Articles | Volume 16, issue 12
https://doi.org/10.5194/amt-16-3221-2023
© 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-16-3221-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Christian Matar
CORRESPONDING AUTHOR
Univ. Lille, CNRS, UMR 8518 – LOA – Laboratoire d'Optique Atmosphérique, 59000 Lille, France
now at: GRASP SAS, 59260 Lezennes, France
Céline Cornet
Univ. Lille, CNRS, UMR 8518 – LOA – Laboratoire d'Optique Atmosphérique, 59000 Lille, France
Frédéric Parol
Univ. Lille, CNRS, UMR 8518 – LOA – Laboratoire d'Optique Atmosphérique, 59000 Lille, France
Laurent C.-Labonnote
Univ. Lille, CNRS, UMR 8518 – LOA – Laboratoire d'Optique Atmosphérique, 59000 Lille, France
Frédérique Auriol
Univ. Lille, CNRS, UMR 8518 – LOA – Laboratoire d'Optique Atmosphérique, 59000 Lille, France
Marc Nicolas
Univ. Lille, CNRS, UMR 8518 – LOA – Laboratoire d'Optique Atmosphérique, 59000 Lille, France
Related authors
Chong Li, Oleg Dubovik, Jing Li, David Fuertes, Anton Lopatin, Pavel Litvinov, Tatsiana Lapyonok, Lukas Bindreiter, Christian Matar, Yiqi Chu, and Wangshu Tan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2694, https://doi.org/10.5194/egusphere-2025-2694, 2025
Short summary
Short summary
Using observational data from Japan’s geostationary satellite – Himawari-8 , this study improved how we track air pollution (aerosols) across East Asia and the Western Pacific. By applying an advanced aerosol retrieval algorithm called GRASP, we were able to more accurately observe both atmospheric and ground conditions and their dynamics over time. The results closely matched ground-based measurements and showed potential for even better monitoring when combined with ground-based lidar data.
Pavel Litvinov, Cheng Chen, Oleg Dubovik, Siyao Zhai, Christian Matar, Chong Li, Anton Lopatin, David Fuertes, Tatyana Lapyonok, Lukas Bindreiter, Manuel Dornacher, Arthur Lehner, Alexandru Dandocsi, Daniele Gasbarra, and Christian Retscher
EGUsphere, https://doi.org/10.5194/egusphere-2025-1536, https://doi.org/10.5194/egusphere-2025-1536, 2025
Short summary
Short summary
Developed SYREMIS/GRASP multi-instrument synergetic approach is based on three main principles: (i) harmonization of the multi-instruments L1 measurements, (ii) their “weighting” and (iii) optimization of the forward models and the retrieval setups. It substantially enhances aerosol and surface BRDF characterization from spaceborne measurements. Being quite universal, the approach can be extended to future missions, including synergy with multi-angular, multi-spectral, polarimetric measurements.
Lei Li, Yevgeny Derimian, Cheng Chen, Xindan Zhang, Huizheng Che, Gregory L. Schuster, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Christian Matar, Fabrice Ducos, Yana Karol, Benjamin Torres, Ke Gui, Yu Zheng, Yuanxin Liang, Yadong Lei, Jibiao Zhu, Lei Zhang, Junting Zhong, Xiaoye Zhang, and Oleg Dubovik
Earth Syst. Sci. Data, 14, 3439–3469, https://doi.org/10.5194/essd-14-3439-2022, https://doi.org/10.5194/essd-14-3439-2022, 2022
Short summary
Short summary
A climatology of aerosol composition concentration derived from POLDER-3 observations using GRASP/Component is presented. The conceptual specifics of the GRASP/Component approach are in the direct retrieval of aerosol speciation without intermediate retrievals of aerosol optical characteristics. The dataset of satellite-derived components represents scarce but imperative information for validation and potential adjustment of chemical transport models.
Mégane Ventura, Fabien Waquet, Isabelle Chiapello, Gérard Brogniez, Frédéric Parol, Frédérique Auriol, Rodrigue Loisil, Cyril Delegove, Luc Blarel, Oleg Dubovik, Marc Mallet, Cyrille Flamant, and Paola Formenti
Atmos. Meas. Tech., 18, 4005–4024, https://doi.org/10.5194/amt-18-4005-2025, https://doi.org/10.5194/amt-18-4005-2025, 2025
Short summary
Short summary
Biomass-burning aerosols (BBAs) from Central Africa are transported above stratocumulus clouds. The absorption of solar energy by aerosols induces warming, altering the cloud dynamics. We developed an approach that combines polarimeter and lidar to quantify this. This methodology is assessed during the AEROCLO-sA (AErosol RadiatiOn and CLOud in Southern Africa) campaign. To validate it, we used irradiance measurements acquired during aircraft spiral descents. A major perspective is the generalization of this method to the global level.
Chong Li, Oleg Dubovik, Jing Li, David Fuertes, Anton Lopatin, Pavel Litvinov, Tatsiana Lapyonok, Lukas Bindreiter, Christian Matar, Yiqi Chu, and Wangshu Tan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2694, https://doi.org/10.5194/egusphere-2025-2694, 2025
Short summary
Short summary
Using observational data from Japan’s geostationary satellite – Himawari-8 , this study improved how we track air pollution (aerosols) across East Asia and the Western Pacific. By applying an advanced aerosol retrieval algorithm called GRASP, we were able to more accurately observe both atmospheric and ground conditions and their dynamics over time. The results closely matched ground-based measurements and showed potential for even better monitoring when combined with ground-based lidar data.
Pavel Litvinov, Cheng Chen, Oleg Dubovik, Siyao Zhai, Christian Matar, Chong Li, Anton Lopatin, David Fuertes, Tatyana Lapyonok, Lukas Bindreiter, Manuel Dornacher, Arthur Lehner, Alexandru Dandocsi, Daniele Gasbarra, and Christian Retscher
EGUsphere, https://doi.org/10.5194/egusphere-2025-1536, https://doi.org/10.5194/egusphere-2025-1536, 2025
Short summary
Short summary
Developed SYREMIS/GRASP multi-instrument synergetic approach is based on three main principles: (i) harmonization of the multi-instruments L1 measurements, (ii) their “weighting” and (iii) optimization of the forward models and the retrieval setups. It substantially enhances aerosol and surface BRDF characterization from spaceborne measurements. Being quite universal, the approach can be extended to future missions, including synergy with multi-angular, multi-spectral, polarimetric measurements.
Raphaël Peroni, Guillaume Penide, Céline Cornet, Olivier Pujol, and Clémence Pierangelo
EGUsphere, https://doi.org/10.5194/egusphere-2025-787, https://doi.org/10.5194/egusphere-2025-787, 2025
Short summary
Short summary
A retrieval algorithm for integrated water vapor above clouds, based on shortwave infrared observations, is developed and evaluated using idealized and realistic atmospheric profiles. It aims to improve the understanding of interactions between water vapor and clouds to enhance weather models and LES. Integrated into the C3IEL mission (2028), it uses a Bayesian approach and demonstrates good accuracy, except for optically thin or low-altitude clouds.
Gabriel Chesnoiu, Nicolas Ferlay, Isabelle Chiapello, Frédérique Auriol, Diane Catalfamo, Mathieu Compiègne, Thierry Elias, and Isabelle Jankowiak
Atmos. Chem. Phys., 24, 12375–12407, https://doi.org/10.5194/acp-24-12375-2024, https://doi.org/10.5194/acp-24-12375-2024, 2024
Short summary
Short summary
The measured ground-based surface solar irradiance variability and its sensitivity to scene parameters are analysed with a filtering of sky conditions at a given site. Its multivariate analysis is applied to observed trends over 2010–2022. The recorded values show, in addition to the dominant effects of cloud occurrence, the variable effects of aerosol and geometry. Clear-sun-with-cloud situations are highlighted by SSI levels close to those of aerosol- and cloud-free situations.
Raphaël Peroni, Céline Cornet, Olivier Pujol, Guillaume Penide, Clémence Pierangelo, and François Thieuleux
EGUsphere, https://doi.org/10.5194/egusphere-2024-1560, https://doi.org/10.5194/egusphere-2024-1560, 2024
Preprint withdrawn
Short summary
Short summary
A new retrieval algorithm to measure integrated water vapor content above clouds using shortwave infrared (SWIR) observations has been developed and evaluated through both idealized and realistic atmospheric profiles. For the latter, the algorithm shows a positive bias in retrieving water vapor content above low/mid-level clouds, with an error margin of about 2.6 kg.m-2.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 17, 3011–3028, https://doi.org/10.5194/amt-17-3011-2024, https://doi.org/10.5194/amt-17-3011-2024, 2024
Short summary
Short summary
We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on the multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals always decreases with the increasing distance from the cloud far edge. The decrease is the direct consequence of the fact that the forward peak of particle phase functions is much larger than the receiver field of view.
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.
Suzanne Crumeyrolle, Jenni S. S. Kontkanen, Clémence Rose, Alejandra Velazquez Garcia, Eric Bourrianne, Maxime Catalfamo, Véronique Riffault, Emmanuel Tison, Joel Ferreira de Brito, Nicolas Visez, Nicolas Ferlay, Frédérique Auriol, and Isabelle Chiapello
Atmos. Chem. Phys., 23, 183–201, https://doi.org/10.5194/acp-23-183-2023, https://doi.org/10.5194/acp-23-183-2023, 2023
Short summary
Short summary
Ultrafine particles (UFPs) are particles with an aerodynamic diameter of 100 nm or less and negligible mass concentration but are the dominant contributor to the total particle number concentration. The present study aims to better understand the environmental factors favoring or inhibiting atmospheric new particle formation (NPF) over Lille, a large city in the north of France, and to analyze the impact of such an event on urban air quality using a long-term dataset (3 years).
Paolo Dandini, Céline Cornet, Renaud Binet, Laetitia Fenouil, Vadim Holodovsky, Yoav Y. Schechner, Didier Ricard, and Daniel Rosenfeld
Atmos. Meas. Tech., 15, 6221–6242, https://doi.org/10.5194/amt-15-6221-2022, https://doi.org/10.5194/amt-15-6221-2022, 2022
Short summary
Short summary
3D cloud envelope and development velocity are retrieved from realistic simulations of multi-view
CLOUD (C3IEL) images. Cloud development velocity is derived by finding matching features
between acquisitions separated by 20 s. The tie points are then mapped from image to space via 3D
reconstruction of the cloud envelope obtained from 2 simultaneous images. The retrieved cloud
topography as well as the velocities are in good agreement with the estimates obtained from the
physical models.
Kostas Eleftheratos, John Kapsomenakis, Ilias Fountoulakis, Christos S. Zerefos, Patrick Jöckel, Martin Dameris, Alkiviadis F. Bais, Germar Bernhard, Dimitra Kouklaki, Kleareti Tourpali, Scott Stierle, J. Ben Liley, Colette Brogniez, Frédérique Auriol, Henri Diémoz, Stana Simic, Irina Petropavlovskikh, Kaisa Lakkala, and Kostas Douvis
Atmos. Chem. Phys., 22, 12827–12855, https://doi.org/10.5194/acp-22-12827-2022, https://doi.org/10.5194/acp-22-12827-2022, 2022
Short summary
Short summary
We present the future evolution of DNA-active ultraviolet (UV) radiation in view of increasing greenhouse gases (GHGs) and decreasing ozone depleting substances (ODSs). It is shown that DNA-active UV radiation might increase after 2050 between 50° N–50° S due to GHG-induced reductions in clouds and ozone, something that is likely not to happen at high latitudes, where DNA-active UV radiation will continue its downward trend mainly due to stratospheric ozone recovery from the reduction in ODSs.
Lei Li, Yevgeny Derimian, Cheng Chen, Xindan Zhang, Huizheng Che, Gregory L. Schuster, David Fuertes, Pavel Litvinov, Tatyana Lapyonok, Anton Lopatin, Christian Matar, Fabrice Ducos, Yana Karol, Benjamin Torres, Ke Gui, Yu Zheng, Yuanxin Liang, Yadong Lei, Jibiao Zhu, Lei Zhang, Junting Zhong, Xiaoye Zhang, and Oleg Dubovik
Earth Syst. Sci. Data, 14, 3439–3469, https://doi.org/10.5194/essd-14-3439-2022, https://doi.org/10.5194/essd-14-3439-2022, 2022
Short summary
Short summary
A climatology of aerosol composition concentration derived from POLDER-3 observations using GRASP/Component is presented. The conceptual specifics of the GRASP/Component approach are in the direct retrieval of aerosol speciation without intermediate retrievals of aerosol optical characteristics. The dataset of satellite-derived components represents scarce but imperative information for validation and potential adjustment of chemical transport models.
Sandrine Bony, Marie Lothon, Julien Delanoë, Pierre Coutris, Jean-Claude Etienne, Franziska Aemisegger, Anna Lea Albright, Thierry André, Hubert Bellec, Alexandre Baron, Jean-François Bourdinot, Pierre-Etienne Brilouet, Aurélien Bourdon, Jean-Christophe Canonici, Christophe Caudoux, Patrick Chazette, Michel Cluzeau, Céline Cornet, Jean-Philippe Desbios, Dominique Duchanoy, Cyrille Flamant, Benjamin Fildier, Christophe Gourbeyre, Laurent Guiraud, Tetyana Jiang, Claude Lainard, Christophe Le Gac, Christian Lendroit, Julien Lernould, Thierry Perrin, Frédéric Pouvesle, Pascal Richard, Nicolas Rochetin, Kevin Salaün, Alfons Schwarzenboeck, Guillaume Seurat, Bjorn Stevens, Julien Totems, Ludovic Touzé-Peiffer, Gilles Vergez, Jessica Vial, Leonie Villiger, and Raphaela Vogel
Earth Syst. Sci. Data, 14, 2021–2064, https://doi.org/10.5194/essd-14-2021-2022, https://doi.org/10.5194/essd-14-2021-2022, 2022
Short summary
Short summary
The French ATR42 research aircraft participated in the EUREC4A international field campaign that took place in 2020 over the tropical Atlantic, east of Barbados. We present the extensive instrumentation of the aircraft, the research flights and the different measurements. We show that the ATR measurements of humidity, wind, aerosols and cloudiness in the lower atmosphere are robust and consistent with each other. They will make it possible to advance understanding of cloud–climate interactions.
Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker
Atmos. Meas. Tech., 15, 1931–1956, https://doi.org/10.5194/amt-15-1931-2022, https://doi.org/10.5194/amt-15-1931-2022, 2022
Short summary
Short summary
A new IIR-based cloud and aerosol discrimination (CAD) algorithm is developed using the IIR brightness temperature differences for cloud and aerosol features confidently identified by the CALIOP version 4 CAD algorithm. IIR classifications agree with the majority of V4 cloud identifications, reduce the ambiguity in a notable fraction of
not confidentV4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.
Valery Shcherbakov, Frédéric Szczap, Alaa Alkasem, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 15, 1729–1754, https://doi.org/10.5194/amt-15-1729-2022, https://doi.org/10.5194/amt-15-1729-2022, 2022
Short summary
Short summary
We performed extensive Monte Carlo (MC) simulations of lidar signals and developed an empirical model to account for the multiple scattering in the lidar signals. The simulations have taken into consideration four types of lidar configurations (the ground based, the airborne, the CALIOP, and the ATLID) and four types of particles (coarse aerosol, water cloud, jet-stream cirrus, and cirrus).
The empirical model has very good quality of MC data fitting for all considered cases.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Aurélien Chauvigné, Fabien Waquet, Frédérique Auriol, Luc Blarel, Cyril Delegove, Oleg Dubovik, Cyrille Flamant, Marco Gaetani, Philippe Goloub, Rodrigue Loisil, Marc Mallet, Jean-Marc Nicolas, Frédéric Parol, Fanny Peers, Benjamin Torres, and Paola Formenti
Atmos. Chem. Phys., 21, 8233–8253, https://doi.org/10.5194/acp-21-8233-2021, https://doi.org/10.5194/acp-21-8233-2021, 2021
Short summary
Short summary
This work presents aerosol above-cloud properties close to the Namibian coast from a combination of airborne passive remote sensing. The complete analysis of aerosol and cloud optical properties and their microphysical and radiative properties allows us to better identify the impacts of biomass burning emissions. This work also gives a complete overview of the key parameters for constraining climate models in case aerosol and cloud coexist in the troposphere.
Frédéric Szczap, Alaa Alkasem, Guillaume Mioche, Valery Shcherbakov, Céline Cornet, Julien Delanoë, Yahya Gour, Olivier Jourdan, Sandra Banson, and Edouard Bray
Atmos. Meas. Tech., 14, 199–221, https://doi.org/10.5194/amt-14-199-2021, https://doi.org/10.5194/amt-14-199-2021, 2021
Short summary
Short summary
Spaceborne lidar and radar are suitable tools to investigate cloud vertical properties on a global scale. This paper presents the McRALI code that provides simulations of lidar and radar signals from the EarthCARE mission. Regarding radar signals, cloud heterogeneity induces a severe bias in velocity estimates. Regarding lidar signals, multiple scattering is not negligible. Our results also give some insight into the reliability of lidar signal modeling using independent column approximation.
Kaisa Lakkala, Jukka Kujanpää, Colette Brogniez, Nicolas Henriot, Antti Arola, Margit Aun, Frédérique Auriol, Alkiviadis F. Bais, Germar Bernhard, Veerle De Bock, Maxime Catalfamo, Christine Deroo, Henri Diémoz, Luca Egli, Jean-Baptiste Forestier, Ilias Fountoulakis, Katerina Garane, Rosa Delia Garcia, Julian Gröbner, Seppo Hassinen, Anu Heikkilä, Stuart Henderson, Gregor Hülsen, Bjørn Johnsen, Niilo Kalakoski, Angelos Karanikolas, Tomi Karppinen, Kevin Lamy, Sergio F. León-Luis, Anders V. Lindfors, Jean-Marc Metzger, Fanny Minvielle, Harel B. Muskatel, Thierry Portafaix, Alberto Redondas, Ricardo Sanchez, Anna Maria Siani, Tove Svendby, and Johanna Tamminen
Atmos. Meas. Tech., 13, 6999–7024, https://doi.org/10.5194/amt-13-6999-2020, https://doi.org/10.5194/amt-13-6999-2020, 2020
Short summary
Short summary
The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. Ground-based data from 25 sites located in Arctic, subarctic, temperate, equatorial and Antarctic
areas were used for the validation of the TROPOMI surface ultraviolet (UV) radiation product. For most sites 60 %–80 % of TROPOMI data was within ± 20 % of ground-based data.
Cited articles
Alexandrov, M. D., Cairns, B., Emde, C., Ackerman, A. S., and van Diedenhoven, B.:
Accuracy assessments of cloud droplet size retrievals from polarized reflectance measurements by the research scanning polarimeter, Remote Sens. Environ., 125, 92–111, https://doi.org/10.1016/j.rse.2012.07.012, 2012.
Alexandrov, M. D., Miller, D. J., Rajapakshe, C., Fridlind, A., van Diedenhoven, B., Cairns, B., Ackerman, A. S., and Zhang, Z.:
Vertical profiles of droplet size distributions derived from cloud-side observations by the research scanning polarimeter: Tests on simulated data, Atmos. Res., 239, 104924, https://doi.org/10.1016/j.atmosres.2020.104924, 2020.
Auriol, F., Léon, J.-F., Balois, J.-Y., Verwaerde, C., François, P., Riedi, J., Parol, F., Waquet, F., Tanré, D., and Goloub, P.:
Multidirectional visible and shortwave infrared polarimeter for atmospheric aerosol and cloud observation: OSIRIS (Observing System Including PolaRisation in the Solar Infrared Spectrum), in: Proceedings of SPIE 7149, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications II, Noumea, New Caledonia, 17–21 November 2008, https://doi.org/10.1117/12.806421, 2008.
Benner, T. C. and Evans, K. F.:
Three-dimensional solar radiative transfer in small tropical cumulus fields derived from high-resolution imagery, J. Geophys. Res.-Atmos., 106, 14975–14984, https://doi.org/10.1029/2001JD900158, 2001.
Bréon, F.-M., and Goloub, P.:
Cloud droplet effective radius from spaceborne polarization measurements, Geophys. Res. Lett., 25, 1879–1882, https://doi.org/10.1029/98GL01221, 1998.
Bruneau, D., Pelon, J., Blouzon, F., Spatazza, J., Genau, P., Buchholtz, G., Amarouche, N., Abchiche, A., and Aouji, O.:
355-nm high spectral resolution airborne lidar LNG: system description and first results, Appl. Optics, 54, 8776–8785, https://doi.org/10.1364/AO.54.008776, 2015.
Buriez, J. C., Vanbauce, C., Parol, F., Goloub, P., Herman, M., Bonnel, B., Fouquart, Y., Couvert, P., and Seze, G.:
Cloud detection and derivation of cloud properties from POLDER, Int. J. Remote Sens., 18, 2785–2813, https://doi.org/10.1080/014311697217332, 1997.
Cahalan, R. F., Ridgway, W., Wiscombe, W. J., Gollmer, S., and Harshvardhan: Independent Pixel and Monte Carlo Estimates of Stratocumulus Albedo, J. Atmos. Sci., 51, 3776–3790, https://doi.org/10.1175/1520-0469(1994)051<3776:IPAMCE>2.0.CO;2, 1994.
Chang, F.:
Estimating the vertical variation of cloud droplet effective radius using multispectral near-infrared satellite measurements, J. Geophys. Res., 107, 4257, https://doi.org/10.1029/2001JD000766, 2002.
Chang, I. and Christopher, S. A.:
Identifying Absorbing Aerosols above Clouds from the Spinning Enhanced Visible and Infrared Imager Coupled with NASA A-Train Multiple Sensors, IEEE T. Geosci. Remote, 54, 3163–3173, https://doi.org/10.1109/TGRS.2015.2513015, 2016.
Cho, H., Zhang, Z., Meyer, K., Lebsock, M., Platnick, S., Ackerman, A. S., Di Girolamo, L., C.-Labonnote, L., Cornet, C., Riedi, J., and Holz, R. E.:
Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans, J. Geophys. Res.-Atmos., 120, 4132–4154, https://doi.org/10.1002/2015JD023161, 2015.
Cooper, S. J., L'Ecuyer, T. S., and Stephens, G. L.:
The impact of explicit cloud boundary information on ice cloud microphysical property retrievals from infrared radiances, J. Geophys. Res.-Atmos., 108, 4107, https://doi.org/10.1029/2002JD002611, 2003.
Cornet, C. and Davies, R.:
Use of MISR measurements to study the radiative transfer of an isolated convective cloud: Implications for cloud optical thickness retrieval, J. Geophys. Res.-Atmos., 113, 1–11, https://doi.org/10.1029/2007JD008921, 2008.
Cornet, C., Buriez, J., Riédi, J., Isaka, H., and Guillemet, B.:
Case study of inhomogeneous cloud parameter retrieval from MODIS data, Geophys. Res. Lett., 32, L13807, https://doi.org/10.1029/2005GL022791, 2005.
Cornet, C., C-Labonnote, L., and Szczap, F.:
Three-dimensional polarized Monte Carlo atmospheric radiative transfer model (3DMCPOL): 3D effects on polarized visible reflectances of a cirrus cloud, J. Quant. Spectrosc. Ra., 111, 174–186, https://doi.org/10.1016/j.jqsrt.2009.06.013, 2010.
Cornet, C., C.-Labonnote, L., Waquet, F., Szczap, F., Deaconu, L., Parol, F., Vanbauce, C., Thieuleux, F., and Riédi, J.:
Cloud heterogeneity on cloud and aerosol above cloud properties retrieved from simulated total and polarized reflectances, Atmos. Meas. Tech., 11, 3627–3643, https://doi.org/10.5194/amt-11-3627-2018, 2018.
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, https://doi.org/10.1364/JOSA.44.000838, 1954.
Davis, A., Marshak, A., Cahalan, R., and Wiscombe, W.:
The Landsat Scale Break in Stratocumulus as a Three-Dimensional Radiative Transfer Effect: Implications for Cloud Remote Sensing, J. Atmos. Sci., 54, 241–260, https://doi.org/10.1175/1520-0469(1997)054<0241:TLSBIS>2.0.CO;2, 1997.
De Haan, J., Bosma, P., and Hovenier, J.:
The adding method for multiple scattering calculations of polarized light, Astron. Astrophys., 183, 371–391, 1987.
Deschamps, P.-Y., Breon, F.-M., Leroy, M., Podaire, A., Bricaud, A., Buriez, J.-C., and Seze, G.:
The POLDER mission: instrument characteristics and scientific objectives, IEEE T. Geosci. Remote, 32, 598–615, https://doi.org/10.1109/36.297978, 1994.
Desmons, M., Ferlay, N., Parol, F., Mcharek, L., and Vanbauce, C.:
Improved information about the vertical location and extent of monolayer clouds from POLDER3 measurements in the oxygen A-band, Atmos. Meas. Tech., 6, 2221–2238, https://doi.org/10.5194/amt-6-2221-2013, 2013.
Elsaesser, G. S. and Kummerow, C. D.:
Toward a Fully Parametric Retrieval of the Nonraining Parameters over the Global Oceans, J. Appl. Meteorol. Clim., 47, 1599–1618, https://doi.org/10.1175/2007JAMC1712.1, 2008.
Ewald, F., Zinner, T., Kölling, T., and Mayer, B.:
Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides – Part 1: Retrieval development and characterization, Atmos. Meas. Tech., 12, 1183–1206, https://doi.org/10.5194/amt-12-1183-2019, 2019.
Fauchez, T., Platnick, S., Várnai, T., Meyer, K., Cornet, C., and Szczap, F.:
Scale dependence of cirrus heterogeneity effects. Part II: MODIS NIR and SWIR channels, Atmos. Chem. Phys., 18, 12105–12121, https://doi.org/10.5194/acp-18-12105-2018, 2018.
Formenti, P., D’Anna, B., Flamant, C., Mallet, M., Piketh, S. J., Schepanski, K., Waquet, F., Auriol, F., Brogniez, G., Burnet, F., Chaboureau, J., Chauvigné, A., Chazette, P., Denjean, C., Desboeufs, K., Doussin, J., Elguindi, N., Feuerstein, S., Gaetani, M., Giorio, C., Klopper, D., Mallet, M. D., Nabat, P., Monod, A., Solmon, F., Namwoonde, A., Chikwililwa, C., Mushi, R., Welton, E. J., and Holben, B.:
The Aerosols, Radiation and Clouds in Southern Africa Field Campaign in Namibia: Overview, Illustrative Observations, and Way Forward, B. Am. Meteorol. Soc., 100, 1277–1298, https://doi.org/10.1175/BAMS-D-17-0278.1, 2019.
Garnier, A., Pelon, J., Dubuisson, P., Faivre, M., Chomette, O., Pascal, N., and Kratz, D. P.: Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part I: Effective Emissivity and Optical Depth, J. Appl. Meteorol. Clim., 51, 1407–1425, https://doi.org/10.1175/JAMC-D-11-0220.1, 2012.
Giraud, V., Buriez, J. C., Fouquart, Y., Parol, F., and Seze, G.:
Large-scale analysis of cirrus clouds from AVHRR data: Assessment of both a microphysical index and the cloud-top temperature, J. Appl. Meteorol., 36, 664–675, https://doi.org/10.1175/1520-0450-36.6.664, 1997.
Hagolle, O., Goloub, P., Deschamps, P.-Y., Cosnefroy, H., Briottet, X., Bailleul, T., Nicolas, J.-M., Parol, F., Lafrance, B., and Herman, M.:
Results of POLDER in-flight calibration, IEEE T. Geosci. Remote, 37, 1550–1566, https://doi.org/10.1109/36.763266, 1999.
Hansen, J. E. and Travis, L. D.:
Light scattering in planetary atmospheres, Space Sci. Rev., 16, 527–610, https://doi.org/10.1007/BF00168069, 1974.
Hickey, J. R. and Karoli, A. R.:
Radiometric Calibrations for the Earth Radiation Budget Experiment, Appl. Opt., 13, 523, https://doi.org/10.1364/AO.13.000523, 1974.
Huazhe, S., Letu, H., Bréon, F.-M., Riedi, J., Ma, R., Wang, Z., Nakajima, T. Y., Wang, Z., and Chen, L.:
An improved algorithm of cloud droplet size distribution from POLDER polarized measurements, Remote Sens. Environ., 228, 61–74, https://doi.org/10.1016/j.rse.2019.04.013, 2019.
Inoue, T.:
On the Temperature and Effective Emissivity Determination of Semi-Transparent Cirrus Clouds by Bi-Spectral Measurements in the 10 µm Window Region, J. Meteorol. Soc. Jpn. Ser. II, 63, 88–99, https://doi.org/10.2151/jmsj1965.63.1_88, 1985.
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, in press, https://doi.org/10.1017/9781009157896, 2021.
Iwabuchi, H., Saito, M., Tokoro, Y., Putri, N. S., and Sekiguchi, M.:
Retrieval of radiative and microphysical properties of clouds from multispectral infrared measurements, Progress in Earth and Planetary Science, 3, 32, https://doi.org/10.1186/s40645-016-0108-3, 2016.
Kato, S. and Marshak, A.:
Solar zenith and viewing geometry-dependent errors in satellite retrieved cloud optical thickness: Marine stratocumulus case, J. Geophys. Res.-Atmos., 114, 1–13, https://doi.org/10.1029/2008JD010579, 2009.
Kaufman, Y. J., Tanré, D., and Boucher, O.:
A satellite view of aerosols in the climate system, Nature, 419, 215–223, https://doi.org/10.1038/nature01091, 2002.
Kokhanovsky, A. and Rozanov, V. V.:
Droplet vertical sizing in warm clouds using passive optical measurements from a satellite, Atmos. Meas. Tech., 5, 517–528, https://doi.org/10.5194/amt-5-517-2012, 2012.
Kollias, P., Szyrmer, W., Rémillard, J., and Luke, E.:
Cloud radar Doppler spectra in drizzling stratiform clouds: 2. Observations and microphysical modeling of drizzle evolution, J. Geophys. Res.-Atmos., 116, D13203, https://doi.org/10.1029/2010JD015238, 2011.
Levenberg, K.:
A method for the solution of certain non-linear problems in least squares, Q. Appl. Math., 2, 164–168, https://doi.org/10.1090/qam/10666, 1944.
Levis, A., Schechner, Y. Y., Aides, A., and Davis, A. B.: Airborne Three-Dimensional Cloud Tomography, IEEE International Conference on Computer Vision (ICCV), 3379–3387, https://doi.org/10.1109/ICCV.2015.386, 2015.
Lohmann, U. and Feichter, J.:
Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005.
Mallet, M., Dulac, F., Formenti, P., Nabat, P., Sciare, J., Roberts, G., Pelon, J., Ancellet, G., Tanré, D., Parol, F., Denjean, C., Brogniez, G., di Sarra, A., Alados-Arboledas, L., Arndt, J., Auriol, F., Blarel, L., Bourrianne, T., Chazette, P., Chevaillier, S., Claeys, M., D'Anna, B., Derimian, Y., Desboeufs, K., Di Iorio, T., Doussin, J.-F., Durand, P., Féron, A., Freney, E., Gaimoz, C., Goloub, P., Gómez-Amo, J. L., Granados-Muñoz, M. J., Grand, N., Hamonou, E., Jankowiak, I., Jeannot, M., Léon, J.-F., Maillé, M., Mailler, S., Meloni, D., Menut, L., Momboisse, G., Nicolas, J., Podvin, T., Pont, V., Rea, G., Renard, J.-B., Roblou, L., Schepanski, K., Schwarzenboeck, A., Sellegri, K., Sicard, M., Solmon, F., Somot, S., Torres, B., Totems, J., Triquet, S., Verdier, N., Verwaerde, C., Waquet, F., Wenger, J., and Zapf, P.:
Overview of the Chemistry-Aerosol Mediterranean Experiment/Aerosol Direct Radiative Forcing on the Mediterranean Climate (ChArMEx/ADRIMED) summer 2013 campaign, Atmos. Chem. Phys., 16, 455–504, https://doi.org/10.5194/acp-16-455-2016, 2016.
Marbach T., Riedi J., Lacan A., and Schlüssel P. : The 3MI mission: multi-viewing-channel-polarisation imager of the EUMETSAT polar system: second generation (EPS-SG) dedicated to aerosol and cloud monitoring, Proc. SPIE 9613, Polarization Science and Remote Sensing VII, https://doi.org/10.1117/12.2186978, 2015.
Marquardt, D. W.:
An Algorithm for Least-Squares Estimation of Nonlinear Parameters, J. Soc. Ind. Appl. Math., 11, 431–441, https://doi.org/10.1137/0111030, 1963.
Marshak, A., Davis, A., Wiscombe, W., and Titov, G.:
The verisimilitude of the independent pixel approximation used in cloud remote sensing, Remote Sens. Environ., 52, 71–78, https://doi.org/10.1016/0034-4257(95)00016-T, 1995.
Marshak, A., Platnick, S., Várnai, T., Wen, G., and Cahalan, R. F.:
Impact of three-dimensional radiative effects on satellite retrievals of cloud droplet sizes, J. Geophys. Res., 111, D09207, https://doi.org/10.1029/2005JD006686, 2006.
Martin, W., Cairns, B., and Bal, G.:
Adjoint methods for adjusting three-dimensional atmosphere and surface properties to fit multi-angle/multi-pixel polarimetric measurements, J. Quant. Spectrosc. Ra., 144, 68–85, https://doi.org/10.1016/j.jqsrt.2014.03.030, 2014.
McClatchey, R. A., Fenn, R. W., Selby, J. E. A., Volz, F. E., and Garing, J. S.:
Optical Properties of the Atmosphere, 3rd Edn., AIR FORCE CAMBRIDGE RESEARCH LABS HANSCOM AFB MA., Defense Technical Information Center, AFCRL-TR-720497, AD715270, 1972.
Merlin, G.:
Préparation à l'exploitation des observationsmulti-spectrales, multi-angulaires et polarisées de l'instrument 3MI pour les atmosphères nuageuses, PhD thesis, University of Lille, France, 2016LIL10184, 212 pp., 2016.
Miles, N. L., Verlinde, J., and Clothiaux, E. E.:
Cloud Droplet Size Distributions in Low-Level Stratiform Clouds, J. Atmos. Sci.. 57. 295–311, https://doi.org/10.1175/1520-0469(2000)057<0295:CDSDIL>2.0.CO;2, 2000.
Miller, D. J., Zhang, Z., Ackerman, A. S., Platnick, S., and Baum, B. A.:
The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large-eddy simulations of shallow marine boundary layer clouds, J. Geophys. Res.-Atmos., 121, 4122–4141, https://doi.org/10.1002/2015JD024322, 2016.
Nakajima, T. and King, M. D.:
Determination of the Optical Thickness and Effective Particle Radius of Clouds from Reflected Solar Radiation Measurements. Part I: Theory, J. Atmos. Sci., 47, 1878–1893, https://doi.org/10.1175/1520-0469(1990)047<1878:DOTOTA>2.0.CO;2, 1990.
Nakajima, T. Y., Suzuki, K., and Stephens, G. L.:
Droplet Growth in Warm Water Clouds Observed by the A-Train. Part II: A Multisensor View, J. Atmos. Sci., 67, 1897–1907, https://doi.org/10.1175/2010JAS3276.1, 2010.
Okamura, R., Iwabuchi, H., and Schmidt, K. S.:
Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning, Atmos. Meas. Tech., 10, 4747–4759, https://doi.org/10.5194/amt-10-4747-2017, 2017.
Oreopoulos, L. and Davies, R.:
Plane Parallel Albedo Biases from Satellite Observations. Part I: Dependence on Resolution and Other Factors, J. Climate, 11, 919–932, https://doi.org/10.1175/1520-0442(1998)011<0919:PPABFS>2.0.CO;2, 1998.
Oreopoulos, L. and Platnick, S.: Radiative susceptibility of cloudy atmospheres to droplet number perturbations: 2. Global analysis from MODIS, J. Geophys. Res., 113, D14S21, https://doi.org/10.1029/2007JD009655, 2008.
Parol, F., Buriez, J. C., Brogniez, G., and Fouquart, Y.:
Information Content of AVHRR Channels 4 and 5 with Respect to the Effective Radius of Cirrus Cloud Particles, J. Appl. Meteorol., 30, 973–984, https://doi.org/10.1175/1520-0450-30.7.973, 1991.
Platnick, S.:
Vertical photon transport in cloud remote sensing problems, J. Geophys. Res.-Atmos., 105, 22919–22935, https://doi.org/10.1029/2000JD900333, 2000.
Platnick, S., King, M. D., Ackerman, S. A., Menzel, W. P., Baum, B. A., Riedi, J. C., and Frey, R. A.:
The MODIS cloud products: algorithms and examples from terra, IEEE T. Geosci. Remote, 41, 459–473, https://doi.org/10.1109/TGRS.2002.808301, 2003.
Platnick, S., Meyer, K. G., D., K. M., Wind, G., Amarasinghe, N., Marchant, B., Arnold, G. T., Zhang, Z., Hubanks, P. A., Holz, R. E., Yang, P., Ridgway, W. L., and Riedi, J.:
The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua, IEEE T. Geosci. Remote, 55, 502–525, https://doi.org/10.1109/TGRS.2016.2610522, 2017.
Poulsen, C. A., Siddans, R., Thomas, G. E., Sayer, A. M., Grainger, R. G., Campmany, E., Dean, S. M., Arnold, C., and Watts, P. D.:
Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR, Atmos. Meas. Tech., 5, 1889–1910, https://doi.org/10.5194/amt-5-1889-2012, 2012.
Rivoire, L., Birner, T., Knaff, J. A., and Tourville, N.:
Quantifying the Radiative Impact of Clouds on Tropopause Layer Cooling in Tropical Cyclones, J. Climate, 33, 6361–6376, https://doi.org/10.1175/JCLI-D-19-0813.1, 2020.
Rodgers, C. D.:
Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation, Rev. Geophys., 14, 609, https://doi.org/10.1029/RG014i004p00609, 1976.
Rodgers, C. D.:
Inverse methods for atmospheric sounding: Theory and Practice/Series on Atmospheric, Oceanic and Planetary Physics, in: Inverse Methods for Atmospheric Sounding, Vol. 2, World Scientific, Publishing Co. Pte. Ltd., Farrer Road, Singapore 912805 https://doi.org/10.1142/9789812813718_0001, 2000.
Saito, M., Yang, P., Hu, Y., Liu, X., Loeb, N., Smith Jr, W. L., and Minnis, P.:
An efficient method for microphysical property retrievals in vertically inhomogeneous marine water clouds using MODIS-CloudSat measurements, J. Geophys. Res.-Atmos., 124, 2174–2193, https://doi.org/10.1029/2018JD029659, 2019.
Seethala, C. and Horváth, Á.:
Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds, J. Geophys. Res., 115, D13202, https://doi.org/10.1029/2009JD012662, 2010.
Sourdeval, O., C.-Labonnote, L. C., Brogniez, G., Jourdan, O., Pelon, J., and Garnier, A.:
A variational approach for retrieving ice cloud properties from infrared measurements: application in the context of two IIR validation campaigns, Atmos. Chem. Phys., 13, 8229–8244, https://doi.org/10.5194/acp-13-8229-2013, 2013.
Sourdeval, O., C.-Labonnote, L., Baran, A. J., and Brogniez, G.:
A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study, Q. J. Roy. Meteor. Soc., 141, 870–882, https://doi.org/10.1002/qj.2405, 2015.
Szczap, F., Isaka, H., Saute, M., Guillemet, B., and Ioltukhovski, A.:
Effective radiative properties of bounded cascade absorbing clouds: Definition of an effective single-scattering albedo, J. Geophys. Res.-Atmos., 105, 20635–20648, https://doi.org/10.1029/2000JD900145, 2000.
Takahashi, H., Lebsock, M., Suzuki, K., Stephens, G., and Wang, M.:
An investigation of microphysics and subgrid-scale variability in warm-rain clouds using the A-Train observations and a multiscale modeling framework, J. Geophys. Res.-Atmos., 122, 7493–7504, https://doi.org/10.1002/2016JD026404, 2017.
Twomey, S.:
Aerosols, clouds and radiation, Atmos. Environ. A-Gen., 25, 2435–2442, https://doi.org/10.1016/0960-1686(91)90159-5, 1991.
Van de Hulst, H. C.:
A new look at multiple scattering, Tech. Rep., Goddard Institute for Space Studies, NASA TM-I03044, NASA Institute for Space Studies, Goddard Space Flight Center, New York, 1963.
Várnai, T.:
Influence of three-dimensional radiative effects on the spatial distribution of shortwave cloud reflection, J. Atmos. Sci., 57, 216–229, https://doi.org/10.1175/1520-0469(2000)057<0216:IOTDRE>2.0.CO;2, 2000.
Várnai, T. and Davies, R.:
Effects of Cloud Heterogeneities on Shortwave Radiation: Comparison of Cloud-Top Variability and Internal Heterogeneity, J. Atmos. Sci., 56, 4206–4224, https://doi.org/10.1175/1520-0469(1999)056<4206:EOCHOS>2.0.CO;2, 1999.
Várnai, T. and Marshak, A.:
A method for analyzing how various parts of clouds influence each other's brightness, J. Geophys. Res., 108, 4706, https://doi.org/10.1029/2003JD003561, 2003.
Várnai, T. and Marshak, A.:
View angle dependence of cloud optical thicknesses retrieved by Moderate Resolution Imaging Spectroradiometer (MODIS), J. Geophys. Res.-Atmos., 112, 1–12, https://doi.org/10.1029/2005JD006912, 2007.
Várnai, T. and Marshak, A.:
MODIS observations of enhanced clear sky reflectance near clouds, Geophys. Res. Lett., 36, L06807, https://doi.org/10.1029/2008GL037089, 2009.
Walther, A. and Heidinger, A. K.:
Implementation of the Daytime Cloud Optical and Microphysical Properties Algorithm (DCOMP) in PATMOS-x, J. Appl. Meteorol. Clim., 51, 1371–1390, https://doi.org/10.1175/JAMC-D-11-0108.1, 2012.
Wang, C., Platnick, S., Zhang, Z., Meyer, K., and Yang, P.:
Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content, J. Geophys. Res.-Atmos., 121, 5809–5826, https://doi.org/10.1002/2015JD024526, 2016.
Wood, R.:
Drizzle in Stratiform Boundary Layer Clouds. Part II: Microphysical Aspects, J. Atmos. Sci., 62, 3034–3050, https://doi.org/10.1175/JAS3530.1, 2005.
Yang, Q., Fu, Q., and Hu, Y.:
Radiative impacts of clouds in the tropical tropopause layer, J. Geophys. Res.-Atmos., 115, 1–21, https://doi.org/10.1029/2009JD012393, 2010.
Zhang, Y., Xie, S., Lin, W., Klein, S. A., Zelinka, M., Ma, P., Rasch, P. J., Qian, Y., Tang, Q., and Ma, H.:
Evaluation of Clouds in Version 1 of the E3SM Atmosphere Model With Satellite Simulators, J. Adv. Model. Earth Sy., 11, 1253–1268, https://doi.org/10.1029/2018MS001562, 2019.
Zhang, Z. and Platnick, S.:
An assessment of differences between cloud effective particle radius retrievals for marine water clouds from three MODIS spectral bands, J. Geophys. Res., 116, D20215, https://doi.org/10.1029/2011JD016216, 2011.
Zhang, Z., Ackerman, A. S., Feingold, G., Platnick, S., Pincus, R., and Xue, H.:
Effects of cloud horizontal inhomogeneity and drizzle on remote sensing of cloud droplet effective radius: Case studies based on large-eddy simulations, J. Geophys. Res.-Atmos., 117, D19208, https://doi.org/10.1029/2012JD017655, 2012.
Zinner, T. and Mayer, B.:
Remote sensing of stratocumulus clouds: Uncertainties and biases due to inhomogeneity, J. Geophys. Res., 111, D14209, https://doi.org/10.1029/2005JD006955, 2006.
Short summary
The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular...