Validation of Ash/Dust Detections from SEVIRI Data Using ACTRIS/EARLINET Ground-Based LIDAR Measurements

Two tailored configurations of the Robust Satellite Technique (RST) multi-temporal approach, for airborne volcanic ash and desert dust detection, have been tested in the framework of the European Natural Airborne Disaster Information and Coordination System for Aviation (EUNADICS-AV) project. The tw...

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Published in:Remote Sensing
Main Authors: Alfredo Falconieri, Nikolaos Papagiannopoulos, Francesco Marchese, Carolina Filizzola, Serena Trippetta, Nicola Pergola, Gelsomina Pappalardo, Valerio Tramutoli, Lucia Mona
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
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Online Access:https://doi.org/10.3390/rs12071172
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author Alfredo Falconieri
Nikolaos Papagiannopoulos
Francesco Marchese
Carolina Filizzola
Serena Trippetta
Nicola Pergola
Gelsomina Pappalardo
Valerio Tramutoli
Lucia Mona
author_facet Alfredo Falconieri
Nikolaos Papagiannopoulos
Francesco Marchese
Carolina Filizzola
Serena Trippetta
Nicola Pergola
Gelsomina Pappalardo
Valerio Tramutoli
Lucia Mona
author_sort Alfredo Falconieri
collection MDPI Open Access Publishing
container_issue 7
container_start_page 1172
container_title Remote Sensing
container_volume 12
description Two tailored configurations of the Robust Satellite Technique (RST) multi-temporal approach, for airborne volcanic ash and desert dust detection, have been tested in the framework of the European Natural Airborne Disaster Information and Coordination System for Aviation (EUNADICS-AV) project. The two algorithms, running on Spinning Enhanced Visible Infra-Red Imager (SEVIRI) data, were previously assessed over wide areas by comparison with independent satellite-based aerosol products. In this study, we present results of a first validation analysis of the above mentioned satellite-based ash/dust products using independent, ground-based observations coming from the European Aerosol Research Lidar Network (EARLINET). The aim is to assess the capabilities of RST-based ash/dust products in providing useful information even at local scale and to verify their applicability as a “trigger” to timely activate EARLINET measurements during airborne hazards. The intense Saharan dust event of May 18–23 2008—which affected both the Mediterranean Basin and Continental Europe—and the strong explosive eruptions of Eyjafjallajökull (Iceland) volcano of April–May 2010, were analyzed as test cases. Our results show that both RST-based algorithms were capable of providing reliable information about the investigated phenomena at specific sites of interest, successfully detecting airborne ash/dust in different geographic regions using both nighttime and daytime SEVIRI data. However, the validation analysis also demonstrates that ash/dust layers remain undetected by satellite in the presence of overlying meteorological clouds and when they are tenuous (i.e., with an integrated backscatter coefficient less than ~0.001 sr−1 and with aerosol backscatter coefficient less than ~1 × 10−6 m−1sr−1). This preliminary analysis confirms that the continuity of satellite-based observations can be used to timely “trigger” ground-based LIDAR measurements in case of airborne hazard events. Finally, this work confirms that advanced satellite-based ...
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/7/1172/ 2025-01-16T21:48:01+00:00 Validation of Ash/Dust Detections from SEVIRI Data Using ACTRIS/EARLINET Ground-Based LIDAR Measurements Alfredo Falconieri Nikolaos Papagiannopoulos Francesco Marchese Carolina Filizzola Serena Trippetta Nicola Pergola Gelsomina Pappalardo Valerio Tramutoli Lucia Mona 2020-04-06 application/pdf https://doi.org/10.3390/rs12071172 EN eng Multidisciplinary Digital Publishing Institute Biogeosciences Remote Sensing https://dx.doi.org/10.3390/rs12071172 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 7; Pages: 1172 ash clouds dust outbreaks SEVIRI EARLINET RST Text 2020 ftmdpi https://doi.org/10.3390/rs12071172 2023-07-31T23:20:12Z Two tailored configurations of the Robust Satellite Technique (RST) multi-temporal approach, for airborne volcanic ash and desert dust detection, have been tested in the framework of the European Natural Airborne Disaster Information and Coordination System for Aviation (EUNADICS-AV) project. The two algorithms, running on Spinning Enhanced Visible Infra-Red Imager (SEVIRI) data, were previously assessed over wide areas by comparison with independent satellite-based aerosol products. In this study, we present results of a first validation analysis of the above mentioned satellite-based ash/dust products using independent, ground-based observations coming from the European Aerosol Research Lidar Network (EARLINET). The aim is to assess the capabilities of RST-based ash/dust products in providing useful information even at local scale and to verify their applicability as a “trigger” to timely activate EARLINET measurements during airborne hazards. The intense Saharan dust event of May 18–23 2008—which affected both the Mediterranean Basin and Continental Europe—and the strong explosive eruptions of Eyjafjallajökull (Iceland) volcano of April–May 2010, were analyzed as test cases. Our results show that both RST-based algorithms were capable of providing reliable information about the investigated phenomena at specific sites of interest, successfully detecting airborne ash/dust in different geographic regions using both nighttime and daytime SEVIRI data. However, the validation analysis also demonstrates that ash/dust layers remain undetected by satellite in the presence of overlying meteorological clouds and when they are tenuous (i.e., with an integrated backscatter coefficient less than ~0.001 sr−1 and with aerosol backscatter coefficient less than ~1 × 10−6 m−1sr−1). This preliminary analysis confirms that the continuity of satellite-based observations can be used to timely “trigger” ground-based LIDAR measurements in case of airborne hazard events. Finally, this work confirms that advanced satellite-based ... Text Eyjafjallajökull Iceland MDPI Open Access Publishing Remote Sensing 12 7 1172
spellingShingle ash clouds
dust outbreaks
SEVIRI
EARLINET
RST
Alfredo Falconieri
Nikolaos Papagiannopoulos
Francesco Marchese
Carolina Filizzola
Serena Trippetta
Nicola Pergola
Gelsomina Pappalardo
Valerio Tramutoli
Lucia Mona
Validation of Ash/Dust Detections from SEVIRI Data Using ACTRIS/EARLINET Ground-Based LIDAR Measurements
title Validation of Ash/Dust Detections from SEVIRI Data Using ACTRIS/EARLINET Ground-Based LIDAR Measurements
title_full Validation of Ash/Dust Detections from SEVIRI Data Using ACTRIS/EARLINET Ground-Based LIDAR Measurements
title_fullStr Validation of Ash/Dust Detections from SEVIRI Data Using ACTRIS/EARLINET Ground-Based LIDAR Measurements
title_full_unstemmed Validation of Ash/Dust Detections from SEVIRI Data Using ACTRIS/EARLINET Ground-Based LIDAR Measurements
title_short Validation of Ash/Dust Detections from SEVIRI Data Using ACTRIS/EARLINET Ground-Based LIDAR Measurements
title_sort validation of ash/dust detections from seviri data using actris/earlinet ground-based lidar measurements
topic ash clouds
dust outbreaks
SEVIRI
EARLINET
RST
topic_facet ash clouds
dust outbreaks
SEVIRI
EARLINET
RST
url https://doi.org/10.3390/rs12071172