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The equilibrium climate sensitivity (ECS) in the latest version of CNRM climate model, CNRM‐CM6‐1, and in its high‐resolution counterpart, CNRM‐CM6‐1‐HR, is significantly larger than in the previous version (CNRM‐CM5.1). The traceability of this climate sensitivity change is investigated using coupled ocean‐atmosphere model climate change simulations. These simulations show that the increase in ECS is the result of changes in the atmospheric component. A particular attention is paid to the method used to decompose the equilibrium temperature response difference, by using a linearized decomposition of the individual radiative agents diagnosed by a radiative kernel technique. The climate sensitivity increase is primarily due to the cloud radiative responses, with a predominant contribution of the tropical longwave response (including both feedback and forcing adjustment) and a significant contribution of the extratropical and tropical shortwave feedback changes. A series of stand‐alone atmosphere experiments is carried out to quantify the contributions of each atmospheric development to this difference between CNRM‐CM5.1 and CNRM‐CM6‐1. The change of the convection scheme appears to play an important role in driving the cloud changes, with a large effect on the tropical longwave cloud feedback change. Plain Language Summary: The global equilibrium temperature change in response to a doubling of the atmospheric carbon dioxide concentration is an important characteristic of the climate system known as the equilibrium climate sensitivity (ECS). Many climate models contributing to CMIP6 (Coupled Model Intercomparison Project phase 6) have a larger ECS than their CMIP5 predecessors. Here, we investigate the origins of this increase for the CNRM model and its high‐resolution version. We find that it primarily results from changes in the atmospheric component, in particular in the convection scheme, through its impact on the cloud radiative responses. Key Points: The CNRM climate models contributing to Coupled Model Intercomparison Project phase 6 have a larger climate sensitivity than their CMIP5 predecessorThe climate sensitivity increase is the result of changes in the atmospheric component, through the dominant role of tropical cloud changesThe new convection scheme appears to play an important role in driving the cloud changes [ABSTRACT FROM AUTHOR]

This 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 CO2 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. Key Points: Description of CNRM‐CM6‐1 model components, their coupling, and tuning procedures are describedHistorical simulations and DECK experiments are assessedPreindustrial simulation is stable and mean climate and variability in historical runs is realistic [ABSTRACT FROM AUTHOR]

This 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 CO2 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. Key Points: Description of CNRM‐CM6‐1 model components, their coupling, and tuning procedures are describedHistorical simulations and DECK experiments are assessedPreindustrial simulation is stable and mean climate and variability in historical runs is realistic [ABSTRACT FROM AUTHOR]

Seasonal predictability of local precipitation is rather weak in the mid-latitudes. This is the case when assessing the skill of the seasonal forecast of Heavy Precipitating Event (HPE) extreme occurrence over the French Mediterranean coast during the fall season. Tropics to extratropics teleconnection patterns do appear when averaging analyzed fields over the years characterised by a frequency of HPE occurrence in the upper 17% of the distribution. A methodology taking weather regime occurrence into account as an intermediate step to forecast HPE extreme occurrence is presented. For the period 1960 to 2001 and four different sets of seasonal forecast, the Economical Value is doubled, compared to the score obtained with the simulated local precipitation data, when using a linear model (Linear Discriminant Analysis in this case) taking simulated 200 hPa velocity potential-stream function regime occurrences as predictors. Interestingly, larger scores are shown for this couple of fields over a large-scale domain including the tropics than for the 500 hPa geopotential height over an Euro-Atlantic domain, despite a tighter link of the latter field to the local precipitation. [ABSTRACT FROM AUTHOR]

BSTRACT A new and consistent convection scheme, providing continuous treatment of this atmospheric process, is described. The main concept ensuring the consistency of the whole system is buoyancy, a key element of any convective vertical motion. The buoyancy constitutes the forcing term of the convective vertical velocity, which is then used to define the triggering condition, the mass flux and the rates of entrainment-detrainment. The buoyancy is also used in its vertically integrated form to express the closure condition as a CAPE relaxation. The continuous treatment of convection from dry thermals to deep precipitating cumulus is made possible through the use of a continuous formulation of the entrainment-detrainment rates and CAPE relaxation time, together with an embedded precipitation scheme. This convection scheme is first evaluated with the help of single-column model simulations of specific case studies encompassing a variety of convective situations. Second, a coupled general-circulation model multiyear simulation is provided as a means to assess the model climate with respect to observations. [ABSTRACT FROM AUTHOR]

A multi-model ensemble-based system for seasonal-to-interannual prediction has been developed in a joint European project known as DEMETER (Development of a European Multimodel Ensemble Prediction System for Seasonal to Interannual Prediction). The DEMETER system comprises seven global atmosphere–ocean coupled models, each running from an ensemble of initial conditions. Comprehensive hindcast evaluation demonstrates the enhanced reliability and skill of the multimodel ensemble over a more conventional single-model ensemble approach. In addition, innovative examples of the application of seasonal ensemble forecasts in malaria and crop yield prediction are discussed. The strategy followed in DEMETER deals with important problems such as communication across disciplines, downscaling of climate simulations, and use of probabilistic forecast information in the applications sector, illustrating the economic value of seasonal-to-interannual prediction for society as a whole. [ABSTRACT FROM AUTHOR]