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Title: Dependence of Vertical Alignment of Cloud and Precipitation Properties on Their Effective Fall Speeds

The vertical structure of clouds unresolved in large-scale weather prediction and climate models is controlled by an overlap assumption. When a binary representation (cloud or no cloud) of subgrid horizontal variability is replaced by a probability density function (PDF) treatment of cloud-related variables, a cloud occurrence overlap needs to be replaced by a PDF overlap. The PDF overlap can be quantified by a correlation length scale, z 0, indicating how rapidly rank correlation of distributions at two levels diminishes with increasing level separation. In this study, we show that z 0 varies widely for different properties (e.g., number and mass mixing ratios) and different hydrometeor types (cloud liquid and ice, rain, snow, and graupel) and that corresponding fall speed, V f, is the primary factor controlling the degree of their vertical alignment, with vertical shear of the horizontal wind playing a smaller role. Linear and power law parametric relationships between z 0 and V f are derived using cloud-resolving simulations of convection under midlatitude continental and tropical oceanic conditions, as well as observations from vertically pointing dual-frequency radar profilers near Darwin, Australia. The functional form of z 0-V f relationship is further examined using simple conceptual models that link variabilitymore » in horizontal and vertical directions and provide insights into the role of V f and wind shear. Being based on a physical property (i.e., fall speed) of hydrometeors rather than artificially defined and model-specific hydrometeor types, the proposed parameterization of vertical PDF overlap can be applied to a wide range of microphysics treatments in regional and global models.« less
Authors:
ORCiD logo [1] ; ORCiD logo [2] ; ORCiD logo [3] ; ORCiD logo [4] ; ORCiD logo [5]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States)
  3. University of Wisconsin–Milwaukee, WI (United States)
  4. Centre for Australian Weather and Climate Research, Melbourne, Victoria (Australia)
  5. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
Publication Date:
Report Number(s):
BNL-211521-2019-JAAM
Journal ID: ISSN 2169-897X
Grant/Contract Number:
SC0012704; AC06‐76RL01830; SC0016287
Type:
Published Article
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 124; Journal Issue: 4; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union
Research Org:
Brookhaven National Lab. (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; cloud and precipitation overlap; microphysics parameterization; hydrometeor classification; subcolumn generator; fall speed; wind shear
OSTI Identifier:
1494968
Alternate Identifier(s):
OSTI ID: 1494970; OSTI ID: 1506630

Ovchinnikov, Mikhail, Giangrande, Scott, Larson, Vincent E., Protat, Alain, and Williams, Christopher R.. Dependence of Vertical Alignment of Cloud and Precipitation Properties on Their Effective Fall Speeds. United States: N. p., Web. doi:10.1029/2018JD029346.
Ovchinnikov, Mikhail, Giangrande, Scott, Larson, Vincent E., Protat, Alain, & Williams, Christopher R.. Dependence of Vertical Alignment of Cloud and Precipitation Properties on Their Effective Fall Speeds. United States. doi:10.1029/2018JD029346.
Ovchinnikov, Mikhail, Giangrande, Scott, Larson, Vincent E., Protat, Alain, and Williams, Christopher R.. 2019. "Dependence of Vertical Alignment of Cloud and Precipitation Properties on Their Effective Fall Speeds". United States. doi:10.1029/2018JD029346.
@article{osti_1494968,
title = {Dependence of Vertical Alignment of Cloud and Precipitation Properties on Their Effective Fall Speeds},
author = {Ovchinnikov, Mikhail and Giangrande, Scott and Larson, Vincent E. and Protat, Alain and Williams, Christopher R.},
abstractNote = {The vertical structure of clouds unresolved in large-scale weather prediction and climate models is controlled by an overlap assumption. When a binary representation (cloud or no cloud) of subgrid horizontal variability is replaced by a probability density function (PDF) treatment of cloud-related variables, a cloud occurrence overlap needs to be replaced by a PDF overlap. The PDF overlap can be quantified by a correlation length scale, z0, indicating how rapidly rank correlation of distributions at two levels diminishes with increasing level separation. In this study, we show that z0 varies widely for different properties (e.g., number and mass mixing ratios) and different hydrometeor types (cloud liquid and ice, rain, snow, and graupel) and that corresponding fall speed, Vf, is the primary factor controlling the degree of their vertical alignment, with vertical shear of the horizontal wind playing a smaller role. Linear and power law parametric relationships between z0 and Vf are derived using cloud-resolving simulations of convection under midlatitude continental and tropical oceanic conditions, as well as observations from vertically pointing dual-frequency radar profilers near Darwin, Australia. The functional form of z0-Vf relationship is further examined using simple conceptual models that link variability in horizontal and vertical directions and provide insights into the role of Vf and wind shear. Being based on a physical property (i.e., fall speed) of hydrometeors rather than artificially defined and model-specific hydrometeor types, the proposed parameterization of vertical PDF overlap can be applied to a wide range of microphysics treatments in regional and global models.},
doi = {10.1029/2018JD029346},
journal = {Journal of Geophysical Research: Atmospheres},
number = 4,
volume = 124,
place = {United States},
year = {2019},
month = {1}
}

Works referenced in this record:

Convective cloud vertical velocity and mass-flux characteristics from radar wind profiler observations during GoAmazon2014/5
journal, November 2016
  • Giangrande, Scott E.; Toto, Tami; Jensen, Michael P.
  • Journal of Geophysical Research: Atmospheres, Vol. 121, Issue 21, p. 12,891-12,913
  • DOI: 10.1002/2016JD025303