Articles | Volume 13, issue 10
Research article 16 Oct 2020
Research article | 16 Oct 2020
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 et al.
No articles found.
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,
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,
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,
Related subject area
Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information RetrievalSimulated reflectance above snow constrained by airborne measurements of solar radiation: implications for the snow grain morphology in the ArcticModIs Dust AeroSol (MIDAS): a global fine-resolution dust optical depth data setIntegrated System for Atmospheric Boundary Layer Height Estimation (ISABLE) using a ceilometer and microwave radiometerEffects of clouds on the UV Absorbing Aerosol Index from TROPOMICorrection of a lunar-irradiance model for aerosol optical depth retrieval and comparison with a star photometerImproving GOES Advanced Baseline Imager (ABI) aerosol optical depth (AOD) retrievals using an empirical bias correction algorithmStratospheric aerosol extinction profiles from SCIAMACHY solar occultationLeveraging spatial textures, through machine learning, to identify aerosols and distinct cloud types from multispectral observationsRetrieval of aerosol properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017OMPS LP Version 2.0 Multi-wavelength Aerosol Extinction Coefficient Retrieval AlgorithmAn uncertainty-based protocol for the setup and measurement of soot/black carbon emissions from gas flares using sky-LOSAAerosol optical properties as observed from an ultralight aircraft over the Strait of GibraltarEvaluation of a method for converting Stratospheric Aerosol and Gas Experiment (SAGE) extinction coefficients to backscatter coefficients for intercomparison with lidar observationsInversion of multiangular polarimetric measurements from the ACEPOL campaign: an application of improving aerosol property and hyperspectral ocean color retrievalsA new measurement approach for validating satellite-based above cloud aerosol optical depthImproved water vapour retrieval from AMSU-B and MHS in the ArcticThe AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2Issues related to the retrieval of stratospheric-aerosol particle size information based on optical measurementsA new lidar inversion method using a surface reference target applied to the backscattering coefficient and lidar ratio retrievals of a fog-oil plume at short rangeA multi-axis differential optical absorption spectroscopy aerosol profile retrieval algorithm for high-altitude measurements: application to measurements at Schneefernerhaus (UFS), GermanyThe potential of elastic and polarization lidars to retrieve extinction profilesIntroducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol productRetrieval of gridded aerosol direct radiative forcing based on multiplatform datasetsAssessing the stability of surface lights for use in retrievals of nocturnal atmospheric parametersA neural network radiative transfer model approach applied to the Tropospheric Monitoring Instrument aerosol height algorithmApplying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaignAbove-cloud aerosol radiative effects based on ORACLES 2016 and ORACLES 2017 aircraft experimentsThe role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observationsCloud-Aerosol Transport System (CATS) 1064 nm calibration and validationCALIPSO level 3 stratospheric aerosol profile product: version 1.00 algorithm description and initial assessmentNeural network for aerosol retrieval from hyperspectral imageryUnified quantitative observation of coexisting volcanic sulfur dioxide and sulfate aerosols using ground-based Fourier transform infrared spectroscopyAerosol direct radiative effect over clouds from a synergy of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) reflectancesA Tale of Two Dust Storms: analysis of a complex dust event in the Middle EastDust mass, cloud condensation nuclei, and ice-nucleating particle profiling with polarization lidar: updated POLIPHON conversion factors from global AERONET analysis3+2 + X: what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?Analyzing the atmospheric boundary layer using high-order moments obtained from multiwavelength lidar data: impact of wavelength choiceYear-round stratospheric aerosol backscatter ratios calculated from lidar measurements above northern NorwayInversion of multiangular polarimetric measurements over open and coastal ocean waters: a joint retrieval algorithm for aerosol and water-leaving radiance propertiesAn adaptation of the CO2 slicing technique for the Infrared Atmospheric Sounding Interferometer to obtain the height of tropospheric volcanic ash cloudsMethod to retrieve cloud condensation nuclei number concentrations using lidar measurementsAerosol-type classification based on AERONET version 3 inversion productsThe Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm: version 4.1 description and evaluationTwo decades observing smoke above clouds in the south-eastern Atlantic Ocean: Deep Blue algorithm updates and validation with ORACLES field campaign dataDetecting layer height of smoke aerosols over vegetated land and water surfaces via oxygen absorption bands: hourly results from EPIC/DSCOVR in deep spaceA new method to determine the aerosol optical properties from multiple-wavelength O4 absorptions by MAX-DOAS observationCharacterization and application of artificial light sources for nighttime aerosol optical depth retrievals using the Visible Infrared Imager Radiometer Suite Day/Night BandPlanetary boundary layer height by means of lidar and numerical simulations over New Delhi, IndiaCharacterization of atmospheric aerosol optical properties based on the combined use of a ground-based Raman lidar and an airborne optical particle counter in the framework of the Hydrological Cycle in the Mediterranean Experiment – Special Observation Period 1A bulk-mass-modeling-based method for retrieving particulate matter pollution using CALIOP observations
Soheila Jafariserajehlou, Vladimir V. Rozanov, Marco Vountas, Charles K. Gatebe, and John P. Burrows
Atmos. Meas. Tech., 14, 369–389,Short summary
In this work, we study retrieval of snow grain morphologies and their impact on the reflectance in a coupled snow–atmosphere system. We present a sensitivity study to highlight the importance of having adequate information about snow and atmosphere. A novel two-stage algorithm for retrieving the size and shape of snow grains is presented. The reflectance simulation results are compared to that of airborne measurements; high correlations of 0.98 at IR and 0.88–0.98 at VIS are achieved.
Antonis Gkikas, Emmanouil Proestakis, Vassilis Amiridis, Stelios Kazadzis, Enza Di Tomaso, Alexandra Tsekeri, Eleni Marinou, Nikos Hatzianastassiou, and Carlos Pérez García-Pando
Atmos. Meas. Tech., 14, 309–334,Short summary
We present the development of the MIDAS (ModIs Dust AeroSol) data set, providing daily dust optical depth (DOD; 550 nm) at a global scale and fine spatial resolution (0.1° x 0.1°) over a 15-year period (2003–2017). It has been developed via the synergy of MODIS-Aqua and MERRA-2 data, while CALIOP and AERONET retrievals are used for its assessment. MIDAS upgrades existing dust observational capabilities, and it is suitable for dust climatological studies, model evaluation, and data assimilation.
Jae-Sik Min, Moon-Soo Park, Jung-Hoon Chae, and Minsoo Kang
Atmos. Meas. Tech., 13, 6965–6987,Short summary
An algorithm for an integrated system for ABLH estimation (ISABLE) was developed and applied to the vertical profile data obtained by a ceilometer and a microwave radiometer in Seoul city, Korea. The ISABLE algorithm finds an optimal ABLH through the post-processing including k-means clustering and density-based spatial clustering of applications with noise (DBSCAN) techniques. The ISABLE ABLH exhibited better performance than those obtained by most conventional methods.
Maurits L. Kooreman, Piet Stammes, Victor Trees, Maarten Sneep, L. Gijsbert Tilstra, Martin de Graaf, Deborah C. Stein Zweers, Ping Wang, Olaf N. E. Tuinder, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 6407–6426,Short summary
We investigated the influence of clouds on the Absorbing Aerosol Index (AAI), an indicator of the presence of small particles in the atmosphere. Clouds produce artifacts in AAI calculations on the individual measurement (7 km) scale, which was not seen with previous instruments, as well as on large (1000+ km) scales. To reduce these artefacts, we used three different AAI calculation techniques of varying complexity. We find that the AAI artifacts are reduced when using more complex techniques.
Roberto Román, Ramiro González, Carlos Toledano, África Barreto, Daniel Pérez-Ramírez, Jose A. Benavent-Oltra, Francisco J. Olmo, Victoria E. Cachorro, Lucas Alados-Arboledas, and Ángel M. de Frutos
Atmos. Meas. Tech., 13, 6293–6310,Short summary
Atmospheric-aerosol and gaseous properties can be derived at night-time if the lunar irradiance at the ground is measured. To this end, the knowledge of lunar irradiance at the top of the atmosphere is necessary. This extraterrestrial lunar irradiance is usually calculated by models since it varies with several geometric factors mainly depending on time and location. This paper proposes a correction to the most used lunar-irradiance model to be applied for atmospheric-aerosol characterization.
Hai Zhang, Shobha Kondragunta, Istvan Laszlo, and Mi Zhou
Atmos. Meas. Tech., 13, 5955–5975,Short summary
Geostationary Operational Environmental Satellites (GOES) retrieve high temporal resolution aerosol optical depth, which is a measure of the aerosol quantity within the atmospheric column. This work introduces an algorithm that improves the accuracy of the aerosol optical depth retrievals from GOES. The resulting data product can be used in monitoring the air quality and climate change research.
Stefan Noël, Klaus Bramstedt, Alexei Rozanov, Elizaveta Malinina, Heinrich Bovensmann, and John P. Burrows
Atmos. Meas. Tech., 13, 5643–5666,Short summary
A new approach to derive stratospheric aerosol extinction profiles from SCIAMACHY solar occultation measurements based on an onion-peeling method is presented. The resulting extinctions at 452, 525 and 750 nm compare well with other limb and occultation data from, e.g. SAGE and SCIAMACHY, but show small oscillating features which vanish in monthly anomalies. Major volcanic eruptions, polar stratospheric clouds and influences of the quasi-biennial oscillation can be identified in the time series.
Willem J. Marais, Robert E. Holz, Jeffrey S. Reid, and Rebecca M. Willett
Atmos. Meas. Tech., 13, 5459–5480,Short summary
Space agencies use moderate-resolution satellite imagery to study how smoke, dust, pollution (aerosols) and cloud types impact the Earth's climate; these space agencies include NASA, ESA and the China Meteorological Administration. We demonstrate in this paper that an algorithm with convolutional neural networks can greatly enhance the automated detection of aerosols and cloud types from satellite imagery. Our algorithm is an improvement on current aerosol and cloud detection algorithms.
Anin Puthukkudy, J. Vanderlei Martins, Lorraine A. Remer, Xiaoguang Xu, Oleg Dubovik, Pavel Litvinov, Brent McBride, Sharon Burton, and Henrique M. J. Barbosa
Atmos. Meas. Tech., 13, 5207–5236,Short summary
In this work, we report the demonstration and validation of the aerosol properties retrieved using AirHARP and GRASP for data from the NASA ACEPOL campaign 2017. These results serve as a proxy for the scale and detail of aerosol retrievals that are anticipated from future space mission data, as HARP CubeSat (mission begins 2020) and HARP2 (aboard the NASA PACE mission with the launch in 2023) are near duplicates of AirHARP and are expected to provide the same level of aerosol characterization.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
This work describes the newly released OMPS LP aerosol extinction profiles multi-wavelength Version 2.0 algorithm and data set. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Bradley M. Conrad and Matthew R. Johnson
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
A general uncertainty analysis (GUA) is performed for the sky-LOSA technique used to remotely measure soot emissions from gas flares. GUA data are compiled in an open-source software tool to help sky-LOSA users select critical setup and acquisition parameters while giving quantitative visual feedback on anticipated uncertainties for a specific measurement. The software tool enables easy acquisition of optimal measurement data, significantly increasing the accessibility of the sky-LOSA technique.
Atmos. Meas. Tech., 13, 4461–4477,Short summary
By coupling lidar on board a ULA and ground-based lidar measurements, this paper highlights aerosol transport over the Strait of Gibraltar. It shows that the lidar-derived aerosol optical properties can be different from what is commonly accepted. It presents unprecedented vertical profiles over this region and relates them to the origin of air masses. The results are based on ground, airborne, and spaceborne observations, as well as multiple retro-trajectory analyses.
Travis N. Knepp, Larry Thomason, Marilee Roell, Robert Damadeo, Kevin Leavor, Thierry Leblanc, Fernando Chouza, Sergey Khaykin, Sophie Godin-Beekmann, and David Flittner
Atmos. Meas. Tech., 13, 4261–4276,Short summary
Two common measurements that represent atmospheric aerosol loading are the backscatter and extinction coefficients. Measuring backscatter and extinction coefficients requires different viewing geometries and fundamentally different instrument systems. Further, these coefficients are not directly comparable. We present an algorithm to convert SAGE-observed extinction coefficients to backscatter coefficients for intercomparison with lidar backscatter products, followed by evaluation of the method.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Kirk Knobelspiesse, Amir Ibrahim, Brian Cairns, Susanne E. Craig, Guangliang Fu, Otto Hasekamp, Yongxiang Hu, and P. Jeremy Werdell
Atmos. Meas. Tech., 13, 3939–3956,
Charles K. Gatebe, Hiren Jethva, Ritesh Gautam, Rajesh Poudyal, and Tamas Várnai
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
The retrieval of aerosol parameters from passive satellite instruments in cloudy scenes is challenging, partly because clouds and cloud-related processes may significantly modify the aerosol properties and partly because of the 3D radiative effects. This study shows demonstrate a novel airborne measurement approach for assessing satellite retrievals of aerosols above clouds using SAFARI 2000 field data over ocean, thereby filling a major gap that exists in the global aerosol observations.
Arantxa M. Triana-Gómez, Georg Heygster, Christian Melsheimer, Gunnar Spreen, Monia Negusini, and Boyan H. Petkov
Atmos. Meas. Tech., 13, 3697–3715,Short summary
In the Arctic, in situ measurements are sparse and standard remote sensing retrieval methods have problems. We present advances in a retrieval algorithm for vertically integrated water vapour tuned for polar regions. In addition to the initial sensor used (AMSU-B), we can now also use data from the successor instrument (MHS). Additionally, certain artefacts are now filtered out. Comparison with radiosondes shows the overall good performance of the updated algorithm.
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Sergey Korkin, Joel S. Schafer, Alexander Smirnov, Mikhail Sorokin, and Alexei Lyapustin
Atmos. Meas. Tech., 13, 3375–3411,
Christian von Savigny and Christoph G. Hoffmann
Atmos. Meas. Tech., 13, 1909–1920,Short summary
Stratospheric sulfate aerosols increase the Earth's planetary albedo and can lead to significant surface cooling, for example in the aftermath of volcanic eruptions. Their particle size distribution, important for physical and chemical effects of these aerosols, is still not fully understood. The present paper proposes an explanation for systematic differences in aerosol particle size retrieved from measurements made in different measurement geometries and reported in earlier studies.
Florian Gaudfrin, Olivier Pujol, Romain Ceolato, Guillaume Huss, and Nicolas Riviere
Atmos. Meas. Tech., 13, 1921–1935,Short summary
A new elastic lidar inversion equation is presented. It is based on the backscattering signal from a surface reference target rather than that from a volumetric layer of reference as is usually done. The method presented can be used in the case of airborne elastic lidar measurements or when the lidar–target line is horizontal. Also, a new algorithm is described to retrieve the lidar ratio and the backscattering coefficient of an aerosol plume without any a priori assumptions about the plume.
Zhuoru Wang, Ka Lok Chan, Klaus-Peter Heue, Adrian Doicu, Thomas Wagner, Robert Holla, and Matthias Wiegner
Atmos. Meas. Tech., 13, 1835–1866,Short summary
We present a new aerosol profile retrieval algorithm for MAX-DOAS measurements at high-altitude sites and applied to the MAX-DOAS measurements at UFS. The retrieval algorithm is based on a O4 DSCD lookup table which is dedicated to high-altitude MAX-DOAS measurements. The comparison of retrieved aerosol optical depths (AODs) to sun photometer observations shows good agreement with a correlation coefficient (R) of 0.733 and 0.798 at 360 and 477 nm, respectively.
Elina Giannakaki, Panos Kokkalis, Eleni Marinou, Nikolaos S. Bartsotas, Vassilis Amiridis, Albert Ansmann, and Mika Komppula
Atmos. Meas. Tech., 13, 893–905,Short summary
A new method, called ElEx, is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. Comparisons with both Raman lidar profiles during nightime and sun photometer daytime aerosol optical depth observations demonstrate the potential of the ElEx methodology.
Michael J. Garay, Marcin L. Witek, Ralph A. Kahn, Felix C. Seidel, James A. Limbacher, Michael A. Bull, David J. Diner, Earl G. Hansen, Olga V. Kalashnikova, Huikyo Lee, Abigail M. Nastan, and Yan Yu
Atmos. Meas. Tech., 13, 593–628,Short summary
The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version (V23) of the MISR aerosol products, which is reported on a 4.4 km spatial grid and contains retrieved aerosol optical depth and aerosol particle property information derived over both land and water. The changes implemented in V23 have significant impacts on the data product and its interpretation.
Yanyu Wang, Rui Lyu, Xin Xie, Ze Meng, Meijin Huang, Junshi Wu, Haizhen Mu, Qiu-Run Yu, Qianshan He, and Tiantao Cheng
Atmos. Meas. Tech., 13, 575–592,Short summary
A satellite-based method for clear-sky aerosol direct radiative forcing (ADRF) retrieval and spatiotemporal characteristics of ADRF in eastern China were displayed during 2000–2016. Our analysis shows aerosols have a strong cooling effect at the surface, and the changes of ADRF are closely related to the changes of AOD with the development of economic growth and rapid urbanization in eastern China.
Jeremy E. Solbrig, Steven D. Miller, Jianglong Zhang, Lewis Grasso, and Anton Kliewer
Atmos. Meas. Tech., 13, 165–190,Short summary
New satellite sensors are able to view visible light, such as that emitted by cities, at night. It may be possible to use the light from cities to assess the amount of particulate matter in the atmosphere and the thickness of clouds. To do this we must understand how light emitted from the Earth's surface changes with time and viewing conditions. This study takes a step towards understanding the characteristics of light emitted by cities and its stability in time.
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Mark ter Linden, Maarten Sneep, Johan de Haan, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 6619–6634,Short summary
This paper discusses a neural network forward model used by the operational aerosol layer height (ALH) retrieval algorithm for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Sentinel-5 Precursor satellite mission. This model replaces online radiative transfer calculations within the oxygen A-band, improving the speed of the algorithm by 3 orders of magnitude. With this advancement in the algorithm's speed, TROPOMI is set to deliver the ALH product operationally.
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Robert E. Holz, and Andrew K. Heidinger
Atmos. Meas. Tech., 12, 6557–6577,Short summary
Aerosol optical depth (AOD) from a geostationary satellite has been retrieved, and validated and diurnal cycles of aerosols are discussed over the eastern hemisphere and a 2-month period of May–June 2016. The new AOD product matches well with AERONET as well as with the standard MODIS product. Future work to make this algorithm operational will need to re-examine masking including snow masks, re-evaluate assumed aerosol models for geosynchronous geometry and address the surface characterization.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Steven Platnick, Kerry Meyer, Rich Ferrare, Sharon Burton, Chris Hostetler, Steven Howell, Steffen Freitag, Amie Dobracki, and Sarah Doherty
Atmos. Meas. Tech., 12, 6505–6528,Short summary
For two cases from the NASA ORACLES experiments, we retrieve aerosol and cloud properties and calculate a direct aerosol radiative effect (DARE). We investigate the relationship between DARE and the cloud albedo by specifying the albedo for which DARE transitions from a cooling to warming radiative effect. Our new aerosol retrieval algorithm is successful despite complexities associated with scenes that contain aerosols above clouds and decreases the uncertainty on retrieved aerosol parameters.
Jiyunting Sun, Pepijn Veefkind, Swadhin Nanda, Peter van Velthoven, and Pieternel Levelt
Atmos. Meas. Tech., 12, 6319–6340,Short summary
Single scattering albedo (SSA) is critical for reducing uncertainties in radiative forcing assessment. This paper presents two methods to retrieve SSA from satellite observations of the near-UV absorbing aerosol index (UVAI). The first is physically based radiative transfer simulations; the second is a statistically based machine learning algorithm. The result of the latter is encouraging. Both methods show that the ALH is necessary to quantitatively interpret aerosol absorption from UVAI.
Rebecca M. Pauly, John E. Yorks, Dennis L. Hlavka, Matthew J. McGill, Vassilis Amiridis, Stephen P. Palm, Sharon D. Rodier, Mark A. Vaughan, Patrick A. Selmer, Andrew W. Kupchock, Holger Baars, and Anna Gialitaki
Atmos. Meas. Tech., 12, 6241–6258,Short summary
The Cloud Aerosol Transport System (CATS) demonstrated that direct calibration of 1064 nm lidar data from a spaceborne platform is possible. By normalizing the CATS signal to a modeled molecular backscatter profile the CATS data were calibrated, enabling the derivation of optical properties of clouds and aerosols. Comparisons of the calibrated signal with airborne lidar, ground-based lidar, and spaceborne lidar all show agreement within the estimated error bars of the respective instruments.
Jayanta Kar, Kam-Pui Lee, Mark A. Vaughan, Jason L. Tackett, Charles R. Trepte, David M. Winker, Patricia L. Lucker, and Brian J. Getzewich
Atmos. Meas. Tech., 12, 6173–6191,Short summary
This work describes the science algorithm for the recently released CALIPSO level 3 stratospheric aerosol product. It is shown that the retrieved extinction profiles capture the major stratospheric perturbations over the last decade resulting from volcanic eruptions, pyroCb smoke events, and signatures of stratospheric dynamics. An initial assessment is also provided by intercomparison with the latest aerosol retrievals from the SAGE III instrument aboard the International Space Station.
Steffen Mauceri, Bruce Kindel, Steven Massie, and Peter Pilewskie
Atmos. Meas. Tech., 12, 6017–6036,Short summary
Aerosols are fine particles that are suspended in Earth’s atmosphere. A better understanding of aerosols is important to lower uncertainties in climate predictions. We propose measuring aerosols from satellites and airplanes equipped with hyperspectral cameras using an artificial neural network, a form of machine learning. We applied our neural network to hyperspectral observations from a recent airplane flight over India and find general agreement with independent aerosol measurements.
Pasquale Sellitto, Henda Guermazi, Elisa Carboni, Richard Siddans, and Mike Burton
Atmos. Meas. Tech., 12, 5381–5389,Short summary
Volcanoes release complex plumes of gas and particles. Volcanic gases, like SO2, can additionally condense, once released, to form particles, sulphate aerosol (SA). Observing simultaneously SO2+SA is important: their proportion provides information on the internal state of volcanoes, and can be used to predict plumes' atmospheric evolution and their environmental and climatic impacts. We developed a new method to observe simultaneously, for the first time, SO2+SA using infrared remote sensing.
Martin de Graaf, L. Gijsbert Tilstra, and Piet Stammes
Atmos. Meas. Tech., 12, 5119–5135,Short summary
A new algorithm is described, which was used to derive direct radiative effects of aerosols above clouds. These effects are among the largest uncertainties in global climate model simulations, and observations are needed to constrain these simulations. A recently developed method was applied to a combination of satellite reflectance measurements to cover the entire shortwave (solar) spectrum. Radiative effects of aerosols over the south-east Atlantic are presented, where the effects are largest.
Steven D. Miller, Louie D. Grasso, Qijing Bian, Sonia M. Kreidenweis, Jack F. Dostalek, Jeremy E. Solbrig, Jennifer Bukowski, Susan C. van den Heever, Yi Wang, Xiaoguang Xu, Jun Wang, Annette L. Walker, Ting-Chi Wu, Milija Zupanski, Christine Chiu, and Jeffrey S. Reid
Atmos. Meas. Tech., 12, 5101–5118,Short summary
Satellite–based detection of lofted mineral via infrared–window channels, well established in the literature, faces significant challenges in the presence of atmospheric moisture. Here, we consider a case featuring the juxtaposition of two dust plumes embedded within dry and moist air masses. The case is considered from the vantage points of numerical modeling, multi–sensor observations, and radiative transfer theory arriving at a new method for mitigating the water vapor masking effect.
Albert Ansmann, Rodanthi-Elisavet Mamouri, Julian Hofer, Holger Baars, Dietrich Althausen, and Sabur F. Abdullaev
Atmos. Meas. Tech., 12, 4849–4865,
Matthias Tesche, Alexei Kolgotin, Moritz Haarig, Sharon P. Burton, Richard A. Ferrare, Chris A. Hostetler, and Detlef Müller
Atmos. Meas. Tech., 12, 4421–4437,Short summary
Today, few lidar are capable of triple-wavelength particle linear depolarization ratio (PLDR) measurements. This study is the first systematic investigation of the effect of different choices of PLDR input on the inversion of lidar measurements of mineral dust and dusty mixtures using light scattering by randomly oriented spheroids. We provide recommendations of the most suitable input parameters for use with the applied methodology, based on a relational assessment of the inversion output.
Gregori de Arruda Moreira, Fábio Juliano da Silva Lopes, Juan Luis Guerrero-Rascado, Jonatan João da Silva, Antonio Arleques Gomes, Eduardo Landulfo, and Lucas Alados-Arboledas
Atmos. Meas. Tech., 12, 4261–4276,Short summary
In this paper, we present a comparative analysis of the use of lidar-backscattered signals at three wavelengths (355, 532 and 1064 nm) to study the ABL by investigating high-order moments, which gives us information about the ABL height (derived using the variance method), aerosol layer movements (skewness) and mixing conditions (kurtosis) at several heights.
Arvid Langenbach, Gerd Baumgarten, Jens Fiedler, Franz-Josef Lübken, Christian von Savigny, and Jacob Zalach
Atmos. Meas. Tech., 12, 4065–4076,Short summary
Stratospheric aerosol backscatter ratios in the Arctic using Rayleigh, Mie and Raman backscattered signals were calculated. A backscatter ratio calculation during daytime was performed for the first time. Sharp aerosol layers thinner than 1 km over several days were observed. The seasonal cycle of stratospheric background aerosol in high latitudes including the summer months was calculated for the first time. Top altitude of the aerosol layer was found to reach up to 34 km, especially in summer.
Meng Gao, Peng-Wang Zhai, Bryan A. Franz, Yongxiang Hu, Kirk Knobelspiesse, P. Jeremy Werdell, Amir Ibrahim, Brian Cairns, and Alison Chase
Atmos. Meas. Tech., 12, 3921–3941,
Isabelle A. Taylor, Elisa Carboni, Lucy J. Ventress, Tamsin A. Mather, and Roy G. Grainger
Atmos. Meas. Tech., 12, 3853–3883,Short summary
Volcanic ash is a hazard associated with volcanoes. Knowing an ash cloud’s location is essential for minimising the hazard. This includes knowing the height. This study adapted a well-known technique for obtaining the height of meteorological clouds, known as CO2 slicing, for volcanic ash. Modelled data were used to refine the method and then demonstrate that the technique could work for volcanic ash. It was then successfully applied to data from the Eyjafjallajökull and Grímsvötn eruptions.
Wangshu Tan, Gang Zhao, Yingli Yu, Chengcai Li, Jian Li, Ling Kang, Tong Zhu, and Chunsheng Zhao
Atmos. Meas. Tech., 12, 3825–3839,Short summary
A new method to retrieve CCN number concentrations using multiwavelength Raman lidars is proposed. The method implements hygroscopic enhancements of backscatter and extinction with relative humidity to represent particle hygroscopicity. The retrieved CCN number concentrations are in good agreement with theoretical calculated values. Sensitivity tests indicate that retrieval error in CCN arises mostly from uncertainties in extinction coefficients and RH profiles.
Sung-Kyun Shin, Matthias Tesche, Youngmin Noh, and Detlef Müller
Atmos. Meas. Tech., 12, 3789–3803,Short summary
This study proposes an aerosol-type classification based on parameters from the AErosol RObotic NETwork (AERONET) version 3 level 2.0 inversion product that describe light depolarization and absorption properties of atmospheric particles. We compare our classification with an earlier method and find that the new approach allows for a refined classification of mineral dust that occurs as a mixture with other absorbing aerosols.
Sieglinde Callewaert, Sophie Vandenbussche, Nicolas Kumps, Arve Kylling, Xiaoxia Shang, Mika Komppula, Philippe Goloub, and Martine De Mazière
Atmos. Meas. Tech., 12, 3673–3698,Short summary
This article presents the updated MAPIR algorithm, which uses infrared satellite data to obtain the global 3-D distribution of mineral aerosols. A description of the method together with its technical improvements is given. Additionally, a 10-year data set was generated and used to evaluate this new algorithm against AERONET, CALIOP, CATS and two ground-based lidar stations. We have shown that the new MAPIR algorithm provides reliable aerosol optical depth and dust layer mean altitude profiles.
Andrew M. Sayer, N. Christina Hsu, Jaehwa Lee, Woogyung V. Kim, Sharon Burton, Marta A. Fenn, Richard A. Ferrare, Meloë Kacenelenbogen, Samuel LeBlanc, Kristina Pistone, Jens Redemann, Michal Segal-Rozenhaimer, Yohei Shinozuka, and Si-Chee Tsay
Atmos. Meas. Tech., 12, 3595–3627,Short summary
Aerosols are small particles in the atmosphere such as dust or smoke. They are routinely monitored by satellites due to their importance for climate and air quality. However aerosols above clouds are more difficult to monitor. This study describes an improvement to a technique to monitor light-absorbing aerosols above clouds from four Earth-orbiting satellite instruments. The improved method is evaluated using data from the ORACLES field campaign, which measured these aerosols from aircraft.
Xiaoguang Xu, Jun Wang, Yi Wang, Jing Zeng, Omar Torres, Jeffrey S. Reid, Steven D. Miller, J. Vanderlei Martins, and Lorraine A. Remer
Atmos. Meas. Tech., 12, 3269–3288,Short summary
Detecting aerosol layer height from space is challenging. The traditional method relies on active sensors such as lidar that provide the detailed vertical structure of the aerosol profile but is costly with limited spatial coverage (more than 1 year is needed for global coverage). Here we developed a passive remote sensing technique that uses backscattered sunlight to retrieve smoke aerosol layer height over both water and vegetated surfaces from a sensor 1.5 million kilometers from the Earth.
Chengzhi Xing, Cheng Liu, Shanshan Wang, Qihou Hu, Haoran Liu, Wei Tan, Wenqiang Zhang, Bo Li, and Jianguo Liu
Atmos. Meas. Tech., 12, 3289–3302,Short summary
Ground-based MAX-DOAS has been utilized for the remote sensing of aerosol and trace gases for more than 10 years. Here we developed a new method to determine the aerosol optical properties, including scattering and absorption, from multiple-wavelength O4 absorptions from ground-based MAX-DOAS observations, which were validated well by other independent instruments at low elevations. It is beneficial to obtain the vertical profiles of aerosol properties using multiple elevations.
Jianglong Zhang, Shawn L. Jaker, Jeffrey S. Reid, Steven D. Miller, Jeremy Solbrig, and Travis D. Toth
Atmos. Meas. Tech., 12, 3209–3222,Short summary
Using nighttime observations from the Visible Infrared Imager Radiometer Suite (VIIRS) Day/Night band (DNB), the characteristics of artificial light sources are evaluated as functions of observation conditions, and incremental improvements are documented on nighttime aerosol retrievals on a regional scale. Results from the study indicate the potential of this method to begin filling critical gaps in diurnal aerosol optical thickness information at both regional and global scales.
Konstantina Nakoudi, Elina Giannakaki, Aggeliki Dandou, Maria Tombrou, and Mika Komppula
Atmos. Meas. Tech., 12, 2595–2610,Short summary
We characterized the height of the boundary layer (BLH) over New Delhi for almost a year using ground and satellite lidar measurements as well as model simulations. In the presence of multiple aerosol layers, the employed algorithm was very efficient. Due to prevailing meteorological conditions, the seasonal BLH cycle was slightly weaker than the one expected from the climatology. The aim was to assess the feasibility of the employed algorithm and compare the results to independent sources.
Dario Stelitano, Paolo Di Girolamo, Andrea Scoccione, Donato Summa, and Marco Cacciani
Atmos. Meas. Tech., 12, 2183–2199,Short summary
Vertical profiles of the particle backscattering coefficient at 355, 532 and 1064 nm measured by the Raman lidar system BASIL are compared with simulated particle backscatter profiles obtained through the application of a Mie scattering code and the use of simultaneous and co-located measurements by an optical particle counter on board the French research aircraft ATR42 operated by SAFIRE in the framework of the Hydrological Cycle in the Mediterranean Experiment – Special Observation Period 1.
Travis D. Toth, Jianglong Zhang, Jeffrey S. Reid, and Mark A. Vaughan
Atmos. Meas. Tech., 12, 1739–1754,Short summary
An innovative method is presented for deriving particulate matter (PM) concentrations using CALIOP measurements. Deviating from conventional approaches of relying on passive satellite column-integrated aerosol measurements, PM concentrations are derived from near-surface CALIOP measurements through a bulk-mass-modeling method. This proof-of-concept study shows that, while limited in spatial and temporal coverage, CALIOP exhibits reasonable skill for PM applications.
Amiridis, V., Marinou, E., Tsekeri, A., Wandinger, U., Schwarz, A., Giannakaki, E., Mamouri, R., Kokkalis, P., Binietoglou, I., Solomos, S., Herekakis, T., Kazadzis, S., Gerasopoulos, E., Proestakis, E., Kottas, M., Balis, D., Papayannis, A., Kontoes, C., Kourtidis, K., Papagiannopoulos, N., Mona, L., Pappalardo, G., Le Rille, O., and Ansmann, A.: LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET, Atmos. Chem. Phys., 15, 7127–7153, https://doi.org/10.5194/acp-15-7127-2015, 2015.
Beirle, S., Dörner, S., Donner, S., Remmers, J., Wang, Y., and Wagner, T.: The Mainz profile algorithm (MAPA), Atmos. Meas. Tech., 12, 1785–1806, https://doi.org/10.5194/amt-12-1785-2019, 2019.
Bodhaine, B. A., Wood, N. B., Dutton, E. G., and Slusser, J. R.: On Rayleigh Optical Depth Calculations, J. Atmos. Ocean. Tech., 16, 1854–1861, https://doi.org/10.1175/1520-0426(1999)016<1854:ORODC>2.0.CO;2, 1999.
Britz, D.: Recurrent Neural Networks Tutorial, Part 1 – Introduction to RNNs, WildML, available at: http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/ (last access: 15 January 2020), 2015.
Clémer, K., Van Roozendael, M., Fayt, C., Hendrick, F., Hermans, C., Pinardi, G., Spurr, R., Wang, P., and De Mazière, M.: Multiple wavelength retrieval of tropospheric aerosol optical properties from MAXDOAS measurements in Beijing, Atmos. Meas. Tech., 3, 863–878, https://doi.org/10.5194/amt-3-863-2010, 2010.
Dong, Y., Spinei, E., and Karpatne, A.: synthetic-AMFs-ML, University Libraries, Virginia Tech, https://doi.org/10.7294/6A3T-ZV25, 2019.
Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanré, D., and Slutsker, I.: Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations, J. Atmos. Sci., 59, 590–608, https://doi.org/10.1175/1520-0469(2002)059<0590:VOAAOP>2.0.CO;2, 2002.
Efremenko, D. S., Loyola R., D. G., Hedelt, P., and Spurr, R. J. D.: Volcanic SO2 plume height retrieval from UV sensors using a full-physics inverse learning machine algorithm, Int. J. Remote Sens., 38, 1–27, https://doi.org/10.1080/01431161.2017.1348644, 2017.
Frieß, U., Beirle, S., Alvarado Bonilla, L., Bösch, T., Friedrich, M. M., Hendrick, F., Piters, A., Richter, A., van Roozendael, M., Rozanov, V. V., Spinei, E., Tirpitz, J.-L., Vlemmix, T., Wagner, T., and Wang, Y.: Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies using synthetic data, Atmos. Meas. Tech., 12, 2155–2181, https://doi.org/10.5194/amt-12-2155-2019, 2019.
Fukushima, K.: Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position, Biol. Cybernetics, 36, 193–202, https://doi.org/10.1007/BF00344251, 1980.
Glorot, X. and Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks, 8, available at: http://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf (last access: 8 September 2020), 2010.
Graves, A. and Schmidhuber, J.: Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks, in: Advances in Neural Information Processing Systems 21, edited by: Koller, D., Schuurmans, D., Bengio, Y., and Bottou, L., 545–552, Curran Associates, Inc., available at: http://papers.nips.cc/paper/3449-offline-handwriting-recognition-with-multidimensional-recurrent-neural-networks.pdf (last access: 4 January 2020), 2009.
Graves, A., Liwicki, M., Bunke, H., Schmidhuber, J., and Fernández, S.: Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks, in: Advances in Neural Information Processing Systems 20, edited by: Platt, J. C., Koller, D., Singer, Y., and Roweis, S. T., 577–584, Curran Associates, Inc., available at: http://papers.nips.cc/paper/3213-unconstrained-on-line-handwriting-recognition-with-recurrent-neural-networks.pdf (last access: 4 January 2020), 2008.
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.
Hedelt, P., Efremenko, D. S., Loyola, D. G., Spurr, R., and Clarisse, L.: Sulfur dioxide layer height retrieval from Sentinel-5 Precursor/TROPOMI using FP_ILM, Atmos. Meas. Tech., 12, 5503–5517, https://doi.org/10.5194/amt-12-5503-2019, 2019.
Hinton, G.: Neural Networks for Machine Learning Lecture 6a, available at: https://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf (last access: 16 March 2019), 2012.
Hochreiter, S. and Schmidhuber, J.: Long Short-Term Memory, Neural Comput., 9, 1735–1780, 1997.
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1535 pp., 2013.
Johansson, E. M., Dowla, F. U., and Goodman, D. M.: Backpropagation learning for multilayer feed-forward neural networks using the conjugate gradient method, Int. J. Neur. Syst., 2, 291–301, https://doi.org/10.1142/S0129065791000261, 1991.
Krizhevsky, A., Sutskever, I., and Hinton, G. E.: ImageNet Classification with Deep Convolutional Neural Networks, in: Advances in Neural Information Processing Systems 25, edited by: Pereira, F., Burges, C. J. C., Bottou, L., and Weinberger, K. Q., 1097–1105, Curran Associates, Inc., available at: http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf (last access: 4 January 2020), 2012.
LeCun, Y., Haffner, P., Bottou, L., and Bengio, Y.: Object Recognition with Gradient-Based Learning, in: Shape, Contour and Grouping in Computer Vision, edited by: Forsyth, D. A., Mundy, J. L., di Gesú, V., and Cipolla, R., Springer Berlin Heidelberg, Berlin, Heidelberg, Germany, 319–345, 1999.
Li, X. and Wu, X.: Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition, arXiv [preprint], arXiv:1410.4281, 11 May 2015.
Platt, U. and Stutz, J.: Differential optical absorption spectroscopy: principles and applications, Springer, Berlin, Germany, 2008.
Rodgers, C. D.: Inverse methods for atmospheric sounding: theory and practice, Reprinted, World Scientific, Singapore, 2004.
Schulz, K., Hänsch, R., and Sörgel, U.: Machine learning methods for remote sensing applications: an overview, Proc. SPIE 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX, 1079002, https://doi.org/10.1117/12.2503653, 2018.
Simonyan, K. and Zisserman, A.: Very Deep Convolutional Networks for Large-Scale Image Recognition, arXiv [preprint], arXiv:1409.1556, 10 April 2015.
Spinei, E., Tiefengraber, M., Müller, M., Cede, A., Berkhout, S., Dong, Y., and Nowak, N.: Simple retrieval of atmospheric trace gas vertical concentration profiles from multi-axis DOAS observations, in preparation, 2020.
Spurr, R.: LIDORT and VLIDORT: Linearized pseudo-spherical scalar and vector discrete ordinate radiative transfer models for use in remote sensing retrieval problems, in: Light Scattering Reviews 3, edited by: Kokhanovsky, A. A., 229–275, Springer Berlin Heidelberg, Berlin, Heidelberg, Germany, 2008.
Thalman, R. and Volkamer, R.: Temperature dependent absorption cross-sections of O2–O2 collision pairs between 340 and 630 nm and at atmospherically relevant pressure, Phys. Chem. Chem. Phys., 15, 15371, https://doi.org/10.1039/c3cp50968k, 2013.
Thomas, A.: Keras LSTM tutorial – How to easily build a powerful deep learning language model, Adventures in Machine Learning, available at: https://adventuresinmachinelearning.com/keras-lstm-tutorial/ (last access: 16 March 2019), 2018.
Vlemmix, T., Eskes, H. J., Piters, A. J. M., Schaap, M., Sauter, F. J., Kelder, H., and Levelt, P. F.: MAX-DOAS tropospheric nitrogen dioxide column measurements compared with the Lotos-Euros air quality model, Atmos. Chem. Phys., 15, 1313–1330, https://doi.org/10.5194/acp-15-1313-2015, 2015.
Wagner, T., Beirle, S., Benavent, N., Bösch, T., Chan, K. L., Donner, S., Dörner, S., Fayt, C., Frieß, U., García-Nieto, D., Gielen, C., González-Bartolome, D., Gomez, L., Hendrick, F., Henzing, B., Jin, J. L., Lampel, J., Ma, J., Mies, K., Navarro, M., Peters, E., Pinardi, G., Puentedura, O., Puķīte, J., Remmers, J., Richter, A., Saiz-Lopez, A., Shaiganfar, R., Sihler, H., Van Roozendael, M., Wang, Y., and Yela, M.: Is a scaling factor required to obtain closure between measured and modelled atmospheric O4 absorptions? An assessment of uncertainties of measurements and radiative transfer simulations for 2 selected days during the MAD-CAT campaign, Atmos. Meas. Tech., 12, 2745–2817, https://doi.org/10.5194/amt-12-2745-2019, 2019.
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...