Assessing the potential for simplification in global climate model cloud microphysics

Abstract. Cloud properties and their evolution influence Earth's radiative balance. The cloud microphysical (CMP) processes that shape these are therefore important to represent in global climate models. Historically, parameterizations models have grown more detailed complex. However, a simpler formulation of CMP may leave the model results mostly unchanged while enabling an easier interpretation helping increase process understanding. This study employs sensitivity analysis emulated perturbed parameter ensemble aerosol–climate ECHAM-HAM illuminate impact selected ice on output. response perturbation serves as proxy for effect simplification. Autoconversion crystals is found be dominant influencing key variables such water path effects, riming droplets snow has most liquid phase. Accretion self-collection negligible output identified suitable candidates future simplifications. In turn, dominating role autoconversion suggests this greatest need represented correctly. A seasonal spatially resolved employing spherical harmonics expansion data corroborates results. introduces new application combination statistical emulation evaluate complex numerical specific parameterized process. It paves way simplifications leading interpretable