PNNL

Abstract

Warm liquid clouds strongly affect Earth’s energy budget but remain imperfectly represented in climate models, partly due to the complexity and covariability of many relevant processes influencing warm rain. This work presents a detailed analysis of different factors affecting rain rate peak intensity (RR) in continental warm clouds. Observations and retrievals of liquid water path (LWP), cloud condensation nuclei concentration (NCCN), cloud depth, cloud duration, and in-cloud turbulence intensity of more than 3000 separate warm clouds sampled during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign are analyzed in this work. Multiple linear regression (MLR) and random forest (RF) models are applied to assess the relative impact of these variables on RR. Overall, RR tends to increase as cloud depth, LWP, and cloud duration increase, or NCCN decreases. Mean cloud depth affects RR the most while NCCN impacts it the least. When considering over 170 warm clouds observed at least 1 hour in which turbulence is retrievable, the effect of NCCN on RR remains most likely suppressive, but this result is not significant at a 75% level for the MLR model and its magnitude is highly uncertain for the RF model. The impact of in-cloud turbulence depends on the moment and location the cloud is sampled. Cloud base turbulence around the time of RR is most important with higher cloud base turbulence likely to suppress RR. Cloud top turbulence effects are inconclusive. Possible reasons for difficulties isolating robust CCN and turbulence effects on RR are discussed.