Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data
Thanks to its observational frequency of 15 min, the Meteosat Second Generation (MSG) geostationary satellite offers a great potential to monitor dust storms. To explore this potential, an algorithm for the detection and the retrieval of dust aerosol optical properties has been tested. This is a mul...
Published in: | Atmosphere |
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Main Authors: | , , , , |
Format: | Text |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute
2013
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Subjects: | |
Online Access: | https://doi.org/10.3390/atmos4010035 |
_version_ | 1821540008227504128 |
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author | Filomena Romano Elisabetta Ricciardelli Domenico Cimini Francesco Di Paola Mariassunta Viggiano |
author_facet | Filomena Romano Elisabetta Ricciardelli Domenico Cimini Francesco Di Paola Mariassunta Viggiano |
author_sort | Filomena Romano |
collection | MDPI Open Access Publishing |
container_issue | 1 |
container_start_page | 35 |
container_title | Atmosphere |
container_volume | 4 |
description | Thanks to its observational frequency of 15 min, the Meteosat Second Generation (MSG) geostationary satellite offers a great potential to monitor dust storms. To explore this potential, an algorithm for the detection and the retrieval of dust aerosol optical properties has been tested. This is a multispectral algorithm based on visible and infrared data which has been applied to 15 case studies selected between 2007 and 2011. The algorithm has been validated in the latitude–longitude box between 30 and 50 degrees north, and −10 and 20 degrees east, respectively. Hereafter we present the obtained results that have been validated against Aerosol Robotic Network (AERONET) ground-based measurements and compared with the retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua satellites. The dust aerosol optical depth variations observed at the AERONET sites are well reproduced, showing good correlation of about 0.77, and a root mean square difference within 0.08, and the spatial patterns retrieved by using the algorithm developed are in agreement with those observed by MODIS. |
format | Text |
genre | Aerosol Robotic Network |
genre_facet | Aerosol Robotic Network |
id | ftmdpi:oai:mdpi.com:/2073-4433/4/1/35/ |
institution | Open Polar |
language | English |
op_collection_id | ftmdpi |
op_container_end_page | 47 |
op_coverage | agris |
op_doi | https://doi.org/10.3390/atmos4010035 |
op_relation | Aerosols https://dx.doi.org/10.3390/atmos4010035 |
op_rights | https://creativecommons.org/licenses/by-nc-sa/3.0/ |
op_source | Atmosphere; Volume 4; Issue 1; Pages: 35-47 |
publishDate | 2013 |
publisher | Multidisciplinary Digital Publishing Institute |
record_format | openpolar |
spelling | ftmdpi:oai:mdpi.com:/2073-4433/4/1/35/ 2025-01-16T18:38:09+00:00 Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data Filomena Romano Elisabetta Ricciardelli Domenico Cimini Francesco Di Paola Mariassunta Viggiano agris 2013-03-05 application/pdf https://doi.org/10.3390/atmos4010035 EN eng Multidisciplinary Digital Publishing Institute Aerosols https://dx.doi.org/10.3390/atmos4010035 https://creativecommons.org/licenses/by-nc-sa/3.0/ Atmosphere; Volume 4; Issue 1; Pages: 35-47 dust optical depth dust detection MSG SEVIRI Text 2013 ftmdpi https://doi.org/10.3390/atmos4010035 2023-07-31T20:31:47Z Thanks to its observational frequency of 15 min, the Meteosat Second Generation (MSG) geostationary satellite offers a great potential to monitor dust storms. To explore this potential, an algorithm for the detection and the retrieval of dust aerosol optical properties has been tested. This is a multispectral algorithm based on visible and infrared data which has been applied to 15 case studies selected between 2007 and 2011. The algorithm has been validated in the latitude–longitude box between 30 and 50 degrees north, and −10 and 20 degrees east, respectively. Hereafter we present the obtained results that have been validated against Aerosol Robotic Network (AERONET) ground-based measurements and compared with the retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua satellites. The dust aerosol optical depth variations observed at the AERONET sites are well reproduced, showing good correlation of about 0.77, and a root mean square difference within 0.08, and the spatial patterns retrieved by using the algorithm developed are in agreement with those observed by MODIS. Text Aerosol Robotic Network MDPI Open Access Publishing Atmosphere 4 1 35 47 |
spellingShingle | dust optical depth dust detection MSG SEVIRI Filomena Romano Elisabetta Ricciardelli Domenico Cimini Francesco Di Paola Mariassunta Viggiano Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data |
title | Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data |
title_full | Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data |
title_fullStr | Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data |
title_full_unstemmed | Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data |
title_short | Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data |
title_sort | dust detection and optical depth retrieval using msg‑seviri data |
topic | dust optical depth dust detection MSG SEVIRI |
topic_facet | dust optical depth dust detection MSG SEVIRI |
url | https://doi.org/10.3390/atmos4010035 |