Observed and Simulated Variability of Droplet Spectral Dispersion in Convective Clouds Over the Amazon
Machado, Luiz A. T.
Morrison, Hugh
Cecchini, Micael A.
Andreae, Meinrat O.
Pöhlker, Christopher
Pöschl, Ulrich
Rosenfeld, Daniel
Vendrasco, Eder P.
Voigt, Christiane
Wendisch, Manfred
Pöhlker, Mira L.
DOI: https://doi.org/10.1029/2021JD035076
Persistent URL: http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/9895
Morrison, Hugh; 3 Mesoscale and Microscale Meteorology Laboratory National Center for Atmospheric Research Boulder CO USA
Cecchini, Micael A.; 4 Institute of Physics University of Sao Paulo São Paulo Brazil
Andreae, Meinrat O.; 1 Multiphase Chemistry Department Max Planck Institute for Chemistry Mainz Germany
Pöhlker, Christopher; 1 Multiphase Chemistry Department Max Planck Institute for Chemistry Mainz Germany
Pöschl, Ulrich; 1 Multiphase Chemistry Department Max Planck Institute for Chemistry Mainz Germany
Rosenfeld, Daniel; 7 Institute of Earth Sciences The Hebrew University of Jerusalem Jerusalem Israel
Vendrasco, Eder P.; 2 Centro de Previsão de Tempo e Estudos Climáticos Instituto Nacional de Pesquisas Espaciais Cachoeira Paulista Brazil
Voigt, Christiane; 8 Institut für Physik der Atmosphäre Deutsches Zentrum für Luft und Raumfahrt Wessling Germany
Wendisch, Manfred; 10 Leipziger Institut für Meteorologie Universität Leipzig Leipzig Germany
Pöhlker, Mira L.; 1 Multiphase Chemistry Department Max Planck Institute for Chemistry Mainz Germany
Abstract
In this study, the variability of the spectral dispersion of droplet size distributions (DSDs) in convective clouds is investigated. Analyses are based on aircraft measurements of growing cumuli near the Amazon basin, and on numerical simulations of an idealized ice‐free cumulus. In cleaner clouds, the relative dispersion ϵ, defined as the ratio of the standard deviation to the mean value of the droplet diameter, is negatively correlated with the ratio of the cloud water content (qc) to the adiabatic liquid water content (qa), while no strong correlation between ϵ and qc/qa is seen in polluted clouds. Bin microphysics numerical simulations suggest that these contrasting behaviors are associated with the effect of collision‐coalescence in cleaner clouds, and secondary droplet activation in polluted clouds, in addition to the turbulent mixing of parcels that experienced different paths within the cloud. Collision‐coalescence simultaneously broadens the DSDs and decreases qc, explaining the inverse relationship between ϵ and qc/qa in cleaner clouds. Secondary droplet activation broadens the DSDs but has little direct impact on qc. The combination of a rather modest DSD broadening due to weak collision‐coalescence with enhanced droplet activation in both diluted and highly undiluted cloud regions may contribute to maintain a relatively uniform ϵ within polluted clouds. These findings can be useful for parameterizing the shape parameter (μ) of gamma DSDs in bulk microphysics cloud‐resolving models. It is shown that emulating the observed μ−qc/qa relationship improves the estimation of the collision‐coalescence rate in bulk microphysics simulations compared to the bin simulations.
Key Points:
Droplet size distribution patterns observed in warm cumuli reflect the roles of collision‐coalescence, secondary activation, and mixing.
The intra‐cloud distribution of droplet spectral dispersion varies with aerosol loading.
Emulating the observed shape‐parameter improves bulk estimations of collision‐coalescence in models.