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Normalized particle size distribution for remote sensing application
The ice particle size distribution (PSD) is fundamental to the quantitative description of a cloud. It is also crucial in the development of remote sensing retrieval techniques using radar and/or lidar measurements. The PSD allows one to link characteristics of individual particles (area, mass, and...
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Published in: | Journal of geophysical research. Atmospheres 2014-04, Vol.119 (7), p.4204-4227 |
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creator | Delanoë, J. M. E. Heymsfield, A. J. Protat, A. Bansemer, A. Hogan, R. J. |
description | The ice particle size distribution (PSD) is fundamental to the quantitative description of a cloud. It is also crucial in the development of remote sensing retrieval techniques using radar and/or lidar measurements. The PSD allows one to link characteristics of individual particles (area, mass, and scattering properties) to characteristics of an ensemble of particles in a sampling volume (e.g., visible extinction (σ), ice water content (IWC), and radar reflectivity (Z)). The aim of this study is to describe a normalization technique to represent the PSD. We update an earlier study by including recent in situ measurements covering a large variety of ice clouds spanning temperatures ranging between −80°C and 0°C. This new data set also includes direct measurements of IWC. We demonstrate that it is possible to scale the PSD in size space by the volume‐weighted diameter Dm and in the concentration space by the intercept parameter N0∗ and obtain the intrinsic shape of the PSD. Therefore, by combining N0∗, Dm, and a modified gamma function representing the normalized PSD shape, we are able to approximate key cloud variables (such as IWC) as well as cloud properties which can be remotely observed (such as Z) with an absolute mean relative error smaller than 20%. The underlying idea is to be able to retrieve the PSD using two independent measurements. We also propose parameterizations for ice cloud key parameters derived from the normalized PSD. We also investigate the effects of uncertainty present in the ice crystal mass‐size relationships on the parameterizations and the normalized PSD approach.
Key PointsThis study describes a normalization technique to represent the PSDIn‐situ measurements are covering a large variety of ice cloudsThis new data set also includes direct measurements of IWC |
doi_str_mv | 10.1002/2013JD020700 |
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Key PointsThis study describes a normalization technique to represent the PSDIn‐situ measurements are covering a large variety of ice cloudsThis new data set also includes direct measurements of IWC</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1002/2013JD020700</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Atmospheric and Oceanic Physics ; Clouds ; Covering ; Earth Sciences ; Geophysics ; Ice ; Ice clouds ; In situ measurement ; Lidar ; Meteorology ; Parametrization ; Particle size ; Particle size distribution ; Physics ; PSI ; Radar ; Remote sensing ; Sampling ; Sciences of the Universe ; Water content</subject><ispartof>Journal of geophysical research. Atmospheres, 2014-04, Vol.119 (7), p.4204-4227</ispartof><rights>2014. American Geophysical Union. All Rights Reserved.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4834-61539b78383d4fc7d33e608e599079c1d8c7072ec1cd8924d0d4f4fe956a6dad3</citedby><cites>FETCH-LOGICAL-c4834-61539b78383d4fc7d33e608e599079c1d8c7072ec1cd8924d0d4f4fe956a6dad3</cites><orcidid>0000-0002-8933-874X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://hal.science/hal-00979328$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Delanoë, J. M. E.</creatorcontrib><creatorcontrib>Heymsfield, A. J.</creatorcontrib><creatorcontrib>Protat, A.</creatorcontrib><creatorcontrib>Bansemer, A.</creatorcontrib><creatorcontrib>Hogan, R. J.</creatorcontrib><title>Normalized particle size distribution for remote sensing application</title><title>Journal of geophysical research. Atmospheres</title><addtitle>J. Geophys. Res. Atmos</addtitle><description>The ice particle size distribution (PSD) is fundamental to the quantitative description of a cloud. It is also crucial in the development of remote sensing retrieval techniques using radar and/or lidar measurements. The PSD allows one to link characteristics of individual particles (area, mass, and scattering properties) to characteristics of an ensemble of particles in a sampling volume (e.g., visible extinction (σ), ice water content (IWC), and radar reflectivity (Z)). The aim of this study is to describe a normalization technique to represent the PSD. We update an earlier study by including recent in situ measurements covering a large variety of ice clouds spanning temperatures ranging between −80°C and 0°C. This new data set also includes direct measurements of IWC. We demonstrate that it is possible to scale the PSD in size space by the volume‐weighted diameter Dm and in the concentration space by the intercept parameter N0∗ and obtain the intrinsic shape of the PSD. Therefore, by combining N0∗, Dm, and a modified gamma function representing the normalized PSD shape, we are able to approximate key cloud variables (such as IWC) as well as cloud properties which can be remotely observed (such as Z) with an absolute mean relative error smaller than 20%. The underlying idea is to be able to retrieve the PSD using two independent measurements. We also propose parameterizations for ice cloud key parameters derived from the normalized PSD. We also investigate the effects of uncertainty present in the ice crystal mass‐size relationships on the parameterizations and the normalized PSD approach.
Key PointsThis study describes a normalization technique to represent the PSDIn‐situ measurements are covering a large variety of ice cloudsThis new data set also includes direct measurements of IWC</description><subject>Atmospheric and Oceanic Physics</subject><subject>Clouds</subject><subject>Covering</subject><subject>Earth Sciences</subject><subject>Geophysics</subject><subject>Ice</subject><subject>Ice clouds</subject><subject>In situ measurement</subject><subject>Lidar</subject><subject>Meteorology</subject><subject>Parametrization</subject><subject>Particle size</subject><subject>Particle size distribution</subject><subject>Physics</subject><subject>PSI</subject><subject>Radar</subject><subject>Remote sensing</subject><subject>Sampling</subject><subject>Sciences of the Universe</subject><subject>Water content</subject><issn>2169-897X</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqF0UtvEzEQAOBVBRJV6Y0fsFIvILEwftvHKmlTQpSKCkRvlmt7qctmvbU3QPn1OFoUoR6oL37MN6OxpqpeIXiHAPB7DIgs54BBABxUhxhx1Uil-LP9WVy_qI5zvoOyJBDK6GE1X8e0MV347V09mDQG2_k6l2vtQh5TuNmOIfZ1G1Od_CaOJej7HPpvtRmGLlizC7-snremy_74735UfTk_-zy7aFaXiw-z01VjqSS04YgRdSMkkcTR1gpHiOcgPVMKhLLISStAYG-RdVJh6qAw2nrFuOHOOHJUvZnq3ppODylsTHrQ0QR9cbrSuzcAJRTB8gcq9vVkhxTvtz6PehOy9V1neh-3WSMuEONYKPo0ZVgpyjnFhZ48ondxm_ry6VKQSAqAGCvq7aRsijkn3-6bRaB3w9L_DqtwMvGfofMP_7V6ubiaM4Torutmyipz8r_2WSZ911wQwfTX9UKvZ2h5_XHxSV-RPzOBogU</recordid><startdate>20140416</startdate><enddate>20140416</enddate><creator>Delanoë, J. M. E.</creator><creator>Heymsfield, A. J.</creator><creator>Protat, A.</creator><creator>Bansemer, A.</creator><creator>Hogan, R. J.</creator><general>Blackwell Publishing Ltd</general><general>American Geophysical Union</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-8933-874X</orcidid></search><sort><creationdate>20140416</creationdate><title>Normalized particle size distribution for remote sensing application</title><author>Delanoë, J. M. E. ; Heymsfield, A. J. ; Protat, A. ; Bansemer, A. ; Hogan, R. 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Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Delanoë, J. M. E.</au><au>Heymsfield, A. J.</au><au>Protat, A.</au><au>Bansemer, A.</au><au>Hogan, R. J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Normalized particle size distribution for remote sensing application</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><addtitle>J. Geophys. Res. Atmos</addtitle><date>2014-04-16</date><risdate>2014</risdate><volume>119</volume><issue>7</issue><spage>4204</spage><epage>4227</epage><pages>4204-4227</pages><issn>2169-897X</issn><eissn>2169-8996</eissn><abstract>The ice particle size distribution (PSD) is fundamental to the quantitative description of a cloud. It is also crucial in the development of remote sensing retrieval techniques using radar and/or lidar measurements. The PSD allows one to link characteristics of individual particles (area, mass, and scattering properties) to characteristics of an ensemble of particles in a sampling volume (e.g., visible extinction (σ), ice water content (IWC), and radar reflectivity (Z)). The aim of this study is to describe a normalization technique to represent the PSD. We update an earlier study by including recent in situ measurements covering a large variety of ice clouds spanning temperatures ranging between −80°C and 0°C. This new data set also includes direct measurements of IWC. We demonstrate that it is possible to scale the PSD in size space by the volume‐weighted diameter Dm and in the concentration space by the intercept parameter N0∗ and obtain the intrinsic shape of the PSD. Therefore, by combining N0∗, Dm, and a modified gamma function representing the normalized PSD shape, we are able to approximate key cloud variables (such as IWC) as well as cloud properties which can be remotely observed (such as Z) with an absolute mean relative error smaller than 20%. The underlying idea is to be able to retrieve the PSD using two independent measurements. We also propose parameterizations for ice cloud key parameters derived from the normalized PSD. We also investigate the effects of uncertainty present in the ice crystal mass‐size relationships on the parameterizations and the normalized PSD approach.
Key PointsThis study describes a normalization technique to represent the PSDIn‐situ measurements are covering a large variety of ice cloudsThis new data set also includes direct measurements of IWC</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/2013JD020700</doi><tpages>24</tpages><orcidid>https://orcid.org/0000-0002-8933-874X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Atmospheric and Oceanic Physics Clouds Covering Earth Sciences Geophysics Ice Ice clouds In situ measurement Lidar Meteorology Parametrization Particle size Particle size distribution Physics PSI Radar Remote sensing Sampling Sciences of the Universe Water content |
title | Normalized particle size distribution for remote sensing application |
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