Evaluation of an entraining droplet activation parameterization using in situ cloud data
Author
Morales, R.
Nenes, A.
Jonsson, H.
Flagan, R.C.
Seinfeld, J.H.
Date
2011Metadata
Show full item recordAbstract
This study investigates the ability of a droplet activation parameterization (which
considers the effects of entrainment and mixing) to reproduce observed cloud droplet
number concentration (CDNC) in ambient clouds. Predictions of the parameterization are
compared against cloud averages of CDNC from ambient cumulus and stratocumulus
clouds sampled during CRYSTAL‐FACE (Key West, Florida, July 2002) and CSTRIPE
(Monterey, California, July 2003), respectively. The entrainment parameters required by the
parameterization are derived from the observed liquid water content profiles. For the
cumulus clouds considered in the study, CDNC is overpredicted by 45% with the adiabatic
parameterization. When entrainment is accounted for, the predicted CDNC agrees within
3.5%. Cloud‐averaged CDNC for stratocumulus clouds is well captured when entrainment is
not considered. In all cases considered, the entraining parameterization compared favorably
against a statistical correlation developed from observations to treat entrainment effects
on droplet number. These results suggest that including entrainment effects in the
calculation of CDNC, as presented here, could address important overprediction biases
associated with using adiabatic CDNC to represent cloud‐scale average values.
Description
The article of record as published may be located at http://dx.doi.org/10.1029/2010JD015324
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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