PNNL

Abstract

In a previous study (Xiao et al. 2023), we found that ignoring the moist convective downdrafts associated with overshooting shallow clouds in parameterizations can lead to significant biases in the simulated depth and liquid water content of a shallow cloud layer. In this study, we seek to better characterize the clouds responsible for these moist downdrafts for further parameterization improvements. We apply a 3-D cloud-tracking algorithm to Large-Eddy Simulations (LESs) of marine and continental shallow convection. We find that top 1–2% of the tracked cloud population ranked by lifetime-mean cloud-base mass flux can explain 90–95% of the total downward moisture transport near cloud top whereas the top 10–20% is required to explain 90–95% of the total upward moisture transport near cloud base. Comparing the vertical structure of the top clouds responsible for cloud-top downward moisture transport to that of the rest of the cloud population, we confirm the bi-modal picture of the shallow cloud population: a deep mode with a few large, overshooting clouds and a shallow mode of ubiquitous small clouds mainly responsible for bringing moisture into the lower cloud layer from below. To represent both the deep and shallow modes, mass-flux parameterizations need to (1) resolve the difference in mass flux or size between the two modes and (2) explicitly represent overshooting cloud updrafts and associated moist downdrafts.