duration, spatial scale) of meteorological, agricultural and hydrological droughts in France during the 21st century are here presented using the different drought indices. This panel of indices may provide useful information at the level of interest of different human activities (water supply, irrigation, hydropower, etc.)

DRIAS: a step toward Climate Services in France

International audienceAbstract. DRIAS (Providing access to Data on French Regionalized climate scenarios and Impacts on the environment and Adaptation of Societies) is a 2-yr project (2010–2012). It is funded by the GICC (Management and Impact of Climate Change) program of the French Ministry of Ecology, Sustainable Development, Transportation, and Housing (MEDDTL). DRIAS is to provide easy access to French regional climate data and products in order to facilitate mitigation and adaptation studies. The DRIAS project focuses on existing French regional climate projections obtained from national modelling groups such as: IPSL, CERFACS, and CNRM. It is more than a data server, it also delivers all kinds of climate information from numerical data to tailored climate products. Moreover, guidance is to be provided to end-users in order to promote best practices and know-how. Whilst the project is coordinated by the Department of Climatology at Météo-France, a multidisciplinary group of users and stakeholders at large concerned by climate change issues is also involved with the project. The ultimate goal will be to identify societal needs, validate the decision making processes, and thus facilitate exchanges between producers and practitioners. Key results from the DRIAS project will contribute to the implementation of French Climate Services

Development and evaluation of CNRM Earth system model – CNRM-ESM1

We document the first version of the Centre National de Recherches Météorologiques Earth system model (CNRM-ESM1). This model is based on the physical core of the CNRM climate model version 5 (CNRM-CM5) model and employs the Interactions between Soil, Biosphere and Atmosphere (ISBA) and the Pelagic Interaction Scheme for Carbon and Ecosystem Studies (PISCES) as terrestrial and oceanic components of the global carbon cycle. We describe a preindustrial and 20th century climate simulation following the CMIP5 protocol. We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers. Over the 1986–2005 period, CNRM-ESM1 reproduces satisfactorily several aspects of the modern carbon cycle. On land, the model captures the carbon cycling through vegetation and soil, resulting in a net terrestrial carbon sink of 2.2 Pg C year⁻¹. In the ocean, the large-scale distribution of hydrodynamical and biogeochemical tracers agrees with a modern climatology from the World Ocean Atlas. The combination of biological and physical processes induces a net CO₂ uptake of 1.7 Pg C year⁻¹ that falls within the range of recent estimates. Our analysis shows that the atmospheric climate of CNRM-ESM1 compares well with that of CNRM-CM5. Biases in precipitation and shortwave radiation over the tropics generate errors in gross primary productivity and ecosystem respiration. Compared to CNRM-CM5, the revised ocean–sea ice coupling has modified the sea-ice cover and ocean ventilation, unrealistically strengthening the flow of North Atlantic deep water (26.1 ± 2 Sv). It results in an accumulation of anthropogenic carbon in the deep ocean

Evaluation of CMIP6 DECK Experiments With CNRM‐CM6‐1

International audienceThis paper describes the main characteristics of CNRM-CM6-1, the fully coupled atmosphere-ocean general circulation model of sixth generation jointly developed by Centre National de Recherches Météorologiques (CNRM) and Cerfacs for the sixth phase of the Coupled Model Intercomparison Project 6 (CMIP6). The paper provides a description of each component of CNRM-CM6-1, including the coupling method and the new online output software. We emphasize where model's components have been updated with respect to the former model version, CNRM-CM5.1. In particular, we highlight major improvements in the representation of atmospheric and land processes. A particular attention has also been devoted to mass and energy conservation in the simulated climate system to limit long-term drifts. The climate simulated by CNRM-CM6-1 is then evaluated using CMIP6 historical and Diagnostic, Evaluation and Characterization of Klima (DECK) experiments in comparison with CMIP5 CNRM-CM5.1 equivalent experiments. Overall, the mean surface biases are of similar magnitude but with different spatial patterns. Deep ocean biases are generally reduced, whereas sea ice is too thin in the Arctic. Although the simulated climate variability remains roughly consistent with CNRM-CM5.1, its sensitivity to rising CO 2 has increased: the equilibrium climate sensitivity is 4.9 K, which is now close to the upper bound of the range estimated from CMIP5 models