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Title: The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud top occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloudmore » properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.« less
Authors:
ORCiD logo [1] ; ORCiD logo [2]
  1. Univ. of Kansas, Lawrence, KS (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States)
Publication Date:
Report Number(s):
BNL-205751-2018-JAAM
Journal ID: ISSN 2169-897X
Grant/Contract Number:
SC0012704
Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 123; Journal Issue: 6; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; MC3E; LES; congestus; radar; forcing; nudging
OSTI Identifier:
1454808

Mechem, David B., and Giangrande, Scott E.. The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E. United States: N. p., Web. doi:10.1002/2017JD027457.
Mechem, David B., & Giangrande, Scott E.. The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E. United States. doi:10.1002/2017JD027457.
Mechem, David B., and Giangrande, Scott E.. 2018. "The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E". United States. doi:10.1002/2017JD027457.
@article{osti_1454808,
title = {The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E},
author = {Mechem, David B. and Giangrande, Scott E.},
abstractNote = {Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud top occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.},
doi = {10.1002/2017JD027457},
journal = {Journal of Geophysical Research: Atmospheres},
number = 6,
volume = 123,
place = {United States},
year = {2018},
month = {3}
}

Works referenced in this record:

Scanning ARM Cloud Radars. Part II: Data Quality Control and Processing
journal, March 2014
  • Kollias, Pavlos; Jo, Leng; Borque, Paloma
  • Journal of Atmospheric and Oceanic Technology, Vol. 31, Issue 3, p. 583-598
  • DOI: 10.1175/JTECH-D-13-00045.1