The vertical velocities of convective clouds are of great practical interest because of their influence on many phenomena, including severe weather and stratospheric moistening. However, the magnitudes of forces giving rise to these vertical velocities are poorly understood, and the dominant balance is in dispute. Here, an algorithm is used to extract thousands of cloud thermals from a large-eddy simulation of deep and tropical maritime convection. Using a streamfunction to define natural boundaries for these thermals, the dominant balance in the vertical momentum equation is revealed. Cloud thermals rise with a nearly constant speed determined by their buoyancy and the standard drag law with a drag coefficient of 0.6. Contrary to suggestions that cloud thermals might be slippery, with a dominant balance between buoyancy and acceleration, cloud thermals are found here to be sticky, with a dominant balance between buoyancy and drag.

The contemporaneous pointwise product of convective available potential energy (CAPE) and precipitation is shown to be a good proxy for lightning. In particular, the CAPE × P proxy for lightning faithfully replicates seasonal maps of lightning over the contiguous United States, as well as the shape, amplitude, and timing of the diurnal cycle in lightning. Globally, CAPE × P correctly predicts the distribution of flash rate densities over land, but it does not predict the pronounced land-ocean contrast in flash rate density; some factor other than CAPE or P is responsible for that land-ocean contrast.

Superparameterized (SP) global climate models have been shown to better simulate various features of precipitation relative to conventional models, including its diurnal cycle as well as its extremes. While various studies have focused on the effect of differing microphysics parameterizations on precipitation within limited-area cloud-resolving models, we examine here the effect on contiguous U.S. (CONUS) extremes in a global SP model. We vary the number of predicted moments for hydrometeor distributions, the character of the rimed ice species, and the representation of raindrop self-collection and breakup. Using a likelihood ratio test and accounting for the effects of multiple hypothesis testing, we find that there are some regional differences, particularly during spring and summer in the Southwest and the Midwest, in both the current climate and a warmer climate with uniformly increased sea surface temperatures. These differences are most statistically significant and widespread when the number of moments is changed. To determine whether these results are due to (fast) local effects of the different microphysics or the (slower) ensuing feedback on the large-scale atmospheric circulation, we run a series of short, 5-day simulations initialized from reanalysis data. We find that the differences largely disappear in these runs and therefore infer that the different parameterizations impact precipitation extremes indirectly via the large-scale circulation. Finally, we compare the present-day results with hourly rain gauge data and find that SP underestimates extremes relative to observations regardless of which microphysics scheme is used given a fixed model configuration and resolution.

A recent study found statistically significant differences in extreme precipitation distributions over the contiguous United States (CONUS) when changing the microphysics scheme in a superparameterized global climate model. Here, we repeat the analysis globally and similarly find that differences are widespread when varying the number of predicted moments in the microphysics parameterization, but not when comparing variants of the double-moment scheme. However, contrary to the previous study in which differences largely disappeared over CONUS when 5-day simulations were conducted, we found that the signal in these shorter integrations remains within the tropics, implying a direct local effect of microphysics on precipitation extremes in these regions. The effect on precipitation is traced back to changes in vertical velocity profiles changes that are then amplified in the climatological simulations compared to the 5-day ones. Finally, the superparameterized extremes, regardless of the microphysics scheme, are shown to be larger than those from the Global Precipitation Climatology Project One-Degree Daily data set and generally smaller than those from the Tropical Rainfall Measuring Mission 3B42 data set.