A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3390/atmos13010077 http://hdl.handle.net/11449/223226 |
Resumo: | Geostationary satellites can retrieve the cloud droplet effective radius (re ) but suffer biases from cloud inhomogeneities, internal retrieval nonlinearities, and 3-D scattering/shadowing from neighboring clouds, among others. A 1-D retrieval method was applied to Geostationary Operational Environmental Satellite 13 (GOES-13) imagery, over large areas in South America (5◦ N–30◦ S; 20◦–70◦ W), the Southeast Pacific (5◦ N–30◦ S; 70◦–120◦ W), and the Amazon (2◦ N–7◦ S; 54◦–73◦ W), for four months in each year from 2014–2017. Results were compared against in situ aircraft measurements and the Moderate Resolution Imaging Spectroradiometer cloud product for Terra and Aqua satellites. Monthly regression parameters approximately followed a seasonal pattern. With up to 108,009 of matchups, slope, intercept, and correlation for Terra (Aqua) ranged from about 0.71 to 1.17, −2.8 to 2.5 µm, and 0.61 to 0.91 (0.54 to 0.78, −1.5 to 1.8 µm, 0.63 to 0.89), respectively. We identified evidence for re overestimation (underestimation) correlated with shadowing (enhanced reflectance) in the forward (backscattering) hemisphere, and limitations to illumination and viewing configurations accessible by GOES-13, depending on the time of day and season. A proposition is hypothesized to ameliorate 3-D biases by studying relative illumination and cloud spatial inhomogeneity. |
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A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast PacificCloud effective radiusGOESMicrophysicsRemote sensingTropicsGeostationary satellites can retrieve the cloud droplet effective radius (re ) but suffer biases from cloud inhomogeneities, internal retrieval nonlinearities, and 3-D scattering/shadowing from neighboring clouds, among others. A 1-D retrieval method was applied to Geostationary Operational Environmental Satellite 13 (GOES-13) imagery, over large areas in South America (5◦ N–30◦ S; 20◦–70◦ W), the Southeast Pacific (5◦ N–30◦ S; 70◦–120◦ W), and the Amazon (2◦ N–7◦ S; 54◦–73◦ W), for four months in each year from 2014–2017. Results were compared against in situ aircraft measurements and the Moderate Resolution Imaging Spectroradiometer cloud product for Terra and Aqua satellites. Monthly regression parameters approximately followed a seasonal pattern. With up to 108,009 of matchups, slope, intercept, and correlation for Terra (Aqua) ranged from about 0.71 to 1.17, −2.8 to 2.5 µm, and 0.61 to 0.91 (0.54 to 0.78, −1.5 to 1.8 µm, 0.63 to 0.89), respectively. We identified evidence for re overestimation (underestimation) correlated with shadowing (enhanced reflectance) in the forward (backscattering) hemisphere, and limitations to illumination and viewing configurations accessible by GOES-13, depending on the time of day and season. A proposition is hypothesized to ameliorate 3-D biases by studying relative illumination and cloud spatial inhomogeneity.National Oceanic and Atmospheric AdministrationFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Institute of Physics University of Sao PauloDepartment of Environmental Engineering Sao Paulo State UniversityDepartment of Atmospheric Science Colorado State UniversityDepartment of Environmental Engineering Sao Paulo State UniversityFAPESP: 2020/13273-9CNPq: 421870/2018-4Universidade de São Paulo (USP)Universidade Estadual Paulista (UNESP)Colorado State UniversityCorreia, Alexandre L.Mendonça, Marina M. [UNESP]Nobrega, Thiago F.Pugliesi, Andre C.Cecchini, Micael A.2022-04-28T19:49:27Z2022-04-28T19:49:27Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/atmos13010077Atmosphere, v. 13, n. 1, 2022.2073-4433http://hdl.handle.net/11449/22322610.3390/atmos130100772-s2.0-85122667329Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAtmosphereinfo:eu-repo/semantics/openAccess2022-04-28T19:49:27Zoai:repositorio.unesp.br:11449/223226Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:22:00.787461Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific |
title |
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific |
spellingShingle |
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific Correia, Alexandre L. Cloud effective radius GOES Microphysics Remote sensing Tropics |
title_short |
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific |
title_full |
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific |
title_fullStr |
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific |
title_full_unstemmed |
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific |
title_sort |
A Multi-Year Study of GOES-13 Droplet Effective Radius Retrievals for Warm Clouds over South America and Southeast Pacific |
author |
Correia, Alexandre L. |
author_facet |
Correia, Alexandre L. Mendonça, Marina M. [UNESP] Nobrega, Thiago F. Pugliesi, Andre C. Cecchini, Micael A. |
author_role |
author |
author2 |
Mendonça, Marina M. [UNESP] Nobrega, Thiago F. Pugliesi, Andre C. Cecchini, Micael A. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Universidade Estadual Paulista (UNESP) Colorado State University |
dc.contributor.author.fl_str_mv |
Correia, Alexandre L. Mendonça, Marina M. [UNESP] Nobrega, Thiago F. Pugliesi, Andre C. Cecchini, Micael A. |
dc.subject.por.fl_str_mv |
Cloud effective radius GOES Microphysics Remote sensing Tropics |
topic |
Cloud effective radius GOES Microphysics Remote sensing Tropics |
description |
Geostationary satellites can retrieve the cloud droplet effective radius (re ) but suffer biases from cloud inhomogeneities, internal retrieval nonlinearities, and 3-D scattering/shadowing from neighboring clouds, among others. A 1-D retrieval method was applied to Geostationary Operational Environmental Satellite 13 (GOES-13) imagery, over large areas in South America (5◦ N–30◦ S; 20◦–70◦ W), the Southeast Pacific (5◦ N–30◦ S; 70◦–120◦ W), and the Amazon (2◦ N–7◦ S; 54◦–73◦ W), for four months in each year from 2014–2017. Results were compared against in situ aircraft measurements and the Moderate Resolution Imaging Spectroradiometer cloud product for Terra and Aqua satellites. Monthly regression parameters approximately followed a seasonal pattern. With up to 108,009 of matchups, slope, intercept, and correlation for Terra (Aqua) ranged from about 0.71 to 1.17, −2.8 to 2.5 µm, and 0.61 to 0.91 (0.54 to 0.78, −1.5 to 1.8 µm, 0.63 to 0.89), respectively. We identified evidence for re overestimation (underestimation) correlated with shadowing (enhanced reflectance) in the forward (backscattering) hemisphere, and limitations to illumination and viewing configurations accessible by GOES-13, depending on the time of day and season. A proposition is hypothesized to ameliorate 3-D biases by studying relative illumination and cloud spatial inhomogeneity. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-04-28T19:49:27Z 2022-04-28T19:49:27Z 2022-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.3390/atmos13010077 Atmosphere, v. 13, n. 1, 2022. 2073-4433 http://hdl.handle.net/11449/223226 10.3390/atmos13010077 2-s2.0-85122667329 |
url |
http://dx.doi.org/10.3390/atmos13010077 http://hdl.handle.net/11449/223226 |
identifier_str_mv |
Atmosphere, v. 13, n. 1, 2022. 2073-4433 10.3390/atmos13010077 2-s2.0-85122667329 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Atmosphere |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128637947346944 |