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Dust Aerosol Detection by the Modified CO(2) Slicing Method
Dust aerosols, which have diverse and strong influences on the environment, must be monitored. Satellite data are effective for monitoring atmospheric conditions globally. In this work, the modified CO(2) slicing method, a cloud detection technique using thermal infrared data from space, was applied...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479980/ https://www.ncbi.nlm.nih.gov/pubmed/30987274 http://dx.doi.org/10.3390/s19071615 |
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author | Someya, Yu Imasu, Ryoichi Shiomi, Kei |
author_facet | Someya, Yu Imasu, Ryoichi Shiomi, Kei |
author_sort | Someya, Yu |
collection | PubMed |
description | Dust aerosols, which have diverse and strong influences on the environment, must be monitored. Satellite data are effective for monitoring atmospheric conditions globally. In this work, the modified CO(2) slicing method, a cloud detection technique using thermal infrared data from space, was applied to GOSAT data to detect the dust aerosol layer height. The results were compared using lidar measurements. Comparison of horizontal distributions found for northern Africa during summer revealed that both the relative frequencies of the low level aerosol layer from the slicing method and the dust frequencies of CALIPSO are high in northern coastal areas. Comparisons of detected layer top heights using collocated data with CALIPSO and ground-based lidar consistently showed high detection frequencies of the lower level aerosol layer, although the slicing method sometimes produces overestimates. This tendency is significant over land. The main causes of this tendency might be uncertainty of the surface skin temperature and a temperature inversion layer in the atmosphere. The results revealed that obtaining the detailed behavior of dust aerosols using the modified slicing method alone is difficult. |
format | Online Article Text |
id | pubmed-6479980 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64799802019-04-29 Dust Aerosol Detection by the Modified CO(2) Slicing Method Someya, Yu Imasu, Ryoichi Shiomi, Kei Sensors (Basel) Article Dust aerosols, which have diverse and strong influences on the environment, must be monitored. Satellite data are effective for monitoring atmospheric conditions globally. In this work, the modified CO(2) slicing method, a cloud detection technique using thermal infrared data from space, was applied to GOSAT data to detect the dust aerosol layer height. The results were compared using lidar measurements. Comparison of horizontal distributions found for northern Africa during summer revealed that both the relative frequencies of the low level aerosol layer from the slicing method and the dust frequencies of CALIPSO are high in northern coastal areas. Comparisons of detected layer top heights using collocated data with CALIPSO and ground-based lidar consistently showed high detection frequencies of the lower level aerosol layer, although the slicing method sometimes produces overestimates. This tendency is significant over land. The main causes of this tendency might be uncertainty of the surface skin temperature and a temperature inversion layer in the atmosphere. The results revealed that obtaining the detailed behavior of dust aerosols using the modified slicing method alone is difficult. MDPI 2019-04-04 /pmc/articles/PMC6479980/ /pubmed/30987274 http://dx.doi.org/10.3390/s19071615 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Someya, Yu Imasu, Ryoichi Shiomi, Kei Dust Aerosol Detection by the Modified CO(2) Slicing Method |
title | Dust Aerosol Detection by the Modified CO(2) Slicing Method |
title_full | Dust Aerosol Detection by the Modified CO(2) Slicing Method |
title_fullStr | Dust Aerosol Detection by the Modified CO(2) Slicing Method |
title_full_unstemmed | Dust Aerosol Detection by the Modified CO(2) Slicing Method |
title_short | Dust Aerosol Detection by the Modified CO(2) Slicing Method |
title_sort | dust aerosol detection by the modified co(2) slicing method |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479980/ https://www.ncbi.nlm.nih.gov/pubmed/30987274 http://dx.doi.org/10.3390/s19071615 |
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