8 research outputs found

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

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    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

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

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    La France a subi des sĂ©cheresses en 2003, 2005 et 2006, dont les consĂ©quences notamment sur les bĂątiments ont mis en lumiĂšre l’importance de ce risque naturel. En raison de ses missions, MĂ©tĂ©o-France suit l’ensemble des phĂ©nomĂšnes mĂ©tĂ©orologiques, dont les sĂ©cheresses, via la quantification des dĂ©ficits pluviomĂ©triques observĂ©s par un important rĂ©seau de mesure de prĂ©cipitations et des systĂšmes d’analyse atmosphĂ©rique. Dans cet article, on prĂ©sente les diffĂ©rents types de sĂ©cheresse et la comparaison des sĂ©cheresses rĂ©centes par rapport aux sĂ©cheresses connues dans le passĂ©. De plus, MĂ©tĂ©o-France utilise des modĂšles de suivi du bilan en eau comme le modĂšle Safran Isba Modcou (SIM) pour mieux apprĂ©hender les consĂ©quences des dĂ©ficits pluviomĂ©triques et de la demande Ă©vaporative sur l’extension et l’intensitĂ© de la sĂ©cheresse. SIM permet de calculer des bilans d’eau spatialisĂ©s et en particulier un indice d’humiditĂ© du sol et un stock de neige sur les montagnes. Ces donnĂ©es sont utilisĂ©es dans le suivi hydrologique en France. Les caractĂ©ristiques et quelques rĂ©sultats en terme de contenu en eau du sol de deux de ces modĂšles sont prĂ©sentĂ©s

    Assessing changes in drought characteristics with standardized indices

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    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

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

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    We document the first version of the Centre National de Recherches MĂ©tĂ©orologiques 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<sup>−1</sup>. 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 CO<sub>2</sub> uptake of 1.7 Pg C year<sup>−1</sup> 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

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    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
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