We assess the reliability of an indirect method of inferring the atmospheric response to projected Arctic sea ice loss from CMIP5 simulations, by comparing the response inferred from the indirect method to that explicitly simulated in sea ice perturbation experiments. We find that the indirect approach works well in winter, but has limited utility in the other seasons. We then apply a modified version of the indirect method to 11 CMIP5 models to reveal the robust and non‐robust aspects of the wintertime atmospheric response to projected Arctic sea ice loss. Despite limitations of the indirect method, we identify a robust enhancement of the Siberian High, weakening of the Icelandic Low, weakening of the westerly wind on the poleward flank of the eddy‐driven jet, strengthening of the subtropical jet, and weakening of the stratospheric polar vortex. The surface air temperature response to projected Arctic sea ice loss over mid‐latitude continents is non‐robust across the models.

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The present study describes the atmospheric component of the sixth-generation climate models of the Centre National de Recherches Météorologiques (CNRM), namely, ARPEGE-Climat 6.3. It builds up on more than a decade of model development and tuning efforts, which led to major updates of its moist physics. The vertical resolution has also been significantly increased, both in the boundary layer and in the stratosphere. ARPEGE-Climat 6.3 is now coupled to the new version (8.0) of the SURFace EXternalisée (SURFEX) surface model, in which several new features (e.g., floodplains, aquifers, and snow processes) improve the water cycle realism. The model calibration is discussed in depth. An amip-type experiment, in which the sea surface temperatures and sea ice concentrations are prescribed, and following the CMIP6 protocol, is extensively evaluated, in terms of climate mean state and variability. ARPEGE-Climat 6.3 is shown to improve over its previous version (5.1) by many climate features. Major improvements include the top-of-atmosphere and surface energy budgets in their various components (shortwave and longwave, total and clear sky), cloud cover, near-surface temperature, precipitation climatology and daily-mean distribution, and water discharges at the outlet of major rivers. In contrast, clouds over subtropical stratocumulus decks, several dynamical variables (sea level pressure, 500-hPa geopotential height), are still significantly biased. The tropical intraseasonal variability and diurnal cycle of precipitation, though improved, remained area of concerns for further model improvement. New biases also emerge, such as a lack of precipitation over several tropical continental areas. Within the CMIP6 context, ARPEGE-Climat 6.3 is the atmospheric component of CNRM-CM6-1 and CNRM-ESM2-1.Plain Language Summary Since the early 1990s, the Centre National de Recherches Météorologiques (CNRM) has been developing a global atmosphere model for climate applications. The present work presents its latest version, ARPEGE-Climat 6.3, as prepared for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). It builds up on more than a decade of model development and tuning efforts. A CMIP6 amip-type numerical experiment, in which the sea surface temperatures and sea ice concentrations are prescribed, is evaluated, in terms of climate mean state and variability. ARPEGE-Climat 6.3 is shown to have better or similar skills compared to its previous version and to rank rather high among CMIP5 state-of-the-art models by many mean-state metrics. Major improvements include the top-ofatmosphere and surface energy budgets, cloud cover, near-surface temperature, precipitation climatology and daily-mean distribution, and water discharges at the outlet of major rivers. In contrast, clouds over the eastern part of ocean basins, and a few dynamical variables, such as sea level pressure, are still significantly biased. New biases also emerge, such as a lack of precipitation over several tropical continental areas. The remaining and n...