Articles | Volume 12, issue 5
https://doi.org/10.5194/amt-12-2819-2019
© Author(s) 2019. 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-12-2819-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 May 2019
Research article |
| 16 May 2019
| 16 May 2019
Evolution of DARDAR-CLOUD ice cloud retrievals: new parameters and impacts on the retrieved microphysical properties
Quitterie Cazenave
CORRESPONDING AUTHOR
Université Versailles St-Quentin, LATMOS-IPSL, Guyancourt, France
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, 82234 Weßling, Germany
Marie Ceccaldi
Université Versailles St-Quentin, LATMOS-IPSL, Guyancourt, France
Julien Delanoë
Université Versailles St-Quentin, LATMOS-IPSL, Guyancourt, France
Jacques Pelon
CNRS/INSU, LATMOS-IPSL, Paris, France
Silke Groß
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, 82234 Weßling, Germany
Andrew Heymsfield
NCAR, Boulder, Colorado, USA
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A method for estimating microphysical properties of ice clouds based on radar measurements is presented. The algorithm exploits the information provided by differences in the radar response at different frequency bands in relation to changes in the snow morphology. The inversion scheme is based on a statistical relation between the radar simulations and the properties of snow calculated from in-cloud sampling.
Lilian Loyer, Jean-Christophe Raut, Claudia Di Biagio, Julia Maillard, Vincent Mariage, and Jacques Pelon
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-326, https://doi.org/10.5194/amt-2021-326, 2021
Revised manuscript not accepted
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The Arctic is facing drastic climate changes, and more observations are needed to better understand what is happening. Unfortunately observations are limited in the High Arctic. To obtain more observations, multiples buoys equipped with lidar, have been deployed in this region. This paper presents an approach to estimate the optical properties of clouds, and solar plus terrestrial energies from lidar measurements in the Arctic.
Gwendal Rivière, Meryl Wimmer, Philippe Arbogast, Jean-Marcel Piriou, Julien Delanoë, Carole Labadie, Quitterie Cazenave, and Jacques Pelon
Weather Clim. Dynam., 2, 1011–1031, https://doi.org/10.5194/wcd-2-1011-2021, https://doi.org/10.5194/wcd-2-1011-2021, 2021
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Inacurracies in representing processes occurring at spatial scales smaller than the grid scales of the weather forecast models are important sources of forecast errors. This is the case of deep convection representation in models with 10 km grid spacing. We performed simulations of a real extratropical cyclone using a model with different representations of deep convection. These forecasts lead to different behaviors in the ascending air masses of the cyclone and the jet stream aloft.
Qiang Li and Silke Groß
Atmos. Chem. Phys., 21, 14573–14590, https://doi.org/10.5194/acp-21-14573-2021, https://doi.org/10.5194/acp-21-14573-2021, 2021
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Aircraft emit exhaust gases and particles directly into the atmosphere, which may contribute to climate change. We present a significant reduction in the occurrence rate and particle linear depolarization ratio of cirrus clouds based on the analysis of measurements with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite during COVID-19 when air traffic was significantly reduced. The findings imply that these clouds formed with less influence from aviation.
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
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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.
Florian Ewald, Silke Groß, Martin Wirth, Julien Delanoë, Stuart Fox, and Bernhard Mayer
Atmos. Meas. Tech., 14, 5029–5047, https://doi.org/10.5194/amt-14-5029-2021, https://doi.org/10.5194/amt-14-5029-2021, 2021
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In this study, we show how solar radiance observations can be used to validate and further constrain ice cloud microphysics retrieved from the synergy of radar–lidar measurements. Since most radar–lidar retrievals rely on a global assumption about the ice particle shape, ice water content and particle size biases are to be expected in individual cloud regimes. In this work, we identify and correct these biases by reconciling simulated and measured solar radiation reflected from these clouds.
Alistair Bell, Pauline Martinet, Olivier Caumont, Benoît Vié, Julien Delanoë, Jean-Charles Dupont, and Mary Borderies
Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, https://doi.org/10.5194/amt-14-4929-2021, 2021
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This paper presents work towards making retrievals on the liquid water content in fog and low clouds. Future retrievals will rely on a radar simulator and high-resolution forecast. In this work, real observations are used to assess the errors associated with the simulator and forecast. A selection method to reduce errors associated with the forecast is proposed. It is concluded that the distribution of errors matches the requirements for future retrievals.
Pierre-Etienne Brilouet, Marie Lothon, Jean-Claude Etienne, Pascal Richard, Sandrine Bony, Julien Lernoult, Hubert Bellec, Gilles Vergez, Thierry Perrin, Julien Delanoë, Tetyana Jiang, Frédéric Pouvesle, Claude Lainard, Michel Cluzeau, Laurent Guiraud, Patrice Medina, and Theotime Charoy
Earth Syst. Sci. Data, 13, 3379–3398, https://doi.org/10.5194/essd-13-3379-2021, https://doi.org/10.5194/essd-13-3379-2021, 2021
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During the EUREC4A field experiment that took place over the tropical Atlantic Ocean east of Barbados, the French ATR 42 environment research aircraft of SAFIRE aimed to characterize the shallow cloud properties near cloud base and the turbulent structure of the subcloud layer. The high-frequency measurements of wind, temperature and humidity as well as their translation in terms of turbulent fluctuations, turbulent moments and characteristic length scales of turbulence are presented.
Didier Bruneau and Jacques Pelon
Atmos. Meas. Tech., 14, 4375–4402, https://doi.org/10.5194/amt-14-4375-2021, https://doi.org/10.5194/amt-14-4375-2021, 2021
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Taking advantage of Aeolus success and of our airborne lidar system expertise, we present a new spaceborne wind lidar design for operational Aeolus follow-on missions, keeping most of the initial lidar system but relying on a single Mach–Zehnder interferometer to relax operational constraints and reduce measurement bias. System parameters are optimized. Random and systematic errors are shown to be compliant with the initial mission requirements. In addition, the system allows unbiased retrieval.
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3253–3276, https://doi.org/10.5194/amt-14-3253-2021, https://doi.org/10.5194/amt-14-3253-2021, 2021
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The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results are presented in a companion paper (Part II).
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, https://doi.org/10.5194/amt-14-3277-2021, 2021
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The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version 3 as a result of the significant changes implemented in the version 4 algorithms, which are presented in a companion paper (Part I).
David L. A. Flack, Gwendal Rivière, Ionela Musat, Romain Roehrig, Sandrine Bony, Julien Delanoë, Quitterie Cazenave, and Jacques Pelon
Weather Clim. Dynam., 2, 233–253, https://doi.org/10.5194/wcd-2-233-2021, https://doi.org/10.5194/wcd-2-233-2021, 2021
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The representation of an extratropical cyclone in simulations of two climate models is studied by comparing them to observations of the international field campaign NAWDEX. We show that the current resolution used to run climate model projections (more than 100 km) is not enough to represent the life cycle accurately, but the use of 50 km resolution is good enough. Despite these encouraging results, cloud properties (partitioning liquid and solid) are found to be far from the observations.
Julia Maillard, François Ravetta, Jean-Christophe Raut, Vincent Mariage, and Jacques Pelon
Atmos. Chem. Phys., 21, 4079–4101, https://doi.org/10.5194/acp-21-4079-2021, https://doi.org/10.5194/acp-21-4079-2021, 2021
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Clouds remain a major source of uncertainty in understanding the Arctic climate, due in part to the lack of measurements over the sea ice. In this paper, we exploit a series of lidar profiles acquired from autonomous drifting buoys deployed in the Arctic Ocean and derive a statistic of low cloud frequency and macrophysical properties. We also show that clouds contribute to warm the surface in the shoulder seasons but not significantly from May to September.
Nicolas Blanchard, Florian Pantillon, Jean-Pierre Chaboureau, and Julien Delanoë
Weather Clim. Dynam., 2, 37–53, https://doi.org/10.5194/wcd-2-37-2021, https://doi.org/10.5194/wcd-2-37-2021, 2021
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Rare aircraft observations in the warm conveyor belt outflow associated with an extratropical cyclone are complemented with convection-permitting simulations. They reveal a complex tropopause structure with two jet stream cores, from which one is reinforced by bands of negative potential vorticity. They show that negative potential vorticity takes its origin in mid-level convection, which indirectly accelerates the jet stream and, thus, may influence the downstream large-scale circulation.
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
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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.
Felipe Toledo, Julien Delanoë, Martial Haeffelin, Jean-Charles Dupont, Susana Jorquera, and Christophe Le Gac
Atmos. Meas. Tech., 13, 6853–6875, https://doi.org/10.5194/amt-13-6853-2020, https://doi.org/10.5194/amt-13-6853-2020, 2020
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Cloud observations are essential to rainfall, fog and climate change forecasts. One key instrument for these observations is cloud radar. Yet, discrepancies are found when comparing radars from different ground stations or satellites. Our work presents a calibration methodology for cloud radars based on reference targets, including an analysis of the uncertainty sources. The method enables the calibration of reference instruments to improve the quality and value of the cloud radar network data.
Ourania Soupiona, Alexandros Papayannis, Panagiotis Kokkalis, Romanos Foskinis, Guadalupe Sánchez Hernández, Pablo Ortiz-Amezcua, Maria Mylonaki, Christina-Anna Papanikolaou, Nikolaos Papagiannopoulos, Stefanos Samaras, Silke Groß, Rodanthi-Elisavet Mamouri, Lucas Alados-Arboledas, Aldo Amodeo, and Basil Psiloglou
Atmos. Chem. Phys., 20, 15147–15166, https://doi.org/10.5194/acp-20-15147-2020, https://doi.org/10.5194/acp-20-15147-2020, 2020
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51 dust events over the Mediterranean from EARLINET were studied regarding the aerosol geometrical, optical and microphysical properties and radiative forcing. We found δp532 values of 0.24–0.28, LR532 values of 49–52 sr and AOT532 of 0.11–0.40. The aerosol mixing state was also examined. Depending on the dust properties, intensity and solar zenith angle, the estimated solar radiative forcing ranged from −59 to −22 W m−2 at the surface and from −24 to −1 W m−2 at the TOA (cooling effect).
Setigui Aboubacar Keita, Eric Girard, Jean-Christophe Raut, Maud Leriche, Jean-Pierre Blanchet, Jacques Pelon, Tatsuo Onishi, and Ana Cirisan
Geosci. Model Dev., 13, 5737–5755, https://doi.org/10.5194/gmd-13-5737-2020, https://doi.org/10.5194/gmd-13-5737-2020, 2020
Anna Gialitaki, Alexandra Tsekeri, Vassilis Amiridis, Romain Ceolato, Lucas Paulien, Anna Kampouri, Antonis Gkikas, Stavros Solomos, Eleni Marinou, Moritz Haarig, Holger Baars, Albert Ansmann, Tatyana Lapyonok, Anton Lopatin, Oleg Dubovik, Silke Groß, Martin Wirth, Maria Tsichla, Ioanna Tsikoudi, and Dimitris Balis
Atmos. Chem. Phys., 20, 14005–14021, https://doi.org/10.5194/acp-20-14005-2020, https://doi.org/10.5194/acp-20-14005-2020, 2020
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Stratospheric smoke particles are found to significantly depolarize incident light, while this effect is also accompanied by a strong spectral dependence. We utilize scattering simulations to show that this behaviour can be attributed to the near-spherical shape of the particles. We also examine whether an extension of the current AERONET scattering model to include the near-spherical shapes could be of benefit to the AERONET retrieval for stratospheric smoke associated with enhanced PLDR.
Manuel Gutleben, Silke Groß, Martin Wirth, and Bernhard Mayer
Atmos. Chem. Phys., 20, 12313–12327, https://doi.org/10.5194/acp-20-12313-2020, https://doi.org/10.5194/acp-20-12313-2020, 2020
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Airborne lidar measurements in the vicinity of Barbados are used to investigate radiative effects of long-range-transported Saharan air layers. Derived atmospheric heating rates indicate that observed enhanced water vapor concentrations inside these layers are the main drivers for dust vertical mixing inside the layers. Additionally, they may play a major role for the suppression of subjacent convective cloud development.
Nicolas Blanchard, Florian Pantillon, Jean-Pierre Chaboureau, and Julien Delanoë
Weather Clim. Dynam., 1, 617–634, https://doi.org/10.5194/wcd-1-617-2020, https://doi.org/10.5194/wcd-1-617-2020, 2020
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The study presents the first results from the airborne RASTA observations measured during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX). Our combined Eulerian–Lagrangian analysis found three types of organized convection (frontal, banded and mid-level) in the warm conveyor belt (WCB) of the Stalactite cyclone. The results emphasize that convection embedded in WCBs occurs in a coherent and organized manner rather than as isolated cells.
Christof G. Beer, Johannes Hendricks, Mattia Righi, Bernd Heinold, Ina Tegen, Silke Groß, Daniel Sauer, Adrian Walser, and Bernadett Weinzierl
Geosci. Model Dev., 13, 4287–4303, https://doi.org/10.5194/gmd-13-4287-2020, https://doi.org/10.5194/gmd-13-4287-2020, 2020
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Mineral dust aerosol plays an important role in the climate system. Previously, dust emissions have often been represented in global models by prescribed monthly-mean emission fields representative of a specific year. We now apply an online calculation of wind-driven dust emissions. This results in an improved agreement with observations, due to a better representation of the highly variable dust emissions. Increasing the model resolution led to an additional performance gain.
Melody A. Avery, Robert A. Ryan, Brian J. Getzewich, Mark A. Vaughan, David M. Winker, Yongxiang Hu, Anne Garnier, Jacques Pelon, and Carolus A. Verhappen
Atmos. Meas. Tech., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, https://doi.org/10.5194/amt-13-4539-2020, 2020
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CALIOP data users will find more cloud layers detected in V4, with edges that extend further than in V3, for an increase in total atmospheric cloud volume of 6 %–9 % for high-confidence cloud phases and 1 %–2 % for all cloudy bins, including cloud fringes and unknown cloud phases. In V4 there are many fewer cloud layers identified as horizontally oriented ice, particularly in the 3° off-nadir view. Depolarization at 532 nm is the predominant parameter determining cloud thermodynamic phase.
Annette K. Miltenberger, Paul R. Field, Adrian H. Hill, and Andrew J. Heymsfield
Atmos. Chem. Phys., 20, 7979–8001, https://doi.org/10.5194/acp-20-7979-2020, https://doi.org/10.5194/acp-20-7979-2020, 2020
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Orographic wave clouds offer a natural laboratory to investigate cloud microphysical processes and their representation in atmospheric models. They impact the larger-scale flow by a vertical redistribution of moisture and aerosol. We use detailed observations from the ICE-L campaign to evaluate the representation of these clouds in a state-of-the-art numerical weather prediction model and explore the impact of environmental conditions on the vertical redistribution of moisture.
Antonin Zabukovec, Gerard Ancellet, Iwan E. Penner, Mikhail Arshinov, Valery Kozlov, Jacques Pelon, Jean-Daniel Paris, Grigory Kokhanenko, Yuri S. Balin, Dmitry Chernov, and Boris D. Belan
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-195, https://doi.org/10.5194/acp-2020-195, 2020
Preprint withdrawn
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Description of two aircraft campaigns results carried out over Siberia in 2013 and 2017 to characterize aerosol emission. A methodology is proposed to derive the aerosol types using transport model and satellite observations. The extinction to backscatter ratio for each aerosol types is reported as it is a key parameter to constrain their radiative impact. These results are compared to previous work conducted in other regions and to aerosol data products observed by spaceborne lidars.
Emmanuel Fontaine, Alfons Schwarzenboeck, Delphine Leroy, Julien Delanoë, Alain Protat, Fabien Dezitter, John Walter Strapp, and Lyle Edward Lilie
Atmos. Chem. Phys., 20, 3503–3553, https://doi.org/10.5194/acp-20-3503-2020, https://doi.org/10.5194/acp-20-3503-2020, 2020
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This study investigates properties of ice hydrometeors (shape, concentration, density, and size) in deep convective systems. The analysis focuses on similarities and differences over four locations in the tropical troposphere. It shows that measurements as a function of temperature and radar reflectivity factors tend to be similar in the four types of deep convective systems when concentrations of ice are larger than 0.1 g m-3.
Carlos Toledano, Benjamín Torres, Cristian Velasco-Merino, Dietrich Althausen, Silke Groß, Matthias Wiegner, Bernadett Weinzierl, Josef Gasteiger, Albert Ansmann, Ramiro González, David Mateos, David Farrel, Thomas Müller, Moritz Haarig, and Victoria E. Cachorro
Atmos. Chem. Phys., 19, 14571–14583, https://doi.org/10.5194/acp-19-14571-2019, https://doi.org/10.5194/acp-19-14571-2019, 2019
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Ground-based sun photometers have been used to analyze the properties of long-range transported Saharan dust over Barbados. The measurements were carried out as part of the Saharan Aerosol Long-Range Transport and Aerosol–Cloud-Interaction Experiment (SALTRACE), carried out in the Caribbean in 2013. A variety of instruments, ground-based and airborne, were used in this research. In this paper, the sun photometer data are presented and related to data collected from other co-located instruments.
Eleni Marinou, Matthias Tesche, Athanasios Nenes, Albert Ansmann, Jann Schrod, Dimitra Mamali, Alexandra Tsekeri, Michael Pikridas, Holger Baars, Ronny Engelmann, Kalliopi-Artemis Voudouri, Stavros Solomos, Jean Sciare, Silke Groß, Florian Ewald, and Vassilis Amiridis
Atmos. Chem. Phys., 19, 11315–11342, https://doi.org/10.5194/acp-19-11315-2019, https://doi.org/10.5194/acp-19-11315-2019, 2019
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We assess the feasibility of ground-based and spaceborne lidars to retrieve profiles of cloud-relevant aerosol concentrations and ice-nucleating particles. The retrieved profiles are in good agreement with airborne in situ measurements. Our methodology will be applied to satellite observations in the future so as to provide a global 3D product of cloud-relevant properties.
Manuel Gutleben, Silke Groß, and Martin Wirth
Atmos. Chem. Phys., 19, 10659–10673, https://doi.org/10.5194/acp-19-10659-2019, https://doi.org/10.5194/acp-19-10659-2019, 2019
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This study concentrates on airborne lidar measurements conducted during the NARVAL field experiments over the western subtropical North Atlantic Ocean to study differences between shallow marine cloud macro-physical properties (i.e. cloud fraction, cloud top height, cloud length, cloud gap length) in Saharan-dust-laden and dust-free trade wind regions. Cloud top heights, cloud fractions and cloud lengths are found to be lower and smaller in Saharan-dust-laden compared to dust-free regions.
Constantino Listowski, Julien Delanoë, Amélie Kirchgaessner, Tom Lachlan-Cope, and John King
Atmos. Chem. Phys., 19, 6771–6808, https://doi.org/10.5194/acp-19-6771-2019, https://doi.org/10.5194/acp-19-6771-2019, 2019
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Using satellite cloud products we investigate the supercooled liquid-water (SLW) distribution Antarctic-wide for the first time. We demonstrate differences between the monthly evolution of the marine low-level mixed-phase clouds and that of the marine low-level pure SLW clouds. In addition to the temperature and sea ice fraction as factors explaining the low-level liquid-cloud seasonal cycle, ice nuclei emissions from open water may also be driving the mixed-phase cloud monthly evolution.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, Nadia Fourrié, and Pascal Marquet
Nat. Hazards Earth Syst. Sci., 19, 907–926, https://doi.org/10.5194/nhess-19-907-2019, https://doi.org/10.5194/nhess-19-907-2019, 2019
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The potential of W-band radar reflectivity to improve the quality of analyses and forecasts of heavy precipitation events in the Mediterranean area is investigated. The 1D + 3DVar assimilation method has been adapted to assimilate the W-band reflectivity in the Météo-France kilometre-scale NWP model AROME. The results suggest that the joint assimilation of W-band reflectivity and horizontal wind profiles lead to a slight improvement of moisture analyses and rainfall precipitation forecasts.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, and Nadia Fourrié
Nat. Hazards Earth Syst. Sci., 19, 821–835, https://doi.org/10.5194/nhess-19-821-2019, https://doi.org/10.5194/nhess-19-821-2019, 2019
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The study reports on the impact of the assimilation of wind data from airborne Doppler cloud-profiling radar in a kilometre-scale NWP model on predicting heavy precipitation events in the Mediterranean area. The positive impact of the assimilation of such data is particularly evidenced for a heavy precipitation event and results are slightly encouraging over a 45-day period. In addition, the impact of the length of the assimilation window in a 3h-3DVar assimilation system is investigated.
Florian Ewald, Silke Groß, Martin Hagen, Lutz Hirsch, Julien Delanoë, and Matthias Bauer-Pfundstein
Atmos. Meas. Tech., 12, 1815–1839, https://doi.org/10.5194/amt-12-1815-2019, https://doi.org/10.5194/amt-12-1815-2019, 2019
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This study gives a summary of lessons learned during the absolute calibration of the airborne, high-power Ka-band cloud radar HAMP MIRA on board the German research aircraft HALO. The first part covers the internal calibration of the instrument where individual instrument components are characterized in the laboratory. In the second part, the internal calibration is validated with external reference sources like the ocean surface backscatter and different air- and spaceborne cloud radars.
Zhaoyan Liu, Jayanta Kar, Shan Zeng, Jason Tackett, Mark Vaughan, Melody Avery, Jacques Pelon, Brian Getzewich, Kam-Pui Lee, Brian Magill, Ali Omar, Patricia Lucker, Charles Trepte, and David Winker
Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, https://doi.org/10.5194/amt-12-703-2019, 2019
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We describe the enhancements made to the cloud–aerosol discrimination (CAD) algorithms used to produce the CALIPSO version 4 (V4) data products. Revisions to the CAD probability distribution functions have greatly improved the recognition of aerosol layers lofted into the upper troposphere, and CAD is now applied to all layers detected in the stratosphere and all layers detected at single-shot resolution. Detailed comparisons show significant improvements relative to previous versions.
Gerard Ancellet, Iogannes E. Penner, Jacques Pelon, Vincent Mariage, Antonin Zabukovec, Jean Christophe Raut, Grigorii Kokhanenko, and Yuri S. Balin
Atmos. Meas. Tech., 12, 147–168, https://doi.org/10.5194/amt-12-147-2019, https://doi.org/10.5194/amt-12-147-2019, 2019
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Aerosol type seasonal variability and sources in Siberia are obtained from an automatic 808 nm micropulse lidar. A total of 540 aerosol backscatter vertical profiles have been retrieved using careful lidar calibration. Aerosol optical depth is retrieved using sun-photometer complementary observations and an aerosol source apportionment based on aerosol transport model simulations. Comparisons with satellite observations are discussed for three case studies.
Mark Vaughan, Anne Garnier, Damien Josset, Melody Avery, Kam-Pui Lee, Zhaoyan Liu, William Hunt, Jacques Pelon, Yongxiang Hu, Sharon Burton, Johnathan Hair, Jason L. Tackett, Brian Getzewich, Jayanta Kar, and Sharon Rodier
Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, https://doi.org/10.5194/amt-12-51-2019, 2019
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The version 4 (V4) release of the CALIPSO data products includes substantial improvements to the calibration of the CALIOP 1064 nm channel. In this paper we review the fundamentals of 1064 nm lidar calibration, explain the motivations for the changes made to the algorithm, and describe the mechanics of the V4 calibration technique. Internal consistency checks and comparisons to collocated high spectral resolution lidar measurements show the V4 1064 nm calibration coefficients to within ~ 3 %.
David L. Mitchell, Anne Garnier, Jacques Pelon, and Ehsan Erfani
Atmos. Chem. Phys., 18, 17325–17354, https://doi.org/10.5194/acp-18-17325-2018, https://doi.org/10.5194/acp-18-17325-2018, 2018
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To realistically model a changing climate, global measurements of cirrus cloud ice-particle number concentration (N) and size (De) are needed, through which one may infer the general mechanism of ice formation. A satellite remote sensing method was developed to measure N and De. It was found that N was highest and De lowest at high latitudes. In the Arctic, cirrus clouds occurred much more often during winter, which may have an impact on mid-latitude winter weather.
Christiane Voigt, Andreas Dörnbrack, Martin Wirth, Silke M. Groß, Michael C. Pitts, Lamont R. Poole, Robert Baumann, Benedikt Ehard, Björn-Martin Sinnhuber, Wolfgang Woiwode, and Hermann Oelhaf
Atmos. Chem. Phys., 18, 15623–15641, https://doi.org/10.5194/acp-18-15623-2018, https://doi.org/10.5194/acp-18-15623-2018, 2018
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The 2015–2016 stratospheric winter was the coldest in the 36-year climatological data record. The extreme conditions promoted the formation of persistent Arctic polar stratospheric ice clouds. An extended ice PSC detected by airborne lidar in January 2016 shows a second mode with higher particle depolarization ratios. Back-trajectories from the high-depol ice matched to CALIOP PSC curtains provide evidence for ice nucleation on NAT. The novel data consolidate our understanding of PSC formation.
Odran Sourdeval, Edward Gryspeerdt, Martina Krämer, Tom Goren, Julien Delanoë, Armin Afchine, Friederike Hemmer, and Johannes Quaas
Atmos. Chem. Phys., 18, 14327–14350, https://doi.org/10.5194/acp-18-14327-2018, https://doi.org/10.5194/acp-18-14327-2018, 2018
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The number concentration of ice crystals (Ni) is a key cloud property that remains very uncertain due to difficulties in determining it using satellites. This lack of global observational constraints limits our ability to constrain this property in models responsible for predicting future climate. This pair of papers fills this gap by showing and analyzing the first rigorously evaluated global climatology of Ni, leading to new information shedding light on the processes that control high clouds.
Edward Gryspeerdt, Odran Sourdeval, Johannes Quaas, Julien Delanoë, Martina Krämer, and Philipp Kühne
Atmos. Chem. Phys., 18, 14351–14370, https://doi.org/10.5194/acp-18-14351-2018, https://doi.org/10.5194/acp-18-14351-2018, 2018
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The concentration of ice crystals in a cloud affects both the properties and the life cycle of the cloud. This work uses a new satellite retrieval to investigate controls on the ice crystal concentration at a global scale. Both temperature and vertical wind speed in a cloud have a strong impact on the concentration of ice crystals. The ice crystal number is also related to the aerosol environment; defining this relation opens up new ways to investigate human impacts on clouds and the climate.
Brian H. Kahn, Hanii Takahashi, Graeme L. Stephens, Qing Yue, Julien Delanoë, Gerald Manipon, Evan M. Manning, and Andrew J. Heymsfield
Atmos. Chem. Phys., 18, 10715–10739, https://doi.org/10.5194/acp-18-10715-2018, https://doi.org/10.5194/acp-18-10715-2018, 2018
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The Atmospheric Infrared Sounder (AIRS) satellite instrument shows statistically significant global trends in ice cloud properties between September 2002 and August 2016. The trends are not explained by known AIRS instrument limitations. Significant differences in the ice cloud particle size is found between convective clouds and thin ice clouds in the tropics. These results will be a useful benchmark for other studies of global ice cloud properties.
Anne Garnier, Thierry Trémas, Jacques Pelon, Kam-Pui Lee, Delphine Nobileau, Lydwine Gross-Colzy, Nicolas Pascal, Pascale Ferrage, and Noëlle A. Scott
Atmos. Meas. Tech., 11, 2485–2500, https://doi.org/10.5194/amt-11-2485-2018, https://doi.org/10.5194/amt-11-2485-2018, 2018
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Residual calibration biases affecting CALIPSO IIR Version 1 calibrated radiances in the Northern Hemisphere are analyzed and reduced through in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels.
Christopher R. Yost, Kristopher M. Bedka, Patrick Minnis, Louis Nguyen, J. Walter Strapp, Rabindra Palikonda, Konstantin Khlopenkov, Douglas Spangenberg, William L. Smith Jr., Alain Protat, and Julien Delanoe
Atmos. Meas. Tech., 11, 1615–1637, https://doi.org/10.5194/amt-11-1615-2018, https://doi.org/10.5194/amt-11-1615-2018, 2018
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Accretion of cloud ice particles upon engine or instrument probe surfaces can cause engine malfunction or even power loss, and therefore it is important for aircraft to avoid flight through clouds that may have produced large quantities of ice particles. This study introduces a method by which potentially hazardous conditions can be detected using satellite imagery. It was found that potentially hazardous conditions were often located near or beneath very cold clouds and thunderstorm updrafts.
Jayanta Kar, Mark A. Vaughan, Kam-Pui Lee, Jason L. Tackett, Melody A. Avery, Anne Garnier, Brian J. Getzewich, William H. Hunt, Damien Josset, Zhaoyan Liu, Patricia L. Lucker, Brian Magill, Ali H. Omar, Jacques Pelon, Raymond R. Rogers, Travis D. Toth, Charles R. Trepte, Jean-Paul Vernier, David M. Winker, and Stuart A. Young
Atmos. Meas. Tech., 11, 1459–1479, https://doi.org/10.5194/amt-11-1459-2018, https://doi.org/10.5194/amt-11-1459-2018, 2018
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We present the motivation for and the implementation of the version 4.1 nighttime 532 nm parallel-channel calibration of the CALIOP lidar. The accuracy of calibration is significantly improved by raising the molecular normalization altitude from 30–34 km to 36–39 km to substantially reduce stratospheric aerosol contamination. The new calibration procedure eliminates biases in earlier versions and leads to an improved representation of stratospheric aerosols.
Volker Freudenthaler, Holger Linné, Anatoli Chaikovski, Dieter Rabus, and Silke Groß
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-395, https://doi.org/10.5194/amt-2017-395, 2018
Revised manuscript has not been submitted
Guillaume Mioche, Olivier Jourdan, Julien Delanoë, Christophe Gourbeyre, Guy Febvre, Régis Dupuy, Marie Monier, Frédéric Szczap, Alfons Schwarzenboeck, and Jean-François Gayet
Atmos. Chem. Phys., 17, 12845–12869, https://doi.org/10.5194/acp-17-12845-2017, https://doi.org/10.5194/acp-17-12845-2017, 2017
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This paper is a study about the mixed-phase clouds frequently occurring in the Arctic region. It is based on airborne measurements and highlights the microphysical properties of these particular clouds composed of liquid droplets at cloud top and ice crystals below precipitating down to the surface. This work may help to improve the representation of the mixed-phase clouds in numerical prediction models as well as the retrieval of their properties from remote sensing observations.
Lucia T. Deaconu, Fabien Waquet, Damien Josset, Nicolas Ferlay, Fanny Peers, François Thieuleux, Fabrice Ducos, Nicolas Pascal, Didier Tanré, Jacques Pelon, and Philippe Goloub
Atmos. Meas. Tech., 10, 3499–3523, https://doi.org/10.5194/amt-10-3499-2017, https://doi.org/10.5194/amt-10-3499-2017, 2017
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This study presents a comparison between active (CALIOP) and passive (POLDER) remote sensing methods, developed for retrieving aerosol above-cloud optical and microphysical properties. Main results show a good agreement when the aerosol microphysics is dominated by fine-mode particles or coarse-mode dust or when the aerosol layer is well separated from the cloud below. The paper is also focused on understanding the differences between the retrievals and the limitations of each method.
Jean-Christophe Raut, Louis Marelle, Jerome D. Fast, Jennie L. Thomas, Bernadett Weinzierl, Katharine S. Law, Larry K. Berg, Anke Roiger, Richard C. Easter, Katharina Heimerl, Tatsuo Onishi, Julien Delanoë, and Hans Schlager
Atmos. Chem. Phys., 17, 10969–10995, https://doi.org/10.5194/acp-17-10969-2017, https://doi.org/10.5194/acp-17-10969-2017, 2017
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We study the cross-polar transport of plumes from Siberian fires to the Arctic in summer, both in terms of transport pathways and efficiency of deposition processes. Those plumes containing soot may originate from anthropogenic and biomass burning sources in mid-latitude regions and may impact the Arctic climate by depositing on snow and ice surfaces. We evaluate the role of the respective source contributions, investigate the transport of plumes and treat pathway-dependent removal of particles.
Jing Yang, Zhien Wang, and Andrew Heymsfield
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-714, https://doi.org/10.5194/acp-2017-714, 2017
Revised manuscript not accepted
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This study shows the freezing time is longer for large drops than small drops. Due to instrumental limitations, freezing drops cannot be identified until they exhibit obvious shape deformation. In models, drop freezing is assumed to be instantaneous, which is not realistic; thus, the model yields a broader
first icePSD than is observed. This study allows us to interpret the observed ice PSDs in developing convective clouds, and notes the deficiency of instantaneous drop freezing in models.
Eivind G. Wærsted, Martial Haeffelin, Jean-Charles Dupont, Julien Delanoë, and Philippe Dubuisson
Atmos. Chem. Phys., 17, 10811–10835, https://doi.org/10.5194/acp-17-10811-2017, https://doi.org/10.5194/acp-17-10811-2017, 2017
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Heating and cooling of fog layers by solar and terrestrial radiation influence the fog life cycle. We quantify these radiative impacts on fog liquid water using detailed cloud radar observations of seven fog events as well as sensitivity studies. We find that the impact of radiation is affected mainly by fog optical thickness, atmospheric humidity and the presence of clouds above the fog. Observing these quantities in real time can therefore be useful for forecasting fog dissipation.
Moritz Haarig, Albert Ansmann, Dietrich Althausen, André Klepel, Silke Groß, Volker Freudenthaler, Carlos Toledano, Rodanthi-Elisavet Mamouri, David A. Farrell, Damien A. Prescod, Eleni Marinou, Sharon P. Burton, Josef Gasteiger, Ronny Engelmann, and Holger Baars
Atmos. Chem. Phys., 17, 10767–10794, https://doi.org/10.5194/acp-17-10767-2017, https://doi.org/10.5194/acp-17-10767-2017, 2017
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Our measurements performed with a lidar on Barbados give a vertical profile of Saharan dust, which was transported over 5000 km across the Atlantic. The new triple-wavelength depolarization technique reveals more information about the shape and size of dust, which will improve our understanding of the aging process of dust in the atmosphere and its representation in dust models. Changing properties of dust particles influence the solar radiation and the cloud properties and thus our climate.
Leslie David, Olivier Bock, Christian Thom, Pierre Bosser, and Jacques Pelon
Atmos. Meas. Tech., 10, 2745–2758, https://doi.org/10.5194/amt-10-2745-2017, https://doi.org/10.5194/amt-10-2745-2017, 2017
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The Raman lidar ability to retrieve atmospheric water vapor with high accuracy makes it a premium instrument in different research fields such as climatology, meteorology, or calibration of GNSS altimetry data. In order to achieve long-term stability of the measurements, the system has to be carefully calibrated. In this work we strove to investigate and mitigate the error and instability sources through numerical simulations as well as experimental tests.
Benedikt Urbanek, Silke Groß, Andreas Schäfler, and Martin Wirth
Atmos. Meas. Tech., 10, 1653–1664, https://doi.org/10.5194/amt-10-1653-2017, https://doi.org/10.5194/amt-10-1653-2017, 2017
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Cirrus evolution from nucleation to cloud breakup can be investigated with a novel classification scheme based on airborne lidar data. Applying it to a case study from the ML-CIRRUS campaign, we investigate the impact of large-scale dynamics and small-scale gravity lee waves on the detailed spatial distribution of evolution stages in individual clouds. Our scheme may help to gain more insights in optical and radiative properties of cirrus under various formation and life cycle conditions.
Anne Garnier, Noëlle A. Scott, Jacques Pelon, Raymond Armante, Laurent Crépeau, Bruno Six, and Nicolas Pascal
Atmos. Meas. Tech., 10, 1403–1424, https://doi.org/10.5194/amt-10-1403-2017, https://doi.org/10.5194/amt-10-1403-2017, 2017
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An assessment of IIR radiances after 9.5 years of nearly continuous operation since June 2006 is presented. First, IIR is compared with similar MODIS or SEVIRI channels in various conditions. Second, clear sky measurements in each channel are compared with simulations. The first approach detects biases and/or trends, and the second approach contributes to identifying which channel deviates from the other. The analyses are based on simulations using the 4A/OP radiative transfer model.
Ulrich Schumann, Robert Baumann, Darrel Baumgardner, Sarah T. Bedka, David P. Duda, Volker Freudenthaler, Jean-Francois Gayet, Andrew J. Heymsfield, Patrick Minnis, Markus Quante, Ehrhard Raschke, Hans Schlager, Margarita Vázquez-Navarro, Christiane Voigt, and Zhien Wang
Atmos. Chem. Phys., 17, 403–438, https://doi.org/10.5194/acp-17-403-2017, https://doi.org/10.5194/acp-17-403-2017, 2017
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The initially linear clouds often seen behind aircraft are known as contrails. Contrails are prototype cirrus clouds forming under well-known conditions, but with less certain life cycle and climate effects. This paper collects contrail data from a large set of measurements and compares them among each other and with models. The observations show consistent contrail properties over a wide range of aircraft and atmosphere conditions. The dataset is available for further research.
Josef Gasteiger, Silke Groß, Daniel Sauer, Moritz Haarig, Albert Ansmann, and Bernadett Weinzierl
Atmos. Chem. Phys., 17, 297–311, https://doi.org/10.5194/acp-17-297-2017, https://doi.org/10.5194/acp-17-297-2017, 2017
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To study aerosol transport in the Saharan Air Layer (SAL) from Africa to the Caribbean, we combine advanced optical models of Saharan aerosols with Stokes settling and two hypotheses about the occurrence of vertical mixing. By testing our hypotheses with lidar and in situ profiles measured near the top of the transported SAL, we find strong evidence that vertical mixing occurs in the SAL over the Atlantic with significant consequences for size distribution of the transported Saharan aerosols.
Christiane Voigt, Andreas Dörnbrack, Martin Wirth, Silke M. Groß, Robert Baumann, Benedikt Ehard, Michael C. Pitts, Lamont R. Poole, Björn-Martin Sinnhuber, and Hermann Oelhaf
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-1082, https://doi.org/10.5194/acp-2016-1082, 2016
Revised manuscript not accepted
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The letter describes unprecedented observations of widespread and persistent polar stratospheric ice clouds (ice PSCs) in the exceptionally cold Arctic stratospheric winter 2015/16. The unique observations are of global relevance because trends in Arctic ozone loss and in polar temperatures are highly uncertain. The new observations at cold conditions serve to enhance our knowledge on ice PSC formation, Arctic ozone loss and polar stratrospheric temperatures in a changing climate.
Manuel Gutleben, Silke Gross, Martin Wirth, and Andreas Schäfler
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-333, https://doi.org/10.5194/amt-2016-333, 2016
Revised manuscript not accepted
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Shallow marine cumulus convection over the Atlantic ocean is studied with observations by airborne and spaceborne lidar instruments. Cloud top height as well as cloud length and cloud gap length distributions are calculated by use of a newly developed algorithm. The distribution of cloud top heights during wintertime measurements shows a two-layer structure. However, significant differences in cloud top height distributions compared to summertime measurements are found.
Silke Groß, Josef Gasteiger, Volker Freudenthaler, Thomas Müller, Daniel Sauer, Carlos Toledano, and Albert Ansmann
Atmos. Chem. Phys., 16, 11535–11546, https://doi.org/10.5194/acp-16-11535-2016, https://doi.org/10.5194/acp-16-11535-2016, 2016
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Dual-wavelength depolarization sensitive Raman lidar measurements were used to characterize the optical properties of the dust loaded convective boundary layer over the Caribbean. Furthermore we derived the dust volume fraction and dust mass concentration within the convective boundary layer.
Jing Yang, Zhien Wang, Andrew J. Heymsfield, and Jeffrey R. French
Atmos. Chem. Phys., 16, 10159–10173, https://doi.org/10.5194/acp-16-10159-2016, https://doi.org/10.5194/acp-16-10159-2016, 2016
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This study provides statistics of the vertical air motion characteristics in convective clouds using aircraft in situ measurements from three field campaigns. Small-scale drafts are frequently observed and make important contributions to total air mass flux. The probability density functions and profiles of the observed vertical velocity and air mass flux are provided. The differences among the three field campaigns are compared. Factors influencing the vertical air motions are discussed.
Jean-Pierre Chaboureau, Cyrille Flamant, Thibaut Dauhut, Cécile Kocha, Jean-Philippe Lafore, Chistophe Lavaysse, Fabien Marnas, Mohamed Mokhtari, Jacques Pelon, Irene Reinares Martínez, Kerstin Schepanski, and Pierre Tulet
Atmos. Chem. Phys., 16, 6977–6995, https://doi.org/10.5194/acp-16-6977-2016, https://doi.org/10.5194/acp-16-6977-2016, 2016
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The Fennec field campaign conducted in June 2011 led to the first observational data set ever obtained that documents the Saharan atmospheric boundary layer under the influence of the heat low. In addition to the aircraft operation, four dust forecasts were run at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara.
Martin Schnaiter, Emma Järvinen, Paul Vochezer, Ahmed Abdelmonem, Robert Wagner, Olivier Jourdan, Guillaume Mioche, Valery N. Shcherbakov, Carl G. Schmitt, Ugo Tricoli, Zbigniew Ulanowski, and Andrew J. Heymsfield
Atmos. Chem. Phys., 16, 5091–5110, https://doi.org/10.5194/acp-16-5091-2016, https://doi.org/10.5194/acp-16-5091-2016, 2016
Gerard Ancellet, Jacques Pelon, Julien Totems, Patrick Chazette, Ariane Bazureau, Michaël Sicard, Tatiana Di Iorio, Francois Dulac, and Marc Mallet
Atmos. Chem. Phys., 16, 4725–4742, https://doi.org/10.5194/acp-16-4725-2016, https://doi.org/10.5194/acp-16-4725-2016, 2016
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A multi-lidar analysis conducted in the Mediterranean basin compares the impact of the long-range transport of North American biomass burning aerosols with the role of frequently observed Saharan dust outbreaks. This paper provides a detailed analysis of the potential North American aerosol sources, their transport to Europe and the mixing of different aerosol sources, using simulations of a particle dispersion model and lidar measurements of the aerosol optical properties.
Ulla Wandinger, Volker Freudenthaler, Holger Baars, Aldo Amodeo, Ronny Engelmann, Ina Mattis, Silke Groß, Gelsomina Pappalardo, Aldo Giunta, Giuseppe D'Amico, Anatoli Chaikovsky, Fiodor Osipenko, Alexander Slesar, Doina Nicolae, Livio Belegante, Camelia Talianu, Ilya Serikov, Holger Linné, Friedhelm Jansen, Arnoud Apituley, Keith M. Wilson, Martin de Graaf, Thomas Trickl, Helmut Giehl, Mariana Adam, Adolfo Comerón, Constantino Muñoz-Porcar, Francesc Rocadenbosch, Michaël Sicard, Sergio Tomás, Diego Lange, Dhiraj Kumar, Manuel Pujadas, Francisco Molero, Alfonso J. Fernández, Lucas Alados-Arboledas, Juan Antonio Bravo-Aranda, Francisco Navas-Guzmán, Juan Luis Guerrero-Rascado, María José Granados-Muñoz, Jana Preißler, Frank Wagner, Michael Gausa, Ivan Grigorov, Dimitar Stoyanov, Marco Iarlori, Vincenco Rizi, Nicola Spinelli, Antonella Boselli, Xuan Wang, Teresa Lo Feudo, Maria Rita Perrone, Ferdinando De Tomasi, and Pasquale Burlizzi
Atmos. Meas. Tech., 9, 1001–1023, https://doi.org/10.5194/amt-9-1001-2016, https://doi.org/10.5194/amt-9-1001-2016, 2016
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We introduce the quality-assurance efforts of the European Aerosol Research Lidar Network (EARLINET) at instrument level. Within several campaigns, 21 EARLINET systems from 18 EARLINET stations were intercompared. A comprehensive strategy for campaign setup and data evaluation was established. The intercomparisons have reinforced our confidence in the EARLINET data quality and allowed us to draw conclusions on necessary system improvements and to identify major challenges for our future work.
Patrick Chazette, Julien Totems, Gérard Ancellet, Jacques Pelon, and Michaël Sicard
Atmos. Chem. Phys., 16, 2863–2875, https://doi.org/10.5194/acp-16-2863-2016, https://doi.org/10.5194/acp-16-2863-2016, 2016
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We performed synergetic active and passive remote-sensing observations at Minorca (Spain), over more than 3 weeks in spring 2013. We characterized the aerosol optical properties and type using a combination of Rayleigh–Mie–Raman lidar and sun-photometer data. Results show a high variability due to changing atmospheric transport regimes and aerosol sources. Such variability significantly influences the radiative balance through the entire atmosphere and then the climate of the Mediterranean area.
M. Mallet, F. Dulac, P. Formenti, P. Nabat, J. Sciare, G. Roberts, J. Pelon, G. Ancellet, D. Tanré, F. Parol, C. Denjean, G. Brogniez, A. di Sarra, L. Alados-Arboledas, J. Arndt, F. Auriol, L. Blarel, T. Bourrianne, P. Chazette, S. Chevaillier, M. Claeys, B. D'Anna, Y. Derimian, K. Desboeufs, T. Di Iorio, J.-F. Doussin, P. Durand, A. Féron, E. Freney, C. Gaimoz, P. Goloub, J. L. Gómez-Amo, M. J. Granados-Muñoz, N. Grand, E. Hamonou, I. Jankowiak, M. Jeannot, J.-F. Léon, M. Maillé, S. Mailler, D. Meloni, L. Menut, G. Momboisse, J. Nicolas, T. Podvin, V. Pont, G. Rea, J.-B. Renard, L. Roblou, K. Schepanski, A. Schwarzenboeck, K. Sellegri, M. Sicard, F. Solmon, S. Somot, B Torres, J. Totems, S. Triquet, N. Verdier, C. Verwaerde, F. Waquet, J. Wenger, and P. Zapf
Atmos. Chem. Phys., 16, 455–504, https://doi.org/10.5194/acp-16-455-2016, https://doi.org/10.5194/acp-16-455-2016, 2016
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The aim of this article is to present an experimental campaign over the Mediterranean focused on aerosol-radiation measurements and modeling. Results indicate an important atmospheric loading associated with a moderate absorbing ability of mineral dust. Observations suggest a complex vertical structure and size distributions characterized by large aerosols within dust plumes. The radiative effect is highly variable, with negative forcing over the Mediterranean and positive over northern Africa.
S. Groß, V. Freudenthaler, K. Schepanski, C. Toledano, A. Schäfler, A. Ansmann, and B. Weinzierl
Atmos. Chem. Phys., 15, 11067–11080, https://doi.org/10.5194/acp-15-11067-2015, https://doi.org/10.5194/acp-15-11067-2015, 2015
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In June and July 2013 dual-wavelength lidar measurements were performed in Barbados to study long-range transported Saharan dust across the Atlantic Ocean and investigate transport-induced changes. The focus of our measurements is the intensive optical properties, the lidar ratio and the particle linear depolarization ratio. While the lidar ratio shows no differences compared to the values of fresh Saharan dust, the particle linear depolarization ratio shows slight differences.
F. Chouza, O. Reitebuch, S. Groß, S. Rahm, V. Freudenthaler, C. Toledano, and B. Weinzierl
Atmos. Meas. Tech., 8, 2909–2926, https://doi.org/10.5194/amt-8-2909-2015, https://doi.org/10.5194/amt-8-2909-2015, 2015
A. Garnier, J. Pelon, M. A. Vaughan, D. M. Winker, C. R. Trepte, and P. Dubuisson
Atmos. Meas. Tech., 8, 2759–2774, https://doi.org/10.5194/amt-8-2759-2015, https://doi.org/10.5194/amt-8-2759-2015, 2015
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Cloud absorption optical depths retrieved at 12.05 microns are compared to extinction optical depths retrieved at 0.532 microns from perfectly co-located observations of single-layered semi-transparent cirrus over oceans made by the space-borne CALIPSO IIR infrared radiometer and CALIOP lidar. A new relationship describing the temperature-dependent effect of multiple scattering in the CALIOP retrievals is derived and discussed.
L. Marelle, J.-C. Raut, J. L. Thomas, K. S. Law, B. Quennehen, G. Ancellet, J. Pelon, A. Schwarzenboeck, and J. D. Fast
Atmos. Chem. Phys., 15, 3831–3850, https://doi.org/10.5194/acp-15-3831-2015, https://doi.org/10.5194/acp-15-3831-2015, 2015
N. Bègue, P. Tulet, J. Pelon, B. Aouizerats, A. Berger, and A. Schwarzenboeck
Atmos. Chem. Phys., 15, 3497–3516, https://doi.org/10.5194/acp-15-3497-2015, https://doi.org/10.5194/acp-15-3497-2015, 2015
G. Mioche, O. Jourdan, M. Ceccaldi, and J. Delanoë
Atmos. Chem. Phys., 15, 2445–2461, https://doi.org/10.5194/acp-15-2445-2015, https://doi.org/10.5194/acp-15-2445-2015, 2015
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The study presents a characterization of the vertical, spatial and seasonal variability of Arctic clouds and mixed-phase clouds (MPCs) over the entire Arctic region. MPC properties in the region of the Svalbard archipelago (78°N, 15°E) are also investigated. The occurrence frequency of clouds and MPCs are determined from CALIPSO/CLOUDSAT measurements processed with the DARDAR retrieval algorithm which allows for a reliable cloud thermodynamic phase classification.
T. Fauchez, P. Dubuisson, C. Cornet, F. Szczap, A. Garnier, J. Pelon, and K. Meyer
Atmos. Meas. Tech., 8, 633–647, https://doi.org/10.5194/amt-8-633-2015, https://doi.org/10.5194/amt-8-633-2015, 2015
C. Liu, P. Yang, P. Minnis, N. Loeb, S. Kato, A. Heymsfield, and C. Schmitt
Atmos. Chem. Phys., 14, 13719–13737, https://doi.org/10.5194/acp-14-13719-2014, https://doi.org/10.5194/acp-14-13719-2014, 2014
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An ice cloud model is developed by assuming an ice cloud to be an ensemble of columns and aggregates with specific habit fractions at each particle size bin. The microphysical and optical properties of this two-habit model (THM) are compared with both laboratory and in situ measurements. When the THM is applied to ice cloud property retrieval, excellent spectral consistency is achieved. A comparison between observed and theoretical polarized reflectivities illustrates the applicability of THM.
F. Marenco, V. Amiridis, E. Marinou, A. Tsekeri, and J. Pelon
Atmos. Chem. Phys., 14, 11871–11881, https://doi.org/10.5194/acp-14-11871-2014, https://doi.org/10.5194/acp-14-11871-2014, 2014
E. Fontaine, A. Schwarzenboeck, J. Delanoë, W. Wobrock, D. Leroy, R. Dupuy, C. Gourbeyre, and A. Protat
Atmos. Chem. Phys., 14, 11367–11392, https://doi.org/10.5194/acp-14-11367-2014, https://doi.org/10.5194/acp-14-11367-2014, 2014
T. Eidhammer, H. Morrison, A. Bansemer, A. Gettelman, and A. J. Heymsfield
Atmos. Chem. Phys., 14, 10103–10118, https://doi.org/10.5194/acp-14-10103-2014, https://doi.org/10.5194/acp-14-10103-2014, 2014
S. Groß, M. Wirth, A. Schäfler, A. Fix, S. Kaufmann, and C. Voigt
Atmos. Meas. Tech., 7, 2745–2755, https://doi.org/10.5194/amt-7-2745-2014, https://doi.org/10.5194/amt-7-2745-2014, 2014
G. Ancellet, J. Pelon, Y. Blanchard, B. Quennehen, A. Bazureau, K. S. Law, and A. Schwarzenboeck
Atmos. Chem. Phys., 14, 8235–8254, https://doi.org/10.5194/acp-14-8235-2014, https://doi.org/10.5194/acp-14-8235-2014, 2014
M. Diao, M. A. Zondlo, A. J. Heymsfield, L. M. Avallone, M. E. Paige, S. P. Beaton, T. Campos, and D. C. Rogers
Atmos. Chem. Phys., 14, 2639–2656, https://doi.org/10.5194/acp-14-2639-2014, https://doi.org/10.5194/acp-14-2639-2014, 2014
C. Jouan, J. Pelon, E. Girard, G. Ancellet, J. P. Blanchet, and J. Delanoë
Atmos. Chem. Phys., 14, 1205–1224, https://doi.org/10.5194/acp-14-1205-2014, https://doi.org/10.5194/acp-14-1205-2014, 2014
P. Dubuisson, H. Herbin, F. Minvielle, M. Compiègne, F. Thieuleux, F. Parol, and J. Pelon
Atmos. Meas. Tech., 7, 359–371, https://doi.org/10.5194/amt-7-359-2014, https://doi.org/10.5194/amt-7-359-2014, 2014
J.-F. Gayet, V. Shcherbakov, L. Bugliaro, A. Protat, J. Delanoë, J. Pelon, and A. Garnier
Atmos. Chem. Phys., 14, 899–912, https://doi.org/10.5194/acp-14-899-2014, https://doi.org/10.5194/acp-14-899-2014, 2014
C. Tsamalis, A. Chédin, J. Pelon, and V. Capelle
Atmos. Chem. Phys., 13, 11235–11257, https://doi.org/10.5194/acp-13-11235-2013, https://doi.org/10.5194/acp-13-11235-2013, 2013
O. Bock, P. Bosser, T. Bourcy, L. David, F. Goutail, C. Hoareau, P. Keckhut, D. Legain, A. Pazmino, J. Pelon, K. Pipis, G. Poujol, A. Sarkissian, C. Thom, G. Tournois, and D. Tzanos
Atmos. Meas. Tech., 6, 2777–2802, https://doi.org/10.5194/amt-6-2777-2013, https://doi.org/10.5194/amt-6-2777-2013, 2013
O. Sourdeval, L. C. -Labonnote, G. Brogniez, O. Jourdan, J. Pelon, and A. Garnier
Atmos. Chem. Phys., 13, 8229–8244, https://doi.org/10.5194/acp-13-8229-2013, https://doi.org/10.5194/acp-13-8229-2013, 2013
G. Pappalardo, L. Mona, G. D'Amico, U. Wandinger, M. Adam, A. Amodeo, A. Ansmann, A. Apituley, L. Alados Arboledas, D. Balis, A. Boselli, J. A. Bravo-Aranda, A. Chaikovsky, A. Comeron, J. Cuesta, F. De Tomasi, V. Freudenthaler, M. Gausa, E. Giannakaki, H. Giehl, A. Giunta, I. Grigorov, S. Groß, M. Haeffelin, A. Hiebsch, M. Iarlori, D. Lange, H. Linné, F. Madonna, I. Mattis, R.-E. Mamouri, M. A. P. McAuliffe, V. Mitev, F. Molero, F. Navas-Guzman, D. Nicolae, A. Papayannis, M. R. Perrone, C. Pietras, A. Pietruczuk, G. Pisani, J. Preißler, M. Pujadas, V. Rizi, A. A. Ruth, J. Schmidt, F. Schnell, P. Seifert, I. Serikov, M. Sicard, V. Simeonov, N. Spinelli, K. Stebel, M. Tesche, T. Trickl, X. Wang, F. Wagner, M. Wiegner, and K. M. Wilson
Atmos. Chem. Phys., 13, 4429–4450, https://doi.org/10.5194/acp-13-4429-2013, https://doi.org/10.5194/acp-13-4429-2013, 2013
S. Groß, M. Esselborn, B. Weinzierl, M. Wirth, A. Fix, and A. Petzold
Atmos. Chem. Phys., 13, 2487–2505, https://doi.org/10.5194/acp-13-2487-2013, https://doi.org/10.5194/acp-13-2487-2013, 2013
S. Groß, M. Esselborn, F. Abicht, M. Wirth, A. Fix, and A. Minikin
Atmos. Chem. Phys., 13, 2435–2444, https://doi.org/10.5194/acp-13-2435-2013, https://doi.org/10.5194/acp-13-2435-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
PEAKO and peakTree: tools for detecting and interpreting peaks in cloud radar Doppler spectra – capabilities and limitations
An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI
Contrail altitude estimation using GOES-16 ABI data and deep learning
The Ice Cloud Imager: retrieval of frozen water column properties
Supercooled liquid water cloud classification using lidar backscatter peak properties
Marine cloud base height retrieval from MODIS cloud properties using machine learning
How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties
ampycloud: an open-source algorithm to determine cloud base heights and sky coverage fractions from ceilometer data
Simulation and detection efficiency analysis for measurements of polar mesospheric clouds using a spaceborne wide-field-of-view ultraviolet imager
The Chalmers Cloud Ice Climatology: retrieval implementation and validation
The algorithm of microphysical-parameter profiles of aerosol and small cloud droplets based on the dual-wavelength lidar data
Dual-frequency (Ka-band and G-band) radar estimates of liquid water content profiles in shallow clouds
Bayesian cloud-top phase determination for Meteosat Second Generation
Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Using machine learning algorithm to retrieve cloud fraction based on FY-4A AGRI observations
Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network
A new approach to crystal habit retrieval from far-infrared spectral radiance measurements
Severe hail detection with C-band dual-polarisation radars using convolutional neural networks
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Optimal estimation of cloud properties from thermal infrared observations with a combination of deep learning and radiative transfer simulation
Retrieval of cloud fraction and optical thickness from multi-angle polarization observations
Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
Infrared Radiometric Image Classification and Segmentation of Cloud Structure Using Deep-learning Framework for Ground-based Infrared Thermal Camera Observations
Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
The EarthCARE mission: science data processing chain overview
3-D Cloud Masking Across a Broad Swath using Multi-angle Polarimetry and Deep Learning
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS
Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation
Cloud and precipitation microphysical retrievals from the EarthCARE Cloud Profiling Radar: the C-CLD product
Teresa Vogl, Martin Radenz, Fabiola Ramelli, Rosa Gierens, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 6547–6568, https://doi.org/10.5194/amt-17-6547-2024, https://doi.org/10.5194/amt-17-6547-2024, 2024
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In this study, we present a toolkit of two Python algorithms to extract information from Doppler spectra measured by ground-based cloud radars. In these Doppler spectra, several peaks can be formed due to populations of droplets/ice particles with different fall velocities coexisting in the same measurement time and height. The two algorithms can detect peaks and assign them to certain particle types, such as small cloud droplets or fast-falling ice particles like graupel.
Athina Argyrouli, Diego Loyola, Fabian Romahn, Ronny Lutz, Víctor Molina García, Pascal Hedelt, Klaus-Peter Heue, and Richard Siddans
Atmos. Meas. Tech., 17, 6345–6367, https://doi.org/10.5194/amt-17-6345-2024, https://doi.org/10.5194/amt-17-6345-2024, 2024
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This paper describes a new treatment of the spatial misregistration of cloud properties for Sentinel-5 Precursor, when the footprints of different spectral bands are not perfectly aligned. The methodology exploits synergies between spectrometers and imagers, like TROPOMI and VIIRS. The largest improvements have been identified for heterogeneous scenes at cloud edges. This approach is generic and can also be applied to future Sentinel-4 and Sentinel-5 instruments.
Vincent R. Meijer, Sebastian D. Eastham, Ian A. Waitz, and Steven R. H. Barrett
Atmos. Meas. Tech., 17, 6145–6162, https://doi.org/10.5194/amt-17-6145-2024, https://doi.org/10.5194/amt-17-6145-2024, 2024
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Aviation's climate impact is partly due to contrails: the clouds that form behind aircraft and which can linger for hours under certain atmospheric conditions. Accurately forecasting these conditions could allow aircraft to avoid forming these contrails and thus reduce their environmental footprint. Our research uses deep learning to identify three-dimensional contrail locations in two-dimensional satellite imagery, which can be used to assess and improve these forecasts.
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson
Atmos. Meas. Tech., 17, 5957–5987, https://doi.org/10.5194/amt-17-5957-2024, https://doi.org/10.5194/amt-17-5957-2024, 2024
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The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Luke Edgar Whitehead, Adrian James McDonald, and Adrien Guyot
Atmos. Meas. Tech., 17, 5765–5784, https://doi.org/10.5194/amt-17-5765-2024, https://doi.org/10.5194/amt-17-5765-2024, 2024
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Supercooled liquid water cloud is important to represent in weather and climate models, particularly in the Southern Hemisphere. Previous work has developed a new machine learning method for measuring supercooled liquid water in Antarctic clouds using simple lidar observations. We evaluate this technique using a lidar dataset from Christchurch, New Zealand, and develop an updated algorithm for accurate supercooled liquid water detection at mid-latitudes.
Julien Lenhardt, Johannes Quaas, and Dino Sejdinovic
Atmos. Meas. Tech., 17, 5655–5677, https://doi.org/10.5194/amt-17-5655-2024, https://doi.org/10.5194/amt-17-5655-2024, 2024
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Clouds play a key role in the regulation of the Earth's climate. Aspects like the height of their base are of essential interest to quantify their radiative effects but remain difficult to derive from satellite data. In this study, we combine observations from the surface and satellite retrievals of cloud properties to build a robust and accurate method to retrieve the cloud base height, based on a computer vision model and ordinal regression.
Johanna Mayer, Bernhard Mayer, Luca Bugliaro, Ralf Meerkötter, and Christiane Voigt
Atmos. Meas. Tech., 17, 5161–5185, https://doi.org/10.5194/amt-17-5161-2024, https://doi.org/10.5194/amt-17-5161-2024, 2024
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This study uses radiative transfer calculations to characterize the relation of two satellite channel combinations (namely infrared window brightness temperature differences – BTDs – of SEVIRI) to the thermodynamic cloud phase. A sensitivity analysis reveals the complex interplay of cloud parameters and their contribution to the observed phase dependence of BTDs. This knowledge helps to design optimal cloud-phase retrievals and to understand their potential and limitations.
Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Sophie Réthoré, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, Pieter du Preez, and Dirk Furrer
Atmos. Meas. Tech., 17, 4891–4914, https://doi.org/10.5194/amt-17-4891-2024, https://doi.org/10.5194/amt-17-4891-2024, 2024
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ampycloud is a new algorithm developed at MeteoSwiss to characterize the height and sky coverage fraction of cloud layers above aerodromes via ceilometer data. This algorithm was devised as part of a larger effort to fully automate the creation of meteorological aerodrome reports (METARs) at Swiss civil airports. The ampycloud algorithm is implemented as a Python package that is made publicly available to the community under the 3-Clause BSD license.
Ke Ren, Haiyang Gao, Shuqi Niu, Shaoyang Sun, Leilei Kou, Yanqing Xie, Liguo Zhang, and Lingbing Bu
Atmos. Meas. Tech., 17, 4825–4842, https://doi.org/10.5194/amt-17-4825-2024, https://doi.org/10.5194/amt-17-4825-2024, 2024
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Ultraviolet imaging technology has significantly advanced the research and development of polar mesospheric clouds (PMCs). In this study, we proposed the wide-field-of-view ultraviolet imager (WFUI) and built a forward model to evaluate the detection capability and efficiency. The results demonstrate that the WFUI performs well in PMC detection and has high detection efficiency. The relationship between ice water content and detection efficiency follows an exponential function distribution.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
Atmos. Meas. Tech., 17, 4337–4368, https://doi.org/10.5194/amt-17-4337-2024, https://doi.org/10.5194/amt-17-4337-2024, 2024
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The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Huige Di, Xinhong Wang, Ning Chen, Jing Guo, Wenhui Xin, Shichun Li, Yan Guo, Qing Yan, Yufeng Wang, and Dengxin Hua
Atmos. Meas. Tech., 17, 4183–4196, https://doi.org/10.5194/amt-17-4183-2024, https://doi.org/10.5194/amt-17-4183-2024, 2024
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This study proposes an inversion method for atmospheric-aerosol or cloud microphysical parameters based on dual-wavelength lidar data. It is suitable for the inversion of uniformly mixed and single-property aerosol layers or small cloud droplets. For aerosol particles, the inversion range that this algorithm can achieve is 0.3–1.7 μm. For cloud droplets, it is 1.0–10 μm. This algorithm can quickly obtain the microphysical parameters of atmospheric particles and has better robustness.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2024-2090, https://doi.org/10.5194/egusphere-2024-2090, 2024
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This article presents a novel technique to estimate the liquid water content (LWC) in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows to retrieve the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of the LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
Johanna Mayer, Luca Bugliaro, Bernhard Mayer, Dennis Piontek, and Christiane Voigt
Atmos. Meas. Tech., 17, 4015–4039, https://doi.org/10.5194/amt-17-4015-2024, https://doi.org/10.5194/amt-17-4015-2024, 2024
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ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI) is a method to detect clouds and their thermodynamic phase with a geostationary satellite, distinguishing between clear sky and ice, mixed-phase, supercooled and warm liquid clouds. It uses a Bayesian approach based on the lidar–radar product DARDAR. The method allows studying cloud phases, especially mixed-phase and supercooled clouds, rarely observed from geostationary satellites. This can be used for comparison with climate models.
Clémantyne Aubry, Julien Delanoë, Silke Groß, Florian Ewald, Frédéric Tridon, Olivier Jourdan, and Guillaume Mioche
Atmos. Meas. Tech., 17, 3863–3881, https://doi.org/10.5194/amt-17-3863-2024, https://doi.org/10.5194/amt-17-3863-2024, 2024
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Radar–lidar synergy is used to retrieve ice, supercooled water and mixed-phase cloud properties, making the most of the radar sensitivity to ice crystals and the lidar sensitivity to supercooled droplets. A first analysis of the output of the algorithm run on the satellite data is compared with in situ data during an airborne Arctic field campaign, giving a mean percent error of 49 % for liquid water content and 75 % for ice water content.
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024, https://doi.org/10.5194/amt-17-3679-2024, 2024
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The number of cloud droplets per unit volume, Nd, in a cloud is important for understanding aerosol–cloud interaction. In this study, we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometers. We show that deriving Nd is very uncertain, although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
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This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Jinyi Xia and Li Guan
EGUsphere, https://doi.org/10.5194/egusphere-2024-977, https://doi.org/10.5194/egusphere-2024-977, 2024
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This study presents a method for estimating cloud cover from FY4A AGRI observations using LSTM neural networks. The results demonstrate excellent performance in distinguishing clear sky scenes and reducing errors in cloud cover estimation. It shows significant improvements compared to existing methods.
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
Atmos. Meas. Tech., 17, 3323–3346, https://doi.org/10.5194/amt-17-3323-2024, https://doi.org/10.5194/amt-17-3323-2024, 2024
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Multilayer clouds (MCs) affect the radiation budget differently than single-layer clouds (SCs) and need to be identified in satellite images. A neural network was trained to identify MCs by matching imagery with lidar/radar data. This method correctly identifies ~87 % SCs and MCs with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
Atmos. Meas. Tech., 17, 3171–3186, https://doi.org/10.5194/amt-17-3171-2024, https://doi.org/10.5194/amt-17-3171-2024, 2024
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This work aims to define a new approach to retrieve the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds from infrared spectral measurements. The capability of retrieving these shapes of the ice crystals from satellites will allow us to extend the currently available climatologies to be used as physical constraints in general circulation models. This could could allow us to improve their accuracy and prediction performance.
Vincent Forcadell, Clotilde Augros, Olivier Caumont, Kévin Dedieu, Maxandre Ouradou, Cloe David, Jordi Figueras i Ventura, Olivier Laurantin, and Hassan Al-Sakka
EGUsphere, https://doi.org/10.5194/egusphere-2024-1336, https://doi.org/10.5194/egusphere-2024-1336, 2024
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This study demonstrates the potential for enhancing severe hail detection through the application of convolutional neural networks (CNNs) to dual-polarization radar data. It is shown that current methods can be calibrated to significantly enhance their performance for severe hail detection. This study establishes the foundation for the solution of a more complex problem: the estimation of the maximum size of hailstones on the ground using deep learning applied to radar data.
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
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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.
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-87, https://doi.org/10.5194/amt-2024-87, 2024
Revised manuscript accepted for AMT
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This study introduces a cloud property retrieval method which integrates traditional radiative transfer simulations with a machine-learning method. Retrievals from a machine learning algorithm are used to provide initial guesses, and a radiative transfer model is used to create radiance lookup tables for later iteration processes. The new method combines the advantages of traditional and machine learning algorithms, and is applicable both daytime and nighttime conditions.
Claudia Emde, Veronika Pörtge, Mihail Manev, and Bernhard Mayer
EGUsphere, https://doi.org/10.5194/egusphere-2024-1180, https://doi.org/10.5194/egusphere-2024-1180, 2024
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We introduce an innovative method to retrieve cloud fraction and optical thickness based on polarimetry, well-suited for satellite observations providing multi-angle polarization measurements. The cloud fraction and the cloud optical thickness can be derived from measurements at two viewing angles: one within the cloudbow and a second in the sun-glint region or at a scattering angle of approximately 90°.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-40, https://doi.org/10.5194/amt-2024-40, 2024
Revised manuscript accepted for AMT
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Our study investigates the impact of cloud shadows on satellite-based aerosol index measurements over Europe by TROPOMI. Using a cloud shadow detection algorithm and simulations, we found that the overall effect on the aerosol index is minimal. Interestingly, we measured that cloud shadows are significantly bluer than their shadow-free surroundings, but the traditional algorithm already (partly) automatically corrects for this increased blueness.
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, https://doi.org/10.5194/amt-17-1739-2024, 2024
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We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Kélian Sommer, Wassim Kabalan, and Romain Brunet
EGUsphere, https://doi.org/10.5194/egusphere-2024-101, https://doi.org/10.5194/egusphere-2024-101, 2024
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Our research introduces a novel deep-learning approach for classifying and segmenting ground-based infrared thermal images, a crucial step in cloud monitoring. Tests on self-captured data showcase its excellent accuracy in distinguishing image types and in structure segmentation. With potential applications in astronomical observations, our work pioneers a robust solution for ground-based sky quality assessment, promising advancements in the photometric observations experiments.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
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In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
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The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
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We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
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The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
EGUsphere, https://doi.org/10.5194/egusphere-2023-2392, https://doi.org/10.5194/egusphere-2023-2392, 2024
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Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles, and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
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The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
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The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
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Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
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A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
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Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
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The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
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Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
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We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
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This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
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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.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
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The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
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We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
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Short summary
The impact of ice clouds on the water cycle and radiative budget is still uncertain due to the complexity of cloud processes that makes it difficult to acquire adequate observations of ice cloud properties and parameterize them into climate and weather prediction models. In this paper we present the latest refinements brought to the DARDAR-CLOUD product, which contains ice cloud microphysical properties retrieved from the cloud radar and lidar measurements from the A-Train space mission.
The impact of ice clouds on the water cycle and radiative budget is still uncertain due to the...
