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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/acp-2017-864
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
06 Oct 2017
Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Atmospheric Chemistry and Physics (ACP) and is expected to appear here in due course.
Microphysical variability of Amazonian deep convective cores observed by CloudSat and simulated by a multi-scale modeling framework
J. Brant Dodson1, Patrick C. Taylor1, and Mark Branson2 1NASA Langley Research Center, 21 Langley Blvd., Mail Stop 420, Hampton, VA, 23681-2199, USA
2Department of Atmospheric Science, Colorado State University, Ft. Collins, CO 80523, USA
Abstract. Recently launched cloud-observing satellites provide information about the vertical structure of deep convection and its microphysical characteristics. In this study, CloudSat reflectivity data is stratified by cloud type, and the contoured frequency by altitude diagrams reveal a double-arc structure in deep convective cores (DCCs) above 8 km. This suggests two distinct hydrometeor modes (snow versus hail/graupel) controlling variability in reflectivity profiles. The day-night contrast in the double-arcs is about four times larger than the wet-dry season contrast. Using QuickBeam, the vertical reflectivity structure of DCCs is analysed in two versions of the Superparameterized Community Atmospheric Model (SP-CAM) with single-moment (no graupel) and double-moment (with graupel) microphysics. Double-moment microphysics shows better agreement with observed reflectivity profiles; however, neither model variant captures the double-arc structure. Ultimately, the results show that simulating realistic DCC vertical structure and its variability requires accurate representation of ice microphysics, in particular the hail/graupel modes, though this alone is insufficient.
Citation: Dodson, J. B., Taylor, P. C., and Branson, M.: Microphysical variability of Amazonian deep convective cores observed by CloudSat and simulated by a multi-scale modeling framework, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-864, in review, 2017.
J. Brant Dodson et al.
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'Technical Review', Anonymous Referee #1, 06 Nov 2017 Printer-friendly Version Supplement 
 
RC2: 'Review on Dodson et al', Anonymous Referee #2, 13 Nov 2017 Printer-friendly Version 
AC1: '(question for RC2) possible inclusion of aerosol data', Jason Dodson, 15 Nov 2017 Printer-friendly Version 
RC3: 'Monthly data', Anonymous Referee #2, 20 Nov 2017 Printer-friendly Version 
J. Brant Dodson et al.
J. Brant Dodson et al.

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Short summary
The vertical profiles of convection in the Amazon are sampled using CloudSat, with particular emphasis on day-night contrast. Focusing on vigorous deep convective cores reveals a distinct, previously unreported double-arc reflectivity feature in the contoured frequency by altitude diagram, likely corresponding with two modes of ice hydrometeor phase – snow versus graupel/hail. Replicating this feature in cloud-resolving models requires further improvements in the microphysical parameterization.
The vertical profiles of convection in the Amazon are sampled using CloudSat, with particular...
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