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The climate impact and radiative effect of clouds and aerosols are significant. Both are among the most considerable sources of uncertainties in the climate system and in modelling the climate system. This arises not only from the fundamental uncertainty in cloud microphysics processes but also from their representation in models, and in particular in Cloud-Resolving Models (CRMs). CRMs are powerful tools for weather prediction, climate study, and investigating aerosol-cloud interactions at regional and global scales. However, they introduce a substantial degree of uncertainty due to model construction and parameterisation. To further investigate the sources of uncertainty in CRMs, we isolate two key aspects: the model's configuration (global and regional) and the employed cloud microphysics scheme (single- and double-moment schemes). Then, for each key aspect, we compare the simulated data to identify any discrepancies.We present results from regional simulation with ICON-Sapphire in limited area mode. The region we focused on in this study is the Amazon basin, using a horizontal resolution of about 1.2 km and a time period of 8 days. First, we compare results obtained using both single- and double-moment bulk microphysics schemes, maintaining consistency in other simulation parameters. Then, we compare results obtained from both regional and global simulations utilising the single-moment bulk microphysics scheme, again maintaining consistency in other simulation parameters. We find that the double-moment cloud microphysics scheme yields increased ice levels and reduced precipitation rates compared to the single-moment cloud microphysics scheme. We also find that the Amazonian diurnal cycle of precipitation rate, ice, and liquid water paths is more pronounced in the global runs compared to the regional runs. These results and other results that we will present may have implications on global radiation balance in global km-scale climate models.

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