Methods for Estimating 2D Cloud Size Distributions from 1D Observations

Romps, David M.; Vogelmann, Andrew M.

doi:10.1175/JAS-D-17-0105.1

Title: Methods for Estimating 2D Cloud Size Distributions from 1D Observations

Abstract

© 2017AmericanMeteorological Society. The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud-chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clouds) in the context of theoretical size distributions. Both methods also perform well when used to predict the size distribution of real clouds from a Landsat scene. When applied to a large number of Landsat scenes, the simple method is able to accurately estimate the mean cloud size. As a demonstration, the methods are applied to aircraft measurements of shallow cumuli during the Routine ARM Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO)campaign, which then allow for an estimate of the true area-weighted mean cloud size.

Authors:

Romps, David M. ^[1]; Vogelmann, Andrew M. ^[2]

Department of Earth and Planetary Science, University of California, Berkeley, and Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California
Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, New York

Publication Date:: Wed Oct 11 00:00:00 EDT 2017

Research Org.:: Brookhaven National Laboratory (BNL), Upton, NY (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

OSTI Identifier:: 1399067

Alternate Identifier(s):: OSTI ID: 1376175; OSTI ID: 1563938

Report Number(s):: BNL-114153-2017-JA
Journal ID: ISSN 0022-4928

Grant/Contract Number:: AC02-05CH11231; SC0012704

Resource Type:: Published Article

Journal Name:: Journal of the Atmospheric Sciences

Additional Journal Information:: Journal Name: Journal of the Atmospheric Sciences Journal Volume: 74 Journal Issue: 10; Journal ID: ISSN 0022-4928

Publisher:: American Meteorological Society

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES

Citation Formats


                    Romps, David M., and Vogelmann, Andrew M. Methods for Estimating 2D Cloud Size Distributions from 1D Observations.  United States: N. p., 2017. 
Web.  doi:10.1175/JAS-D-17-0105.1.

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                    Romps, David M., & Vogelmann, Andrew M. Methods for Estimating 2D Cloud Size Distributions from 1D Observations.  United States.  https://doi.org/10.1175/JAS-D-17-0105.1

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                    Romps, David M., and Vogelmann, Andrew M. Wed .  
"Methods for Estimating 2D Cloud Size Distributions from 1D Observations".  United States.  https://doi.org/10.1175/JAS-D-17-0105.1.

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@article{osti_1399067,

  title        = {Methods for Estimating 2D Cloud Size Distributions from 1D Observations},

  author       = {Romps, David M. and Vogelmann, Andrew M.},

  abstractNote = {© 2017AmericanMeteorological Society. The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud-chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clouds) in the context of theoretical size distributions. Both methods also perform well when used to predict the size distribution of real clouds from a Landsat scene. When applied to a large number of Landsat scenes, the simple method is able to accurately estimate the mean cloud size. As a demonstration, the methods are applied to aircraft measurements of shallow cumuli during the Routine ARM Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO)campaign, which then allow for an estimate of the true area-weighted mean cloud size.},

  doi          = {10.1175/JAS-D-17-0105.1},

  journal      = {Journal of the Atmospheric Sciences},

  number       = 10,

  volume       = 74,

  place        = {United States},

  year         = {Wed Oct 11 00:00:00 EDT 2017},

  month        = {Wed Oct 11 00:00:00 EDT 2017}

}

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Works referencing / citing this record:

Thermodynamic Constraints on the Size Distributions of Tropical Clouds
journal, August 2018

Garrett, Timothy J.; Glenn, Ian B.; Krueger, Steven K.
Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 16
DOI: 10.1029/2018jd028803

Characteristics of Optically Thin Coastal Florida Cumuli Derived From Surface-Based Lidar Measurements
journal, September 2018

Delgadillo, Rodrigo; Voss, Kenneth J.; Zuidema, Paquita
Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 18
DOI: 10.1029/2018jd028867

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Title: Methods for Estimating 2D Cloud Size Distributions from 1D Observations

Abstract

Citation Formats

Thermodynamic Constraints on the Size Distributions of Tropical Clouds journal, August 2018

Characteristics of Optically Thin Coastal Florida Cumuli Derived From Surface-Based Lidar Measurements journal, September 2018

Thermodynamic Constraints on the Size Distributions of Tropical Clouds
journal, August 2018

Characteristics of Optically Thin Coastal Florida Cumuli Derived From Surface-Based Lidar Measurements
journal, September 2018