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Illustration of microphysical processes in Amazonian deep convective clouds in the Gamma phase space: Introduction and potential applications

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Andreae,  M. O.
Biogeochemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons100858

Borrmann,  S.
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons101066

Klimach,  T.
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons145446

Mahnke,  Christoph
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons140247

Molleker,  S.
Particle Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons104597

Pöhlker,  C.
Multiphase Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons203102

Pöhlker,  M. L.
Multiphase Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons101189

Pöschl,  U.
Multiphase Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

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Citation

Cecchini, M. A., Machado, L. A. T., Wendisch, M., Costa, A., Krämer, M., Andreae, M. O., et al. (2017). Illustration of microphysical processes in Amazonian deep convective clouds in the Gamma phase space: Introduction and potential applications. Atmospheric Chemistry and Physics, 17(23), 14727-14746. doi:10.5194/acp-17-14727-2017.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002E-8FE2-6
Abstract
The behavior of tropical clouds remains a major open scientific question, given that the associated phys-ics is not well represented by models. One challenge is to realistically reproduce cloud droplet size dis-tributions (DSD) and their evolution over time and space. Many applications, not limited to models, use the Gamma function to represent DSDs. However, there is almost no study dedicated to understanding the phase space of this function, which is given by the three parameters that define the DSD intercept, shape, and curvature. Gamma phase space may provide a common framework for parameterizations and inter-comparisons. Here, we introduce the phase-space approach and its characteristics, focusing on warm-phase microphysical cloud properties and the transition to the mixed-phase layer. We show that trajectories in this phase space can represent DSD evolution and can be related to growth processes. Condensational and collisional growth may be interpreted as pseudo-forces that induce displacements in opposite directions within the phase space. The actually observed movements in the phase space are a result of the combination of such pseudo-forces. Additionally, aerosol effects can be evaluated given their significant impact on DSDs. The DSDs associated with liquid droplets that favor cloud glaciation can be delimited in the phase space, which can help models to adequately predict the transition to the mixed phase. We also consider possible ways to constrain the DSD in two-moment bulk microphysics schemes, where the relative dispersion parameter of the DSD can play a significant role. Overall, the Gamma phase-space approach can be an invaluable tool for studying cloud microphysical evolution and can be readily applied in many scenarios that rely on Gamma DSDs.