Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign
International audience Abstract. The European Aerosol Research Lidar Network (EARLINET), part of the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS), organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during...
Published in: | Atmospheric Measurement Techniques |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Other Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2023
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Online Access: | https://hal.science/hal-04459590 https://hal.science/hal-04459590/document https://hal.science/hal-04459590/file/amt-16-6025-2023.pdf https://doi.org/10.5194/amt-16-6025-2023 |
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ftunivreunion:oai:HAL:hal-04459590v1 |
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record_format |
openpolar |
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Open Polar |
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Université de la Réunion: HAL |
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ftunivreunion |
language |
English |
topic |
Algorithm meteorological GRASP GARRLIC AOD AERONET lidar radiometer aerosol particles atmospheric photometer uncertainties inversion algorithm combined data properties characteristics [SDE]Environmental Sciences [SDU]Sciences of the Universe [physics] [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
spellingShingle |
Algorithm meteorological GRASP GARRLIC AOD AERONET lidar radiometer aerosol particles atmospheric photometer uncertainties inversion algorithm combined data properties characteristics [SDE]Environmental Sciences [SDU]Sciences of the Universe [physics] [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere Tsekeri, Alexandra Gialitaki, Anna Di Paolantonio, Marco Dionisi, Davide Liberti, Gian, Luigi Fernandes, Alnilam Szkop, Artur Pietruczuk, Aleksander Pérez-Ramírez, Daniel Granados Muñoz, Maria, J Guerrero-Rascado, Juan, Luis Alados-Arboledas, Lucas Bermejo Pantaleón, Diego Bravo-Aranda, Juan, Antonio Kampouri, Anna Marinou, Eleni Amiridis, Vassilis Sicard, Michael Comerón, Adolfo Muñoz-Porcar, Constantino Rodríguez-Gómez, Alejandro Romano, Salvatore Perrone, Maria, Rita Shang, Xiaoxia Komppula, Mika Mamouri, Rodanthi-Elisavet Nisantzi, Argyro Hadjimitsis, Diofantos Navas-Guzmán, Francisco Haefele, Alexander Szczepanik, Dominika Tomczak, Artur Stachlewska, Iwona, S Belegante, Livio Nicolae, Doina Voudouri, Kalliopi, Artemis Balis, Dimitris Floutsi, Athena, A Baars, Holger Miladi, Linda Pascal, Nicolas Dubovik, Oleg Lopatin, Anton Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign |
topic_facet |
Algorithm meteorological GRASP GARRLIC AOD AERONET lidar radiometer aerosol particles atmospheric photometer uncertainties inversion algorithm combined data properties characteristics [SDE]Environmental Sciences [SDU]Sciences of the Universe [physics] [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
description |
International audience Abstract. The European Aerosol Research Lidar Network (EARLINET), part of the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS), organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. Besides the standard operational processing of the lidar data in EARLINET, for seven EARLINET sites having collocated sun-photometric observations in the Aerosol Robotic Network (AERONET), a network exercise was held in order to derive profiles of the concentration and effective column size distributions of the aerosols in the atmosphere, by applying the GRASP/GARRLiC (from Generalized Aerosol Retrieval from Radiometer and Lidar Combined data – GARRLiC – part of the Generalized Retrieval of Atmosphere and Surface Properties – GRASP) inversion algorithm. The objective of this network exercise was to explore the possibility of identifying the anthropogenic component and of monitoring its spatial and temporal characteristics in the COVID-19 lockdown and relaxation period. While the number of cases is far from being statistically significant so as to provide a conclusive description of the atmospheric aerosols over Europe during this period, this network exercise was fundamental to deriving a common methodology for applying GRASP/GARRLiC to a network of instruments with different characteristics. The limits of the approach are discussed, in particular the missing information close to the ground in the lidar measurements due to the instrument geometry and the sensitivity of the GRASP/GARRLiC retrieval to the settings used, especially for cases with low aerosol optical depth (AOD) like the ones we show here. We found that this sensitivity is well-characterized in the GRASP/GARRLiC products, since it is included in their retrieval uncertainties. |
author2 |
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing Penteli (IAASARS) National Observatory of Athens (NOA) Aristotle University of Thessaloniki Earth Observation Science Group Leicester (EOS) Space Research Centre Leicester University of Leicester-University of Leicester Istituto di Science Marine (ISMAR ) National Research Council of Italy Scuola di Ingegneria Potenza Università degli studi della Basilicata = University of Basilicata (UNIBAS) Institute of Geophysics Warsaw Polska Akademia Nauk = Polish Academy of Sciences = Académie polonaise des sciences (PAN) Department of Applied Physics Granada Universidad de Granada = University of Granada (UGR) Instituto Interuniversitario de Investigacion del Sistema Tierra en Andalucia (IISTA-CEAMA) Department of Meteorology and Climatology Thessaloniki Universitat Politècnica de Catalunya = Université polytechnique de Catalogne Barcelona (UPC) Laboratoire de l'Atmosphère et des Cyclones (LACy) Institut national des sciences de l'Univers (INSU - CNRS)-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS)-Météo-France Department of Mathematics and Physics Lecce University of Salento Lecce Finnish Meteorological Institute (FMI) Department of Civil Engineering and Geomatics Cyprus Cyprus University of Technology Federal Office of Meteorology and Climatology MeteoSwiss Faculty of Physics Warsaw University of Technology Warsaw National Institute of Research and Development for Optoelectronics (INOE) Laboratory of Atmospheric Physics Thessaloniki Leibniz Institute for Tropospheric Research (TROPOS) interaction Clouds Aerosols Radiations - ICARE/AERIS Data and Services Center - UMS 2877 (ICARE) Centre National d'Études Spatiales Toulouse (CNES)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA) Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) Generalized Retrieval of Atmosphere and Surface Properties (GRASP SAS) This research was financially supported by D-TECT (grant agreement no. 725698) funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme and by PANGEA4CalVal (grant agreement no. 101079201) funded by the European Union https://amt.copernicus.org/articles/16/6025/2023/amt-16-6025-2023-g01. The Barcelona site has been funded by the REALISTIC project (grant agreement no. 101086690) under the European Union's Horizon Widera 2022 Talents programme. The Warsaw site has been supported by the European Commission H2020 (ACTRIS IMP (grant no. 871115)). The Belsk site has been supported by the National Science Centre, Poland (grant no. 2021/41/B/ST10/03660). European Project: 101086690,REALISTIC European Project: 871115,H2020,H2020-INFRADEV-2018-2020,ACTRIS IMP(2020) European Project: 101079201,PANGEA4CalVal |
format |
Article in Journal/Newspaper |
author |
Tsekeri, Alexandra Gialitaki, Anna Di Paolantonio, Marco Dionisi, Davide Liberti, Gian, Luigi Fernandes, Alnilam Szkop, Artur Pietruczuk, Aleksander Pérez-Ramírez, Daniel Granados Muñoz, Maria, J Guerrero-Rascado, Juan, Luis Alados-Arboledas, Lucas Bermejo Pantaleón, Diego Bravo-Aranda, Juan, Antonio Kampouri, Anna Marinou, Eleni Amiridis, Vassilis Sicard, Michael Comerón, Adolfo Muñoz-Porcar, Constantino Rodríguez-Gómez, Alejandro Romano, Salvatore Perrone, Maria, Rita Shang, Xiaoxia Komppula, Mika Mamouri, Rodanthi-Elisavet Nisantzi, Argyro Hadjimitsis, Diofantos Navas-Guzmán, Francisco Haefele, Alexander Szczepanik, Dominika Tomczak, Artur Stachlewska, Iwona, S Belegante, Livio Nicolae, Doina Voudouri, Kalliopi, Artemis Balis, Dimitris Floutsi, Athena, A Baars, Holger Miladi, Linda Pascal, Nicolas Dubovik, Oleg Lopatin, Anton |
author_facet |
Tsekeri, Alexandra Gialitaki, Anna Di Paolantonio, Marco Dionisi, Davide Liberti, Gian, Luigi Fernandes, Alnilam Szkop, Artur Pietruczuk, Aleksander Pérez-Ramírez, Daniel Granados Muñoz, Maria, J Guerrero-Rascado, Juan, Luis Alados-Arboledas, Lucas Bermejo Pantaleón, Diego Bravo-Aranda, Juan, Antonio Kampouri, Anna Marinou, Eleni Amiridis, Vassilis Sicard, Michael Comerón, Adolfo Muñoz-Porcar, Constantino Rodríguez-Gómez, Alejandro Romano, Salvatore Perrone, Maria, Rita Shang, Xiaoxia Komppula, Mika Mamouri, Rodanthi-Elisavet Nisantzi, Argyro Hadjimitsis, Diofantos Navas-Guzmán, Francisco Haefele, Alexander Szczepanik, Dominika Tomczak, Artur Stachlewska, Iwona, S Belegante, Livio Nicolae, Doina Voudouri, Kalliopi, Artemis Balis, Dimitris Floutsi, Athena, A Baars, Holger Miladi, Linda Pascal, Nicolas Dubovik, Oleg Lopatin, Anton |
author_sort |
Tsekeri, Alexandra |
title |
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign |
title_short |
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign |
title_full |
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign |
title_fullStr |
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign |
title_full_unstemmed |
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign |
title_sort |
combined sun-photometer–lidar inversion: lessons learned during the earlinet/actris covid-19 campaign |
publisher |
HAL CCSD |
publishDate |
2023 |
url |
https://hal.science/hal-04459590 https://hal.science/hal-04459590/document https://hal.science/hal-04459590/file/amt-16-6025-2023.pdf https://doi.org/10.5194/amt-16-6025-2023 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
ISSN: 1867-1381 EISSN: 1867-8548 Atmospheric Measurement Techniques https://hal.science/hal-04459590 Atmospheric Measurement Techniques, 2023, 16 (24), pp.6025 - 6050. ⟨10.5194/amt-16-6025-2023⟩ |
op_relation |
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op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/amt-16-6025-2023 |
container_title |
Atmospheric Measurement Techniques |
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16 |
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24 |
container_start_page |
6025 |
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6050 |
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1810447634951831552 |
spelling |
ftunivreunion:oai:HAL:hal-04459590v1 2024-09-15T17:35:15+00:00 Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign Tsekeri, Alexandra Gialitaki, Anna Di Paolantonio, Marco Dionisi, Davide Liberti, Gian, Luigi Fernandes, Alnilam Szkop, Artur Pietruczuk, Aleksander Pérez-Ramírez, Daniel Granados Muñoz, Maria, J Guerrero-Rascado, Juan, Luis Alados-Arboledas, Lucas Bermejo Pantaleón, Diego Bravo-Aranda, Juan, Antonio Kampouri, Anna Marinou, Eleni Amiridis, Vassilis Sicard, Michael Comerón, Adolfo Muñoz-Porcar, Constantino Rodríguez-Gómez, Alejandro Romano, Salvatore Perrone, Maria, Rita Shang, Xiaoxia Komppula, Mika Mamouri, Rodanthi-Elisavet Nisantzi, Argyro Hadjimitsis, Diofantos Navas-Guzmán, Francisco Haefele, Alexander Szczepanik, Dominika Tomczak, Artur Stachlewska, Iwona, S Belegante, Livio Nicolae, Doina Voudouri, Kalliopi, Artemis Balis, Dimitris Floutsi, Athena, A Baars, Holger Miladi, Linda Pascal, Nicolas Dubovik, Oleg Lopatin, Anton Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing Penteli (IAASARS) National Observatory of Athens (NOA) Aristotle University of Thessaloniki Earth Observation Science Group Leicester (EOS) Space Research Centre Leicester University of Leicester-University of Leicester Istituto di Science Marine (ISMAR ) National Research Council of Italy Scuola di Ingegneria Potenza Università degli studi della Basilicata = University of Basilicata (UNIBAS) Institute of Geophysics Warsaw Polska Akademia Nauk = Polish Academy of Sciences = Académie polonaise des sciences (PAN) Department of Applied Physics Granada Universidad de Granada = University of Granada (UGR) Instituto Interuniversitario de Investigacion del Sistema Tierra en Andalucia (IISTA-CEAMA) Department of Meteorology and Climatology Thessaloniki Universitat Politècnica de Catalunya = Université polytechnique de Catalogne Barcelona (UPC) Laboratoire de l'Atmosphère et des Cyclones (LACy) Institut national des sciences de l'Univers (INSU - CNRS)-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS)-Météo-France Department of Mathematics and Physics Lecce University of Salento Lecce Finnish Meteorological Institute (FMI) Department of Civil Engineering and Geomatics Cyprus Cyprus University of Technology Federal Office of Meteorology and Climatology MeteoSwiss Faculty of Physics Warsaw University of Technology Warsaw National Institute of Research and Development for Optoelectronics (INOE) Laboratory of Atmospheric Physics Thessaloniki Leibniz Institute for Tropospheric Research (TROPOS) interaction Clouds Aerosols Radiations - ICARE/AERIS Data and Services Center - UMS 2877 (ICARE) Centre National d'Études Spatiales Toulouse (CNES)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA) Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) Generalized Retrieval of Atmosphere and Surface Properties (GRASP SAS) This research was financially supported by D-TECT (grant agreement no. 725698) funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme and by PANGEA4CalVal (grant agreement no. 101079201) funded by the European Union https://amt.copernicus.org/articles/16/6025/2023/amt-16-6025-2023-g01. The Barcelona site has been funded by the REALISTIC project (grant agreement no. 101086690) under the European Union's Horizon Widera 2022 Talents programme. The Warsaw site has been supported by the European Commission H2020 (ACTRIS IMP (grant no. 871115)). The Belsk site has been supported by the National Science Centre, Poland (grant no. 2021/41/B/ST10/03660). European Project: 101086690,REALISTIC European Project: 871115,H2020,H2020-INFRADEV-2018-2020,ACTRIS IMP(2020) European Project: 101079201,PANGEA4CalVal 2023-12-15 https://hal.science/hal-04459590 https://hal.science/hal-04459590/document https://hal.science/hal-04459590/file/amt-16-6025-2023.pdf https://doi.org/10.5194/amt-16-6025-2023 en eng HAL CCSD European Geosciences Union info:eu-repo/semantics/altIdentifier/doi/10.5194/amt-16-6025-2023 info:eu-repo/grantAgreement//101086690/EU/centRe of Excellence in AerosoL remote sensIng technology and Science in The Indian oCean/REALISTIC info:eu-repo/grantAgreement//871115/EU/Aerosol, Clouds and Trace Gases Research Infrastructure Implementation Project/ACTRIS IMP info:eu-repo/grantAgreement//101079201/EU/PANGEA Cal/Val center for enhancing Earth Observation R&I in the Mediterranean/PANGEA4CalVal hal-04459590 https://hal.science/hal-04459590 https://hal.science/hal-04459590/document https://hal.science/hal-04459590/file/amt-16-6025-2023.pdf doi:10.5194/amt-16-6025-2023 info:eu-repo/semantics/OpenAccess ISSN: 1867-1381 EISSN: 1867-8548 Atmospheric Measurement Techniques https://hal.science/hal-04459590 Atmospheric Measurement Techniques, 2023, 16 (24), pp.6025 - 6050. ⟨10.5194/amt-16-6025-2023⟩ Algorithm meteorological GRASP GARRLIC AOD AERONET lidar radiometer aerosol particles atmospheric photometer uncertainties inversion algorithm combined data properties characteristics [SDE]Environmental Sciences [SDU]Sciences of the Universe [physics] [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere info:eu-repo/semantics/article Journal articles 2023 ftunivreunion https://doi.org/10.5194/amt-16-6025-2023 2024-07-15T23:39:08Z International audience Abstract. The European Aerosol Research Lidar Network (EARLINET), part of the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS), organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. Besides the standard operational processing of the lidar data in EARLINET, for seven EARLINET sites having collocated sun-photometric observations in the Aerosol Robotic Network (AERONET), a network exercise was held in order to derive profiles of the concentration and effective column size distributions of the aerosols in the atmosphere, by applying the GRASP/GARRLiC (from Generalized Aerosol Retrieval from Radiometer and Lidar Combined data – GARRLiC – part of the Generalized Retrieval of Atmosphere and Surface Properties – GRASP) inversion algorithm. The objective of this network exercise was to explore the possibility of identifying the anthropogenic component and of monitoring its spatial and temporal characteristics in the COVID-19 lockdown and relaxation period. While the number of cases is far from being statistically significant so as to provide a conclusive description of the atmospheric aerosols over Europe during this period, this network exercise was fundamental to deriving a common methodology for applying GRASP/GARRLiC to a network of instruments with different characteristics. The limits of the approach are discussed, in particular the missing information close to the ground in the lidar measurements due to the instrument geometry and the sensitivity of the GRASP/GARRLiC retrieval to the settings used, especially for cases with low aerosol optical depth (AOD) like the ones we show here. We found that this sensitivity is well-characterized in the GRASP/GARRLiC products, since it is included in their retrieval uncertainties. Article in Journal/Newspaper Aerosol Robotic Network Université de la Réunion: HAL Atmospheric Measurement Techniques 16 24 6025 6050 |