More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short) scales, the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similar to past studies we find an improved representation of precipitation at kilometer scales, as compared to models with parameterised convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the timescales considered-most notably over the Tropical ocean. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hecto-meter scales. Hectometer scales appear more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when reducing the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct 1 connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with an already improved simulation as compared to more parameterised models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change.

Abstract. In the last decades several convection parameterisations have been developed to consider the impact of small-scale unresolved processes in Earth System Models associated with convective clouds. Global model simulations, which have been performed under current climate conditions with different convection schemes, significantly differ among each other in the simulated transport of trace gases and precipitation patterns due to the parameterisation assumptions and formulations, e.g. the computation of convective rainfall rates, calculation of entrainment and detrainment rates etc. Here we address sensitivity studies comparing four different convection schemes under alternative climate conditions (with doubling of the CO 2 concentrations) to identify uncertainties related to convective processes. The increase in surface temperature reveals regional differences up to 4 K dependent on the chosen convection parameterisation. These differences are statistically significant almost everywhere in the troposphere of the intertropical convergence zone. The increase in upper tropospheric temperature affects the amount of water vapour transported to the lower stratosphere, leading to enhanced water vapour contents between 40 % and 60 % at the cold point temperature in the Tropics. Furthermore, the change in transporting short-lived pollutants within the atmosphere is highly ambiguous for the lower and upper troposphere. These results reflect that different approaches to compute mass fluxes, detrainment levels or trigger functions determine the transport of short-lived trace gases from the planetary boundary layer to lower, middle or upper tropospheric levels. Finally, cloud radiative effects have been analysed, uncovering a shift in different cloud types in the Tropics, especially for cirrus and deep convective clouds. These cloud types induce a change in net cloud radiative forcing varying from 0.5 W m −2 to 2.0 W m −2 .

In the last decades several convection parameterisations have been developed to consider the impact of small-scale unresolved processes in Earth System Models associated with convective clouds. Global model simulations, which have been performed under current climate conditions with different convection schemes, significantly differ among each other in the simulated transport of trace gases and precipitation patterns due to the parameterisation assumptions and formulations, e.g. the simplified treatment of the cloud microphysics. Here we address sensitivity studies comparing four different convection schemes under alternative climate conditions (doubling of the CO₂ concentrations) to identify uncertainties related to convective processes. The increase in surface temperature reveals regional differences up to 4 K dependent on the chosen convection parameterisation. The increase in upper tropospheric temperature affects the amount of water vapour transported to the lower stratosphere. Furthermore, the change in transporting short-lived pollutants within the atmosphere is highly ambiguous for the lower and upper troposphere. Finally, cloud radiative effects have been analysed uncovering a shift in different cloud types in the tropics

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Abstract. Current state-of-the-art regional numerical weather prediction (NWP) models employ kilometer-scale horizontal grid resolutions, thereby simulating convection within the grey zone. Increasing resolution leads to resolving the 3D motion field and has been shown to improve the representation of clouds and precipitation. Using a hectometer-scale model in forecasting mode on a large domain therefore offers a chance to study processes that require the simulation of the 3D motion field at small horizontal scales, such as deep summertime moist convection, a notorious problem in NWP. We use the ICOsahedral Nonhydrostatic weather and climate model in large-eddy simulation mode (ICON-LEM) to simulate deep moist convection and distinguish between scattered, large-scale dynamically forced, and frontal convection. We use different ground- and satellite-based observational data sets, which supply information on ice water content and path, ice cloud cover, and cloud-top height on a similar scale as the simulations, in order to evaluate and constrain our model simulations. We find that the timing and geometric extent of the convectively generated cloud shield agree well with observations, while the lifetime of the convective anvil was, at least in one case, significantly overestimated. Given the large uncertainties of individual ice water path observations, we use a suite of observations in order to better constrain the simulations. ICON-LEM simulates a cloud ice water path that lies between the different observational data sets, but simulations appear to be biased towards a large frozen water path (all frozen hydrometeors). Modifications of parameters within the microphysical scheme have little effect on the bias in the frozen water path and the longevity of the anvil. In particular, one of our convective days appeared to be very sensitive to the initial and boundary conditions, which had a large impact on the convective triggering but little impact on the high frozen water path and long anvil lifetime bias. Based on this limited set of sensitivity experiments, the evolution of locally forced convection appears to depend more on the uncertainty of the large-scale dynamical state based on data assimilation than of microphysical parameters. Overall, we judge ICON-LEM simulations of deep moist convection to be very close to observations regarding the timing, geometrical structure, and cloud ice water path of the convective anvil, but other frozen hydrometeors, in particular graupel, are likely overestimated. Therefore, ICON-LEM supplies important information for weather forecasting and forms a good basis for parameterization development based on physical processes or machine learning.