Articles | Volume 13, issue 10
https://doi.org/10.5194/amt-13-5537-2020
© Author(s) 2020. 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-13-5537-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A feasibility study to use machine learning as an inversion algorithm for aerosol profile and property retrieval from multi-axis differential absorption spectroscopy measurements
Yun Dong
Department of Electrical and Computer Engineering, Virginia Tech,
Blacksburg, VA 24060, USA
Elena Spinei
CORRESPONDING AUTHOR
Department of Electrical and Computer Engineering, Virginia Tech,
Blacksburg, VA 24060, USA
Anuj Karpatne
Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, USA
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Zhenyu Zhang, Jing Li, Huizheng Che, Yueming Dong, Oleg Dubovik, Thomas Eck, Pawan Gupta, Brent Holben, Jhoon Kim, Elena Lind, Trailokya Saud, Sachchida Nand Tripathi, and Tong Ying
EGUsphere, https://doi.org/10.5194/egusphere-2024-2533, https://doi.org/10.5194/egusphere-2024-2533, 2024
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We used ground-based remote sensing data from the Aerosol Robotic Network to examine long-term trends in aerosol characteristics. We found aerosol loadings generally decreased globally, and aerosols became more scattering. These changes are closely related to variations in aerosol compositions, such as decreased anthropogenic emissions over East Asia, Europe, and North America, increased anthropogenic source over North India, increased dust activities over the Arabian Peninsula, etc.
Elena Spinei, Martin Tiefengraber, Moritz Müller, Manuel Gebetsberger, Alexander Cede, Luke Valin, James Szykman, Andrew Whitehill, Alexander Kotsakis, Fernando Santos, Nader Abbuhasan, Xiaoyi Zhao, Vitali Fioletov, Sum Chi Lee, and Robert Swap
Atmos. Meas. Tech., 14, 647–663, https://doi.org/10.5194/amt-14-647-2021, https://doi.org/10.5194/amt-14-647-2021, 2021
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Plastics are widely used in everyday life and scientific equipment. This paper presents Delrin plastic off-gassing as a function of temperature on the atmospheric measurements of formaldehyde by Pandora spectroscopic instruments. The sealed telescope assembly containing Delrin components emitted large amounts of formaldehyde at 30–45 °C, interfering with the Pandora measurements. These results have a broader implication since electronic products often experience the same temperature.
Jan-Lukas Tirpitz, Udo Frieß, François Hendrick, Carlos Alberti, Marc Allaart, Arnoud Apituley, Alkis Bais, Steffen Beirle, Stijn Berkhout, Kristof Bognar, Tim Bösch, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Mirjam den Hoed, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Martina M. Friedrich, Arnoud Frumau, Lou Gast, Clio Gielen, Laura Gomez-Martín, Nan Hao, Arjan Hensen, Bas Henzing, Christian Hermans, Junli Jin, Karin Kreher, Jonas Kuhn, Johannes Lampel, Ang Li, Cheng Liu, Haoran Liu, Jianzhong Ma, Alexis Merlaud, Enno Peters, Gaia Pinardi, Ankie Piters, Ulrich Platt, Olga Puentedura, Andreas Richter, Stefan Schmitt, Elena Spinei, Deborah Stein Zweers, Kimberly Strong, Daan Swart, Frederik Tack, Martin Tiefengraber, René van der Hoff, Michel van Roozendael, Tim Vlemmix, Jan Vonk, Thomas Wagner, Yang Wang, Zhuoru Wang, Mark Wenig, Matthias Wiegner, Folkard Wittrock, Pinhua Xie, Chengzhi Xing, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 14, 1–35, https://doi.org/10.5194/amt-14-1-2021, https://doi.org/10.5194/amt-14-1-2021, 2021
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Multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a ground-based remote sensing measurement technique that derives atmospheric aerosol and trace gas vertical profiles from skylight spectra. In this study, consistency and reliability of MAX-DOAS profiles are assessed by applying nine different evaluation algorithms to spectral data recorded during an intercomparison campaign in the Netherlands and by comparing the results to colocated supporting observations.
Karin Kreher, Michel Van Roozendael, Francois Hendrick, Arnoud Apituley, Ermioni Dimitropoulou, Udo Frieß, Andreas Richter, Thomas Wagner, Johannes Lampel, Nader Abuhassan, Li Ang, Monica Anguas, Alkis Bais, Nuria Benavent, Tim Bösch, Kristof Bognar, Alexander Borovski, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Henning Finkenzeller, David Garcia-Nieto, Clio Gielen, Laura Gómez-Martín, Nan Hao, Bas Henzing, Jay R. Herman, Christian Hermans, Syedul Hoque, Hitoshi Irie, Junli Jin, Paul Johnston, Junaid Khayyam Butt, Fahim Khokhar, Theodore K. Koenig, Jonas Kuhn, Vinod Kumar, Cheng Liu, Jianzhong Ma, Alexis Merlaud, Abhishek K. Mishra, Moritz Müller, Monica Navarro-Comas, Mareike Ostendorf, Andrea Pazmino, Enno Peters, Gaia Pinardi, Manuel Pinharanda, Ankie Piters, Ulrich Platt, Oleg Postylyakov, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Alfonso Saiz-Lopez, Anja Schönhardt, Stefan F. Schreier, André Seyler, Vinayak Sinha, Elena Spinei, Kimberly Strong, Frederik Tack, Xin Tian, Martin Tiefengraber, Jan-Lukas Tirpitz, Jeroen van Gent, Rainer Volkamer, Mihalis Vrekoussis, Shanshan Wang, Zhuoru Wang, Mark Wenig, Folkard Wittrock, Pinhua H. Xie, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 13, 2169–2208, https://doi.org/10.5194/amt-13-2169-2020, https://doi.org/10.5194/amt-13-2169-2020, 2020
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In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants during an instrument intercomparison campaign (CINDI-2) at Cabauw, the Netherlands. Here we report on the outcome of this intercomparison exercise. The three major goals were to characterise the differences between the participating instruments, to define a robust methodology for performance assessment, and to contribute to the harmonisation of the measurement settings and retrieval methods.
Caroline R. Nowlan, Xiong Liu, Scott J. Janz, Matthew G. Kowalewski, Kelly Chance, Melanie B. Follette-Cook, Alan Fried, Gonzalo González Abad, Jay R. Herman, Laura M. Judd, Hyeong-Ahn Kwon, Christopher P. Loughner, Kenneth E. Pickering, Dirk Richter, Elena Spinei, James Walega, Petter Weibring, and Andrew J. Weinheimer
Atmos. Meas. Tech., 11, 5941–5964, https://doi.org/10.5194/amt-11-5941-2018, https://doi.org/10.5194/amt-11-5941-2018, 2018
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The GEO-CAPE Airborne Simulator (GCAS) was developed in support of future air quality and ocean color geostationary satellite missions. GCAS flew in its first field campaign on NASA's King Air B-200 aircraft during DISCOVER-AQ Texas in 2013. In this paper, we determine nitrogen dioxide and formaldehyde columns over Houston from the GCAS air quality sensor and compare those results with measurements made from ground-based Pandora spectrometers and in situ airborne instruments.
Elena Spinei, Andrew Whitehill, Alan Fried, Martin Tiefengraber, Travis N. Knepp, Scott Herndon, Jay R. Herman, Moritz Müller, Nader Abuhassan, Alexander Cede, Dirk Richter, James Walega, James Crawford, James Szykman, Lukas Valin, David J. Williams, Russell Long, Robert J. Swap, Youngjae Lee, Nabil Nowak, and Brett Poche
Atmos. Meas. Tech., 11, 4943–4961, https://doi.org/10.5194/amt-11-4943-2018, https://doi.org/10.5194/amt-11-4943-2018, 2018
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Formaldehyde is toxic to humans and is formed in the atmosphere in the presence of air pollution, but the measurements are sparse. Pandonia Global Network instruments measure total formaldehyde column from the surface to the top of troposphere and will be widely available. This study compared formaldehyde Pandora columns with the surface and aircraft-integrated columns near Seoul, South Korea. Relatively good agreement was observed between the three datasets with some overestimation by Pandora.
Jay Herman, Elena Spinei, Alan Fried, Jhoon Kim, Jae Kim, Woogyung Kim, Alexander Cede, Nader Abuhassan, and Michal Segal-Rozenhaimer
Atmos. Meas. Tech., 11, 4583–4603, https://doi.org/10.5194/amt-11-4583-2018, https://doi.org/10.5194/amt-11-4583-2018, 2018
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Nine Pandora Spectrometer Instruments were installed at 8 sites for KORUS-AQ (Korea U.S.-Air Quality) field study from ground, aircraft, and satellite measurements. The quantities retrieved were total column measurements of ozone, nitrogen dioxide, and formaldehyde. We show the distribution of NO2 and HCHO air pollutants vs location and time of day and comparisons with aircraft and satellite data. For some of the sites, long-term time series are available to asses changes.
E. Spinei, A. Cede, J. Herman, G. H. Mount, E. Eloranta, B. Morley, S. Baidar, B. Dix, I. Ortega, T. Koenig, and R. Volkamer
Atmos. Meas. Tech., 8, 793–809, https://doi.org/10.5194/amt-8-793-2015, https://doi.org/10.5194/amt-8-793-2015, 2015
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This paper presents ground-based direct-sun and airborne multi-axis DOAS measurements of O2O2 absorption optical depths under atmospheric conditions in two wavelength regions (335-–390nm and 435--490nm). Our results show that laboratory-measured σ(O2O2) is applicable for observations over a wide range of atmospheric conditions. Temperature dependence of σ(O2O2) is about 9±2.5% from 231K to 275K.
E. Spinei, A. Cede, W. H. Swartz, J. Herman, and G. H. Mount
Atmos. Meas. Tech., 7, 4299–4316, https://doi.org/10.5194/amt-7-4299-2014, https://doi.org/10.5194/amt-7-4299-2014, 2014
V. Buchard, A. M. da Silva, P. Colarco, N. Krotkov, R. R. Dickerson, J. W. Stehr, G. Mount, E. Spinei, H. L. Arkinson, and H. He
Atmos. Chem. Phys., 14, 1929–1941, https://doi.org/10.5194/acp-14-1929-2014, https://doi.org/10.5194/acp-14-1929-2014, 2014
G. Pinardi, M. Van Roozendael, N. Abuhassan, C. Adams, A. Cede, K. Clémer, C. Fayt, U. Frieß, M. Gil, J. Herman, C. Hermans, F. Hendrick, H. Irie, A. Merlaud, M. Navarro Comas, E. Peters, A. J. M. Piters, O. Puentedura, A. Richter, A. Schönhardt, R. Shaiganfar, E. Spinei, K. Strong, H. Takashima, M. Vrekoussis, T. Wagner, F. Wittrock, and S. Yilmaz
Atmos. Meas. Tech., 6, 167–185, https://doi.org/10.5194/amt-6-167-2013, https://doi.org/10.5194/amt-6-167-2013, 2013
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Total column optical depths retrieved from CALIPSO lidar ocean surface backscatter
ALICENET – an Italian network of automated lidar ceilometers for four-dimensional aerosol monitoring: infrastructure, data processing, and applications
Post-process correction improves the accuracy of satellite PM2.5 retrievals
Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites
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
Ground-based contrail observations: comparisons with flight telemetry and contrail model estimates
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
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
Derivation of depolarization ratios of aerosol fluorescence and water vapor Raman backscatters from lidar measurements
Retrieval of stratospheric aerosol extinction coefficients from OMPS-LP 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
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
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
Robert A. Ryan, Mark A. Vaughan, Sharon D. Rodier, Jason L. Tackett, John A. Reagan, Richard A. Ferrare, Johnathan W. Hair, John A. Smith, and Brian J. Getzewich
Atmos. Meas. Tech., 17, 6517–6545, https://doi.org/10.5194/amt-17-6517-2024, https://doi.org/10.5194/amt-17-6517-2024, 2024
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We introduce Ocean Derived Column Optical Depth (ODCOD), a new way to estimate column optical depths using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements from the ocean surface. ODCOD estimates include contributions from particulates in the full column, which CALIOP estimates do not, making it a complement measurement to CALIOP’s standard estimates. We find that ODCOD compares well with other established data sets in the daytime but tends to estimate higher at night.
Annachiara Bellini, Henri Diémoz, Luca Di Liberto, Gian Paolo Gobbi, Alessandro Bracci, Ferdinando Pasqualini, and Francesca Barnaba
Atmos. Meas. Tech., 17, 6119–6144, https://doi.org/10.5194/amt-17-6119-2024, https://doi.org/10.5194/amt-17-6119-2024, 2024
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We provide a comprehensive overview of the Italian Automated LIdar-CEilometer network, ALICENET, describing its infrastructure, aerosol retrievals, and main applications. The supplement covers data-processing details. We include examples of output products, comparisons with independent data, and examples of the network capability to provide near-real-time aerosol fields over Italy. ALICENET is expected to benefit the sectors of air quality, radiative budget/solar energy, and aviation safety.
Andrea Porcheddu, Ville Kolehmainen, Timo Lähivaara, and Antti Lipponen
Atmos. Meas. Tech., 17, 5747–5764, https://doi.org/10.5194/amt-17-5747-2024, https://doi.org/10.5194/amt-17-5747-2024, 2024
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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.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan
Atmos. Meas. Tech., 17, 5455–5476, https://doi.org/10.5194/amt-17-5455-2024, https://doi.org/10.5194/amt-17-5455-2024, 2024
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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 min. 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.
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
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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
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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
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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
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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
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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
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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
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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
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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.
Jade Low, Roger Teoh, Joel Ponsonby, Edward Gryspeerdt, Marc Shapiro, and Marc Stettler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1458, https://doi.org/10.5194/egusphere-2024-1458, 2024
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The radiative forcing due to contrails is the same order of magnitude as aviation CO2 emissions yet has a higher uncertainty. Observations are vital to improve understanding of the contrail lifecycle, to improve model and to measure the effect of mitigation action. Here, we use ground-based cameras combined with flight telemetry to track visible contrails and measure their lifetime and width. We evaluate model predictions and demonstrate the capability of this approach.
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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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.
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
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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.
Alexei Rozanov, Christine Pohl, Carlo Arosio, Adam Bourassa, Klaus Bramstedt, Elizaveta Malinina, Landon Rieger, and John P. Burrows
EGUsphere, https://doi.org/10.5194/egusphere-2024-358, https://doi.org/10.5194/egusphere-2024-358, 2024
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We developed a new algorithm to retrieve vertical distributions of the aerosol extinction coefficient in the stratosphere. The algorithm is applied to measurements of the scattered solar light form the space borne OMPS-LP (Ozone Mapping and Profiler Suite-Limb Profiler) instrument. The retrieval results are compared to the data from other space borne instruments and used to investigate the evolution of the aerosol plume after the eruption of the Hunga Tonga-Hunga Ha'apai volcano in January 2022.
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
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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
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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
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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.
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
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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
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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.
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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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Short summary
This paper is about a feasibility study of applying a machine learning technique to derive aerosol properties from a single MAX-DOAS sky scan, which detects sky-scattered UV–visible photons at multiple elevation angles. Evaluation of retrieved aerosol properties shows good performance of the ML algorithm, suggesting several advantages of a ML-based inversion algorithm such as fast data inversion, simple implementation and the ability to extract information not available using other algorithms.
This paper is about a feasibility study of applying a machine learning technique to derive...