{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/99431"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/99431","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"The impact of vertical variations of cloud mircrophysics and drizzle on the angular anisotropic behavior of weighted cloud droplet effective radius","abstract":"The effective radius (Re) of the cloud droplet size distribution is an Essential Climate Variable identified by the Global Climate Observing System for its important role in energy and water cycle studies. It is retrieved simultaneously with optical depth (τ) from passive satellite imagers, like Moderate Resolution Imaging Spectroradiometer (MODIS), using two shortwave spectral channels (so called bispectral method), typically one in visible or near-infrared spectral region and the other from a shortwave infrared spectral region. The MODIS-retrieved Re product has been extensively used in many applications, including studies that assess aerosol-cloud interactions and evaluating cloud microphysical parameterizations in climate models. Given the widespread use of Re products, it is essential that our understanding of the error characteristics of this product are accurate. Recently, a method has been developed by Liang et al. (2015) to estimate the systematic errors in MODIS-retrieved Re by examining the angular variations in retrieved optical depth variability with scattering angle, specifically around the rainbow scattering angle, using MODIS data alone and with MODIS data fused with data from the Multi-angle Imaging SpectroRadiometer (MISR). Both datasets show a zonally varying zonal mean bias in MODIS-retrieved Re of ~3 to 11 μm for marine liquid water clouds. The source of this bias remains a point of research, but it is certainly rooted in the assumptions used by the MODIS cloud product algorithm. This study explores the importance of breakdowns of the vertically homogenous assumption and the single modal size distribution assumption in the bispectral method on the interpretation of angular behavior of weighted Re (designated as Rw hereafter). Specifically, this study will use a weighting function introduced by Platnick (2000) to explore the impact of vertical variations of cloud microphysics and drizzle on the angular variations of Rw with respect of scattering angle. Furthermore, this study focuses on the angular behavior of Rw near rainbow scattering directions and discusses how vertical variations of cloud microphysics and drizzle can contribute to the Re bias reported in Liang et al. (2015). Our results show vertical variation and drizzle are important to the distribution of Rw with sun-view geometry. Variations of Rw in vertical inhomogeneous clouds range from 1.5~5 μm, depending on the cloud Re profiles. The presence of a realistic drizzle mode can reduce the angular variation of Rw. However, in terms of interpreting the optical depth variation in MODIS Re retrieval across rainbow scattering angles observed by Liang et al. (2015), the vertical variation and drizzle are insignificant, contributing no more than~1 μm to the bias estimate. An important implication of our results is that other factors, such as 3D effects, cannot be ignored in the interpretation of MODIS Re bias.","abstract_html":"The effective radius (Re) of the cloud droplet size distribution is an Essential Climate Variable identified by the Global Climate Observing System for its important role in energy and water cycle studies. It is retrieved simultaneously with optical depth (τ) from passive satellite imagers, like Moderate Resolution Imaging Spectroradiometer (MODIS), using two shortwave spectral channels (so called bispectral method), typically one in visible or near-infrared spectral region and the other from a shortwave infrared spectral region. The MODIS-retrieved Re product has been extensively used in many applications, including studies that assess aerosol-cloud interactions and evaluating cloud microphysical parameterizations in climate models. Given the widespread use of Re products, it is essential that our understanding of the error characteristics of this product are accurate. Recently, a method has been developed by Liang et al. (2015) to estimate the systematic errors in MODIS-retrieved Re by examining the angular variations in retrieved optical depth variability with scattering angle, specifically around the rainbow scattering angle, using MODIS data alone and with MODIS data fused with data from the Multi-angle Imaging SpectroRadiometer (MISR). Both datasets show a zonally varying zonal mean bias in MODIS-retrieved Re of ~3 to 11 μm for marine liquid water clouds. The source of this bias remains a point of research, but it is certainly rooted in the assumptions used by the MODIS cloud product algorithm. This study explores the importance of breakdowns of the vertically homogenous assumption and the single modal size distribution assumption in the bispectral method on the interpretation of angular behavior of weighted Re (designated as Rw hereafter). Specifically, this study will use a weighting function introduced by Platnick (2000) to explore the impact of vertical variations of cloud microphysics and drizzle on the angular variations of Rw with respect of scattering angle. Furthermore, this study focuses on the angular behavior of Rw near rainbow scattering directions and discusses how vertical variations of cloud microphysics and drizzle can contribute to the Re bias reported in Liang et al. (2015). Our results show vertical variation and drizzle are important to the distribution of Rw with sun-view geometry. Variations of Rw in vertical inhomogeneous clouds range from 1.5~5 μm, depending on the cloud Re profiles. The presence of a realistic drizzle mode can reduce the angular variation of Rw. However, in terms of interpreting the optical depth variation in MODIS Re retrieval across rainbow scattering angles observed by Liang et al. (2015), the vertical variation and drizzle are insignificant, contributing no more than~1 μm to the bias estimate. An important implication of our results is that other factors, such as 3D effects, cannot be ignored in the interpretation of MODIS Re bias.","abstract_has_math":false,"creators":["Su, Ming"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Atmospheric Sciences","degree_department":null,"school":null,"contributors":["Di Girolamo, Larry"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-03-13T15:49:17Z","date_published":"2018-03-13T15:49:17Z","updated_at":"2026-07-22T22:24:37Z","subjects":["Cloud droplet effective radius","Satellite remote sensing"],"languages":["en"],"rights":["Copyright 2017 Ming Su"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/99431","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Di Girolamo, Larry"]},{"key":"dc:creator","label":"Author","values":["Su, Ming"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-03-13T15:49:17Z","2017-12-14","2017-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Atmospheric Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Cloud droplet effective radius","Satellite remote sensing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2017 Ming Su"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/99431"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The effective radius (Re) of the cloud droplet size distribution is an Essential Climate Variable identified by the Global Climate Observing System for its important role in energy and water cycle studies. It is retrieved simultaneously with optical depth (τ) from passive satellite imagers, like Moderate Resolution Imaging Spectroradiometer (MODIS), using two shortwave spectral channels (so called bispectral method), typically one in visible or near-infrared spectral region and the other from a shortwave infrared spectral region. The MODIS-retrieved Re product has been extensively used in many applications, including studies that assess aerosol-cloud interactions and evaluating cloud microphysical parameterizations in climate models. Given the widespread use of Re products, it is essential that our understanding of the error characteristics of this product are accurate. Recently, a method has been developed by Liang et al. (2015) to estimate the systematic errors in MODIS-retrieved Re by examining the angular variations in retrieved optical depth variability with scattering angle, specifically around the rainbow scattering angle, using MODIS data alone and with MODIS data fused with data from the Multi-angle Imaging SpectroRadiometer (MISR). Both datasets show a zonally varying zonal mean bias in MODIS-retrieved Re of ~3 to 11 μm for marine liquid water clouds. The source of this bias remains a point of research, but it is certainly rooted in the assumptions used by the MODIS cloud product algorithm. This study explores the importance of breakdowns of the vertically homogenous assumption and the single modal size distribution assumption in the bispectral method on the interpretation of angular behavior of weighted Re (designated as Rw hereafter). Specifically, this study will use a weighting function introduced by Platnick (2000) to explore the impact of vertical variations of cloud microphysics and drizzle on the angular variations of Rw with respect of scattering angle. Furthermore, this study focuses on the angular behavior of Rw near rainbow scattering directions and discusses how vertical variations of cloud microphysics and drizzle can contribute to the Re bias reported in Liang et al. (2015). Our results show vertical variation and drizzle are important to the distribution of Rw with sun-view geometry. Variations of Rw in vertical inhomogeneous clouds range from 1.5~5 μm, depending on the cloud Re profiles. The presence of a realistic drizzle mode can reduce the angular variation of Rw. However, in terms of interpreting the optical depth variation in MODIS Re retrieval across rainbow scattering angles observed by Liang et al. (2015), the vertical variation and drizzle are insignificant, contributing no more than~1 μm to the bias estimate. An important implication of our results is that other factors, such as 3D effects, cannot be ignored in the interpretation of MODIS Re bias.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-03-13 without embargo terms","The student, Ming Su, accepted the attached license on 2017-12-13 at 19:28.","The student, Ming Su, submitted this Thesis for approval on 2017-12-13 at 19:40.","This Thesis was approved for publication on 2017-12-14 at 13:08.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11975 on 2018-03-13 at 10:12:26","Made available in DSpace on 2018-03-13T15:49:17Z (GMT). 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It is retrieved simultaneously with optical depth (τ) from passive satellite imagers, like Moderate Resolution Imaging Spectroradiometer (MODIS), using two shortwave spectral channels (so called bispectral method), typically one in visible or near-infrared spectral region and the other from a shortwave infrared spectral region. The MODIS-retrieved Re product has been extensively used in many applications, including studies that assess aerosol-cloud interactions and evaluating cloud microphysical parameterizations in climate models. Given the widespread use of Re products, it is essential that our understanding of the error characteristics of this product are accurate. Recently, a method has been developed by Liang et al. (2015) to estimate the systematic errors in MODIS-retrieved Re by examining the angular variations in retrieved optical depth variability with scattering angle, specifically around the rainbow scattering angle, using MODIS data alone and with MODIS data fused with data from the Multi-angle Imaging SpectroRadiometer (MISR). Both datasets show a zonally varying zonal mean bias in MODIS-retrieved Re of ~3 to 11 μm for marine liquid water clouds. The source of this bias remains a point of research, but it is certainly rooted in the assumptions used by the MODIS cloud product algorithm. This study explores the importance of breakdowns of the vertically homogenous assumption and the single modal size distribution assumption in the bispectral method on the interpretation of angular behavior of weighted Re (designated as Rw hereafter). Specifically, this study will use a weighting function introduced by Platnick (2000) to explore the impact of vertical variations of cloud microphysics and drizzle on the angular variations of Rw with respect of scattering angle. Furthermore, this study focuses on the angular behavior of Rw near rainbow scattering directions and discusses how vertical variations of cloud microphysics and drizzle can contribute to the Re bias reported in Liang et al. (2015). Our results show vertical variation and drizzle are important to the distribution of Rw with sun-view geometry. Variations of Rw in vertical inhomogeneous clouds range from 1.5~5 μm, depending on the cloud Re profiles. The presence of a realistic drizzle mode can reduce the angular variation of Rw. However, in terms of interpreting the optical depth variation in MODIS Re retrieval across rainbow scattering angles observed by Liang et al. (2015), the vertical variation and drizzle are insignificant, contributing no more than~1 μm to the bias estimate. An important implication of our results is that other factors, such as 3D effects, cannot be ignored in the interpretation of MODIS Re bias.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-03-13 without embargo terms","The student, Ming Su, accepted the attached license on 2017-12-13 at 19:28.","The student, Ming Su, submitted this Thesis for approval on 2017-12-13 at 19:40.","This Thesis was approved for publication on 2017-12-14 at 13:08.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11975 on 2018-03-13 at 10:12:26","Made available in DSpace on 2018-03-13T15:49:17Z (GMT). No. of bitstreams: 2 SU-THESIS-2017.pdf: 28825065 bytes, checksum: 096f319c660c77283d8def394dbbaa44 (MD5) LICENSE.txt: 4204 bytes, checksum: 04e4f42e2f97db204c86878dc278a03a (MD5) Previous issue date: 2017-12-14"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/99431"],"dc:language":["en"],"dc:rights":["Copyright 2017 Ming Su"],"dc:subject":["Cloud droplet effective radius","Satellite remote sensing"],"dc:title":["The impact of vertical variations of cloud mircrophysics and drizzle on the angular anisotropic behavior of weighted cloud droplet effective radius"],"dc:type":["text"],"thesis:degree_discipline":["Atmospheric Sciences"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:37Z"}