Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-Phase Microphysics Using a Cloud-Resolving Model

Abstract

Abstract This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement Program and output from the University of California, Los Angeles/Colorado State University cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties analyzed by applying the SCM’s assumptions about cloud vertical overlap and horizontal homogeneity to its profiles of cloud water/ice mixing ratio, cloud fraction, and snow flux differed from the cloud radar observations while the CRM simulation reproduced most of the observed cirrus properties. The present study evaluates, through a comparison with the CRM, the SCM’s representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. This study finds that, although the SCM’s detrainment rate profile averaged over the entire simulation period is comparable to the CRM’s, detrainment in the SCM is comparatively sporadic and vertically localized. Too much detrained ice is sublimated when first detrained. Snow formed from detrained cloud ice falls through too deep of a layer. These aspects of the SCM’s parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM), and suggest several possible improvements for the SCM: 1) allowing multiple coexisting cumulus cloud types as in the original Arakawa–Schubert scheme, 2) prognostically determining the stratiform cloud fraction, and 3) explicitly predicting the snow mixing ratio. These would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow flux.