How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICON

Abstract. Cloud microphysics is a prime example of processes that remain unresolved in atmospheric modeling at storm-resolving resolution. In this study, we explore how uncertainties in the representation of microphysical processes affect the tropical condensate distribution in a global storm-resolving model. We use ICON in its global storm-resolving configuration, with a one- or two-moment microphysical scheme and perform several sensitivity runs, where, in each, we modify parameters of one hydrometeor category of the applied microphysics scheme. Differences between the one- and two-moment schemes are most prominent in partitioning frozen condensate in cloud ice and snow and can be understood in terms of the habit's definition for each scheme, which is associated with different process rates. Overall differences between the simulations are moderate and tend to be larger for individual condensate habits than for more integrated quantities, like cloud fraction or total condensate burden. Yet, the resulting spread in the tropical energy balance of several W m−2 at the top of the atmosphere and at the surface is substantial. Although the modified parameters within one scheme generally affect different process rates, most of the change in the condensate amount of the modified habit and even the total condensate burden can be attributed to a single property: the change in fall speed. The tropical-mean precipitation efficiency is also well explained by changes in the relative fall speed across different habits in both schemes.