This study presents the global climate model IPSL‐CM6A‐LR developed at IPSL to study natural climate variability and climate response to natural and anthropogenic forcings as part of the 6^th phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from a range of metrics (related in particular to radiation, temperature, precipitation, wind), is strongly improved in comparison to previous model versions. Although they are reduced, a number of known biases and shortcomings (e.g., double ITCZ, frequency of midlatitude wintertime blockings, and ENSO dynamics) persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL‐CM5A‐LR used in CMIP5. A large ensemble of more than 30 members for the historical period (1850‐2018) and a smaller ensemble for a range of emissions scenarios (until 2100 and 2300) are also presented and discussed.

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling with its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. We discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.

This study presents the version of the LMDZ global atmospheric model used as the atmospheric component of the Institut Pierre Simon Laplace coupled model (IPSL‐CM6A‐LR) to contribute to the 6th phase of the international Coupled Model Intercomparison Project (CMIP6). This LMDZ6A version includes original convective parameterizations that define the LMDZ “New Physics”: a mass flux parameterization of the organized structures of the convective boundary layer, the “thermal plume model,” and a parameterization of the cold pools created by reevaporation of convective rainfall. The vertical velocity associated with thermal plumes and gust fronts of cold pools are used to control the triggering and intensity of deep convection. Because of several shortcomings, the early version 5B of this New Physics was worse than the previous “Standard Physics” version 5A regarding several classical climate metrics. To overcome these deficiencies, version 6A includes new developments: a stochastic triggering of deep convection, a modification of the thermal plume model that allows the representation of stratocumulus and cumulus clouds in a unified framework, an improved parameterization of very stable boundary layers, and the modification of the gravity waves scheme targeting the quasi‐biennal oscillation in the stratosphere. These improvements to the physical content and a more well‐defined tuning strategy led to major improvements in the LMDZ6A version model climatology. Beyond the presentation of this particular model version and documentation of its climatology, the present paper underlines possible methodological pathways toward model improvement that can be shared across modeling groups.

Based on a decade of research on cloud processes, a new version of the LMDZ atmospheric general circulation model has been developed that corresponds to a complete recasting of the parameterization of turbulence, convection and clouds. This LMDZ5B version includes a mass-flux representation of the thermal plumes or rolls of the convective boundary layer, coupled to a bi-Gaussian statistical cloud scheme, as well as a parameterization of the cold pools generated below cumulonimbus by re-evaporation of convective precipitation. The triggering and closure of deep convection are now controlled by lifting processes in the sub-cloud layer. An available lifting energy and lifting power are provided both by the thermal plumes and by the spread of cold pools. The individual parameterizations were carefully validated against the results of explicit high resolution simulations. Here we present the work done to go from those new concepts and developments to a full 3D atmospheric model, used in particular for climate change projections with the IPSL-CM5B coupled model. Based on a series of sensitivity experiments, we document the differences with the previous LMDZ5A version distinguishing the role of parameterization changes from that of model tuning. Improvements found previously in single-column simulations of case studies are confirmed in the 3D model: (1) the convective boundary layer and cumulus clouds are better represented and (2) the diurnal cycle of convective rainfall over continents is delayed by several hours, solving a longstanding problem in climate modeling. The variability of tropical rainfall is also larger in LMDZ5B at intraseasonal time-scales. Significant biases of the LMDZ5A model however remain, or are even sometimes amplified. The paper emphasizes the importance of parameterization improvements and model tuning in the frame of climate change studies as well as the new paradigm that represents the improvement of 3D climate models under the control of single-column case studies simulations.

The IPSL-CM5A climate model was used to perform a large number of control, historical and climate change simulations in the frame of CMIP5. The refined horizontal and vertical grid of the atmospheric component, LMDZ, constitutes a major difference compared to the previous IPSL-CM4 version used for CMIP3. From imposed-SST (Sea Surface Temperature) and coupled numerical experiments, we systematically analyze the impact of the horizontal and vertical grid resolution on the simulated climate. The refinement of the horizontal grid results in a systematic reduction of major biases in the mean tropospheric structures and SST. The mid-latitude jets, located too close to the equator with the coarsest grids, move poleward. This robust feature, is accompanied by a drying at mid-latitudes and a reduction of cold biases in mid-latitudes relative to the equator. The model was also extended to the stratosphere by increasing the number of layers on the vertical from 19 to 39 (15 in the stratosphere) and adding relevant parameterizations. The 39-layer version captures the dominant modes of the stratospheric variability and exhibits stratospheric sudden warmings. Changing either the vertical or horizontal resolution modifies the global energy balance in imposed-SST simulations by typically several W/m² which translates in the coupled atmosphere-ocean simulations into a different global-mean SST. The sensitivity is of about 1.2 K per 1 W/m² when varying the horizontal grid. A re-tuning of model parameters was thus required to restore this energy balance in the imposed-SST simulations and reduce the biases in the simulated mean surface temperature and, to some extent, latitudinal SST variations in the coupled experiments for the modern climate. The tuning hardly compensates, however, for robust biases of the coupled model. Despite the wide range of grid configurations explored and their significant impact on the present-day climate, the climate sensitivity remains essentially unchanged.