Search

Cloud microphysics fulfills a fundamental role in the formation and evolution of marine fog, but it is not fully understood. Numerous studies have addressed this by means of direct observations and modeling efforts. However, collision–coalescence of aerosols and fog droplets is a process often neglected. In this study we perform an analysis of the role of particle collections on the formation, development, and microphysical structure of marine fog. It was found that collisions open a path for aerosol activation by means of collisional activation. In addition, collisions contribute to the diffusional activation of fog particles by adding water mass to the growing aerosols, making them reach the required critical radius faster. Furthermore, collisions have a homogenizing effect on hygroscopicity, facilitating the activation of accumulation‐mode aerosols by increasing their diffusional growth. [ABSTRACT FROM AUTHOR]

High‐intensity precipitation represents a threat for several regions of the world because of the related risk of natural disasters (e.g. floods and landslides). This work focuses on low‐level precipitation enhancement that occurs in the cloud warm layer and has been observed in relation to collision‐coalescence (CC) leading to flash floods and extreme rainfall events in tropical and temperate latitudes. Specifically, signatures of precipitation enhancement (referred to as CC‐dominant precipitation) are investigated in the observations from the Global Precipitation Measurement (GPM) core mission Dual‐frequency Precipitation Radar (DPR) over the central/eastern Contiguous United States (CONUS) during June 2014–May 2018. A classification scheme for CC‐dominant precipitation, developed for dual‐polarization S‐band radar measurements and applied in a previous work to X‐band radar observations in complex terrain, is used as a benchmark. The scheme is here applied to the GPM ground validation dataset that matches ground‐based radar observations across CONUS to space‐borne DPR retrievals. The occurrence of CC‐dominant precipitation is documented and the corresponding signatures of CC‐dominant precipitation at Ku‐ and Ka‐band are studied. CC‐dominant profiles show distinguishing features when compared to profiles not dominated by CC, e.g. characteristic vertical slopes of reflectivity at Ku‐ and Ka‐band in the liquid layer, lower freezing‐level height, and shallower ice layer, which are linked to environmental conditions driving the peculiar CC microphysics. This work aims at improving satellite quantitative precipitation estimation, particularly GPM retrievals, by targeting CC development in precipitation columns. [ABSTRACT FROM AUTHOR]

Precipitation forms in warm clouds via collision-coalescence. This process is difficult to observe directly in situ and its implementation in numerical models is uncertain. We use aircraft observations of the drop-size distribution (DSD) near marine stratocumulus tops to estimate collision-coalescence rates. Marine stratocumulus is a useful system to study collisional growth because it is initiated near the cloud top and the clouds evolve slowly enough to obtain statistically useful data from aircraft. We compare rate constants estimated from observations with reference rate constants derived from a collision-coalescence box model, the result of which is termed the enhancement factor (EF). We evaluate two hydrodynamic collision-coalescence kernels, one quiescent and one including the effects of small-scale turbulence. Due to sampling volume limitations, DSDs must be averaged over length-scales much greater than those relevant to the underlying physics, such that we also examine the role of averaging length-scale with respect to process representation. Averaging length-scales of 1.5 and 30 km are used, corresponding roughly to the horizontal grid lengths of cloud-resolving models and high-resolution climate models, respectively. EF values range from 0.1 to 40, with the greatest EFs associated with small mode diameter cases and a generally decreasing trend with drop size. For any given drop size or averaging length-scale, there is about an order of magnitude variability in EFs. These results suggest that spatial variability on length-scales smaller than 1.5 km prevents accurate retrieval of rate constants from large-scale average DSDs. Large-scale models must therefore account for small-scale variability to represent cloud microphysical processes accurately. The turbulent kernel reduces EFs for all drop sizes, but can only account for at most half of the calculated EFs in marine stratocumulus. [ABSTRACT FROM AUTHOR]