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On the representation of droplet coalescence and autoconversion: evaluation using ambient cloud droplet size distributions

Hsieh, W. C. and Jonsson, H. and Wang, L.-P. and Buzorius, G. and Flagan, R. C. and Seinfeld, J. H. and Nenes, A. (2009) On the representation of droplet coalescence and autoconversion: evaluation using ambient cloud droplet size distributions. Journal of Geophysical Research D, 114 (7). D07201. ISSN 0148-0227. https://resolver.caltech.edu/CaltechAUTHORS:20090610-095123943

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Abstract

In this study, we evaluate eight autoconversion parameterizations against integration of the Kinetic Collection Equation (KCE) for cloud size distributions measured during the NASA CRYSTAL‐FACE and CSTRIPE campaigns. KCE calculations are done using both the observed data and fits of these data to a gamma distribution function; it is found that the fitted distributions provide a good approximation for calculations of total coalescence but not for autoconversion because of fitting errors near the drop‐drizzle separation size. Parameterizations that explicitly compute autoconversion tend to be in better agreement with KCE but are subject to substantial uncertainty, about an order of magnitude in autoconversion rate. Including turbulence effects on droplet collection increases autoconversion by a factor of 1.82 and 1.24 for CRYSTAL‐FACE and CSTRIPE clouds, respectively; this enhancement never exceeds a factor of 3, even under the most aggressive collection conditions. Shifting the droplet‐drizzle separation radius from 20 to 25 μm results in about a twofold uncertainty in autoconversion rate. The polynomial approximation to the gravitation collection kernel used to develop parameterizations provides computation of autoconversion that agree to within 30%. Collectively, these uncertainties have an important impact on autoconversion but are all within the factor of 10 uncertainty of autoconversion parameterizations. Incorporating KCE calculations in GCM simulations of aerosol‐cloud interactions studies is computationally feasible by using precalculated collection kernel tables and can quantify the autoconversion uncertainty associated with application of parameterizations.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1029/2008JD010502DOIArticle
ORCID:
AuthorORCID
Jonsson, H.0000-0003-3043-1074
Flagan, R. C.0000-0001-5690-770X
Seinfeld, J. H.0000-0003-1344-4068
Nenes, A.0000-0003-3873-9970
Additional Information:© 2009 American Geophysical Union. Received 27 May 2008; accepted 30 January 2009; published 1 April 2009. Support was provided by the Department of Energy, an NSF CAREER award, the Office of Naval Research under grant N00014-04-1-0118, and the School of Earth and Atmospheric Science at Georgia Institute of Technology. We thank Dr. Andreas Bott for sharing his KCE code and Dr. Yangang Liu for helpful discussions. Finally, we thank three anonymous reviewers for their constructive comments. W.C.H. thanks Chien-Yu Peng for assistance in numerical techniques.
Funders:
Funding AgencyGrant Number
Department of Energy (DOE)UNSPECIFIED
NSFUNSPECIFIED
Office of Naval Research (ONR)N00014-04-1-0118
Georgia Institute of TechnologyUNSPECIFIED
Issue or Number:7
Record Number:CaltechAUTHORS:20090610-095123943
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20090610-095123943
Official Citation:Hsieh, W. C., H. Jonsson, L.‐P. Wang, G. Buzorius, R. C. Flagan, J. H. Seinfeld, and A. Nenes (2009), On the representation of droplet coalescence and autoconversion: Evaluation using ambient cloud droplet size distributions, J. Geophys. Res., 114, D07201, doi:10.1029/2008JD010502.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:14387
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:20 Aug 2009 19:54
Last Modified:03 Oct 2019 00:49

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