Articles | Volume 25, issue 19
https://doi.org/10.5194/acp-25-12549-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-12549-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Oct 2025
Research article |
| 09 Oct 2025
| 09 Oct 2025
Aerosol type classification with machine learning techniques applied to multiwavelength lidar data from EARLINET
Andalusian Institute for Earth System Research (IISTA-CEAMA), 18006 Granada, Spain
Department of Applied Physics, University of Granada, 18071 Granada, Spain
Pablo Ortiz-Amezcua
Andalusian Institute for Earth System Research (IISTA-CEAMA), 18006 Granada, Spain
Department of Applied Physics, University of Granada, 18071 Granada, Spain
Siham Tabik
Department of Computer Science and Artificial Intelligence, University of Granada, 18071 Granada, Spain
Andalusian Research Institute in Data Science and Computational Intelligence (DASCI), University of Granada, 18071 Granada, Spain
Juan Antonio Bravo-Aranda
Andalusian Institute for Earth System Research (IISTA-CEAMA), 18006 Granada, Spain
Department of Applied Physics, University of Granada, 18071 Granada, Spain
Sol Fernández-Carvelo
Andalusian Institute for Earth System Research (IISTA-CEAMA), 18006 Granada, Spain
Department of Applied Physics, University of Granada, 18071 Granada, Spain
Lucas Alados-Arboledas
Andalusian Institute for Earth System Research (IISTA-CEAMA), 18006 Granada, Spain
Department of Applied Physics, University of Granada, 18071 Granada, Spain
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María Ángeles López-Cayuela, Carmen Córdoba-Jabonero, Michaël Sicard, Jesús Abril-Gago, Vanda Salgueiro, Adolfo Comerón, María José Granados-Muñoz, Maria João Costa, Constantino Muñoz-Porcar, Juan Antonio Bravo-Aranda, Daniele Bortoli, Alejandro Rodríguez-Gómez, Lucas Alados-Arboledas, and Juan Luis Guerrero-Rascado
EGUsphere, https://doi.org/10.5194/egusphere-2025-4905, https://doi.org/10.5194/egusphere-2025-4905, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Due to the major radiative role of dust in Climate Change, a vertical assessment of the long-wave (and net) dust direct radiative effect of both fine and coarse dust, separately, is introduced. The study relies on an intense Saharan dust outbreak across the Iberian Peninsula, observed by five lidar stations with SW-centre-NE coverage. A comparative evaluation of the differences by considering the total dust (no separation) is also examined. It complements a similar study in the short-wave range.
Jesús Yus-Díez, Luka Drinovec, Lucas Alados-Arboledas, Gloria Titos, Elena Bazo, Andrea Casans, Diego Patrón, Xavier Querol, Adolfo Gonzalez-Romero, Carlos Perez García-Pando, and Griša Močnik
Atmos. Meas. Tech., 18, 3073–3093, https://doi.org/10.5194/amt-18-3073-2025, https://doi.org/10.5194/amt-18-3073-2025, 2025
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We have used absorption from a photothermal interferometer and scattering measurements to evaluate the most deployed filter photometers used to measure absorption for monitoring networks. We used soot- and dust-dominated aerosol samples in both laboratory and ambient settings. Our results indicated that one of these filter photometers, the MAAP (Multiangle Absorption Photometer), usually used as a pseudo-reference instrument, had 47 % higher absorption values than our reference measurements.
Elena Bazo, Daniel Pérez-Ramírez, Antonio Valenzuela, J. Vanderlei Martins, Gloria Titos, Alberto Cazorla, Fernando Rejano, Diego Patrón, Arlett Díaz-Zurita, Francisco José García-Izquierdo, David Fuertes, Lucas Alados-Arboledas, and Francisco José Olmo
Atmos. Chem. Phys., 25, 6325–6352, https://doi.org/10.5194/acp-25-6325-2025, https://doi.org/10.5194/acp-25-6325-2025, 2025
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This works analyzes the aerosol scattering phase function for transported Saharan dust to the city of Granada – located in southwestern Europe. We use the novel technique polar imaging nephelometry that helps to determine the phase functions using a CMOS camera. The capability of measuring with polarized light helps to infer new properties about the mixture of Saharan dust particles with those of anthropogenic origin.
María-Ángeles López-Cayuela, Carmen Córdoba-Jabonero, Michaël Sicard, Jesús Abril-Gago, Vanda Salgueiro, Adolfo Comerón, María José Granados-Muñoz, Maria João Costa, Constantino Muñoz-Porcar, Juan Antonio Bravo-Aranda, Daniele Bortoli, Alejandro Rodríguez-Gómez, Lucas Alados-Arboledas, and Juan Luis Guerrero-Rascado
Atmos. Chem. Phys., 25, 3213–3231, https://doi.org/10.5194/acp-25-3213-2025, https://doi.org/10.5194/acp-25-3213-2025, 2025
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Due to the significant radiative role of dust in climate change, vertical assessments of the short-wave dust direct radiative effect of both fine and coarse dust particles are performed separately. The study is focused on an intense Saharan dust outbreak crossing the Iberian Peninsula in springtime monitored by five Iberian lidar stations with southwest–northeast coverage. A comparative study to evaluate the differences found by considering the total dust (no separation) is also examined.
Fernando Rejano, Andrea Casans, Marta Via, Juan Andrés Casquero-Vera, Sonia Castillo, Hassan Lyamani, Alberto Cazorla, Elisabeth Andrews, Daniel Pérez-Ramírez, Andrés Alastuey, Francisco Javier Gómez-Moreno, Lucas Alados-Arboledas, Francisco José Olmo, and Gloria Titos
Atmos. Chem. Phys., 24, 13865–13888, https://doi.org/10.5194/acp-24-13865-2024, https://doi.org/10.5194/acp-24-13865-2024, 2024
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This study provides valuable insights to improve cloud condensation nuclei (CCN) estimations at a high-altitude remote site which is influenced by nearby urban pollution. Understanding the factors that affect CCN estimations is essential to improve the CCN data coverage worldwide and assess aerosol–cloud interactions on a global scale. This is crucial for improving climate models, since aerosol–cloud interactions are the most important source of uncertainty in climate projections.
Wenyue Wang, Klemens Hocke, Leonardo Nania, Alberto Cazorla, Gloria Titos, Renaud Matthey, Lucas Alados-Arboledas, Agustín Millares, and Francisco Navas-Guzmán
Atmos. Chem. Phys., 24, 1571–1585, https://doi.org/10.5194/acp-24-1571-2024, https://doi.org/10.5194/acp-24-1571-2024, 2024
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The south-central interior of Andalusia experiences complex precipitation patterns as a result of the semi-arid Mediterranean climate and the influence of Saharan dust. This study monitored the inter-relations between aerosols, clouds, meteorological variables, and precipitation systems using ground-based remote sensing and in situ instruments.
Juan Andrés Casquero-Vera, Daniel Pérez-Ramírez, Hassan Lyamani, Fernando Rejano, Andrea Casans, Gloria Titos, Francisco José Olmo, Lubna Dada, Simo Hakala, Tareq Hussein, Katrianne Lehtipalo, Pauli Paasonen, Antti Hyvärinen, Noemí Pérez, Xavier Querol, Sergio Rodríguez, Nikos Kalivitis, Yenny González, Mansour A. Alghamdi, Veli-Matti Kerminen, Andrés Alastuey, Tuukka Petäjä, and Lucas Alados-Arboledas
Atmos. Chem. Phys., 23, 15795–15814, https://doi.org/10.5194/acp-23-15795-2023, https://doi.org/10.5194/acp-23-15795-2023, 2023
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Here we present the first study of the effect of mineral dust on the inhibition/promotion of new particle formation (NPF) events in different dust-influenced areas. Unexpectedly, we show that the occurrence of NPF events is highly frequent during mineral dust outbreaks, occurring even during extreme dust outbreaks. We also show that the occurrence of NPF events during mineral dust outbreaks significantly affects the potential cloud condensation nuclei budget.
Alexandra Tsekeri, Anna Gialitaki, Marco Di Paolantonio, Davide Dionisi, Gian Luigi Liberti, Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk, Daniel Pérez-Ramírez, Maria J. Granados Muñoz, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Diego Bermejo Pantaleón, Juan Antonio Bravo-Aranda, Anna Kampouri, Eleni Marinou, Vassilis Amiridis, Michael Sicard, Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Salvatore Romano, Maria Rita Perrone, Xiaoxia Shang, Mika Komppula, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Diofantos Hadjimitsis, Francisco Navas-Guzmán, Alexander Haefele, Dominika Szczepanik, Artur Tomczak, Iwona S. Stachlewska, Livio Belegante, Doina Nicolae, Kalliopi Artemis Voudouri, Dimitris Balis, Athena A. Floutsi, Holger Baars, Linda Miladi, Nicolas Pascal, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 16, 6025–6050, https://doi.org/10.5194/amt-16-6025-2023, https://doi.org/10.5194/amt-16-6025-2023, 2023
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EARLINET/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. The work presented herein focuses on deriving a common methodology for applying a synergistic retrieval that utilizes the network's ground-based passive and active remote sensing measurements and deriving the aerosols from anthropogenic activities over Europe.
Jesús Abril-Gago, Pablo Ortiz-Amezcua, Diego Bermejo-Pantaleón, Juana Andújar-Maqueda, Juan Antonio Bravo-Aranda, María José Granados-Muñoz, Francisco Navas-Guzmán, Lucas Alados-Arboledas, Inmaculada Foyo-Moreno, and Juan Luis Guerrero-Rascado
Atmos. Chem. Phys., 23, 8453–8471, https://doi.org/10.5194/acp-23-8453-2023, https://doi.org/10.5194/acp-23-8453-2023, 2023
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Validation activities of Aeolus wind products were performed in Granada with different upward-probing instrumentation (Doppler lidar system and radiosondes) and spatiotemporal collocation criteria. Specific advantages and disadvantages of each instrument were identified, and an optimal comparison criterion is proposed. Aeolus was proven to provide reliable wind products, and the upward-probing instruments were proven to be useful for Aeolus wind product validation activities.
Konstantinos Michailidis, Maria-Elissavet Koukouli, Dimitris Balis, J. Pepijn Veefkind, Martin de Graaf, Lucia Mona, Nikolaos Papagianopoulos, Gesolmina Pappalardo, Ioanna Tsikoudi, Vassilis Amiridis, Eleni Marinou, Anna Gialitaki, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Daniele Bortoli, Maria João Costa, Vanda Salgueiro, Alexandros Papayannis, Maria Mylonaki, Lucas Alados-Arboledas, Salvatore Romano, Maria Rita Perrone, and Holger Baars
Atmos. Chem. Phys., 23, 1919–1940, https://doi.org/10.5194/acp-23-1919-2023, https://doi.org/10.5194/acp-23-1919-2023, 2023
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Comparisons with ground-based correlative lidar measurements constitute a key component in the validation of satellite aerosol products. This paper presents the validation of the TROPOMI aerosol layer height (ALH) product, using archived quality assured ground-based data from lidar stations that belong to the EARLINET network. Comparisons between the TROPOMI ALH and co-located EARLINET measurements show good agreement over the ocean.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
María Ángeles López-Cayuela, Carmen Córdoba-Jabonero, Diego Bermejo-Pantaleón, Michaël Sicard, Vanda Salgueiro, Francisco Molero, Clara Violeta Carvajal-Pérez, María José Granados-Muñoz, Adolfo Comerón, Flavio T. Couto, Rubén Barragán, María-Paz Zorzano, Juan Antonio Bravo-Aranda, Constantino Muñoz-Porcar, María João Costa, Begoña Artíñano, Alejandro Rodríguez-Gómez, Daniele Bortoli, Manuel Pujadas, Jesús Abril-Gago, Lucas Alados-Arboledas, and Juan Luis Guerrero-Rascado
Atmos. Chem. Phys., 23, 143–161, https://doi.org/10.5194/acp-23-143-2023, https://doi.org/10.5194/acp-23-143-2023, 2023
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An intense Saharan dust outbreak crossing the Iberian Peninsula in springtime was monitored to determinine the specific contribution of fine and coarse dust particles at five lidar stations, strategically covering its SW–central–NE pathway. Expected dust ageing along the transport started unappreciated. A different fine-dust impact on optical (~30 %) and mass (~10 %) properties was found. Use of polarized lidar measurements (mainly in elastic systems) for fine/coarse dust separation is crucial.
Rohaifa Khaldi, Domingo Alcaraz-Segura, Emilio Guirado, Yassir Benhammou, Abdellatif El Afia, Francisco Herrera, and Siham Tabik
Earth Syst. Sci. Data, 14, 1377–1411, https://doi.org/10.5194/essd-14-1377-2022, https://doi.org/10.5194/essd-14-1377-2022, 2022
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This dataset with millions of 22-year time series for seven spectral bands was built by merging Terra and Aqua satellite data and annotated for 29 LULC classes by spatial–temporal agreement across 15 global LULC products. The mean F1 score was 96 % at the coarsest classification level and 87 % at the finest one. The dataset is born to develop and evaluate machine learning models to perform global LULC mapping given the disagreement between current global LULC products.
Jesús Abril-Gago, Juan Luis Guerrero-Rascado, Maria João Costa, Juan Antonio Bravo-Aranda, Michaël Sicard, Diego Bermejo-Pantaleón, Daniele Bortoli, María José Granados-Muñoz, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Adolfo Comerón, Pablo Ortiz-Amezcua, Vanda Salgueiro, Marta María Jiménez-Martín, and Lucas Alados-Arboledas
Atmos. Chem. Phys., 22, 1425–1451, https://doi.org/10.5194/acp-22-1425-2022, https://doi.org/10.5194/acp-22-1425-2022, 2022
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A validation of Aeolus reprocessed optical products is carried out via an intercomparison with ground-based measurements taken at several ACTRIS/EARLINET stations in western Europe. Case studies and a statistical analysis are presented. The stations are located in a hot spot between Africa and the rest of Europe, which guarantees a variety of aerosol types, from mineral dust layers to continental/anthropogenic aerosol, and allows us to test Aeolus performance under different scenarios.
Mariana Adam, Iwona S. Stachlewska, Lucia Mona, Nikolaos Papagiannopoulos, Juan Antonio Bravo-Aranda, Michaël Sicard, Doina N. Nicolae, Livio Belegante, Lucja Janicka, Dominika Szczepanik, Maria Mylonaki, Christina-Anna Papanikolaou, Nikolaos Siomos, Kalliopi Artemis Voudouri, Luca Alados-Arboledas, Arnoud Apituley, Ina Mattis, Anatoli Chaikovsky, Constantino Muñoz-Porcar, Aleksander Pietruczuk, Daniele Bortoli, Holger Baars, Ivan Grigorov, and Zahary Peshev
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-759, https://doi.org/10.5194/acp-2021-759, 2021
Revised manuscript not accepted
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Results over 10 years of biomass burning events measured by EARLINET are analysed by means of the intensive parameters, based on the methodology described in Part I. Smoke type is characterized for each of the four geographical regions based on continental smoke origin. Relationships between intensive parameters or colour ratios are shown. The smoke is labelled in average as aged smoke.
Gloria Titos, María A. Burgos, Paul Zieger, Lucas Alados-Arboledas, Urs Baltensperger, Anne Jefferson, James Sherman, Ernest Weingartner, Bas Henzing, Krista Luoma, Colin O'Dowd, Alfred Wiedensohler, and Elisabeth Andrews
Atmos. Chem. Phys., 21, 13031–13050, https://doi.org/10.5194/acp-21-13031-2021, https://doi.org/10.5194/acp-21-13031-2021, 2021
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This paper investigates the impact of water uptake on aerosol optical properties, in particular the aerosol light-scattering coefficient. Although in situ measurements are performed at low relative humidity (typically at
RH < 40 %), to address the climatic impact of aerosol particles it is necessary to take into account the effect that water uptake may have on the aerosol optical properties.
Jose Antonio Benavent-Oltra, Juan Andrés Casquero-Vera, Roberto Román, Hassan Lyamani, Daniel Pérez-Ramírez, María José Granados-Muñoz, Milagros Herrera, Alberto Cazorla, Gloria Titos, Pablo Ortiz-Amezcua, Andrés Esteban Bedoya-Velásquez, Gregori de Arruda Moreira, Noemí Pérez, Andrés Alastuey, Oleg Dubovik, Juan Luis Guerrero-Rascado, Francisco José Olmo-Reyes, and Lucas Alados-Arboledas
Atmos. Chem. Phys., 21, 9269–9287, https://doi.org/10.5194/acp-21-9269-2021, https://doi.org/10.5194/acp-21-9269-2021, 2021
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In this paper, we use the GRASP algorithm combining different remote sensing measurements to obtain the aerosol vertical and column properties during the SLOPE I and II campaigns. We show an overview of aerosol properties retrieved by GRASP during these campaigns and evaluate the retrievals of aerosol properties using the in situ measurements performed at a high-altitude station and airborne flights. For the first time we present an evaluation of the absorption coefficient by GRASP.
Nikolaos Evangeliou, Stephen M. Platt, Sabine Eckhardt, Cathrine Lund Myhre, Paolo Laj, Lucas Alados-Arboledas, John Backman, Benjamin T. Brem, Markus Fiebig, Harald Flentje, Angela Marinoni, Marco Pandolfi, Jesus Yus-Dìez, Natalia Prats, Jean P. Putaud, Karine Sellegri, Mar Sorribas, Konstantinos Eleftheriadis, Stergios Vratolis, Alfred Wiedensohler, and Andreas Stohl
Atmos. Chem. Phys., 21, 2675–2692, https://doi.org/10.5194/acp-21-2675-2021, https://doi.org/10.5194/acp-21-2675-2021, 2021
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Following the transmission of SARS-CoV-2 to Europe, social distancing rules were introduced to prevent further spread. We investigate the impacts of the European lockdowns on black carbon (BC) emissions by means of in situ observations and inverse modelling. BC emissions declined by 23 kt in Europe during the lockdowns as compared with previous years and by 11 % as compared to the period prior to lockdowns. Residential combustion prevailed in Eastern Europe, as confirmed by remote sensing data.
Ourania Soupiona, Alexandros Papayannis, Panagiotis Kokkalis, Romanos Foskinis, Guadalupe Sánchez Hernández, Pablo Ortiz-Amezcua, Maria Mylonaki, Christina-Anna Papanikolaou, Nikolaos Papagiannopoulos, Stefanos Samaras, Silke Groß, Rodanthi-Elisavet Mamouri, Lucas Alados-Arboledas, Aldo Amodeo, and Basil Psiloglou
Atmos. Chem. Phys., 20, 15147–15166, https://doi.org/10.5194/acp-20-15147-2020, https://doi.org/10.5194/acp-20-15147-2020, 2020
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51 dust events over the Mediterranean from EARLINET were studied regarding the aerosol geometrical, optical and microphysical properties and radiative forcing. We found δp532 values of 0.24–0.28, LR532 values of 49–52 sr and AOT532 of 0.11–0.40. The aerosol mixing state was also examined. Depending on the dust properties, intensity and solar zenith angle, the estimated solar radiative forcing ranged from −59 to −22 W m−2 at the surface and from −24 to −1 W m−2 at the TOA (cooling effect).
Juan Andrés Casquero-Vera, Hassan Lyamani, Lubna Dada, Simo Hakala, Pauli Paasonen, Roberto Román, Roberto Fraile, Tuukka Petäjä, Francisco José Olmo-Reyes, and Lucas Alados-Arboledas
Atmos. Chem. Phys., 20, 14253–14271, https://doi.org/10.5194/acp-20-14253-2020, https://doi.org/10.5194/acp-20-14253-2020, 2020
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New particle formation was investigated at two stations located close to each other but at different altitudes: urban and high-altitude sites. Results show that sulfuric acid is able to explain a minimal fraction contribution to the observed growth rates and point to the availability of volatile organic compounds as the main factor controlling NPF events at both sites. A closer analysis of the NPF events that were observed at high-altitude sites during a Saharan dust episode was carried out.
Roberto Román, Ramiro González, Carlos Toledano, África Barreto, Daniel Pérez-Ramírez, Jose A. Benavent-Oltra, Francisco J. Olmo, Victoria E. Cachorro, Lucas Alados-Arboledas, and Ángel M. de Frutos
Atmos. Meas. Tech., 13, 6293–6310, https://doi.org/10.5194/amt-13-6293-2020, https://doi.org/10.5194/amt-13-6293-2020, 2020
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Atmospheric-aerosol and gaseous properties can be derived at night-time if the lunar irradiance at the ground is measured. To this end, the knowledge of lunar irradiance at the top of the atmosphere is necessary. This extraterrestrial lunar irradiance is usually calculated by models since it varies with several geometric factors mainly depending on time and location. This paper proposes a correction to the most used lunar-irradiance model to be applied for atmospheric-aerosol characterization.
Cited articles
Alabadla, M., Sidi, F., Ishak, I., Ibrahim, H., Affendey, L. S., Che Ani, Z., Jabar, M. A., Bukar, U. A., Devaraj, N. K., Muda, A. S., Tharek, A., Omar, N., and Jaya, M. I. M.: Systematic Review of Using Machine Learning in Imputing Missing Values, IEEE Access, 10, 44483–44502, https://doi.org/10.1109/access.2022.3160841, 2022.
Alados-Arboledas, L. and Guerrero-Rascado, J. L. ACTRIS-EARLINET 2024 aerosol optical property profiles over GRA Granada – Spain (Version 1), ACTRIS-ARES Data Centre [data set], https://doi.org/10.57837/CNR-IMAA/ARES/ACTRIS-EARLINET/2024/GRA/AEROSOL_OPTICAL_PROPERTY_ PROFILES, 2024.
Alados-Arboledas, L., Müller, D., Guerrero-Rascado, J. L., Navas-Guzmán, F., Pérez-Ramírez, D., and Olmo, F. J.: Optical and microphysical properties of fresh biomass burning aerosol retrieved by Raman lidar, and star-and sun-photometry, Geophys. Res. Lett., 38, https://doi.org/10.1029/2010gl045999, 2011.
Baars, H., Seifert, P., Engelmann, R., and Wandinger, U.: Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements, Atmos. Meas. Tech., 10, 3175–3201, https://doi.org/10.5194/amt-10-3175-2017, 2017.
Belegante, L., Nicolae, D., Nemuc, A., Talianu, C., and Derognat, C.: Retrieval of the boundary layer height from active and passive remote sensors, Comparison with a NWP model, Acta Geophys., 62, 276–289, https://doi.org/10.2478/s11600-013-0167-4, 2014.
Belegante, L., Bravo-Aranda, J. A., Freudenthaler, V., Nicolae, D., Nemuc, A., Ene, D., Alados-Arboledas, L., Amodeo, A., Pappalardo, G., D'Amico, G., Amato, F., Engelmann, R., Baars, H., Wandinger, U., Papayannis, A., Kokkalis, P., and Pereira, S. N.: Experimental techniques for the calibration of lidar depolarization channels in EARLINET, Atmos. Meas. Tech., 11, 1119–1141, https://doi.org/10.5194/amt-11-1119-2018, 2018.
Benavent-Oltra, J. A., Román, R., Casquero-Vera, J. A., Pérez-Ramírez, D., Lyamani, H., Ortiz-Amezcua, P., Bedoya-Velásquez, A. E., de Arruda Moreira, G., Barreto, Á., Lopatin, A., Fuertes, D., Herrera, M., Torres, B., Dubovik, O., Guerrero-Rascado, J. L., Goloub, P., Olmo-Reyes, F. J., and Alados-Arboledas, L.: Different strategies to retrieve aerosol properties at night-time with the GRASP algorithm, Atmos. Chem. Phys., 19, 14149–14171, https://doi.org/10.5194/acp-19-14149-2019, 2019.
Benavent-Oltra, J. A., Casquero-Vera, J. A., Román, R., Lyamani, H., Pérez-Ramírez, D., Granados-Muñoz, M. J., Herrera, M., Cazorla, A., Titos, G., Ortiz-Amezcua, P., Bedoya-Velásquez, A. E., de Arruda Moreira, G., Pérez, N., Alastuey, A., Dubovik, O., Guerrero-Rascado, J. L., Olmo-Reyes, F. J., and Alados-Arboledas, L.: Overview of the SLOPE I and II campaigns: aerosol properties retrieved with lidar and sun–sky photometer measurements, Atmos. Chem. Phys., 21, 9269–9287, https://doi.org/10.5194/acp-21-9269-2021, 2021.
Bravo-Aranda, J. A., Belegante, L., Freudenthaler, V., Alados-Arboledas, L., Nicolae, D., Granados-Muñoz, M. J., Guerrero-Rascado, J. L., Amodeo, A., D'Amico, G., Engelmann, R., Pappalardo, G., Kokkalis, P., Mamouri, R., Papayannis, A., Navas-Guzmán, F., Olmo, F. J., Wandinger, U., Amato, F., and Haeffelin, M.: Assessment of lidar depolarization uncertainty by means of a polarimetric lidar simulator, Atmos. Meas. Tech., 9, 4935–4953, https://doi.org/10.5194/amt-9-4935-2016, 2016.
Breiman, L.: Random Forests, Machine Learning, 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Breiman, L. and Spector, P.: Submodel Selection and Evaluation in Regression. The X-Random Case, International Statistical Review/Revue Internationale de Statistique, 60, 291, https://doi.org/10.2307/1403680, 1992.
Cazorla, A., Casquero-Vera, J. A., Román, R., Guerrero-Rascado, J. L., Toledano, C., Cachorro, V. E., Orza, J. A. G., Cancillo, M. L., Serrano, A., Titos, G., Pandolfi, M., Alastuey, A., Hanrieder, N., and Alados-Arboledas, L.: Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula, Atmos. Chem. Phys., 17, 11861–11876, https://doi.org/10.5194/acp-17-11861-2017, 2017.
Chen, T. and Guestrin, C.: XGBoost, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, https://doi.org/10.1145/2939672.2939785, 2016.
Chen, B., Ye, Q., Zhou, X., Song, Z., and Ren, Y.: Aerosol classification under non-clear sky conditions based on geostationary satellite FY-4A and machine learning models, Atmospheric Environment, 339, 120891, https://doi.org/10.1016/j.atmosenv.2024.120891, 2024.
Córdoba-Jabonero, C., Sicard, M., Ansmann, A., del Águila, A., and Baars, H.: Separation of the optical and mass features of particle components in different aerosol mixtures by using POLIPHON retrievals in synergy with continuous polarized Micro-Pulse Lidar (P-MPL) measurements, Atmos. Meas. Tech., 11, 4775–4795, https://doi.org/10.5194/amt-11-4775-2018, 2018.
del Águila, A., Sorribas, M., Lyamani, H., Titos, G., Olmo, F. J., Arruda-Moreira, G., Yela, M., and Alados-Arboledas, L.: Sources and physicochemical characteristics of submicron aerosols during three intensive campaigns in Granada (Spain), Atmospheric Research, 213, 398–410, https://doi.org/10.1016/j.atmosres.2018.06.004, 2018.
del Águila, A., Efremenko, D. S., and Trautmann, T.: A Review of Dimensionality Reduction Techniques for Processing Hyper-Spectral Optical Signal, Light & Engineering, 85–98, https://doi.org/10.33383/2019-017, 2019.
del Águila, A., Alcaraz-Segura, D., Martínez-López, J., Postma, T., Alados-Arboledas, L., Zamora, R., and Navas-Guzmán, F.: Two decades of high-resolution aerosol product over the Sierra Nevada Mountain region (SE Spain): Spatio-temporal distribution and impact on ecosystems, Atmospheric Research, 308, 107515, https://doi.org/10.1016/j.atmosres.2024.107515, 2024.
del Águila, A., Ortiz-Amezcua, P., and Alados-Arboledas, L.: Manually Labelled Aerosol Typing from the Multiwavelength Raman Lidar MULHACEN at ACTRIS/EARLINET UGR Station for Machine Learning Applications, Zenodo [data set], https://doi.org/10.5281/zenodo.16925786, 2025.
Floutsi, A. A., Baars, H., Engelmann, R., Althausen, D., Ansmann, A., Bohlmann, S., Heese, B., Hofer, J., Kanitz, T., Haarig, M., Ohneiser, K., Radenz, M., Seifert, P., Skupin, A., Yin, Z., Abdullaev, S. F., Komppula, M., Filioglou, M., Giannakaki, E., Stachlewska, I. S., Janicka, L., Bortoli, D., Marinou, E., Amiridis, V., Gialitaki, A., Mamouri, R.-E., Barja, B., and Wandinger, U.: DeLiAn – a growing collection of depolarization ratio, lidar ratio and Ångström exponent for different aerosol types and mixtures from ground-based lidar observations, Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, 2023.
Floutsi, A. A., Baars, H., and Wandinger, U.: HETEAC-Flex: an optimal estimation method for aerosol typing based on lidar-derived intensive optical properties, Atmos. Meas. Tech., 17, 693–714, https://doi.org/10.5194/amt-17-693-2024, 2024.
Freudenthaler, V.: About the effects of polarising optics on lidar signals and the Δ90 calibration, Atmos. Meas. Tech., 9, 4181–4255, https://doi.org/10.5194/amt-9-4181-2016, 2016.
Granados-Muñoz, M. J., Navas-Guzmán, F., Bravo-Aranda, J. A., Guerrero-Rascado, J. L., Lyamani, H., Fernández-Gálvez, J., and Alados-Arboledas, L.: Automatic determination of the planetary boundary layer height using lidar: One-year analysis over southeastern Spain, J. Geophys. Res., 117, https://doi.org/10.1029/2012jd017524, 2012.
Groß, S., Esselborn, M., Weinzierl, B., Wirth, M., Fix, A., and Petzold, A.: Aerosol classification by airborne high spectral resolution lidar observations, Atmos. Chem. Phys., 13, 2487–2505, https://doi.org/10.5194/acp-13-2487-2013, 2013.
Groß, S., Freudenthaler, V., Wirth, M., and Weinzierl, B.: Towards an aerosol classification scheme for future EarthCARE lidar observations and implications for research needs, Atmospheric Science Letters, 16, 77–82, https://doi.org/10.1002/asl2.524, 2014.
Guerrero-Rascado, J. L., Ruiz, B., and Alados-Arboledas, L.: Multi-spectral Lidar characterization of the vertical structure of Saharan dust aerosol over southern Spain, Atmospheric Environment, 42, 2668–2681, https://doi.org/10.1016/j.atmosenv.2007.12.062, 2008.
Guerrero-Rascado, J. L., Olmo, F. J., Avilés-Rodríguez, I., Navas-Guzmán, F., Pérez-Ramírez, D., Lyamani, H., and Alados Arboledas, L.: Extreme Saharan dust event over the southern Iberian Peninsula in september 2007: active and passive remote sensing from surface and satellite, Atmos. Chem. Phys., 9, 8453–8469, https://doi.org/10.5194/acp-9-8453-2009, 2009.
Illingworth, A. J., Barker, H. W., Beljaars, A., Ceccaldi, M., Chepfer, H., Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., Donovan, D. P., Fukuda, S., Hirakata, M., Hogan, R. J., Huenerbein, A., Kollias, P., Kubota, T., Nakajima, T., Nakajima, T. Y., Nishizawa, T., Ohno, Y., Okamoto, H., Oki, R., Sato, K., Satoh, M., Shephard, M. W., Velázquez-Blázquez, A., Wandinger, U., Wehr, T., and van Zadelhoff, G.-J.: The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation, Bulletin of the American Meteorological Society, 96, 1311–1332, https://doi.org/10.1175/bams-d-12-00227.1, 2015.
IPCC: Climate Change 2023: Synthesis Report, Contribution of Working Groups I, II and III to the Sixth 742 Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Core Writing Team, Lee, H. and Romero, J., IPCC, Geneva, Switzerland, 35–115, https://doi.org/10.59327/IPCC/AR6-9789291691647, 2023.
Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q., and Liu, T.-Y.: Lightgbm: A highly efficient gradient boosting decision tree, Advances in Neural Information Processing Systems, 30, 3146–3154, 2017.
Kim, M.-H., Omar, A. H., Tackett, J. L., Vaughan, M. A., Winker, D. M., Trepte, C. R., Hu, Y., Liu, Z., Poole, L. R., Pitts, M. C., Kar, J., and Magill, B. E.: The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm, Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, 2018.
Kohavi, R.: A study of cross-validation and bootstrap for accuracy estimation and model selection, Proc. 14th Int. Joint Conf. on Artificial Intelligence (IJCAI), Montréal, Canada, 1137–1143, https://www.ijcai.org/Proceedings/95-2/Papers/016.pdf (last access: 28 May 2025), 1995.
Laj, P., Lund Myhre, C., Riffault, V., Amiridis, V., Fuchs, H., Eleftheriadis, K., Petäjä, T., Salameh, T., Kivekäs, N., Juurola, E., Saponaro, G., Philippin, S., Cornacchia, C., Alados Arboledas, L., Baars, H., Claude, A., De Mazière, M., Dils, B., Dufresne, M., Evangeliou, N., Favez, O., Fiebig, M., Haeffelin, M., Herrmann, H., Höhler, K., Illmann, N., Kreuter, A., Ludewig, E., Marinou, E., Möhler, O., Mona, L., Eder Murberg, L., Nicolae, D., Novelli, A., O'Connor, E., Ohneiser, K., Petracca Altieri, R. M., Picquet-Varrault, B., van Pinxteren, D., Pospichal, B., Putaud, J.-P., Reimann, S., Siomos, N., Stachlewska, I., Tillmann, R., Voudouri, K. A., Wandinger, U., Wiedensohler, A., Apituley, A., Comerón, A., Gysel-Beer, M., Mihalopoulos, N., Nikolova, N., Pietruczuk, A., Sauvage, S., Sciare, J., Skov, H., Svendby, T., Swietlicki, E., Tonev, D., Vaughan, G., Zdimal, V., Baltensperger, U., Doussin, J.-F., Kulmala, M., Pappalardo, G., Sorvari Sundet, S., and Vana, M.: Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS): The European Research Infrastructure Supporting Atmospheric Science, Bulletin of the American Meteorological Society, 105, E1098–E1136, https://doi.org/10.1175/bams-d-23-0064.1, 2024.
Li, W., Sun, J., Xu, L., Shi, Z., Riemer, N., Sun, Y., Fu, P., Zhang, J., Lin, Y., Wang, X., Shao, L., Chen, J., Zhang, X., Wang, Z., and Wang, W.: A conceptual framework for mixing structures in individual aerosol particles, J. Geophys. Res.-Atmos., 121, https://doi.org/10.1002/2016jd025252, 2016.
Li, Z., Liu, F., Yang, W., Peng, S., and Zhou, J.: A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects, IEEE Trans. Neural Netw. Learning Syst., 33, 6999–7019, https://doi.org/10.1109/tnnls.2021.3084827, 2022.
López-Cayuela, M. Á., Córdoba-Jabonero, C., Bermejo-Pantaleón, D., Sicard, M., Salgueiro, V., Molero, F., Carvajal-Pérez, C. V., Granados-Muñoz, M. J., Comerón, A., Couto, F. T., Barragán, R., Zorzano, M.-P., Bravo-Aranda, J. A., Muñoz-Porcar, C., Costa, M. J., Artíñano, B., Rodríguez-Gómez, A., Bortoli, D., Pujadas, M., Abril-Gago, J., Alados-Arboledas, L., and Guerrero-Rascado, J. L.: Vertical characterization of fine and coarse dust particles during an intense Saharan dust outbreak over the Iberian Peninsula in springtime 2021, Atmos. Chem. Phys., 23, 143–161, https://doi.org/10.5194/acp-23-143-2023, 2023.
Lundberg, S. and Lee, S.-I.: A Unified Approach to Interpreting Model Predictions, arXiv [preprint], https://doi.org/10.48550/ARXIV.1705.07874, 2017.
Lynch, P., Reid, J. S., Westphal, D. L., Zhang, J., Hogan, T. F., Hyer, E. J., Curtis, C. A., Hegg, D. A., Shi, Y., Campbell, J. R., Rubin, J. I., Sessions, W. R., Turk, F. J., and Walker, A. L.: An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences, Geosci. Model Dev., 9, 1489–1522, https://doi.org/10.5194/gmd-9-1489-2016, 2016.
Matus, A. V., L'Ecuyer, T. S., and Henderson, D. S.: New Estimates of Aerosol Direct Radiative Effects and Forcing From A-Train Satellite Observations, Geophysical Research Letters, 46, 8338–8346, https://doi.org/10.1029/2019gl083656, 2019.
Mylonaki, M., Giannakaki, E., Papayannis, A., Papanikolaou, C.-A., Komppula, M., Nicolae, D., Papagiannopoulos, N., Amodeo, A., Baars, H., and Soupiona, O.: Aerosol type classification analysis using EARLINET multiwavelength and depolarization lidar observations, Atmos. Chem. Phys., 21, 2211–2227, https://doi.org/10.5194/acp-21-2211-2021, 2021.
Navas-Guzmán, F., Bravo-Aranda, J. A., Guerrero-Rascado, J. L., Granados-Muñoz, M. J., and Alados-Arboledas, L.: Statistical analysis of aerosol optical properties retrieved by Raman lidar over Southeastern Spain, Tellus B: Chemical and Physical Meteorology, 65, 21234, https://doi.org/10.3402/tellusb.v65i0.21234, 2013.
Nicolae, D., Vasilescu, J., Talianu, C., and Dandocsi, A.: Independent Retrieval of Aerosol Type From Lidar, edited by: Gross, B., Moshary, F., and Arend, M., EPJ Web of Conferences, 119, 18002, https://doi.org/10.1051/epjconf/201611918002, 2016.
Nicolae, D., Vasilescu, J., Talianu, C., Binietoglou, I., Nicolae, V., Andrei, S., and Antonescu, B.: A neural network aerosol-typing algorithm based on lidar data, Atmos. Chem. Phys., 18, 14511–14537, https://doi.org/10.5194/acp-18-14511-2018, 2018.
Ortiz-Amezcua, P., Guerrero-Rascado, J. L., Granados-Muñoz, M. J., Benavent-Oltra, J. A., Böckmann, C., Samaras, S., Stachlewska, I. S., Janicka, Ł., Baars, H., Bohlmann, S., and Alados-Arboledas, L.: Microphysical characterization of long-range transported biomass burning particles from North America at three EARLINET stations, Atmos. Chem. Phys., 17, 5931–5946, https://doi.org/10.5194/acp-17-5931-2017, 2017.
Papagiannopoulos, N., Mona, L., Amodeo, A., D'Amico, G., Gumà Claramunt, P., Pappalardo, G., Alados-Arboledas, L., Guerrero-Rascado, J. L., Amiridis, V., Kokkalis, P., Apituley, A., Baars, H., Schwarz, A., Wandinger, U., Binietoglou, I., Nicolae, D., Bortoli, D., Comerón, A., Rodríguez-Gómez, A., Sicard, M., Papayannis, A., and Wiegner, M.: An automatic observation-based aerosol typing method for EARLINET, Atmos. Chem. Phys., 18, 15879–15901, https://doi.org/10.5194/acp-18-15879-2018, 2018.
Pappalardo, G., Amodeo, A., Apituley, A., Comeron, A., Freudenthaler, V., Linné, H., Ansmann, A., Bösenberg, J., D'Amico, G., Mattis, I., Mona, L., Wandinger, U., Amiridis, V., Alados-Arboledas, L., Nicolae, D., and Wiegner, M.: EARLINET: towards an advanced sustainable European aerosol lidar network, Atmos. Meas. Tech., 7, 2389–2409, https://doi.org/10.5194/amt-7-2389-2014, 2014.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, É.: Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research, 12, 2825–2830, http://jmlr.org/papers/v12/pedregosa11a.html (last access: 20 January 2025), 2011.
Philippus, D., Sytsma, A., Rust, A., and Hogue, T. S.: A machine learning model for estimating the temperature of small rivers using satellite-based spatial data, Remote Sensing of Environment, 311, 114271, https://doi.org/10.1016/j.rse.2024.114271, 2024.
Quinlan, J. R.: Induction of decision trees, Mach. Learn., 1, 81–106, https://doi.org/10.1007/bf00116251, 1986.
scikit-learn developers: GroupKFold, https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GroupKFold.html (last access: 15 May 2025), 2025a.
scikit-learn developers: GroupShuffleSplit, https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GroupShuffleSplit.html (last access: 15 May 2025), 2025b.
Soupiona, O., Samaras, S., Ortiz-Amezcua, P., Böckmann, C., Papayannis, A., Moreira, G. A., Benavent-Oltra, J. A., Guerrero-Rascado, J. L., Bedoya-Velásquez, A. E., Olmo, F. J., Román, R., Kokkalis, P., Mylonaki, M., Alados-Arboledas, L., Papanikolaou, C. A., and Foskinis, R.: Retrieval of optical and microphysical properties of transported Saharan dust over Athens and Granada based on multi-wavelength Raman lidar measurements: Study of the mixing processes, Atmospheric Environment, 214, 116824, https://doi.org/10.1016/j.atmosenv.2019.116824, 2019.
Soupiona, O., Papayannis, A., Kokkalis, P., Foskinis, R., Sánchez Hernández, G., Ortiz-Amezcua, P., Mylonaki, M., Papanikolaou, C.-A., Papagiannopoulos, N., Samaras, S., Groß, S., Mamouri, R.-E., Alados-Arboledas, L., Amodeo, A., and Psiloglou, B.: EARLINET observations of Saharan dust intrusions over the northern Mediterranean region (2014–2017): properties and impact on radiative forcing, Atmos. Chem. Phys., 20, 15147–15166, https://doi.org/10.5194/acp-20-15147-2020, 2020.
Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D., and Ngan, F.: NOAA's HYSPLIT Atmospheric Transport and Dispersion Modeling System, Bulletin of the American Meteorological Society, 96, 2059–2077, https://doi.org/10.1175/bams-d-14-00110.1, 2015.
Titos, G., del Águila, A., Cazorla, A., Lyamani, H., Casquero-Vera, J. A., Colombi, C., Cuccia, E., Gianelle, V., Močnik, G., Alastuey, A., Olmo, F. J., and Alados-Arboledas, L.: Spatial and temporal variability of carbonaceous aerosols: Assessing the impact of biomass burning in the urban environment, Science of The Total Environment, 578, 613–625, https://doi.org/10.1016/j.scitotenv.2016.11.007, 2017.
Voudouri, K. A., Siomos, N., Michailidis, K., Papagiannopoulos, N., Mona, L., Cornacchia, C., Nicolae, D., and Balis, D.: Comparison of two automated aerosol typing methods and their application to an EARLINET station, Atmos. Chem. Phys., 19, 10961–10980, https://doi.org/10.5194/acp-19-10961-2019, 2019.
Wehr, T., Kubota, T., Tzeremes, G., Wallace, K., Nakatsuka, H., Ohno, Y., Koopman, R., Rusli, S., Kikuchi, M., Eisinger, M., Tanaka, T., Taga, M., Deghaye, P., Tomita, E., and Bernaerts, D.: The EarthCARE mission – science and system overview, Atmos. Meas. Tech., 16, 3581–3608, https://doi.org/10.5194/amt-16-3581-2023, 2023.
Zhou, Z.-H.: A brief introduction to weakly supervised learning, National Science Review, 5, 44–53, https://doi.org/10.1093/nsr/nwx106, 2018.
Short summary
This study applies machine learning (ML) techniques to classify aerosols using high-resolution multiwavelength lidar data from EARLINET network. We developed a reference dataset and evaluated six ML models, with LightGBM achieving over 90 % accuracy. Depolarization data proved critical for improving dust classification. Validated against independent datasets, our approach improves aerosol classification and may help refine lidar-based processing strategies.
This study applies machine learning (ML) techniques to classify aerosols using high-resolution...
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