Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications
The behavior of tropical clouds remains a major open scientific question, resulting in poor representation by models. One challenge is to realistically reproduce cloud droplet size distributions (DSDs) and their evolution over time and space. Many applications, not limited to models, use the gamm...
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Copernicus Publications
2017-12-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/17/14727/2017/acp-17-14727-2017.pdf |
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| author | M. A. Cecchini M. A. Cecchini L. A. T. Machado M. Wendisch A. Costa M. Krämer M. O. Andreae M. O. Andreae A. Afchine R. I. Albrecht P. Artaxo S. Borrmann S. Borrmann D. Fütterer T. Klimach C. Mahnke C. Mahnke S. T. Martin A. Minikin A. Minikin S. Molleker L. H. Pardo C. Pöhlker M. L. Pöhlker U. Pöschl D. Rosenfeld B. Weinzierl B. Weinzierl B. Weinzierl |
| author_facet | M. A. Cecchini M. A. Cecchini L. A. T. Machado M. Wendisch A. Costa M. Krämer M. O. Andreae M. O. Andreae A. Afchine R. I. Albrecht P. Artaxo S. Borrmann S. Borrmann D. Fütterer T. Klimach C. Mahnke C. Mahnke S. T. Martin A. Minikin A. Minikin S. Molleker L. H. Pardo C. Pöhlker M. L. Pöhlker U. Pöschl D. Rosenfeld B. Weinzierl B. Weinzierl B. Weinzierl |
| author_sort | M. A. Cecchini |
| collection | DOAJ |
| description | The behavior of tropical clouds remains a major open scientific question,
resulting in poor representation by models. One challenge is to realistically
reproduce cloud droplet size distributions (DSDs) and their evolution over
time and space. Many applications, not limited to models, use the gamma
function to represent DSDs. However, even though the statistical
characteristics of the gamma parameters have been widely studied, there is
almost no study dedicated to understanding the phase space of this function
and the associated physics. This phase space can be defined by the three
parameters that define the DSD intercept, shape, and curvature. Gamma phase
space may provide a common framework for parameterizations and
intercomparisons. 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, in which 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. |
| first_indexed | 2024-04-12T02:20:11Z |
| format | Article |
| id | doaj.art-9727efb2428746a398bb0c0c13f9c020 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-04-12T02:20:11Z |
| publishDate | 2017-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-9727efb2428746a398bb0c0c13f9c0202022-12-22T03:52:08ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242017-12-0117147271474610.5194/acp-17-14727-2017Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applicationsM. A. Cecchini0M. A. Cecchini1L. A. T. Machado2M. Wendisch3A. Costa4M. Krämer5M. O. Andreae6M. O. Andreae7A. Afchine8R. I. Albrecht9P. Artaxo10S. Borrmann11S. Borrmann12D. Fütterer13T. Klimach14C. Mahnke15C. Mahnke16S. T. Martin17A. Minikin18A. Minikin19S. Molleker20L. H. Pardo21C. Pöhlker22M. L. Pöhlker23U. Pöschl24D. Rosenfeld25B. Weinzierl26B. Weinzierl27B. Weinzierl28Centro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais, Cachoeira Paulista, BrazilDepartamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG), Universidade de São Paulo (USP), São Paulo, BrazilCentro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais, Cachoeira Paulista, BrazilLeipziger Institut für Meteorologie (LIM), Universität Leipzig, Stephanstr. 3, 04103 Leipzig, GermanyForschungszentrum Jülich, Institut für Energie und Klimaforschung (IEK-7), Jülich, GermanyForschungszentrum Jülich, Institut für Energie und Klimaforschung (IEK-7), Jülich, GermanyBiogeochemistry, Multiphase Chemistry, and Particle Chemistry Departments, Max Planck Institute for Chemistry, P.O. Box 3060, 55020 Mainz, GermanyScripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92037, USAForschungszentrum Jülich, Institut für Energie und Klimaforschung (IEK-7), Jülich, GermanyDepartamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG), Universidade de São Paulo (USP), São Paulo, BrazilInstituto de Física (IF), Universidade de São Paulo (USP), São Paulo, BrazilBiogeochemistry, Multiphase Chemistry, and Particle Chemistry Departments, Max Planck Institute for Chemistry, P.O. Box 3060, 55020 Mainz, GermanyInstitut für Physik der Atmosphäre (IPA), Johannes Gutenberg-Universität, Mainz, GermanyInstitut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, 82234 Wessling, GermanyBiogeochemistry, Multiphase Chemistry, and Particle Chemistry Departments, Max Planck Institute for Chemistry, P.O. Box 3060, 55020 Mainz, GermanyBiogeochemistry, Multiphase Chemistry, and Particle Chemistry Departments, Max Planck Institute for Chemistry, P.O. Box 3060, 55020 Mainz, GermanyInstitut für Physik der Atmosphäre (IPA), Johannes Gutenberg-Universität, Mainz, GermanySchool of Engineering and Applied Sciences and Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts, USAInstitut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, 82234 Wessling, GermanyFlugexperimente, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, GermanyInstitut für Physik der Atmosphäre (IPA), Johannes Gutenberg-Universität, Mainz, GermanyCentro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais, Cachoeira Paulista, BrazilBiogeochemistry, Multiphase Chemistry, and Particle Chemistry Departments, Max Planck Institute for Chemistry, P.O. Box 3060, 55020 Mainz, GermanyBiogeochemistry, Multiphase Chemistry, and Particle Chemistry Departments, Max Planck Institute for Chemistry, P.O. Box 3060, 55020 Mainz, GermanyBiogeochemistry, Multiphase Chemistry, and Particle Chemistry Departments, Max Planck Institute for Chemistry, P.O. Box 3060, 55020 Mainz, GermanyInstitute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem, IsraelInstitut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, 82234 Wessling, GermanyFaculty of Physics, University of Vienna, Boltzmanngasse 5, 1090 Vienna, AustriaLudwig-Maximilians-Universität, Meteorologisches Institut, Munich, GermanyThe behavior of tropical clouds remains a major open scientific question, resulting in poor representation by models. One challenge is to realistically reproduce cloud droplet size distributions (DSDs) and their evolution over time and space. Many applications, not limited to models, use the gamma function to represent DSDs. However, even though the statistical characteristics of the gamma parameters have been widely studied, there is almost no study dedicated to understanding the phase space of this function and the associated physics. This phase space can be defined by the three parameters that define the DSD intercept, shape, and curvature. Gamma phase space may provide a common framework for parameterizations and intercomparisons. 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, in which 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.https://www.atmos-chem-phys.net/17/14727/2017/acp-17-14727-2017.pdf |
| spellingShingle | M. A. Cecchini M. A. Cecchini L. A. T. Machado M. Wendisch A. Costa M. Krämer M. O. Andreae M. O. Andreae A. Afchine R. I. Albrecht P. Artaxo S. Borrmann S. Borrmann D. Fütterer T. Klimach C. Mahnke C. Mahnke S. T. Martin A. Minikin A. Minikin S. Molleker L. H. Pardo C. Pöhlker M. L. Pöhlker U. Pöschl D. Rosenfeld B. Weinzierl B. Weinzierl B. Weinzierl Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications Atmospheric Chemistry and Physics |
| title | Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications |
| title_full | Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications |
| title_fullStr | Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications |
| title_full_unstemmed | Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications |
| title_short | Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications |
| title_sort | illustration of microphysical processes in amazonian deep convective clouds in the gamma phase space introduction and potential applications |
| url | https://www.atmos-chem-phys.net/17/14727/2017/acp-17-14727-2017.pdf |
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