{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/102790"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/102790","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Examination of the behavior of modis-retrieved cloud droplet effective radius through misr-modis data fusion","abstract":"Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude [Liang et al., 2015]. Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud horizontal heterogeneity, cloud optical depth, and sun-view geometry. Our results reveal that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in the MODIS-retrieved Re bias. Through data stratification by observed cloud properties and latitude, we introduce a bias-correction approach for MODIS-retrieved Re at regional scales. Our estimates reveal global distribution of MODIS-retrieved Re monthly mean bias ~1 to 12 μm depending on latitude and cloud types, the bias-corrected Re estimates of ~ 4 to 16 μm are consistent with available validations of MODIS Re reported in previous studies over limited regions. Removing the mean bias from the original MODIS Re2.1 and Re3.7 monthly means show more consistent behavior among the two channels that range from 0 to +0.6 μm in the marine stratocumulus regions and -2 to 0 μm in the cumuliform cloud regions. This curious finding seems to suggest that the vertical distribution of drop sizes for marine stratocumulus clouds are very different from other types of marine liquid water clouds.","abstract_html":"Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude [Liang et al., 2015]. Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud horizontal heterogeneity, cloud optical depth, and sun-view geometry. Our results reveal that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in the MODIS-retrieved Re bias. Through data stratification by observed cloud properties and latitude, we introduce a bias-correction approach for MODIS-retrieved Re at regional scales. Our estimates reveal global distribution of MODIS-retrieved Re monthly mean bias ~1 to 12 μm depending on latitude and cloud types, the bias-corrected Re estimates of ~ 4 to 16 μm are consistent with available validations of MODIS Re reported in previous studies over limited regions. Removing the mean bias from the original MODIS Re2.1 and Re3.7 monthly means show more consistent behavior among the two channels that range from 0 to +0.6 μm in the marine stratocumulus regions and -2 to 0 μm in the cumuliform cloud regions. This curious finding seems to suggest that the vertical distribution of drop sizes for marine stratocumulus clouds are very different from other types of marine liquid water clouds.","abstract_has_math":false,"creators":["Fu, Dongwei"],"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":2019,"date_issued":"2019-02-07T20:35:56Z","date_published":"2019-02-07T20:35:56Z","updated_at":"2026-07-22T22:24:42Z","subjects":["Cloud Effective Radius","Data Fusion","Bias Correction","Remote Sensing","Radiative Transfer","MISR","MODIS"],"languages":["en"],"rights":["Copyright 2018 Dongwei Fu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/102790","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":["Fu, Dongwei"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-02-07T20:35:56Z","2021-02-08T10:15:22Z","2018-11-08","2018-12"]},{"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 Effective Radius","Data Fusion","Bias Correction","Remote Sensing","Radiative Transfer","MISR","MODIS"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2018 Dongwei Fu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/102790"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude [Liang et al., 2015]. Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud horizontal heterogeneity, cloud optical depth, and sun-view geometry. Our results reveal that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in the MODIS-retrieved Re bias. Through data stratification by observed cloud properties and latitude, we introduce a bias-correction approach for MODIS-retrieved Re at regional scales. Our estimates reveal global distribution of MODIS-retrieved Re monthly mean bias ~1 to 12 μm depending on latitude and cloud types, the bias-corrected Re estimates of ~ 4 to 16 μm are consistent with available validations of MODIS Re reported in previous studies over limited regions. Removing the mean bias from the original MODIS Re2.1 and Re3.7 monthly means show more consistent behavior among the two channels that range from 0 to +0.6 μm in the marine stratocumulus regions and -2 to 0 μm in the cumuliform cloud regions. This curious finding seems to suggest that the vertical distribution of drop sizes for marine stratocumulus clouds are very different from other types of marine liquid water clouds.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-12-01","The student, Dongwei Fu, accepted the attached license on 2018-11-06 at 14:51.","The student, Dongwei Fu, submitted this Thesis for approval on 2018-11-06 at 15:00.","This Thesis was approved for publication on 2018-11-08 at 13:07.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13064 on 2019-02-07 at 14:17:05","Made available in DSpace on 2019-02-07T20:35:56Z (GMT). No. of bitstreams: 7 FU-THESIS-2018.pdf: 12784031 bytes, checksum: 8c6b3ddd7136cd1d9fa862fa75bd7c74 (MD5) AMS_copyright_policy_Miles_et_al_2000.pdf: 36282 bytes, checksum: 3e15cd0ee5355171fe1af5cea9985af6 (MD5) BanWeiss_2014_License.pdf: 96340 bytes, checksum: 892e1243c5a3ab04518e85acd0222167 (MD5) LICENSE.txt: 4207 bytes, checksum: ee4744e66483ddecf7819a6d322fc482 (MD5) Liang_2015_License.pdf: 93468 bytes, checksum: 8dba119241a2d4805c17f2af81fe83de (MD5) Varnai_2007_License.pdf: 92859 bytes, checksum: 6e07afed47d7417b136dde0a2232bf0d (MD5) Zhang_2016_License.pdf: 97291 bytes, checksum: 0c856ad23994f9497f78057a8c21a671 (MD5) Previous issue date: 2018-11-08","Embargo set by: Seth Robbins for item 109814 Lift date: 2021-02-07T20:36:09Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","Embargo set by: Seth Robbins for item 109814 Lift date: 2021-02-07T20:39:46Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","Embargo set by: Seth Robbins for item 109814 Lift date: 2021-02-07T20:44:35Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","U of I Only Restriction Lifted for Item 109814 on 2021-02-08T10:15:22Z."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Examination of the behavior of modis-retrieved cloud droplet effective radius through misr-modis data fusion"]}]}],"canonical_facts":{"dc:contributor":["Di Girolamo, Larry"],"dc:creator":["Fu, Dongwei"],"dc:date":["2019-02-07T20:35:56Z","2021-02-08T10:15:22Z","2018-11-08","2018-12"],"dc:description":["Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude [Liang et al., 2015]. Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud horizontal heterogeneity, cloud optical depth, and sun-view geometry. Our results reveal that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in the MODIS-retrieved Re bias. Through data stratification by observed cloud properties and latitude, we introduce a bias-correction approach for MODIS-retrieved Re at regional scales. Our estimates reveal global distribution of MODIS-retrieved Re monthly mean bias ~1 to 12 μm depending on latitude and cloud types, the bias-corrected Re estimates of ~ 4 to 16 μm are consistent with available validations of MODIS Re reported in previous studies over limited regions. Removing the mean bias from the original MODIS Re2.1 and Re3.7 monthly means show more consistent behavior among the two channels that range from 0 to +0.6 μm in the marine stratocumulus regions and -2 to 0 μm in the cumuliform cloud regions. This curious finding seems to suggest that the vertical distribution of drop sizes for marine stratocumulus clouds are very different from other types of marine liquid water clouds.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-12-01","The student, Dongwei Fu, accepted the attached license on 2018-11-06 at 14:51.","The student, Dongwei Fu, submitted this Thesis for approval on 2018-11-06 at 15:00.","This Thesis was approved for publication on 2018-11-08 at 13:07.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13064 on 2019-02-07 at 14:17:05","Made available in DSpace on 2019-02-07T20:35:56Z (GMT). No. of bitstreams: 7 FU-THESIS-2018.pdf: 12784031 bytes, checksum: 8c6b3ddd7136cd1d9fa862fa75bd7c74 (MD5) AMS_copyright_policy_Miles_et_al_2000.pdf: 36282 bytes, checksum: 3e15cd0ee5355171fe1af5cea9985af6 (MD5) BanWeiss_2014_License.pdf: 96340 bytes, checksum: 892e1243c5a3ab04518e85acd0222167 (MD5) LICENSE.txt: 4207 bytes, checksum: ee4744e66483ddecf7819a6d322fc482 (MD5) Liang_2015_License.pdf: 93468 bytes, checksum: 8dba119241a2d4805c17f2af81fe83de (MD5) Varnai_2007_License.pdf: 92859 bytes, checksum: 6e07afed47d7417b136dde0a2232bf0d (MD5) Zhang_2016_License.pdf: 97291 bytes, checksum: 0c856ad23994f9497f78057a8c21a671 (MD5) Previous issue date: 2018-11-08","Embargo set by: Seth Robbins for item 109814 Lift date: 2021-02-07T20:36:09Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","Embargo set by: Seth Robbins for item 109814 Lift date: 2021-02-07T20:39:46Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","Embargo set by: Seth Robbins for item 109814 Lift date: 2021-02-07T20:44:35Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","U of I Only Restriction Lifted for Item 109814 on 2021-02-08T10:15:22Z."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/102790"],"dc:language":["en"],"dc:rights":["Copyright 2018 Dongwei Fu"],"dc:subject":["Cloud Effective Radius","Data Fusion","Bias Correction","Remote Sensing","Radiative Transfer","MISR","MODIS"],"dc:title":["Examination of the behavior of modis-retrieved cloud droplet effective radius through misr-modis data fusion"],"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":"2026-07-22T22:24:42Z"}