Surface melting on Antarctic Peninsula ice shelves can influence ice shelf mass balance, and consequently sea level rise. We show that summertime cloud phase on the Larsen C ice shelf on the Antarctic Peninsula strongly influences the amount of radiation received at the surface and can determine whether or not melting occurs. While previous work has separately evaluated cloud phase and the surface energy balance (SEB) during summertime over Larsen C, no previous studies have examined this relationship quantitatively. Furthermore, regional climate models frequently produce surface radiation biases related to cloud ice and liquid water content. This study uses a high‐resolution regional configuration of the UK Met Office Unified Model (MetUM) to assess the influence of cloud ice and liquid properties on the SEB, and consequently melting, over the Larsen C ice shelf. Results from a case‐study show that simulations producing a vertical cloud phase structure more comparable to aircraft observations exhibit smaller surface radiative biases. A configuration of the MetUM adapted to improve the simulation of cloud phase reproduces the observed surface melt most closely. During a five‐week simulation of summertime conditions, model melt biases are reduced to <2 W·m−2: a four‐fold improvement on a previous study that used default MetUM settings. This demonstrates the importance of cloud phase in determining summertime melt rates on Larsen C.

The Kinematic Driver-Aerosol (KiD-A) intercomparison was established to test the hypothesis that detailed warm microphysical schemes provide a benchmark for lower-complexity bulk microphysics schemes. KiD-A is the first intercomparison to compare multiple Lagrangian cloud models (LCMs), size bin-resolved schemes, and double-moment bulk microphysics schemes in a consistent 1D dynamic framework and box cases. In the absence of sedimentation and collision-coalescence, the drop size distributions (DSDs) from the LCMs exhibit similar evolution with expected physical behaviors and good inter-scheme agreement, with the volume mean diameter (Dvol ) from the LCMs within 1 to 5% of each other. In contrast, the bin schemes exhibit non-physical broadening with condensational growth. These results further strengthen the case that LCMs are an appropriate numerical benchmark for DSD evolution under condensational growth. When precipitation processes are included, however, the simulated liquid water path, precipitation rates, and response to modified cloud drop/aerosol number concentrations from the LCMs vary substantially, while the bin and bulk schemes are relatively more consistent with each other. The lack of consistency in the LCM results stems from both the collision-coalescence process and the sedimentation process, limiting their application as a numerical benchmark for precipitation processes. Reassuringly, however, precipitation from bulk schemes, which are the basis for cloud microphysics in weather and climate prediction, is within the spread of precipitation from the detailed schemes (LCMs and bin). Overall, this intercomparison identifies the need for focused effort on the comparison of collision-coalescence methods and sedimentation in detailed microphysics schemes, especially LCMs.

Abstract. Convection-permitting simulations are used to understand the effects of cloud–aerosol interactions in a case of heavy rainfall over southern China. The simulations are evaluated using radar observations from the Southern China Monsoon Rainfall Experiment (SCMREX) and remotely sensed estimates of precipitation, clouds and radiation. We focus on the effects of complexity in cloud–aerosol interactions, especially the depletion and transport of aerosol material by clouds. In particular, simulations with aerosol concentrations held constant are compared with a fully cloud–aerosol-interacting system to investigate the effects of two-way coupling between aerosols and clouds on a line of organised deep convection. It is shown that the cloud processing of aerosols can change the vertical structure of the storm by using up aerosols within the core of line, thereby maintaining a relatively clean environment which propagates with the heaviest rainfall. This induces changes in the statistics of surface rainfall, with a cleaner environment being associated with less-intense but more-frequent rainfall. These effects are shown to be related to a shortening of the timescale for converting cloud droplets to rain as the aerosol number concentration is decreased. The simulations are compared to satellite-derived estimates of surface rainfall, a condensed-water path and the outgoing flux of short-wave radiation. Simulations for fewer aerosol particles outperform the more polluted simulations for surface rainfall but give poorer representations of top-of-atmosphere (TOA) radiation.