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

Abstract

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:
 [1];  [2]
  1. Department of Earth and Planetary Science, University of California, Berkeley, and Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California
  2. Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, New York
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
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.
Romps, David M., & Vogelmann, Andrew M. Methods for Estimating 2D Cloud Size Distributions from 1D Observations. United States. doi:10.1175/JAS-D-17-0105.1.
Romps, David M., and Vogelmann, Andrew M. Sun . "Methods for Estimating 2D Cloud Size Distributions from 1D Observations". United States. doi:10.1175/JAS-D-17-0105.1.
@article{osti_1399067,
title = {Methods for Estimating 2D Cloud Size Distributions from 1D Observations},
author = {Romps, David M. and Vogelmann, Andrew M.},
abstractNote = {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 = {2017},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1175/JAS-D-17-0105.1

Citation Metrics:
Cited by: 3 works
Citation information provided by
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