Articles | Volume 15, issue 24
https://doi.org/10.5194/amt-15-7195-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-7195-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Dec 2022
Research article |
| 14 Dec 2022
| 14 Dec 2022
Volcanic cloud detection using Sentinel-3 satellite data by means of neural networks: the Raikoke 2019 eruption test case
Ilaria Petracca
CORRESPONDING AUTHOR
Department of Civil Engineering and Computer Science Engineering,
Tor Vergata University of Rome, 00133 Rome, Italy
Davide De Santis
Department of Civil Engineering and Computer Science Engineering,
Tor Vergata University of Rome, 00133 Rome, Italy
Matteo Picchiani
GEO-K s.r.l., 00133 Rome, Italy
GMATICS s.r.l., 00173 Rome, Italy
Stefano Corradini
Istituto Nazionale di Geofisica e Vulcanologia, ONT, 00143 Rome,
Italy
Lorenzo Guerrieri
Istituto Nazionale di Geofisica e Vulcanologia, ONT, 00143 Rome,
Italy
Fred Prata
AIRES Pty. Ltd., Mount Eliza, Victoria 3930, Australia
Luca Merucci
Istituto Nazionale di Geofisica e Vulcanologia, ONT, 00143 Rome,
Italy
Dario Stelitano
Istituto Nazionale di Geofisica e Vulcanologia, ONT, 00143 Rome,
Italy
Fabio Del Frate
Department of Civil Engineering and Computer Science Engineering,
Tor Vergata University of Rome, 00133 Rome, Italy
Giorgia Salvucci
Department of Civil Engineering and Computer Science Engineering,
Tor Vergata University of Rome, 00133 Rome, Italy
Giovanni Schiavon
Department of Civil Engineering and Computer Science Engineering,
Tor Vergata University of Rome, 00133 Rome, Italy
Related authors
No articles found.
Fred Prata
Atmos. Meas. Tech., 17, 3751–3764, https://doi.org/10.5194/amt-17-3751-2024, https://doi.org/10.5194/amt-17-3751-2024, 2024
Short summary
Short summary
Geostationary satellite data have been used to measure the stratospheric aerosols from the explosive Hunga volcanic eruption by using the data in a novel way. The onboard imager views part of the Earth's limb and data from this region were analysed to generate vertical cross-sections of aerosols high in the atmosphere. The analyses show the hemispheric spread of the aerosols and their vertical structure in layers from 22–28 km in the stratosphere.
Alessandro Bigi, Giorgio Veratti, Elisabeth Andrews, Martine Collaud Coen, Lorenzo Guerrieri, Vera Bernardoni, Dario Massabò, Luca Ferrero, Sergio Teggi, and Grazia Ghermandi
Atmos. Chem. Phys., 23, 14841–14869, https://doi.org/10.5194/acp-23-14841-2023, https://doi.org/10.5194/acp-23-14841-2023, 2023
Short summary
Short summary
Atmospheric particles include compounds that play a key role in the greenhouse effect and air toxicity. Concurrent observations of these compounds by multiple instruments are presented, following deployment within an urban environment in the Po Valley, one of Europe's pollution hotspots. The study compares these data, highlighting the impact of ground emissions, mainly vehicular traffic and biomass burning, on the absorption of sun radiation and, ultimately, on climate change and air quality.
Herizo Narivelo, Paul David Hamer, Virginie Marécal, Luke Surl, Tjarda Roberts, Sophie Pelletier, Béatrice Josse, Jonathan Guth, Mickaël Bacles, Simon Warnach, Thomas Wagner, Stefano Corradini, Giuseppe Salerno, and Lorenzo Guerrieri
Atmos. Chem. Phys., 23, 10533–10561, https://doi.org/10.5194/acp-23-10533-2023, https://doi.org/10.5194/acp-23-10533-2023, 2023
Short summary
Short summary
Volcanic emissions emit large quantities of gases and primary aerosols that can play an important role in atmospheric chemistry. We present a study of the fate of volcanic bromine emissions from the eruption of Mount Etna around Christmas 2018. Using a numerical model and satellite observations, we analyse the impact of the volcanic plume and how it modifies the composition of the air over the whole Mediterranean basin, in particular on tropospheric ozone through the bromine-explosion cycle.
Pierre-Yves Tournigand, Valeria Cigala, Elzbieta Lasota, Mohammed Hammouti, Lieven Clarisse, Hugues Brenot, Fred Prata, Gottfried Kirchengast, Andrea K. Steiner, and Riccardo Biondi
Earth Syst. Sci. Data, 12, 3139–3159, https://doi.org/10.5194/essd-12-3139-2020, https://doi.org/10.5194/essd-12-3139-2020, 2020
Short summary
Short summary
The detection and monitoring of volcanic clouds are important for aviation management, climate and weather forecasts. We present in this paper the first comprehensive archive collecting spatial and temporal information about volcanic clouds generated by the 11 largest eruptions of this century. We provide a complete set of state-of-the-art data allowing the development and testing of new algorithms contributing to improve the accuracy of the estimation of fundamental volcanic cloud parameters.
Ludwin Lopez-Lopez, Flavio Parmiggiani, Miguel Moctezuma-Flores, and Lorenzo Guerrieri
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-180, https://doi.org/10.5194/tc-2020-180, 2020
Manuscript not accepted for further review
Short summary
Short summary
A methodology for examining a temporal sequence of Synthetic Aperture Radar (SAR) images as applied to the detection of the A-68 iceberg and its drifting trajectory, is presented. Using an improved image processing scheme, the analysis covers a period of eighteen months. A-68 is one of the largest icebergs observed by remote sensing on record. It is expected to continue its path for more than a decade. It is important to track the huge A-68 iceberg to retrieve information on the drift movement.
Matthieu Poret, Stefano Corradini, Luca Merucci, Antonio Costa, Daniele Andronico, Mario Montopoli, Gianfranco Vulpiani, and Valentin Freret-Lorgeril
Atmos. Chem. Phys., 18, 4695–4714, https://doi.org/10.5194/acp-18-4695-2018, https://doi.org/10.5194/acp-18-4695-2018, 2018
Short summary
Short summary
This study aims at proposing a method to better assess the initial magma fragmentation produced during explosive volcanic eruptions. We worked on merging field, radar, and satellite data to estimate the total grain-size distribution, which is used within simulations to reconstruct the tephra loading and far-travelling airborne ash dispersal. This approach is applied to 23 November 2013, giving the very fine ash fraction related to volcanic hazards (e.g. air traffic safety).
Sergio Pugnaghi, Lorenzo Guerrieri, Stefano Corradini, and Luca Merucci
Atmos. Meas. Tech., 9, 3053–3062, https://doi.org/10.5194/amt-9-3053-2016, https://doi.org/10.5194/amt-9-3053-2016, 2016
Pasquale Sellitto, Alcide di Sarra, Stefano Corradini, Marie Boichu, Hervé Herbin, Philippe Dubuisson, Geneviève Sèze, Daniela Meloni, Francesco Monteleone, Luca Merucci, Justin Rusalem, Giuseppe Salerno, Pierre Briole, and Bernard Legras
Atmos. Chem. Phys., 16, 6841–6861, https://doi.org/10.5194/acp-16-6841-2016, https://doi.org/10.5194/acp-16-6841-2016, 2016
Short summary
Short summary
We combine plume dispersion and radiative transfer modelling, and satellite and surface remote sensing observations to study the regional influence of a relatively weak volcanic eruption from Mount Etna (25–27 October 2013) on the optical/micro-physical properties of Mediterranean aerosols. Our results indicate that even relatively weak volcanic eruptions may produce an observable effect on the aerosol properties at the regional scale, with a significant impact on the regional radiative balance.
A. Piscini, M. Picchiani, M. Chini, S. Corradini, L. Merucci, F. Del Frate, and S. Stramondo
Atmos. Meas. Tech., 7, 4023–4047, https://doi.org/10.5194/amt-7-4023-2014, https://doi.org/10.5194/amt-7-4023-2014, 2014
D. Summa, P. Di Girolamo, D. Stelitano, and M. Cacciani
Atmos. Meas. Tech., 6, 3515–3525, https://doi.org/10.5194/amt-6-3515-2013, https://doi.org/10.5194/amt-6-3515-2013, 2013
N. Theys, R. Campion, L. Clarisse, H. Brenot, J. van Gent, B. Dils, S. Corradini, L. Merucci, P.-F. Coheur, M. Van Roozendael, D. Hurtmans, C. Clerbaux, S. Tait, and F. Ferrucci
Atmos. Chem. Phys., 13, 5945–5968, https://doi.org/10.5194/acp-13-5945-2013, https://doi.org/10.5194/acp-13-5945-2013, 2013
S. Pugnaghi, L. Guerrieri, S. Corradini, L. Merucci, and B. Arvani
Atmos. Meas. Tech., 6, 1315–1327, https://doi.org/10.5194/amt-6-1315-2013, https://doi.org/10.5194/amt-6-1315-2013, 2013
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Multi-angle aerosol optical depth retrieval method based on improved surface reflectance
Comparison of diurnal aerosol products retrieved from combinations of micro-pulse lidar and sun photometer observations over the KAUST observation site
First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia
Aerosol optical depth data fusion with Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT-2) instruments GEMS, AMI, and GOCI-II: statistical and deep neural network methods
Stratospheric aerosol characteristics from SCIAMACHY limb observations: two-parameter retrieval
Retrieval and analysis of the composition of an aerosol mixture through Mie–Raman–fluorescence lidar observations
Transport of the Hunga volcanic aerosols inferred from Himawari-8/9 limb measurements
A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure dust
Innovative aerosol hygroscopic growth study from Mie–Raman–fluorescence lidar and microwave radiometer synergy
Evaluation of calibration performance of a low-cost particulate matter sensor using collocated and distant NO2
Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
Multi-wavelength dataset of aerosol extinction profiles retrieved from GOMOS stellar occultation measurements
Deep-Pathfinder: a boundary layer height detection algorithm based on image segmentation
An iterative algorithm to simultaneously retrieve aerosol extinction and effective radius profiles using CALIOP
Cloud detection from multi-angular polarimetric satellite measurements using a neural network ensemble approach
Alicenet – An Italian network of Automated Lidar-Ceilometers for 4D aerosol monitoring: infrastructure, data processing, and applications
Retrieving UV–Vis spectral single-scattering albedo of absorbing aerosols above clouds from synergy of ORACLES airborne and A-train sensors
Characterization of stratospheric particle size distribution uncertainties using SAGE II and SAGE III/ISS extinction spectra
Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager
Aerosol and cloud data processing and optical property retrieval algorithms for the spaceborne ACDL/DQ-1
Total Column Optical Depths Retrieved from CALIPSO Lidar Ocean Surface Backscatter
Derivation of depolarization ratios of aerosol fluorescence and water vapor Raman backscatters from lidar measurements
Long-term aerosol particle depolarization ratio measurements with HALO Photonics Doppler lidar
HETEAC-Flex: an optimal estimation method for aerosol typing based on lidar-derived intensive optical properties
MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm
Increasing Aerosol Optical Depth Spatial And Temporal Availability By Merging Datasets from Geostationary And Sun-Synchronous Satellites
Multi-section reference value for the analysis of horizontally scanning aerosol lidar observations
Retrieval of aerosol optical depth over the Arctic cryosphere during spring and summer using satellite observations
Post-process correction improves the accuracy of satellite PM2.5 retrievals
Quantifying particulate matter optical properties and flow rate in industrial stack plumes from the PRISMA hyperspectral imager
Aerosol retrieval over snow using the RemoTAP algorithm
Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign
Simultaneous retrieval of aerosol and ocean properties from PACE HARP2 with uncertainty assessment using cascading neural network radiative transfer models
Linear polarization signatures of atmospheric dust with the SolPol direct-sun polarimeter
Retrieval of aerosol properties from zenith sky radiance measurements
An ensemble method for improving the estimation of planetary boundary layer height from radiosonde data
Detection and analysis of Lhù'ààn Mân' (Kluane Lake) dust plumes using passive and active ground-based remote sensing supported by physical surface measurements
Cloud top heights and aerosol layer properties from EarthCARE lidar observations: the A-CTH and A-ALD products
Influence of electromagnetic interference on the evaluation of lidar-derived aerosol properties from Ny-Ålesund, Svalbard
Global 3-D distribution of aerosol composition by synergistic use of CALIOP and MODIS observations
Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product
Evaluating the effects of columnar NO2 on the accuracy of aerosol optical properties retrievals
An explicit formulation for the retrieval of the overlap function in an elastic and Raman aerosol lidar
The classification of atmospheric hydrometeors and aerosols from the EarthCARE radar and lidar: the A-TC, C-TC and AC-TC products
SAGE III/ISS aerosol/cloud categorization and its impact on GloSSAC
Exploring geometrical stereoscopic aerosol top height retrieval from geostationary satellite imagery in East Asia
Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals
Instantaneous aerosol and surface retrieval using satellites in geostationary orbit (iAERUS-GEO) – estimation of 15 min aerosol optical depth from MSG/SEVIRI and evaluation with reference data
HETEAC – the Hybrid End-To-End Aerosol Classification model for EarthCARE
DeLiAn – a growing collection of depolarization ratio, lidar ratio and Ångström exponent for different aerosol types and mixtures from ground-based lidar observations
Lijuan Chen, Ren Wang, Ying Fei, Peng Fang, Yong Zha, and Haishan Chen
Atmos. Meas. Tech., 17, 4411–4424, https://doi.org/10.5194/amt-17-4411-2024, https://doi.org/10.5194/amt-17-4411-2024, 2024
Short summary
Short summary
This study explores the problems of surface reflectance estimation from previous MISR satellite remote sensing images and develops an error correction model to obtain a higher-precision aerosol optical depth (AOD) product. High-accuracy AOD is important not only for the daily monitoring of air pollution but also for the study of energy exchange between land and atmosphere. This will help further improve the retrieval accuracy of multi-angle AOD on large spatial scales and for long time series.
Anton Lopatin, Oleg Dubovik, Georgiy Stenchikov, Ellsworth J. Welton, Illia Shevchenko, David Fuertes, Marcos Herreras-Giralda, Tatsiana Lapyonok, and Alexander Smirnov
Atmos. Meas. Tech., 17, 4445–4470, https://doi.org/10.5194/amt-17-4445-2024, https://doi.org/10.5194/amt-17-4445-2024, 2024
Short summary
Short summary
We compare aerosol properties over the King Abdullah University of Science and Technology campus using Generalized Retrieval of Aerosol and Surface Properties (GRASP) and the Micro-Pulse Lidar Network (MPLNET). We focus on the impact of different aerosol retrieval assumptions on daytime and nighttime retrievals and analyze seasonal variability in aerosol properties, aiding in understanding aerosol behavior and improving retrieval. Our work has implications for climate and public health.
Yeseul Cho, Jhoon Kim, Sujung Go, Mijin Kim, Seoyoung Lee, Minseok Kim, Heesung Chong, Won-Jin Lee, Dong-Won Lee, Omar Torres, and Sang Seo Park
Atmos. Meas. Tech., 17, 4369–4390, https://doi.org/10.5194/amt-17-4369-2024, https://doi.org/10.5194/amt-17-4369-2024, 2024
Short summary
Short summary
Aerosol optical properties have been provided by the Geostationary Environment Monitoring Spectrometer (GEMS), the world’s first geostationary-Earth-orbit (GEO) satellite instrument designed for atmospheric environmental monitoring. This study describes improvements made to the GEMS aerosol retrieval algorithm (AERAOD) and presents its validation results. These enhancements aim to provide more accurate and reliable aerosol-monitoring results for Asia.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Yun-Gon Lee, Sujung Go, and Kyunghwa Lee
Atmos. Meas. Tech., 17, 4317–4335, https://doi.org/10.5194/amt-17-4317-2024, https://doi.org/10.5194/amt-17-4317-2024, 2024
Short summary
Short summary
Information about aerosol loading in the atmosphere can be collected from various satellite instruments. Aerosol products from various satellite instruments have their own error characteristics. This study statistically merged aerosol optical depth datasets from multiple instruments aboard geostationary satellites considering uncertainties. Also, a deep neural network technique is adopted for aerosol data merging.
Christine Pohl, Felix Wrana, Alexei Rozanov, Terry Deshler, Elizaveta Malinina, Christian von Savigny, Landon A. Rieger, Adam E. Bourassa, and John P. Burrows
Atmos. Meas. Tech., 17, 4153–4181, https://doi.org/10.5194/amt-17-4153-2024, https://doi.org/10.5194/amt-17-4153-2024, 2024
Short summary
Short summary
Knowledge of stratospheric aerosol characteristics is important for understanding chemical and climate aerosol feedbacks. Two particle size distribution parameters, the aerosol extinction coefficient and the effective radius, are obtained from SCIAMACHY limb observations. The aerosol characteristics show good agreement with independent data sets from balloon-borne and satellite observations. This data set expands the limited knowledge of stratospheric aerosol characteristics.
Igor Veselovskii, Boris Barchunov, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Mikhail Korenskii, Gaël Dubois, William Boissiere, and Nikita Kasianik
Atmos. Meas. Tech., 17, 4137–4152, https://doi.org/10.5194/amt-17-4137-2024, https://doi.org/10.5194/amt-17-4137-2024, 2024
Short summary
Short summary
The paper presents a new method that categorizes atmospheric aerosols by analyzing their optical properties with a Mie–Raman–fluorescence lidar. The research specifically looks into understanding the presence of smoke, urban, and dust aerosols in the mixtures identified by this lidar. The reliability of the results is evaluated using the Monte Carlo technique. The effectiveness of this approach is successfully demonstrated through testing in ATOLL, an observatory influenced by diverse aerosols.
Fred Prata
Atmos. Meas. Tech., 17, 3751–3764, https://doi.org/10.5194/amt-17-3751-2024, https://doi.org/10.5194/amt-17-3751-2024, 2024
Short summary
Short summary
Geostationary satellite data have been used to measure the stratospheric aerosols from the explosive Hunga volcanic eruption by using the data in a novel way. The onboard imager views part of the Earth's limb and data from this region were analysed to generate vertical cross-sections of aerosols high in the atmosphere. The analyses show the hemispheric spread of the aerosols and their vertical structure in layers from 22–28 km in the stratosphere.
Emmanouil Proestakis, Antonis Gkikas, Thanasis Georgiou, Anna Kampouri, Eleni Drakaki, Claire L. Ryder, Franco Marenco, Eleni Marinou, and Vassilis Amiridis
Atmos. Meas. Tech., 17, 3625–3667, https://doi.org/10.5194/amt-17-3625-2024, https://doi.org/10.5194/amt-17-3625-2024, 2024
Short summary
Short summary
A new four-dimensional, multiyear, and near-global climate data record of the fine-mode (submicrometer diameter) and coarse-mode (supermicrometer diameter) components of atmospheric pure dust is presented. The dataset is considered unique with respect to a wide range of potential applications, including climatological, time series, and trend analysis over extensive geographical domains and temporal periods, validation of atmospheric dust models and datasets, and air quality.
Robin Miri, Olivier Pujol, Qiaoyun Hu, Philippe Goloub, Igor Veselovskii, Thierry Podvin, and Fabrice Ducos
Atmos. Meas. Tech., 17, 3367–3375, https://doi.org/10.5194/amt-17-3367-2024, https://doi.org/10.5194/amt-17-3367-2024, 2024
Short summary
Short summary
This paper focuses on the use of fluorescence to study aerosols with lidar. An innovative method for aerosol hygroscopic growth study using fluorescence is presented. The paper presents case studies to showcase the effectiveness and potential of the proposed approach. These advancements will contribute to better understanding the interactions between aerosols and water vapor, with future work expected to be dedicated to aerosol–cloud interaction.
Kabseok Ko, Seokheon Cho, and Ramesh R. Rao
Atmos. Meas. Tech., 17, 3303–3322, https://doi.org/10.5194/amt-17-3303-2024, https://doi.org/10.5194/amt-17-3303-2024, 2024
Short summary
Short summary
In our study, we examined how NO2, temperature, and relative humidity influence the calibration of PurpleAir PA-II sensors. We found that incorporating NO2 data from collocated reliable instruments enhances PM2.5 calibration performance. Due to the impracticality of collocating reliable NO2 instruments with sensors, we suggest using distant NO2 data for calibration. We demonstrated that performance improves when distant NO2 correlates highly with collocated NO2 measurements.
Daniel J. V. Robbins, Caroline A. Poulsen, Steven T. Siems, Simon R. Proud, Andrew T. Prata, Roy G. Grainger, and Adam C. Povey
Atmos. Meas. Tech., 17, 3279–3302, https://doi.org/10.5194/amt-17-3279-2024, https://doi.org/10.5194/amt-17-3279-2024, 2024
Short summary
Short summary
Extreme wildfire events are becoming more common with climate change. The smoke plumes associated with these wildfires are not captured by current operational satellite products due to their high optical thickness. We have developed a novel aerosol retrieval for the Advanced Himawari Imager to study these plumes. We find very high values of optical thickness not observed in other operational satellite products, suggesting these plumes have been missed in previous studies.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Didier Fussen, Christine Bingen, Filip Vanhellemont, Nina Mateshvili, Alexei Rozanov, and Christine Pohl
Atmos. Meas. Tech., 17, 3085–3101, https://doi.org/10.5194/amt-17-3085-2024, https://doi.org/10.5194/amt-17-3085-2024, 2024
Short summary
Short summary
We have developed the new multi-wavelength dataset of aerosol extinction profiles, which are retrieved from the averaged transmittance spectra by the Global Ozone Monitoring by Occultation of Stars instrument aboard Envisat. The retrieved aerosol extinction profiles are provided in the altitude range 10–40 km at 400, 440, 452, 470, 500, 525, 550, 672 and 750 nm for the period 2002–2012. FMI-GOMOSaero aerosol profiles have improved quality; they are in good agreement with other datasets.
Jasper S. Wijnands, Arnoud Apituley, Diego Alves Gouveia, and Jan Willem Noteboom
Atmos. Meas. Tech., 17, 3029–3045, https://doi.org/10.5194/amt-17-3029-2024, https://doi.org/10.5194/amt-17-3029-2024, 2024
Short summary
Short summary
The mixing of air in the lower atmosphere influences the concentration of air pollutants and greenhouse gases. Our study developed a new method, Deep-Pathfinder, to estimate mixing layer height. Deep-Pathfinder analyses imagery with aerosol observations using artificial intelligence techniques for computer vision. Compared to existing methods, it improves temporal consistency and resolution and can be used in real time, which is valuable for aviation, forecasting, and air quality monitoring.
Liang Chang, Jing Li, Jingjing Ren, Changrui Xiong, and Lu Zhang
Atmos. Meas. Tech., 17, 2637–2648, https://doi.org/10.5194/amt-17-2637-2024, https://doi.org/10.5194/amt-17-2637-2024, 2024
Short summary
Short summary
We described a modified lidar inversion algorithm to retrieve aerosol extinction and size distribution simultaneously from two-wavelength elastic lidar measurements. Its major advantage is that the lidar ratio of each layer is determined iteratively by a lidar ratio–Ångström exponent lookup table. The algorithm was applied to the Raman lidar and CALIOP measurements. The retrieved results by our method are in good agreement with those achieved by Raman method.
Zihao Yuan, Guangliang Fu, Bastiaan van Diedenhoven, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech., 17, 2595–2610, https://doi.org/10.5194/amt-17-2595-2024, https://doi.org/10.5194/amt-17-2595-2024, 2024
Short summary
Short summary
Currently, aerosol properties from spaceborne multi-angle polarimeter (MAP) instruments can only be retrieved in cloud-free areas or in areas where an aerosol layer is located above a cloud. Therefore, it is important to be able to identify cloud-free pixels for which an aerosol retrieval algorithm can provide meaningful output. The developed neural network cloud screening demonstrates that cloud masking for MAP aerosol retrieval can be based on the MAP measurements themselves.
Annachiara Bellini, Henri Diémoz, Luca Di Liberto, Gian Paolo Gobbi, Alessandro Bracci, Ferdinando Pasqualini, and Francesca Barnaba
EGUsphere, https://doi.org/10.5194/egusphere-2024-730, https://doi.org/10.5194/egusphere-2024-730, 2024
Short summary
Short summary
The work provides a comprehensive view of the configuration, retrieval algorithms, and relevant applications of the Italian network of Automated Lidar-Ceilometer, Alicenet. It describes the full Alicenet data processing converting raw instrumental data into quantitative aerosol information. It includes relevant examples of the Alicenet derived quantities and their comparison with independent data, and recent examples of the network monitoring potential over Italy.
Hiren T. Jethva, Omar Torres, Richard A. Ferrare, Sharon P. Burton, Anthony L. Cook, David B. Harper, Chris A. Hostetler, Jens Redemann, Vinay Kayetha, Samuel LeBlanc, Kristina Pistone, Logan Mitchell, and Connor J. Flynn
Atmos. Meas. Tech., 17, 2335–2366, https://doi.org/10.5194/amt-17-2335-2024, https://doi.org/10.5194/amt-17-2335-2024, 2024
Short summary
Short summary
We introduce a novel synergy algorithm applied to ORALCES airborne measurements of above-cloud aerosol optical depth and UV–Vis satellite observations from OMI and MODIS to retrieve spectral aerosol single-scattering albedo of lofted layers of carbonaceous smoke aerosols over clouds. The development of the proposed aerosol–cloud algorithm implies a possible synergy of CALIOP and OMI–MODIS passive sensors to deduce a global product of AOD and SSA of absorbing aerosols above clouds.
Travis N. Knepp, Mahesh Kovilakam, Larry Thomason, and Stephen J. Miller
Atmos. Meas. Tech., 17, 2025–2054, https://doi.org/10.5194/amt-17-2025-2024, https://doi.org/10.5194/amt-17-2025-2024, 2024
Short summary
Short summary
An algorithm is presented to derive a new SAGE III/ISS (Stratospheric Aerosol and Gas Experiment III on the International Space Station) Level-2 product: the size distribution of stratospheric particles. This is a significant improvement over previous techniques in that we now provide uncertainty estimates for all inferred parameters. We also evaluated the stability of this method in retrieving bimodal distribution parameters. We present a special application to the 2022 eruption of Hunga Tonga.
Mijin Kim, Robert C. Levy, Lorraine A. Remer, Shana Mattoo, and Pawan Gupta
Atmos. Meas. Tech., 17, 1913–1939, https://doi.org/10.5194/amt-17-1913-2024, https://doi.org/10.5194/amt-17-1913-2024, 2024
Short summary
Short summary
The study focused on evaluating and modifying the surface reflectance parameterization (SRP) of the Dark Target (DT) algorithm for geostationary observation. When using the DT SRP with the ABIs sensor on GOES-R, artificial diurnal signatures were present in AOD retrieval. To overcome this issue, a new SRP was developed, incorporating solar zenith angle and land cover type. The revised SRP resulted in improved AOD retrieval, demonstrating reduced bias around local noon.
Guangyao Dai, Songhua Wu, Wenrui Long, Jiqiao Liu, Yuan Xie, Kangwen Sun, Fanqian Meng, Xiaoquan Song, Zhongwei Huang, and Weibiao Chen
Atmos. Meas. Tech., 17, 1879–1890, https://doi.org/10.5194/amt-17-1879-2024, https://doi.org/10.5194/amt-17-1879-2024, 2024
Short summary
Short summary
An overview is given of the main algorithms applied to derive the aerosol and cloud optical property product of the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The paper demonstrates the observational capabilities of ACDL for aerosol and cloud vertical structure and global distribution through two optical property product measurement cases and global aerosol optical depth profile observations.
Robert A. Ryan, Mark A. Vaughan, Sharon D. Rodier, Jason L. Tackett, John A. Reagan, Richard A. Ferrare, Johnathan W. Hair, and Brian J. Getzewich
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-23, https://doi.org/10.5194/amt-2024-23, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This paper introduces Ocean Derived Column Optical Depths (ODCOD), a new way to estimate column optical depths using the CALOP lidar measurements from the ocean surface. ODCOD estimates include contributions from particulates in the full column, which CALIOP estimates do not, making it a compliment measurement to CALIOP’s standard estimates. We find that ODCOD compares well with other established datasets in the daytime but tends to estimate higher at night.
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, William Boissiere, Mikhail Korenskiy, Nikita Kasianik, Sergey Khaykyn, and Robin Miri
Atmos. Meas. Tech., 17, 1023–1036, https://doi.org/10.5194/amt-17-1023-2024, https://doi.org/10.5194/amt-17-1023-2024, 2024
Short summary
Short summary
Measurements of transported smoke layers were performed with a lidar in Lille and a five-channel fluorescence lidar in Moscow. Results show the peak of fluorescence in the boundary layer is at 438 nm, while in the smoke layer it shifts to longer wavelengths. The fluorescence depolarization is 45 % to 55 %. The depolarization ratio of the water vapor channel is low (2 ± 0.5 %) in the absence of fluorescence and can be used to evaluate the contribution of fluorescence to water vapor signal.
Viet Le, Hannah Lobo, Ewan J. O'Connor, and Ville Vakkari
Atmos. Meas. Tech., 17, 921–941, https://doi.org/10.5194/amt-17-921-2024, https://doi.org/10.5194/amt-17-921-2024, 2024
Short summary
Short summary
This study offers a long-term overview of aerosol particle depolarization ratio at the wavelength of 1565 nm obtained from vertical profiling measurements by Halo Doppler lidars during 4 years at four different locations across Finland. Our observations support the long-term usage of Halo Doppler lidar depolarization ratio such as the detection of aerosols that may pose a safety risk for aviation. Long-range Saharan dust transport and pollen transport are also showcased here.
Athena Augusta Floutsi, Holger Baars, and Ulla Wandinger
Atmos. Meas. Tech., 17, 693–714, https://doi.org/10.5194/amt-17-693-2024, https://doi.org/10.5194/amt-17-693-2024, 2024
Short summary
Short summary
We introduce an aerosol-typing scheme (HETEAC-Flex) based on lidar-derived intensive optical properties and applicable to ground-based and spaceborne lidars. HETEAC-Flex utilizes the optimal estimation method and enables the identification of up to four different aerosol components, as well as the determination of their contribution to the aerosol mixture in terms of relative volume. The aerosol components represent common aerosol types such as dust, sea salt, smoke and pollution.
James A. Limbacher, Ralph A. Kahn, Mariel D. Friberg, Jaehwa Lee, Tyler Summers, and Hai Zhang
Atmos. Meas. Tech., 17, 471–498, https://doi.org/10.5194/amt-17-471-2024, https://doi.org/10.5194/amt-17-471-2024, 2024
Short summary
Short summary
We present the new Multi-Angle Geostationary Aerosol Retrieval Algorithm (MAGARA) that fuses observations from GOES-16 and GOES-17 to retrieve information about aerosol loading (at 10–15 min cadence) and aerosol particle properties (daily), all at pixel-level resolution. We present MAGARA results for three case studies: the 2018 California Camp Fire, the 2019 Williams Flats Fire, and the 2019 Kincade Fire. We also compare MAGARA aerosol loading and particle properties with AERONET.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-259, https://doi.org/10.5194/amt-2023-259, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
In this study, for the first time, we combined aerosol data from six satellites using a unified algorithm. The global datasets are generated at a high spatial resolution of about 25 km with an interval of 30 minutes. The new datasets are compared against ground truth and verified. They will be useful for various applications such as air quality monitoring, climate research, pollution diurnal variability, long-range smoke and dust transport, and evaluation of regional and global models.
Juseon Shin, Gahyeong Kim, Dukhyeon Kim, Matthias Tesche, Gahyeon Park, and Youngmin Noh
Atmos. Meas. Tech., 17, 397–406, https://doi.org/10.5194/amt-17-397-2024, https://doi.org/10.5194/amt-17-397-2024, 2024
Short summary
Short summary
We introduce the multi-section method, a novel approach for stable extinction coefficient retrievals in horizontally scanning aerosol lidar measurements, in this study. Our method effectively removes signal–noise-induced irregular peaks and derives a reference extinction coefficient, αref, from multiple scans, resulting in a strong correlation (>0.74) with PM2.5 mass concentrations. Case studies demonstrate its utility in retrieving spatio-temporal aerosol distributions and PM2.5 concentrations.
Basudev Swain, Marco Vountas, Adrien Deroubaix, Luca Lelli, Yanick Ziegler, Soheila Jafariserajehlou, Sachin S. Gunthe, Andreas Herber, Christoph Ritter, Hartmut Bösch, and John P. Burrows
Atmos. Meas. Tech., 17, 359–375, https://doi.org/10.5194/amt-17-359-2024, https://doi.org/10.5194/amt-17-359-2024, 2024
Short summary
Short summary
Aerosols are suspensions of particles dispersed in the air. In this study, we use a novel retrieval of satellite data to investigate an optical property of aerosols, the aerosol optical depth, in the high Arctic to assess their direct and indirect roles in climate change. This study demonstrates that the presented approach shows good quality and very promising potential.
Andrea Porcheddu, Ville Kolehmainen, Timo Lähivaara, and Antti Lipponen
EGUsphere, https://doi.org/10.5194/egusphere-2023-2635, https://doi.org/10.5194/egusphere-2023-2635, 2024
Short summary
Short summary
This study focuses on improving the accuracy of satellite-based PM2.5 retrieval, crucial for monitoring air quality and its impact on health. It employs machine learning to correct the AOD-to-PM2.5 conversion ratio using various data sources. The approach produces high-resolution PM2.5 estimates with improved accuracy. The method is flexible and can incorporate additional training data from different sources, making it a valuable tool for air quality monitoring and epidemiological studies.
Gabriel Calassou, Pierre-Yves Foucher, and Jean-François Léon
Atmos. Meas. Tech., 17, 57–71, https://doi.org/10.5194/amt-17-57-2024, https://doi.org/10.5194/amt-17-57-2024, 2024
Short summary
Short summary
We propose analyzing the aerosol composition of plumes emitted by different industrial stacks using PRISMA satellite hyperspectral observations. Three industrial sites have been observed: a coal-fired power plant in South Africa, a steel plant in China, and gas flaring at an oil extraction site in Algeria. Aerosol optical thickness and particle radius are retrieved within the plumes. The mass flow rate of particulate matter is estimated in the plume using the integrated mass enhancement method.
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
Short summary
Short summary
In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm is extended with a bi-directional reflection distribution function for snow surfaces. The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover > 75 %.
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
Short summary
Short summary
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.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
Short summary
Short summary
This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Vasiliki Daskalopoulou, Panagiotis I. Raptis, Alexandra Tsekeri, Vassilis Amiridis, Stelios Kazadzis, Zbigniew Ulanowski, Vassilis Charmandaris, Konstantinos Tassis, and William Martin
Atmos. Meas. Tech., 16, 4529–4550, https://doi.org/10.5194/amt-16-4529-2023, https://doi.org/10.5194/amt-16-4529-2023, 2023
Short summary
Short summary
Atmospheric dust particles may present a preferential alignment due to their shape on long range transport. Since dust is abundant and plays a key role to global climate, the elusive observation of orientation will be a game changer to existing measurement techniques and the representation of particles in climate models. We utilize a specifically designed instrument, SolPol, and target the Sun from the ground for large polarization values under dusty conditions, a clear sign of orientation.
Sara Herrero-Anta, Roberto Román, David Mateos, Ramiro González, Juan Carlos Antuña-Sánchez, Marcos Herreras-Giralda, Antonio Fernando Almansa, Daniel González-Fernández, Celia Herrero del Barrio, Carlos Toledano, Victoria E. Cachorro, and Ángel M. de Frutos
Atmos. Meas. Tech., 16, 4423–4443, https://doi.org/10.5194/amt-16-4423-2023, https://doi.org/10.5194/amt-16-4423-2023, 2023
Short summary
Short summary
This paper shows the potential of a simple radiometer like the ZEN-R52 as a possible alternative for aerosol property retrieval in remote areas. A calibration method based on radiative transfer simulations together with an inversion methodology using the GRASP code is proposed here. The results demonstrate that this methodology is useful for the retrieval of aerosol extensive properties like aerosol optical depth (AOD) and aerosol volume concentration for total, fine and coarse modes.
Xi Chen, Ting Yang, Zifa Wang, Futing Wang, and Haibo Wang
Atmos. Meas. Tech., 16, 4289–4302, https://doi.org/10.5194/amt-16-4289-2023, https://doi.org/10.5194/amt-16-4289-2023, 2023
Short summary
Short summary
Uncertainties remain great in the planetary boundary layer height (PBLH) determination from radiosonde, especially during the transition period of different PBL regimes. We combine seven existing methods along with statistical modification on gradient-based methods. We find that the ensemble method can eliminate the overestimation of PBLH and reduce the inconsistency between individual methods. The ensemble method improves the effectiveness of PBLH determination to 62.6 %.
Seyed Ali Sayedain, Norman T. O'Neill, James King, Patrick L. Hayes, Daniel Bellamy, Richard Washington, Sebastian Engelstaedter, Andy Vicente-Luis, Jill Bachelder, and Malo Bernhard
Atmos. Meas. Tech., 16, 4115–4135, https://doi.org/10.5194/amt-16-4115-2023, https://doi.org/10.5194/amt-16-4115-2023, 2023
Short summary
Short summary
We used (columnar) ground-based remote sensing (RS) tools and surface measurements to characterize local (drainage-basin) dust plumes at a site in the Yukon. Plume height, particle size, and column-to-surface ratios enabled insights into how satellite RS could be used to analyze Arctic-wide dust transport. This helps modelers refine dust impacts in their climate change simulations. It is an important step since local dust is a key source of dust deposition on snow in the sensitive Arctic region.
Ulla Wandinger, Moritz Haarig, Holger Baars, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 4031–4052, https://doi.org/10.5194/amt-16-4031-2023, https://doi.org/10.5194/amt-16-4031-2023, 2023
Short summary
Short summary
We introduce the algorithms that have been developed to derive cloud top height and aerosol layer products from observations with the Atmospheric Lidar (ATLID) onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE). The products provide information on the uppermost cloud and geometrical and optical properties of aerosol layers in an atmospheric column. They can be used individually but also serve as input for algorithms that combine observations with EarthCARE’s lidar and imager.
Tim Poguntke and Christoph Ritter
Atmos. Meas. Tech., 16, 4009–4014, https://doi.org/10.5194/amt-16-4009-2023, https://doi.org/10.5194/amt-16-4009-2023, 2023
Short summary
Short summary
In this work we analyze the impact of electromagnetic interference on an aerosol lidar. We found that aging transient recorders may produce a noise with fixed frequency that can be removed a posteriori.
Rei Kudo, Akiko Higurashi, Eiji Oikawa, Masahiro Fujikawa, Hiroshi Ishimoto, and Tomoaki Nishizawa
Atmos. Meas. Tech., 16, 3835–3863, https://doi.org/10.5194/amt-16-3835-2023, https://doi.org/10.5194/amt-16-3835-2023, 2023
Short summary
Short summary
A synergistic retrieval method of aerosol components (water-soluble, light-absorbing, dust, and sea salt particles) from CALIOP and MODIS observations was developed. The total global 3-D distributions and those for each component showed good consistency with the CALIOP and MODIS official products and previous studies. The shortwave direct radiative effects of each component at the top and bottom of the atmosphere and for the heating rate were also consistent with previous studies.
Nicole Docter, Rene Preusker, Florian Filipitsch, Lena Kritten, Franziska Schmidt, and Jürgen Fischer
Atmos. Meas. Tech., 16, 3437–3457, https://doi.org/10.5194/amt-16-3437-2023, https://doi.org/10.5194/amt-16-3437-2023, 2023
Short summary
Short summary
We describe the stand-alone retrieval algorithm used to derive aerosol properties relying on measurements of the Multi-Spectral Imager (MSI) aboard the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite. This aerosol data product will be available as M-AOT after the launch of EarthCARE. Additionally, we applied the algorithm to simulated EarthCARE MSI and Moderate Resolution Imaging Spectroradiometer (MODIS) data for prelaunch algorithm verification.
Theano Drosoglou, Ioannis-Panagiotis Raptis, Massimo Valeri, Stefano Casadio, Francesca Barnaba, Marcos Herreras-Giralda, Anton Lopatin, Oleg Dubovik, Gabriele Brizzi, Fabrizio Niro, Monica Campanelli, and Stelios Kazadzis
Atmos. Meas. Tech., 16, 2989–3014, https://doi.org/10.5194/amt-16-2989-2023, https://doi.org/10.5194/amt-16-2989-2023, 2023
Short summary
Short summary
Aerosol optical properties derived from sun photometers depend on the optical depth of trace gases absorbing solar radiation at specific spectral ranges. Various networks use satellite-based climatologies to account for this or neglect their effect. In this work, we evaluate the effect of NO2 absorption in aerosol retrievals from AERONET and SKYNET over two stations in Rome, Italy, with relatively high NO2 spatiotemporal variations, using NO2 data from the Pandora network and the TROPOMI sensor.
Adolfo Comerón, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Michaël Sicard, Federico Dios, Cristina Gil-Díaz, Daniel Camilo Fortunato dos Santos Oliveira, and Francesc Rocadenbosch
Atmos. Meas. Tech., 16, 3015–3025, https://doi.org/10.5194/amt-16-3015-2023, https://doi.org/10.5194/amt-16-3015-2023, 2023
Short summary
Short summary
We derive an explicit (i.e., non-iterative) formula for the retrieval of the overlap function in an aerosol lidar with both elastic and Raman N2 and/or O2 channels used for independent measurements of aerosol backscatter and extinction coefficients. The formula requires only the measured, range-corrected elastic and the corresponding Raman signals, plus an assumed lidar ratio. We assess the influence of the lidar ratio error in the overlap function retrieval and present retrieval examples.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
Short summary
Short summary
The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Mahesh Kovilakam, Larry Thomason, and Travis Knepp
Atmos. Meas. Tech., 16, 2709–2731, https://doi.org/10.5194/amt-16-2709-2023, https://doi.org/10.5194/amt-16-2709-2023, 2023
Short summary
Short summary
The paper describes SAGE III/ISS aerosol/cloud categorization and its implications on Global Space-based Stratospheric Aerosol Climatology (GloSSAC). The presence of data from the SAGE type of multi-wavelength measurements is important in GloSSAC. The new aerosol/cloud categorization method described in this paper will help retain more measurements, particularly in the lower stratosphere during and following a volcanic event and other processes.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Huidong Yeo, and Sang-Woo Kim
Atmos. Meas. Tech., 16, 2673–2690, https://doi.org/10.5194/amt-16-2673-2023, https://doi.org/10.5194/amt-16-2673-2023, 2023
Short summary
Short summary
Aerosol height information is important when seeking an understanding of the vertical structure of the aerosol layer and long-range transport. In this study, a geometrical aerosol top height (ATH) retrieval using a parallax of two geostationary satellites is investigated. With sufficient longitudinal separation between the two satellites, a decent ATH product could be retrieved.
Jianglong Zhang, Jeffrey S. Reid, Steven D. Miller, Miguel Román, Zhuosen Wang, Robert J. D. Spurr, and Shawn Jaker
Atmos. Meas. Tech., 16, 2531–2546, https://doi.org/10.5194/amt-16-2531-2023, https://doi.org/10.5194/amt-16-2531-2023, 2023
Short summary
Short summary
We adapted the spherical harmonics discrete ordinate method 3-dimentional radiative transfer model (3-D RTM) and developed a nighttime 3-D RTM capability for simulating top-of-atmosphere radiances from artificial light sources for aerosol retrievals. Our study suggests that both aerosol optical depth and aerosol plume height can be effectively retrieved using nighttime observations over artificial light sources, through the newly developed radiative transfer modeling capability.
Xavier Ceamanos, Bruno Six, Suman Moparthy, Dominique Carrer, Adèle Georgeot, Josef Gasteiger, Jérôme Riedi, Jean-Luc Attié, Alexei Lyapustin, and Iosif Katsev
Atmos. Meas. Tech., 16, 2575–2599, https://doi.org/10.5194/amt-16-2575-2023, https://doi.org/10.5194/amt-16-2575-2023, 2023
Short summary
Short summary
A new algorithm to retrieve the diurnal evolution of aerosol optical depth over land and ocean from geostationary meteorological satellites is proposed and successfully evaluated with reference ground-based and satellite data. The high-temporal-resolution aerosol observations that are obtained from the EUMETSAT Meteosat Second Generation mission are unprecedented and open the door to studies that cannot be conducted with the once-a-day observations available from low-Earth-orbit satellites.
Ulla Wandinger, Athena Augusta Floutsi, Holger Baars, Moritz Haarig, Albert Ansmann, Anja Hünerbein, Nicole Docter, David Donovan, Gerd-Jan van Zadelhoff, Shannon Mason, and Jason Cole
Atmos. Meas. Tech., 16, 2485–2510, https://doi.org/10.5194/amt-16-2485-2023, https://doi.org/10.5194/amt-16-2485-2023, 2023
Short summary
Short summary
We introduce an aerosol classification model that has been developed for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The model provides a consistent description of microphysical, optical, and radiative properties of common aerosol types such as dust, sea salt, pollution, and smoke. It is used for aerosol classification and assessment of radiation effects based on the synergy of active and passive observations with lidar, imager, and radiometer of the multi-instrument platform.
Athena Augusta Floutsi, Holger Baars, Ronny Engelmann, Dietrich Althausen, Albert Ansmann, Stephanie Bohlmann, Birgit Heese, Julian Hofer, Thomas Kanitz, Moritz Haarig, Kevin Ohneiser, Martin Radenz, Patric Seifert, Annett Skupin, Zhenping Yin, Sabur F. Abdullaev, Mika Komppula, Maria Filioglou, Elina Giannakaki, Iwona S. Stachlewska, Lucja Janicka, Daniele Bortoli, Eleni Marinou, Vassilis Amiridis, Anna Gialitaki, Rodanthi-Elisavet Mamouri, Boris Barja, and Ulla Wandinger
Atmos. Meas. Tech., 16, 2353–2379, https://doi.org/10.5194/amt-16-2353-2023, https://doi.org/10.5194/amt-16-2353-2023, 2023
Short summary
Short summary
DeLiAn is a collection of lidar-derived aerosol intensive optical properties for several aerosol types, namely the particle linear depolarization ratio, the extinction-to-backscatter ratio (lidar ratio) and the Ångström exponent. The data collection is based on globally distributed, long-term, ground-based, multiwavelength, Raman and polarization lidar measurements and currently covers two wavelengths, 355 and 532 nm, for 13 aerosol categories ranging from basic aerosol types to mixtures.
Cited articles
Atkinson, P. M. and Tatnall, A. R. L.: Introduction Neural networks in
remote sensing, Int. J. Remote Sens., 18, 699–709,
https://doi.org/10.1080/014311697218700, 1997.
Bishop, C. M.: Neural networks and their applications, Rev. Sci. Instrum.,
65, 1803–1832, https://doi.org/10.1063/1.1144830, 1994.
Bourassa, A. E., Robock, A., Randel, W. J., Deshler, T., Rieger, L. A.,
Lloyd, N. D., Llewellyn, E. J. (Ted), and Degenstein, D. A.: Large Volcanic
Aerosol Load in the Stratosphere Linked to Asian Monsoon Transport, Science,
337, 78–81, https://doi.org/10.1126/science.1219371, 2012.
Bruckert, J., Hoshyaripour, G. A., Horváth, Á., Muser, L. O., Prata, F. J., Hoose, C., and Vogel, B.: Online treatment of eruption dynamics improves the volcanic ash and SO2 dispersion forecast: case of the 2019 Raikoke eruption, Atmos. Chem. Phys., 22, 3535–3552, https://doi.org/10.5194/acp-22-3535-2022, 2022.
Casadevall, T. J.: The 1989–1990 eruption of Redoubt Volcano, Alaska:
Impacts on aircraft operations, J. Volcanol. Geoth. Res., 62, 301–316,
https://doi.org/10.1016/0377-0273(94)90038-8, 1994.
Clarisse, L. and Prata, F.: Infrared Sounding of Volcanic Ash, in:
Volcanic Ash, Elsevier, 189–215, https://doi.org/10.1016/B978-0-08-100405-0.00017-3, 2016.
Corradini, S., Spinetti, C., Carboni, E., Tirelli, C., Buongiorno, M. F.,
Pugnaghi, S., and Gangale, G.: Mt. Etna tropospheric ash retrieval and
sensitivity analysis using Moderate Resolution Imaging Spectroradiometer
measurements, J. Appl. Remote Sens., 2, 023550, https://doi.org/10.1117/1.3046674, 2008.
Corradini, S., Merucci, L., and Prata, A. J.: Retrieval of SO2 from thermal infrared satellite measurements: correction procedures for the effects of volcanic ash, Atmos. Meas. Tech., 2, 177–191, https://doi.org/10.5194/amt-2-177-2009, 2009.
Cox, C., Polehampton, E., and Smith, D.: Sentinel-3 SLSTR Level-1 ATBD, Doc. No.: S3-TN-RAL-SL-032, 171 pp., https://sentinels.copernicus.eu/documents/247904/2731673/S3_TN_RAL_SL_032+-Issue+8.0+version1.0-++SLSTR+L1+ATBD.pdf/fb45d35c-0d87-dca6-ea3c-dc7c2215b5bc?t=1656685672747, last access: 12 October 2021.
Craig, H., Wilson, T., Stewart, C., Outes, V., Villarosa, G., and Baxter,
P.: Impacts to agriculture and critical infrastructure in Argentina after
ashfall from the 2011 eruption of the Cordón Caulle volcanic complex: An
assessment of published damage and function thresholds, Journal of Applied Volcanology, 5, 7, https://doi.org/10.1186/s13617-016-0046-1, 2016.
Delmelle, P., Stix, J., Baxter, P., Garcia-Alvarez, J., and Barquero, J.:
Atmospheric dispersion, environmental effects and potential health hazard
associated with the low-altitude gas plume of Masaya volcano, Nicaragua,
B. Volcanol., 64, 423–434, https://doi.org/10.1007/s00445-002-0221-6, 2022.
Di Noia, A. and Hasekamp, O. P.: Neural Networks and Support Vector Machines and Their Application to Aerosol and Cloud Remote Sensing: A Review, in: Springer Series in Light Scattering, Springer, Cham, 279–329,
https://doi.org/10.1007/978-3-319-70796-9_4, 2018.
ESA: Copernicus Open Access Hub, ESA, https://scihub.copernicus.eu/dhus/#/home, last access: 16 January 2021.
Fawcett, T.: An introduction to ROC analysis, Pattern Recogn. Lett., 27,
861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006.
Francis, P. N., Cooke, M. C., and Saunders, R. W.: Retrieval of physical
properties of volcanic ash using Meteosat: A case study from the 2010
Eyjafjallajökull eruption, J. Geophys. Res.-Atmos., 117, D00U09,
https://doi.org/10.1029/2011JD016788, 2012.
Gardner, M. W. and Dorling, S. R.: Artificial neural networks (the
multilayer perceptron) – a review of applications in the atmospheric
sciences, Atmos. Environ., 32, 2627–2636, https://doi.org/10.1016/S1352-2310(97)00447-0, 1998.
Glaze, L. S., Baloga, S. M., and Wilson, L.: Transport of atmospheric water
vapor by volcanic eruption columns, J. Geophys. Res.-Atmos., 102, 6099–6108, https://doi.org/10.1029/96JD03125, 1997.
Gorkavyi, N., Krotkov, N., Li, C., Lait, L., Colarco, P., Carn, S., DeLand, M., Newman, P., Schoeberl, M., Taha, G., Torres, O., Vasilkov, A., and Joiner, J.: Tracking aerosols and SO2 clouds from the Raikoke eruption: 3D view from satellite observations, Atmos. Meas. Tech., 14, 7545–7563, https://doi.org/10.5194/amt-14-7545-2021, 2021.
Gray, T. M. and Bennartz, R.: Automatic volcanic ash detection from MODIS observations using a back-propagation neural network, Atmos. Meas. Tech., 8, 5089–5097, https://doi.org/10.5194/amt-8-5089-2015, 2015.
Haywood, J. and Boucher, O.: Estimates of the direct and indirect radiative forcing due to tropospheric aerosols: A review, Rev. Geophys., 38, 513–543, https://doi.org/10.1029/1999RG000078, 2000.
Horwell, C. J. and Baxter, P. J.: The respiratory health hazards of
volcanic ash: A review for volcanic risk mitigation, B. Volcanol., 69, 1–24, https://doi.org/10.1007/s00445-006-0052-y, 2006.
Horwell, C. J., Baxter, P. J., Hillman, S. E., Calkins, J. A., Damby, D. E.,
Delmelle, P., Donaldson, K., Dunster, C., Fubini, B., Kelly, F. J., Le
Blond, J. S., Livi, K. J. T., Murphy, F., Nattrass, C., Sweeney, S., Tetley,
T. D., Thordarson, T., and Tomatis, M.: Physicochemical and toxicological
profiling of ash from the 2010 and 2011 eruptions of Eyjafjallajökull and Grímsvötn volcanoes, Iceland using a rapid respiratory hazard
assessment protocol, Environ. Res., 127, 63–73, https://doi.org/10.1016/j.envres.2013.08.011, 2013.
LAADS DAAC (Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center): https://ladsweb.modaps.eosdis.nasa.gov/search/, last access: 4 February 2021.
Mather, T. A., Pyle, D. M., and Oppenheimer, C.: Tropospheric volcanic
aerosol, in: Volcanism and the Earth's Atmosphere, edited by: Robock, A. and
Oppenheimer, C., Geophysical Monograph-American Geophysical Union, 139,
189–212, https://doi.org/10.1029/139GM12, 2003.
McKee, K., Smith, C. M., Reath, K., Snee, E., Maher, S., Matoza, R. S., Carn, S., Mastin, L., Anderson, K., Damby, D., Roman, D. C., Degterev, A., Rybin, A., Chibisova, M., Assink, J. D., de Negri Leiva, R., and Perttu, A.: Evaluating the state-of-the-art in remote volcanic eruption characterization Part I: Raikoke volcano, Kuril Islands, J. Volcanol. Geoth. Res., 419, 107354, https://doi.org/10.1016/j.jvolgeores.2021.107354, 2021.
Menzel, W. P., Frey, R. A., and Baum, B. A.: Cloud top properties and cloud phase ATBD, https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ModAtmo/MOD06-ATBD_2015_05_01_1.pdf (last access: 23 September 2021), 2015.
Millán, L., Santee, M. L., Lambert, A., Livesey, N. J., Werner, F.,
Schwartz, M. J., Pumphrey, H. C., Manney, G. L., Wang, Y., Su, H., Wu, L.,
Read, W. G., and Froidevaux, L.: The Hunga Tonga-Hunga Ha'apai Hydration of
the Stratosphere, Geophys. Res. Lett., 49, e2022GL099381, https://doi.org/10.1029/2022GL099381, 2022.
Murcray, D. G., Murcray, F. J., Barker, D. B., and Mastenbrook, H. J.:
Changes in Stratospheric Water Vapor Associated with the Mount St. Helens
Eruption, Science, 211, 823–824, https://doi.org/10.1126/science.211.4484.823, 1981.
Muser, L. O., Hoshyaripour, G. A., Bruckert, J., Horváth, Á., Malinina, E., Wallis, S., Prata, F. J., Rozanov, A., von Savigny, C., Vogel, H., and Vogel, B.: Particle aging and aerosol–radiation interaction affect volcanic plume dispersion: evidence from the Raikoke 2019 eruption, Atmos. Chem. Phys., 20, 15015–15036, https://doi.org/10.5194/acp-20-15015-2020, 2020.
Nishihama, M., Blanchette, J., Fleig, A., Freeze, M., Patt, F., and Wolfe,
R.: MODIS Level 1A Earth Location ATBD, https://modis.gsfc.nasa.gov/data/atbd/atbd_mod28_v3.pdf (last access: 23 September 2021), 1997.
Oppenheimer, C., Scaillet, B., and Martin, R. S.: Sulfur Degassing From
Volcanoes: Source Conditions, Surveillance, Plume Chemistry and Earth System
Impacts, Rev. Mineral. Geochem., 73, 363–421, https://doi.org/10.2138/rmg.2011.73.13, 2011, 2011.
Pavolonis, M. and Sieglaff, J.: GOES-R Advanced Baseline Imager ATBD for Volcanic Ash, https://www.star.nesdis.noaa.gov/goesr/docs/ATBD/VolAsh.pdf (last access: 22 November 2021), 2012.
Pavolonis, M. J.: Advances in Extracting Cloud Composition Information from
Spaceborne Infrared Radiances – A Robust Alternative to Brightness
Temperatures. Part I: Theory, J. Appl. Meteorol. Clim., 49, 1992–2012,
https://doi.org/10.1175/2010JAMC2433.1, 2010.
Petracca, I. and De Santis, D.: Sentinel-3 SLSTR and MODIS satellite images of Raikoke 2019 and Eyjafjallajökull 2010 eruptions, Zenodo [data set], https://doi.org/10.5281/zenodo.7050771, 2022.
Picchiani, M., Chini, M., Corradini, S., Merucci, L., Sellitto, P., Del Frate, F., and Stramondo, S.: Volcanic ash detection and retrievals using MODIS data by means of neural networks, Atmos. Meas. Tech., 4, 2619–2631, https://doi.org/10.5194/amt-4-2619-2011, 2011.
Picchiani, M., Chini, M., Corradini, S., Merucci, L., Piscini, A., and
Frate, F. D.: Neural network multispectral satellite images classification
of volcanic ash plumes in a cloudy scenario, Ann. Geophys.-Italy, 57, 6638, https://doi.org/10.4401/ag-6638, 2014.
Picchiani, M., Del Frate, F., and Sist, M.: A Neural Network Sea-Ice Cloud
Classification Algorithm for Copernicus Sentinel-3 Sea and Land Surface
Temperature Radiometer, in: Proceedings of IGARSS 2018-2018 IEEE
International Geoscience and Remote Sensing Symposium, Valencia, Spain,
22–27 July 2018, IEEE, 3015–3018, https://doi.org/10.1109/IGARSS.2018.8517857,
2018.
Piscini, A., Carboni, E., Del Frate, F., and Grainger, R. G.: Simultaneous
retrieval of volcanic sulphur dioxide and plume height from hyperspectral
data using artificial neural networks, Geophys. J. Int., 198, 697–709,
https://doi.org/10.1093/gji/ggu152, 2014.
Polehampton, E., Cox, C., Smith, D., Ghent, D., Wooster, M., Xu, W.,
Bruniquel, J., and Dransfeld, S.: Copernicus Sentinel-3 SLSTR Land User Handbook, https://sentinels.copernicus.eu/documents/247904/4598082/Sentinel-3-SLSTR-Land-Handbook.pdf/bee342eb-40d4-9b31-babb-8bea2748264a?t=1663336317087 (last access: 15 January 2022), 2021.
Prata, A. J.: Infrared radiative transfer calculations for volcanic ash
clouds, Geophys. Res. Lett., 16, 1293–1296,
https://doi.org/10.1029/GL016i011p01293, 1989a.
Prata, A. J.: Observations of volcanic ash clouds in the 10–12 µm window using AVHRR/2 data, Int. J. Remote Sens., 10, 751–761, https://doi.org/10.1080/01431168908903916, 1989b.
Prata, A. J. and Grant, I. F.: Determination of mass loadings and plume heights of volcanic ash clouds from satellite data, CSIRO Atmospheric Research, Aspendale, Vic., Australia, http://hdl.handle.net/102.100.100/204502?index=1 (last access: 23 June 2021), 2001.
Prata, A. T., Grainger, R. G., Taylor, I. A., Povey, A. C., Proud, S. R., and Poulsen, C. A.: Uncertainty-bounded estimates of ash cloud properties using the ORAC algorithm: application to the 2019 Raikoke eruption, Atmos. Meas. Tech., 15, 5985–6010, https://doi.org/10.5194/amt-15-5985-2022, 2022.
Prata, F., Bluth, G., Rose, B., Schneider, D., and Tupper, A.: Comments on
“Failures in detecting volcanic ash from a satellite-based technique”,
Remote Sens. Environ., 78, 341–346, https://doi.org/10.1016/S0034-4257(01)00231-0, 2001.
Rose, W. I., Delene, D. J., Schneider, D. J., Bluth, G. J. S., Krueger, A.
J., Sprod, I., McKee, C., Davies, H. L., and Ernst, G. G. J.: Ice in the
1994 Rabaul eruption cloud: Implications for volcano hazard and atmospheric
effects, Nature, 375, 477–479, https://doi.org/10.1038/375477a0, 1995.
Shinohara, H.: Excess degassing from volcanoes and its role on eruptive and
intrusive activity, Rev. Geophys., 46, RG4005, https://doi.org/10.1029/2007RG000244,
2008.
Solomon, S., Daniel, J. S., Neely, R. R., Vernier, J.-P., Dutton, E. G.,
and Thomason, L. W.: The Persistently Variable “Background” Stratospheric
Aerosol Layer and Global Climate Change, Science, 333, 866–870,
https://doi.org/10.1126/science.1206027, 2011.
Toller, G. N., Isaacman, A., Kuyper J., Geng, X. and Xiong, J.: MODIS Level 1B Product User's Guide, https://mcst.gsfc.nasa.gov/sites/default/files/file_attachments/M1054E_PUG_2017_0901_V6.2.2_Terra_V6.2.1_Aqua.pdf (last access: 14 September 2021), 2017.
Vermote, E. F. and Vermeulen, A.: Atmospheric correction algorithm: spectral reflectance, https://eospso.gsfc.nasa.gov/sites/default/files/atbd/atbd_mod08.pdf (last access: 6 May 2021), 1999.
Vogl, T. P., Mangis, J. K., Rigler, A. K., Zink, W. T., and Alkon, D. L.:
Accelerating the convergence of the back-propagation method, Biol. Cybern.,
59, 257–263, https://doi.org/10.1007/BF00332914, 1998.
Xu, J., Li, D., Bai, Z., Tao, M., and Bian, J.: Large Amounts of Water
Vapor Were Injected into the Stratosphere by the Hunga Tonga–Hunga Ha'apai
Volcano Eruption, Atmosphere, 13, 912, https://doi.org/10.3390/atmos13060912, 2022.
Short summary
The authors propose a near-real-time procedure for the detection of volcanic clouds by means of Sentinel-3 satellite data and neural networks. The algorithm results in an automatic image classification where ashy pixels are distinguished from other surfaces with remarkable accuracy. The model is considerably faster if compared to other approaches which are time consuming, case specific, and not automatic. The algorithm can be significantly helpful for emergency management during eruption events.
The authors propose a near-real-time procedure for the detection of volcanic clouds by means of...
