Articles | Volume 16, issue 10
https://doi.org/10.5194/amt-16-2575-2023
© Author(s) 2023. 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-16-2575-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 May 2023
Research article |
| 26 May 2023
| 26 May 2023
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
CNRM, Météo-France, CNRS, Université de Toulouse, Toulouse, France
Bruno Six
University of Lille, CNRS, CNES, UMS 2877 – ICARE Data and Services Center, 59000 Lille, France
Suman Moparthy
CNRM, Météo-France, CNRS, Université de Toulouse, Toulouse, France
now at: ACRI-ST, Toulouse, France
Dominique Carrer
CNRM, Météo-France, CNRS, Université de Toulouse, Toulouse, France
Adèle Georgeot
CNRM, Météo-France, CNRS, Université de Toulouse, Toulouse, France
Josef Gasteiger
Faculty of Physics, University of Vienna, Vienna, Austria
now at: Hamtec Consulting GmbH at EUMETSAT, Darmstadt, Germany
Jérôme Riedi
University of Lille, CNRS, CNES, UMS 2877 – ICARE Data and Services Center, 59000 Lille, France
University of Lille, CNRS, UMR 8518 – LOA – Laboratoire d'Optique Atmosphérique, 59000 Lille, France
Jean-Luc Attié
LAERO-Laboratoire d'Aérologie, UPS, CNRS, Université de Toulouse, 14 Avenue Edouard Belin, 31400 Toulouse, France
Alexei Lyapustin
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Iosif Katsev
B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Pr. Nezavisimosti 68, 220072, Minsk, Belarus
Related authors
Gloria Klein, Xavier Ceamanos, Jérôme Vidot, Didier Ramon, and Mustapha Moulana
EGUsphere, https://doi.org/10.5194/egusphere-2025-3263, https://doi.org/10.5194/egusphere-2025-3263, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
This work investigates the impact of the Earth's sphericity on geostationary satellite observations, particularly in the context of the operational estimation of aerosol and land surface properties from the Meteosat Third Generation-Imager's Flexible Combined Imager. We demonstrate that the plane-parallel approximation widely used in fast radiative transfer codes can introduce significant biases in certain situations, mainly depending on the observing geometry and wavelength.
Adèle Georgeot, Xavier Ceamanos, Jean-Luc Attié, Daniel Juncu, Josef Gasteiger, and Mathieu Compiègne
EGUsphere, https://doi.org/10.5194/egusphere-2025-1353, https://doi.org/10.5194/egusphere-2025-1353, 2025
Short summary
Short summary
This work investigates the aerosol remote sensing capabilities offered by the new Meteosat Third Generation-Imager geostationary satellite. First, aerosol load retrieval performance is demonstrated based on realistic synthetic data. Second, the potential for aerosol type characterization is proven, with the estimation of fine mode fraction. This work opens pathways for the future study of diurnal aerosol variations from space thanks to the high temporal resolution of geostationary satellites.
Daniel Juncu, Xavier Ceamanos, Isabel F. Trigo, Sandra Gomes, and Sandra C. Freitas
Geosci. Instrum. Method. Data Syst., 11, 389–412, https://doi.org/10.5194/gi-11-389-2022, https://doi.org/10.5194/gi-11-389-2022, 2022
Short summary
Short summary
MDAL is a near real-time, satellite-based surface albedo product based on the geostationary Meteosat Second Generation mission. We propose an update to the processing algorithm that generates MDAL and evaluate the results of these changes through comparison with the pre-update, currently operational MDAL product as well as reference data using different satellite-based albedo products and in situ measurements. We find that the update provides a valuable improvement.
Gloria Klein, Xavier Ceamanos, Jérôme Vidot, Didier Ramon, and Mustapha Moulana
EGUsphere, https://doi.org/10.5194/egusphere-2025-3263, https://doi.org/10.5194/egusphere-2025-3263, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
This work investigates the impact of the Earth's sphericity on geostationary satellite observations, particularly in the context of the operational estimation of aerosol and land surface properties from the Meteosat Third Generation-Imager's Flexible Combined Imager. We demonstrate that the plane-parallel approximation widely used in fast radiative transfer codes can introduce significant biases in certain situations, mainly depending on the observing geometry and wavelength.
Xin Xi, Jun Wang, Zhendong Lu, Andrew M. Sayer, Jaehwa Lee, Robert C. Levy, Yujie Wang, Alexei Lyapustin, Hongqing Liu, Istvan Laszlo, Changwoo Ahn, Omar Torres, Sabur Abdullaev, James Limbacher, and Ralph A. Kahn
Atmos. Chem. Phys., 25, 7403–7429, https://doi.org/10.5194/acp-25-7403-2025, https://doi.org/10.5194/acp-25-7403-2025, 2025
Short summary
Short summary
The Aralkum Desert is challenging for aerosol retrieval due to its bright, heterogeneous, and dynamic surfaces and the lack of in situ constraints on aerosol properties. The performance and consistency of satellite algorithms in observing Aralkum-generated saline dust remain unknown. This study compares multisensor UVAI (ultraviolet aerosol index), AOD (aerosol optical depth), and ALH (aerosol layer height) products and reveals inconsistencies and potential biases over the Aral Sea basin.
Marilena Teri, Josef Gasteiger, Katharina Heimerl, Maximilian Dollner, Manuel Schöberl, Petra Seibert, Anne Tipka, Thomas Müller, Sudharaj Aryasree, Konrad Kandler, and Bernadett Weinzierl
Atmos. Chem. Phys., 25, 6633–6662, https://doi.org/10.5194/acp-25-6633-2025, https://doi.org/10.5194/acp-25-6633-2025, 2025
Short summary
Short summary
The A-LIFE aircraft field experiment was carried out in the eastern Mediterranean in 2017. Using A-LIFE data, we studied the change in mineral dust optical properties due to mixing with anthropogenic aerosols. We found that increasing pollution affects dust optical properties, which has implications for identifying dust events and understanding their climate effects. We also show that optical properties of Saharan and Arabian dust are similar when comparing cases with equal pollution content.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
Short summary
Short summary
This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Adèle Georgeot, Xavier Ceamanos, Jean-Luc Attié, Daniel Juncu, Josef Gasteiger, and Mathieu Compiègne
EGUsphere, https://doi.org/10.5194/egusphere-2025-1353, https://doi.org/10.5194/egusphere-2025-1353, 2025
Short summary
Short summary
This work investigates the aerosol remote sensing capabilities offered by the new Meteosat Third Generation-Imager geostationary satellite. First, aerosol load retrieval performance is demonstrated based on realistic synthetic data. Second, the potential for aerosol type characterization is proven, with the estimation of fine mode fraction. This work opens pathways for the future study of diurnal aerosol variations from space thanks to the high temporal resolution of geostationary satellites.
Silke Groß, Volker Freudenthaler, Moritz Haarig, Albert Ansmann, Carlos Toledano, David Mateos, Petra Seibert, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Josef Gasteiger, Maximilian Dollner, Anne Tipka, Manuel Schöberl, Marilena Teri, and Bernadett Weinzierl
Atmos. Chem. Phys., 25, 3191–3211, https://doi.org/10.5194/acp-25-3191-2025, https://doi.org/10.5194/acp-25-3191-2025, 2025
Short summary
Short summary
Aerosols contribute to the largest uncertainties in climate change predictions. The eastern Mediterranean is a hotspot for aerosols with natural and anthropogenic contributions. We present lidar measurements performed during A-LIFE (Absorbing aerosol layers in a changing climate: aging, lifetime and dynamics) to characterize aerosols and aerosol mixtures. We extend current lidar classification and separation schemes and compare them to classification schemes using different methods.
Natalie G. Ratcliffe, Claire L. Ryder, Nicolas Bellouin, Stephanie Woodward, Anthony Jones, Ben Johnson, Lisa-Maria Wieland, Maximilian Dollner, Josef Gasteiger, and Bernadett Weinzierl
Atmos. Chem. Phys., 24, 12161–12181, https://doi.org/10.5194/acp-24-12161-2024, https://doi.org/10.5194/acp-24-12161-2024, 2024
Short summary
Short summary
Large mineral dust particles are more abundant in the atmosphere than expected and have different impacts on the environment than small particles, which are better represented in climate models. We use aircraft measurements to assess a climate model representation of large-dust transport. We find that the model underestimates the amount of large dust at all stages of transport and that fast removal of the large particles increases this underestimation with distance from the Sahara.
Karlie N. Rees, Timothy J. Garrett, Thomas D. DeWitt, Corey Bois, Steven K. Krueger, and Jérôme C. Riedi
Nonlin. Processes Geophys., 31, 497–513, https://doi.org/10.5194/npg-31-497-2024, https://doi.org/10.5194/npg-31-497-2024, 2024
Short summary
Short summary
The shapes of clouds viewed from space reflect vertical and horizontal motions in the atmosphere. We theorize that, globally, cloud perimeter complexity is related to the dimension of turbulence also governed by horizontal and vertical motions. We find agreement between theory and observations from various satellites and a numerical model and, remarkably, that the theory applies globally using only basic planetary physical parameters from the smallest scales of turbulence to the planetary scale.
Haihui Zhu, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Chi Li, Jun Meng, Christopher R. Oxford, Xuan Liu, Yanshun Li, Dandan Zhang, Inderjeet Singh, and Alexei Lyapustin
Atmos. Chem. Phys., 24, 11565–11584, https://doi.org/10.5194/acp-24-11565-2024, https://doi.org/10.5194/acp-24-11565-2024, 2024
Short summary
Short summary
Ambient fine particulate matter (PM2.5) contributes to 4 million deaths globally each year. Satellite remote sensing of aerosol optical depth (AOD), coupled with a simulated PM2.5–AOD relationship (η), can provide global PM2.5 estimations. This study aims to understand the spatial patterns and driving factors of η to guide future measurement and modeling efforts. We quantified η globally and regionally and found that its spatial variation is strongly influenced by aerosol composition.
Myungje Choi, Alexei Lyapustin, Gregory L. Schuster, Sujung Go, Yujie Wang, Sergey Korkin, Ralph Kahn, Jeffrey S. Reid, Edward J. Hyer, Thomas F. Eck, Mian Chin, David J. Diner, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, and Hans Moosmüller
Atmos. Chem. Phys., 24, 10543–10565, https://doi.org/10.5194/acp-24-10543-2024, https://doi.org/10.5194/acp-24-10543-2024, 2024
Short summary
Short summary
This paper introduces a retrieval algorithm to estimate two key absorbing components in smoke (black carbon and brown carbon) using DSCOVR EPIC measurements. Our analysis reveals distinct smoke properties, including spectral absorption, layer height, and black carbon and brown carbon, over North America and central Africa. The retrieved smoke properties offer valuable observational constraints for modeling radiative forcing and informing health-related studies.
Manuel Schöberl, Maximilian Dollner, Josef Gasteiger, Petra Seibert, Anne Tipka, and Bernadett Weinzierl
Atmos. Meas. Tech., 17, 2761–2776, https://doi.org/10.5194/amt-17-2761-2024, https://doi.org/10.5194/amt-17-2761-2024, 2024
Short summary
Short summary
Transporting a representative aerosol sample to instrumentation inside a research aircraft remains a challenge due to losses or enhancements of particles in the aerosol sampling system. Here, we present sampling efficiencies and the cutoff diameter for the DLR Falcon aerosol sampling system as a function of true airspeed by comparing the in-cabin and the out-cabin particle number size distributions observed during the A-LIFE aircraft mission.
Philippe Ricaud, Massimo Del Guasta, Angelo Lupi, Romain Roehrig, Eric Bazile, Pierre Durand, Jean-Luc Attié, Alessia Nicosia, and Paolo Grigioni
Atmos. Chem. Phys., 24, 613–630, https://doi.org/10.5194/acp-24-613-2024, https://doi.org/10.5194/acp-24-613-2024, 2024
Short summary
Short summary
Clouds affect the Earth's climate in ways that depend on the type of cloud (solid/liquid water). From observations at Concordia (Antarctica), we show that in supercooled liquid water (liquid water for temperatures below 0°C) clouds (SLWCs), temperature and SLWC radiative forcing increase with liquid water (up to 70 W m−2). We extrapolated that the maximum SLWC radiative forcing can reach 40 W m−2 over the Antarctic Peninsula, highlighting the importance of SLWCs for global climate prediction.
Huazhe Shang, Souichiro Hioki, Guillaume Penide, Céline Cornet, Husi Letu, and Jérôme Riedi
Atmos. Chem. Phys., 23, 2729–2746, https://doi.org/10.5194/acp-23-2729-2023, https://doi.org/10.5194/acp-23-2729-2023, 2023
Short summary
Short summary
We find that cloud profiles can be divided into four prominent patterns, and the frequency of these four patterns is related to intensities of cloud-top entrainment and precipitation. Based on these analyses, we further propose a cloud profile parameterization scheme allowing us to represent these patterns. Our results shed light on how to facilitate the representation of cloud profiles and how to link them to cloud entrainment or precipitating status in future remote-sensing applications.
Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão
Earth Syst. Sci. Data, 15, 345–358, https://doi.org/10.5194/essd-15-345-2023, https://doi.org/10.5194/essd-15-345-2023, 2023
Short summary
Short summary
The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
Daniel Juncu, Xavier Ceamanos, Isabel F. Trigo, Sandra Gomes, and Sandra C. Freitas
Geosci. Instrum. Method. Data Syst., 11, 389–412, https://doi.org/10.5194/gi-11-389-2022, https://doi.org/10.5194/gi-11-389-2022, 2022
Short summary
Short summary
MDAL is a near real-time, satellite-based surface albedo product based on the geostationary Meteosat Second Generation mission. We propose an update to the processing algorithm that generates MDAL and evaluate the results of these changes through comparison with the pre-update, currently operational MDAL product as well as reference data using different satellite-based albedo products and in situ measurements. We find that the update provides a valuable improvement.
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109, https://doi.org/10.5194/gmd-15-8085-2022, https://doi.org/10.5194/gmd-15-8085-2022, 2022
Short summary
Short summary
The smoke from fires is composed of different compounds that interact with the atmosphere and can create poor air-quality episodes. Here, we present a new fire inventory based on satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS). We named this inventory the VIIRS-based Fire Emission Inventory (VFEI). Advantages of VFEI are its high resolution (~500 m) and that it provides information for many species. VFEI is publicly available and has provided data since 2012.
Marilena Teri, Thomas Müller, Josef Gasteiger, Sara Valentini, Helmuth Horvath, Roberta Vecchi, Paulus Bauer, Adrian Walser, and Bernadett Weinzierl
Atmos. Meas. Tech., 15, 3161–3187, https://doi.org/10.5194/amt-15-3161-2022, https://doi.org/10.5194/amt-15-3161-2022, 2022
Short summary
Short summary
We performed an extensive closure study including laboratory and simulated experiments to evaluate various angular corrections for the Aurora 4000 polar nephelometer, focusing on irregularly shaped aerosols such as mineral dust. We describe the impact of particle size, refractive index, and shape on the determination of the particle scattering coefficient and propose a guideline to establish the most appropriate angular correction depending on the aerosol type and the investigated size range.
Luca Bugliaro, Dennis Piontek, Stephan Kox, Marius Schmidl, Bernhard Mayer, Richard Müller, Margarita Vázquez-Navarro, Daniel M. Peters, Roy G. Grainger, Josef Gasteiger, and Jayanta Kar
Nat. Hazards Earth Syst. Sci., 22, 1029–1054, https://doi.org/10.5194/nhess-22-1029-2022, https://doi.org/10.5194/nhess-22-1029-2022, 2022
Short summary
Short summary
The monitoring of ash dispersion in the atmosphere is an important task for satellite remote sensing since ash represents a threat to air traffic. We present an AI-based method that retrieves the spatial extension and properties of volcanic ash clouds with high temporal resolution during day and night by means of geostationary satellite measurements. This algorithm, trained on realistic observations simulated with a radiative transfer model, runs operationally at the German Weather Service.
Sujung Go, Alexei Lyapustin, Gregory L. Schuster, Myungje Choi, Paul Ginoux, Mian Chin, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, Arlindo da Silva, Brent Holben, and Jeffrey S. Reid
Atmos. Chem. Phys., 22, 1395–1423, https://doi.org/10.5194/acp-22-1395-2022, https://doi.org/10.5194/acp-22-1395-2022, 2022
Short summary
Short summary
This paper presents a retrieval algorithm of iron-oxide species (hematite, goethite) content in the atmosphere from DSCOVR EPIC observations. Our results display variations within the published range of hematite and goethite over the main dust-source regions but show significant seasonal and spatial variability. This implies a single-viewing satellite instrument with UV–visible channels may provide essential information on shortwave dust direct radiative effects for climate modeling.
Alexandra Tsekeri, Vassilis Amiridis, Alexandros Louridas, George Georgoussis, Volker Freudenthaler, Spiros Metallinos, George Doxastakis, Josef Gasteiger, Nikolaos Siomos, Peristera Paschou, Thanasis Georgiou, George Tsaknakis, Christos Evangelatos, and Ioannis Binietoglou
Atmos. Meas. Tech., 14, 7453–7474, https://doi.org/10.5194/amt-14-7453-2021, https://doi.org/10.5194/amt-14-7453-2021, 2021
Short summary
Short summary
Dust orientation in the Earth's atmosphere has been an ongoing investigation in recent years, and its potential proof will be a paradigm shift for dust remote sensing. We have designed and developed a polarization lidar that provides direct measurements of dust orientation, as well as more detailed information of the particle microphysics. We provide a description of its design as well as its first measurements.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
Short summary
Short summary
Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Souichiro Hioki, Jérôme Riedi, and Mohamed S. Djellali
Atmos. Meas. Tech., 14, 1801–1816, https://doi.org/10.5194/amt-14-1801-2021, https://doi.org/10.5194/amt-14-1801-2021, 2021
Short summary
Short summary
This research estimates the magnitude of a motion-induced error in the measurement of polarimetric state of light by a planned instrument on a future satellite. We discovered that the motion-induced error can not be cancelled out by spatiotemporal averaging, but it can be predicted from the along-track change of the intensity of light. With the estimated statistics and the simulation model, this research paves a way to provide pixel-level quality information in the future satellite products.
Cheng Chen, Oleg Dubovik, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Fabrice Ducos, Yevgeny Derimian, Maurice Herman, Didier Tanré, Lorraine A. Remer, Alexei Lyapustin, Andrew M. Sayer, Robert C. Levy, N. Christina Hsu, Jacques Descloitres, Lei Li, Benjamin Torres, Yana Karol, Milagros Herrera, Marcos Herreras, Michael Aspetsberger, Moritz Wanzenboeck, Lukas Bindreiter, Daniel Marth, Andreas Hangler, and Christian Federspiel
Earth Syst. Sci. Data, 12, 3573–3620, https://doi.org/10.5194/essd-12-3573-2020, https://doi.org/10.5194/essd-12-3573-2020, 2020
Short summary
Short summary
Aerosol products obtained from POLDER/PARASOL processed by the GRASP algorithm have been released. The entire archive of PARASOL/GRASP aerosol products is evaluated against AERONET and compared with MODIS (DT, DB and MAIAC), as well as PARASOL/Operational products. PARASOL/GRASP aerosol products provide spectral 443–1020 nm AOD correlating well with AERONET with a maximum bias of 0.02. Finally, GRASP shows capability to derive detailed spectral properties, including aerosol absorption.
Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457, https://doi.org/10.5194/acp-20-12431-2020, https://doi.org/10.5194/acp-20-12431-2020, 2020
Short summary
Short summary
We intercompare 14 different datasets of satellite observations of aerosol. Such measurements are challenging but also provide the best opportunity to globally observe an atmospheric component strongly related to air pollution and climate change. Our study shows that most datasets perform similarly well on a global scale but that locally errors can be quite different. We develop a technique to estimate satellite errors everywhere, even in the absence of surface reference data.
Cited articles
Backman, J., Rizzo, L. V., Hakala, J., Nieminen, T., Manninen, H. E., Morais, F., Aalto, P. P., Siivola, E., Carbone, S., Hillamo, R., Artaxo, P., Virkkula, A., Petäjä, T., and Kulmala, M.: On the diurnal cycle of urban aerosols, black carbon and the occurrence of new particle formation events in springtime São Paulo, Brazil, Atmos. Chem. Phys., 12, 11733–11751, https://doi.org/10.5194/acp-12-11733-2012, 2012.
Bessho, K., Date, K., Hayashi, M., Ikeda, A., Imai, T., Inoue, H., Kumagai,
Y., Miyakawa, T., Murata, H., Ohno, T., Okuyama, A., Oyama, R., Sasaki, Y.,
Shimazu, Y., Shimoji, K., Sumida, Y., Suzuki, M., Taniguchi, H., Tsuchiyama,
H., Uesawa, D., Yokota, H., and Yoshida, R.: An introduction to
Himawari-8/9 – Japan's new-generation geostationary meteorological
satellites, J. Meteorol. Soc. Jpn., 94, 151–183,
https://doi.org/10.2151/jmsj.2016-009, 2016.
Boucher, O.: Atmospheric Aerosols–Properties and Climate Impacts, Springer
Dordrecht, https://doi.org/10.1007/978-94-017-9649-1, 2015.
Bozzo, A., Benedetti, A., Flemming, J., Kipling, Z., and Rémy, S.: An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF, Geosci. Model Dev., 13, 1007–1034, https://doi.org/10.5194/gmd-13-1007-2020, 2020.
Carrer, D., Roujean, J.-L., Hautecoeur, O., and Elias, T.: Daily estimates
of aerosol optical thickness over land surface based on a directional and
temporal analysis of SEVIRI MSG visible observations, J. Geophys. Res., 115,
D10208, https://doi.org/10.1029/2009JD012272, 2010.
Carrer, D., Ceamanos, X., Six, B., and Roujean, J.-L.: AERUS-GEO: A newly
available satellite-derived aerosol optical depth product over Europe and
Africa, Geophys. Res. Lett., 41, 7731–7738, https://doi.org/10.1002/2014GL061707, 2014.
Ceamanos, X., Douté, S., Fernando, J., Schmidt, F., Pinet, P., and
Lyapustin, A.: Surface reflectance of Mars observed by CRISM/MRO: 1.
Multi-angle Approach for Retrieval of Surface Reflectance from CRISM
observations (MARS-ReCO), J. Geophys. Res.-Planets, 118, 540– 559,
https://doi.org/10.1029/2012JE004195, 2013.
Ceamanos, X., Moparthy, S., Carrer, D., and Seidel, F. C.: Assessing the
potential of geostationary satellites for aerosol remote sensing based on
critical surface albedo, Remote Sensing, 11, 2958, https://doi.org/10.3390/rs11242958, 2019.
Ceamanos, X., Six, B., and Riedi, J.: Quasi-global maps of daily aerosol
optical depth from a ring of five geostationary meteorological satellites
using AERUS-GEO, J. Geophys. Res., 126, e2021JD034906, https://doi.org/10.1029/2021JD034906, 2021.
Chandrasekhar, S.: Radiative Transfer, Dover, New York, ISBN-13 9780486605906, 1960.
Chen, C., Dubovik, O., Fuertes, D., Litvinov, P., Lapyonok, T., Lopatin, A., Ducos, F., Derimian, Y., Herman, M., Tanré, D., Remer, L. A., Lyapustin, A., Sayer, A. M., Levy, R. C., Hsu, N. C., Descloitres, J., Li, L., Torres, B., Karol, Y., Herrera, M., Herreras, M., Aspetsberger, M., Wanzenboeck, M., Bindreiter, L., Marth, D., Hangler, A., and Federspiel, C.: Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring, Earth Syst. Sci. Data, 12, 3573–3620, https://doi.org/10.5194/essd-12-3573-2020, 2020.
Choi, M., Kim, J., Lee, J., Kim, M., Park, Y.-J., Jeong, U., Kim, W., Hong, H., Holben, B., Eck, T. F., Song, C. H., Lim, J.-H., and Song, C.-K.: GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign, Atmos. Meas. Tech., 9, 1377–1398, https://doi.org/10.5194/amt-9-1377-2016, 2016.
Cox, C. and Munk, W.: Measurement of the Roughness of the Sea Surface from
Photographs of the Sun's Glitter, J. Opt. Soc. Am., 44, 838–850,
https://doi.org/10.1364/josa.44.000838, 1954.
Derrien, M. and Le Gleau, H.: MSG/SEVIRI cloud mask and type from SAFNWC,
Int. J. Remote Sens., 26, 4707–4732, https://doi.org/10.1080/01431160500166128, 2005.
Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang,
P., Eck, T. F., Volten. H., Muñoz, O., Veihelmann, B., van der Zande, W.
J., Leon, J.-F., Sorokin, M., and Slutsker, I.: Application of Spheroid
Models to Account for Aerosol Particle Nonsphericity in Remote Sensing of
Desert Dust, J. Geophys. Res., 111, D11208, https://doi.org/10.1029/2005JD006619, 2006.
Dubovik, O., Herman, M., Holdak, A., Lapyonok, T., Tanré, D., Deuzé, J. L., Ducos, F., Sinyuk, A., and Lopatin, A.: Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations, Atmos. Meas. Tech., 4, 975–1018, https://doi.org/10.5194/amt-4-975-2011, 2011.
Escribano, J., Boucher, O., Chevallier, F., and Huneeus, N.: Impact of the choice of the satellite aerosol optical depth product in a sub-regional dust emission inversion, Atmos. Chem. Phys., 17, 7111–7126, https://doi.org/10.5194/acp-17-7111-2017, 2017.
Gasteiger, J. and Wiegner, M.: MOPSMAP v1.0: a versatile tool for the modeling of aerosol optical properties, Geosci. Model Dev., 11, 2739–2762, https://doi.org/10.5194/gmd-11-2739-2018, 2018.
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019.
Govaerts, Y. and Luffarelli, M.: Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space – Part 1: theoretical concept, Atmos. Meas. Tech., 11, 6589–6603, https://doi.org/10.5194/amt-11-6589-2018, 2018.
Govaerts, Y. M., Wagner, S., Lattanzio, A., and Watts, P.: Joint retrieval
of surface reflectance and aerosol optical depth from MSG/SEVIRI
observations with an optimal estimation approach: 1. Theory, J. Geophys.
Res., 115, D02203, https://doi.org/10.1029/2009JD011779, 2010.
Gupta, P., Levy, R. C., Mattoo, S., Remer, L. A., Holz, R. E., and Heidinger, A. K.: Applying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaign, Atmos. Meas. Tech., 12, 6557–6577, https://doi.org/10.5194/amt-12-6557-2019, 2019.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5
global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer,
A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F.,
Jankowiak, I., and Smirnov, A.: AERONET – A federated instrument network and
data archive for aerosol characterization, Remote Sens. Environ., 66, 1–16,
https://doi.org/10.1016/S0034-4257(98)00031-5, 1998.
Holmlund, K., Grandell, J., Schmetz, J., Stuhlmann, R., Bojkov, B., Munro,
R., Lekouara, M., Coppens, D., Viticchie, B., August, T., Theodore, B.,
Watts, P., Dobber, M., Fowler, G., Bojinski, S., Schmid, A., Salonen, K.,
Tjemkes, S., Aminou, D., and Blythe, P.: Meteosat Third Generation (MTG):
Continuation and innovation of observations from geostationary orbit, B. Am. Meteorol. Soc., 102, E990–E1015, https://doi.org/10.1175/BAMS-D-19-0304.1, 2021.
Hsu, N. C., Jeong, M.-J., Bettenhausen, C., Sayer, A. M., Hansell, R.,
Seftor, C. S., Huang, J., and Tsay, S.-C.: Enhanced Deep Blue aerosol
retrieval algorithm: The second generation, J. Geophys. Res., 118,
9296–9315, https://doi.org/10.1002/jgrd.50712, 2013.
Joseph, J. H., Wiscombe, W. J., and Weinman, J. A.: The Delta-Eddington
Approximation for Radiative Flux Transfer, J. Atmos. Sci., 33, 2452–2459, 1976.
Katsev, I. L., Prikhach, A. S., Zege, E. P., Grudo, J. O., and Kokhanovsky, A. A.: Speeding up the aerosol optical thickness retrieval using analytical solutions of radiative transfer theory, Atmos. Meas. Tech., 3, 1403–1422, https://doi.org/10.5194/amt-3-1403-2010, 2010.
Knapp, K. R.: Quantification of aerosol signal in GOES 8 visible imagery over the United States, J. Geophys. Res., 107, 4426, https://doi.org/10.1029/2001JD002001, 2002.
Kocha, C., Tulet, P., Lafore, J.-P., and Flamant, C.: The importance of the
diurnal cycle of Aerosol Optical Depth in West Africa, Geophys. Res. Lett.,
40, 785–790, https://doi.org/10.1002/grl.50143, 2013.
Koepke, P.: Effective reflectance of oceanic whitecaps, Appl. Optics, 23,
1816–1824, https://doi.org/10.1364/AO.23.001816, 1984.
Kondragunta, S., Laszlo, I., Zhang, H., Ciren, P., and Huff, A.: Air quality
applications of ABI aerosol products from the GOES-R series, The GOES-R
series: A new generation of geostationary environmental satellites,
Elsevier, 203–217, https://doi.org/10.1016/B978-0-12-814327-8.00017-2, 2020.
Korkin, S., Yang, E.-S., Spurr, R., Emde, C., Krotkov, N., Vasilkov, A.,
Haffner, D., Mok, J., and Lyapustin, A.: Revised and extended benchmark
results for Rayleigh scattering of sunlight in spherical atmospheres, J.
Quant. Spectrosc. Ra., 254, 107181, https://doi.org/10.1016/j.jqsrt.2020.107181, 2020.
Kotchenova, S. Y., Vermote, E. F., Matarrese, R., and Klemm, F. J.:
Validation of a vector version of the 6S radiative transfer code for
atmospheric correction of satellite data. Part I: Path radiance, Appl. Optics, 45, 6762–6774, https://doi.org/10.1364/AO.45.006762, 2006.
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, 2013.
Li, Z., Roy, D. P., and Zhang, H. K.: The incidence and magnitude of the
hot-spot bidirectional reflectance distribution function (BRDF) signature in
GOES-16 Advanced Baseline Imager (ABI) 10 and 15 minute reflectance over
north America, Remote Sens. Environ., 265, 112638, https://doi.org/10.1016/j.rse.2021.112638, 2021.
Lim, H., Choi, M., Kim, J., Kasai, Y., and Chan, P. W.: AHI/Himawari-8
Yonsei Aerosol Retrieval (YAER): Algorithm, validation and merged products,
Remote Sensing, 10, 699, https://doi.org/10.3390/rs10050699, 2018.
Lucht, W., Schaaf, C. B., and Strahler, A. H.: An algorithm for the retrieval of albedo from space using semiempirical BRDF models, IEEE T. Geosci. Remote, 38, 977–998, https://doi.org/10.1109/36.841980, 2000.
Luffarelli, M. and Govaerts, Y.: Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space – Part 2: application to geostationary and polar-orbiting satellite observations, Atmos. Meas. Tech., 12, 791–809, https://doi.org/10.5194/amt-12-791-2019, 2019.
Lyapustin, A., Wang, Y., Korkin, S., and Huang, D.: MODIS Collection 6 MAIAC algorithm, Atmos. Meas. Tech., 11, 5741–5765, https://doi.org/10.5194/amt-11-5741-2018, 2018.
Maignan, F., Bréon, F. M., and Lacaze, R.: Bidirectional reflectance of
Earth targets: evaluation of analytical models using a large set of
spaceborne measurements with emphasis of the hot spot, Remote Sens.
Environ., 90, 210–220, https://doi.org/10.1016/j.rse.2003.12.006, 2004.
Meirink, J. F., Roebeling, R. A., and Stammes, P.: Inter-calibration of polar imager solar channels using SEVIRI, Atmos. Meas. Tech., 6, 2495–2508, https://doi.org/10.5194/amt-6-2495-2013, 2013.
Mishchenko, M. I. and Travis, L. D.: Satellite Retrieval of Aerosol
Properties over the Ocean Using Measurements of Reflected Sunlight: Effect
of Instrumental Errors and Aerosol Absorption, J. Geophys. Res., 102,
13543–13553, https://doi.org/10.1029/97jd01124, 1997.
Mishchenko, M. I. and Travis, L. D.: Capabilities and limitations of a
current FORTRAN implementation of the T-matrix method for randomly oriented, rotationally symmetric scatterers, J. Quant. Spectrosc. Ra., 60, 309–324, https://doi.org/10.1016/S0022-4073(98)00008-9, 1998.
Monahan, E. C. and Muircheartaigh, I. O.: Optimal power-law description of
oceanic whitecap coverage dependence on wind speed, J. Phys. Oceanogr., 10,
2094–2099, https://doi.org/10.1175/1520-0485(1980)010<2094:OPLDOO>2.0.CO;2, 1980.
Plu, M., Bigeard, G., Sič, B., Emili, E., Bugliaro, L., El Amraoui, L., Guth, J., Josse, B., Mona, L., and Piontek, D.: Modelling the volcanic ash plume from Eyjafjallajökull eruption (May 2010) over Europe: evaluation of the benefit of source term improvements and of the assimilation of aerosol measurements, Nat. Hazards Earth Syst. Sci., 21, 3731–3747, https://doi.org/10.5194/nhess-21-3731-2021, 2021.
Rahman, H. and Dedieu, G.: SMAC: A simplified method for the atmospheric
correction of satellite measurements in the solar spectrum, Int. J. Remote
Sens., 15, 123–143, https://doi.org/10.1080/01431169408954055, 1994.
Remer, L. A. and Kaufman, Y. J.: Dynamical aerosol model: Urban/industrial
aerosol, J. Geophys. Res., 103, 13859–13871, https://doi.org/10.1029/98JD00994, 1998.
Roberts, A. J., Woodage, M. J., Marsham, J. H., Highwood, E. J., Ryder, C. L., McGinty, W., Wilson, S., and Crook, J.: Can explicit convection improve modelled dust in summertime West Africa?, Atmos. Chem. Phys., 18, 9025–9048, https://doi.org/10.5194/acp-18-9025-2018, 2018.
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding: Theory and
Practice, World Scientific, River Edge, ISBN-13 978-9810227401, 2000.
Rozanov, V. V. and Kokhanovsky, A. A.: On the molecular-aerosol scattering
coupling in remote sensing of aerosol from space, IEEE T. Geosci. Remote, 43, 1536–1541, https://doi.org/10.1109/TGRS.2005.846859, 2005.
Sayer, A. M., Thomas, G. E., and Grainger, R. G.: A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals, Atmos. Meas. Tech., 3, 813–838, https://doi.org/10.5194/amt-3-813-2010, 2010.
Sayer, A. M., Smirnov, A., Hsu, N. C., and Holben, B. N.: A pure marine
aerosol model, for use in remote sensing applications, J. Geophys. Res.,
117, D05213, https://doi.org/10.1029/2011JD016689, 2012.
Schmetz, J., Pili, P., Tjemkes, S., Just, D., Kerkmann, J., Rota, S., and
Ratier, A.: An introduction to Meteosat Second Generation (MSG), B. Am. Meteorol. Soc., 83, 977–992, https://doi.org/10.1175/1520-0477(2002)083<0977:AITMSG>2.3.CO;2, 2002.
Schmit, T. J., Griffith, P., Gunshor, M. M., Daniels, J. M., Goodman, S. J.,
and Lebair, W. J.: A closer look at the ABI on the GOES-R series, B. Am.
Meteorol. Soc., 98, 681–698, https://doi.org/10.1175/BAMS-D-15-00230.1, 2017.
Shi, C., Hashimoto, M., and Nakajima, T.: Remote sensing of aerosol properties from multi-wavelength and multi-pixel information over the ocean, Atmos. Chem. Phys., 19, 2461–2475, https://doi.org/10.5194/acp-19-2461-2019, 2019.
Sobolev, V. V.: Light Scattering In Planetary Atmospheres, Pergamon, New
York, 335 pp., ISBN 978-0-08-017934-6, 1975.
Thieuleux, F., Moulin, C., Bréon, F. M., Maignan, F., Poitou, J., and Tanré, D.: Remote sensing of aerosols over the oceans using MSG/SEVIRI imagery, Ann. Geophys., 23, 3561–3568, https://doi.org/10.5194/angeo-23-3561-2005, 2005.
Xu, H., Ceamanos, X., Roujean, J.-L., Carrer, D., and Xue, Y.: Can
satellite-derived aerosol optical depth quantify the surface aerosol
radiative forcing?, Atmos. Res., 150, 151–167,
https://doi.org/10.1016/j.atmosres.2014.07.008., 2014.
Xu, H., Guo, J., Ceamanos, X., Roujean, J.-L., Min, M., and Carrer, D.: On
the influence of the diurnal variations of aerosol content to estimate
direct aerosol radiative forcing using MODIS data, Atmos. Environ., 141,
186–196, https://doi.org/10.1016/j.atmosenv.2016.06.067, 2016.
Yoshida, M., Kikuchi, M., Nagao, T. M., Murakami, H., Nomaki, T., and
Higurashi, A.: Common retrieval of aerosol properties for imaging satellite
sensors, J. Meteorol. Soc. Jpn., 96B, 193–209, https://doi.org/10.2151/jmsj.2018-039,
2018.
Wei, X., Chang, N.-B., Bai, K., and Gao, W.: Satellite remote sensing of
aerosol optical depth: Advances, challenges, and perspectives, Crit. Rev.
Env. Sci. Tech., 50, 1640–1725, https://doi.org/10.1080/10643389.2019.1665944, 2020.
Zhang, Y., Yu, H., Eck, T. F., Smirnov, A., Chin, M., Remer, L. A., Bian,
H., Tan, Q., Levy, R., Holben, B. N., and Piazzolla, S.: Aerosol daytime
variations over North and South America derived from multiyear AERONET
measurements, J. Geophys. Res., 117, D05211, https://doi.org/10.1029/2011JD017242, 2012.
Zhang, X., Jiao, Z., Dong, Y., Zhang, H., Li, Y., He, D., Ding, A., Yin, S.,
Cui, L., and Chang, Y.: Potential Investigation of Linking PROSAIL with the
Ross-Li BRDF Model for Vegetation Characterization, Remote Sensing, 10, 437, https://doi.org/10.3390/rs10030437, 2018.
Short summary
A new algorithm to retrieve the diurnal evolution of aerosol optical depth over land and ocean from geostationary meteorological satellites is proposed and successfully evaluated with reference ground-based and satellite data. The high-temporal-resolution aerosol observations that are obtained from the EUMETSAT Meteosat Second Generation mission are unprecedented and open the door to studies that cannot be conducted with the once-a-day observations available from low-Earth-orbit satellites.
A new algorithm to retrieve the diurnal evolution of aerosol optical depth over land and ocean...
