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...

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Published in:Atmosphere
Main Authors: Francesco Di Paola, Mariassunta Viggiano, Domenico Cimini, Elisabetta Ricciardelli, Filomena Romano
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2013
Subjects:
MSG
Online Access:https://doi.org/10.3390/atmos4010035
https://doaj.org/article/9efb5d7925f849569eb86428db83728a
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spelling ftdoajarticles:oai:doaj.org/article:9efb5d7925f849569eb86428db83728a 2023-05-15T13:06:07+02:00 Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data Francesco Di Paola Mariassunta Viggiano Domenico Cimini Elisabetta Ricciardelli Filomena Romano 2013-03-01T00:00:00Z https://doi.org/10.3390/atmos4010035 https://doaj.org/article/9efb5d7925f849569eb86428db83728a EN eng MDPI AG http://www.mdpi.com/2073-4433/4/1/35 https://doaj.org/toc/2073-4433 doi:10.3390/atmos4010035 2073-4433 https://doaj.org/article/9efb5d7925f849569eb86428db83728a Atmosphere, Vol 4, Iss 1, Pp 35-47 (2013) dust optical depth dust detection MSG SEVIRI Meteorology. Climatology QC851-999 article 2013 ftdoajarticles https://doi.org/10.3390/atmos4010035 2022-12-31T12:09:46Z 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. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmosphere 4 1 35 47
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic dust optical depth
dust detection
MSG
SEVIRI
Meteorology. Climatology
QC851-999
spellingShingle dust optical depth
dust detection
MSG
SEVIRI
Meteorology. Climatology
QC851-999
Francesco Di Paola
Mariassunta Viggiano
Domenico Cimini
Elisabetta Ricciardelli
Filomena Romano
Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data
topic_facet dust optical depth
dust detection
MSG
SEVIRI
Meteorology. Climatology
QC851-999
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 Article in Journal/Newspaper
author Francesco Di Paola
Mariassunta Viggiano
Domenico Cimini
Elisabetta Ricciardelli
Filomena Romano
author_facet Francesco Di Paola
Mariassunta Viggiano
Domenico Cimini
Elisabetta Ricciardelli
Filomena Romano
author_sort Francesco Di Paola
title Dust Detection and Optical Depth Retrieval Using MSG‑SEVIRI Data
title_short 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_sort dust detection and optical depth retrieval using msg‑seviri data
publisher MDPI AG
publishDate 2013
url https://doi.org/10.3390/atmos4010035
https://doaj.org/article/9efb5d7925f849569eb86428db83728a
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Atmosphere, Vol 4, Iss 1, Pp 35-47 (2013)
op_relation http://www.mdpi.com/2073-4433/4/1/35
https://doaj.org/toc/2073-4433
doi:10.3390/atmos4010035
2073-4433
https://doaj.org/article/9efb5d7925f849569eb86428db83728a
op_doi https://doi.org/10.3390/atmos4010035
container_title Atmosphere
container_volume 4
container_issue 1
container_start_page 35
op_container_end_page 47
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