Articles | Volume 16, issue 11
https://doi.org/10.5194/amt-16-2821-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-16-2821-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Jun 2023
Research article |
| 07 Jun 2023
| 07 Jun 2023
Cloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Sebastian Bley
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Stefan Horn
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Meteologix AG, Sattel, Switzerland
Hartwig Deneke
Remote Sensing of Atmospheric Processes, Leibniz Institute for Tropospheric Research, Leipzig, Germany
Andi Walther
Cooperative Institute for Meteorological Satellite Studies, Madison, WI, United States
Related authors
Nicole Docter, Anja Hünerbein, David Patrick Donovan, Rene Preusker, Jürgen Fischer, Jan Fokke Meirink, Piet Stammes, and Michael Eisinger
EGUsphere, https://doi.org/10.5194/egusphere-2023-2002, https://doi.org/10.5194/egusphere-2023-2002, 2023
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
MSI is the imaging spectrometer on board EarthCARE and will provide across track information on clouds and aerosol properties. The MSI solar channels exhibit a spectral misalignment effect (SMILE) in the measurements. This paper describes and evaluates how the SMILE will affect the cloud and aerosol retrievals that do not account for it.
Shannon L. Mason, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-1682, https://doi.org/10.5194/egusphere-2023-1682, 2023
Short summary
Short summary
When the EarthCARE mission enters its operational phase a large number of retrieval data products will be available, many of which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the ESA production model, with the intention of providing a compact guide to users.
Hannes Jascha Griesche, Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Patric Seifert, and Andreas Macke
EGUsphere, https://doi.org/10.5194/egusphere-2023-358, https://doi.org/10.5194/egusphere-2023-358, 2023
Short summary
Short summary
The Arctic is strongly affected by climate change and the role of clouds therein is not yet completely understood. Measurements from the Arctic expedition PS106 were used to simulate radiative fluxes with and without clouds at very low altitudes (below 165 m), and their radiative effect was calculated to be 43 W m-2. The low heights of these clouds make them hard to observe. This study shows the importance of accurate measurements and simulations of clouds and provides suggestions for improvements.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-327, https://doi.org/10.5194/egusphere-2023-327, 2023
Short summary
Short summary
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 benefits of MSI in observing the complete scene besides the satellite track and to extend the lidar information to the swath. The algorithm is validated against simulated test scenes.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
EGUsphere, https://doi.org/10.5194/egusphere-2023-305, https://doi.org/10.5194/egusphere-2023-305, 2023
Short summary
Short summary
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 combine the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size, and water path.
Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Hannes J. Griesche, Patric Seifert, and Andreas Macke
Atmos. Chem. Phys., 22, 9313–9348, https://doi.org/10.5194/acp-22-9313-2022, https://doi.org/10.5194/acp-22-9313-2022, 2022
Short summary
Short summary
This article describes an intercomparison of radiative fluxes and cloud properties from satellite, shipborne observations, and 1D radiative transfer simulations. The analysis focuses on research for PS106 expedition aboard the German research vessel, Polarstern. The results are presented in detailed case studies, time series for the PS106 cruise and extended to the central Arctic region. The findings illustrate the main periods of agreement and discrepancies of both points of view.
Jonas Witthuhn, Anja Hünerbein, Florian Filipitsch, Stefan Wacker, Stefanie Meilinger, and Hartwig Deneke
Atmos. Chem. Phys., 21, 14591–14630, https://doi.org/10.5194/acp-21-14591-2021, https://doi.org/10.5194/acp-21-14591-2021, 2021
Short summary
Short summary
Knowledge of aerosol–radiation interactions is important for understanding the climate system and for the renewable energy sector. Here, two complementary approaches are used to assess the consistency of the underlying aerosol properties and the resulting radiative effect in clear-sky conditions over Germany in 2015. An approach based on clear-sky models and broadband irradiance observations is contrasted to the use of explicit radiative transfer simulations using CAMS reanalysis data.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
Short summary
Short summary
The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Jonas Witthuhn, Anja Hünerbein, and Hartwig Deneke
Atmos. Meas. Tech., 13, 1387–1412, https://doi.org/10.5194/amt-13-1387-2020, https://doi.org/10.5194/amt-13-1387-2020, 2020
Short summary
Short summary
Reliable reference measurements over ocean are essential for the evaluation and improvement of satellite- and model-based aerosol datasets. Here, a uniqe set of shipborne reference aerosol products obtained from Microtops sunphotometer and GUVis-3511 shadowband radiometer observations are compared to aerosol products from the MODIS and SEVIRI satellite sensors, and the CAMS reanalysis over the Atlantic Ocean. The present evaluation highlights the importance of an aerosol-type based analysis.
Jamie R. Banks, Anja Hünerbein, Bernd Heinold, Helen E. Brindley, Hartwig Deneke, and Kerstin Schepanski
Atmos. Chem. Phys., 19, 6893–6911, https://doi.org/10.5194/acp-19-6893-2019, https://doi.org/10.5194/acp-19-6893-2019, 2019
Short summary
Short summary
Saharan dust storms may be observed over the desert using false-colour infrared satellite imagery; in one widely used scheme dust displays characteristic pink colours. Simulating satellite imagery using a dust transport model, we confirm that water vapour is a major control on the apparent colour of dust in the false-colour imagery and that dust displays its deepest colours when it is at a high altitude and when the atmosphere is dry. Water vapour can obscure the presence of low-altitude dust.
Heike Wex, Lin Huang, Wendy Zhang, Hayley Hung, Rita Traversi, Silvia Becagli, Rebecca J. Sheesley, Claire E. Moffett, Tate E. Barrett, Rossana Bossi, Henrik Skov, Anja Hünerbein, Jasmin Lubitz, Mareike Löffler, Olivia Linke, Markus Hartmann, Paul Herenz, and Frank Stratmann
Atmos. Chem. Phys., 19, 5293–5311, https://doi.org/10.5194/acp-19-5293-2019, https://doi.org/10.5194/acp-19-5293-2019, 2019
Short summary
Short summary
We found an annual cycle for ice-nucleating particles in the Arctic. These particles are important for Arctic clouds, as they can change the lifetime of clouds. We suggest that higher concentrations of these particles in summertime originate from the Arctic biosphere (both marine and terrestrial). With a warming Arctic, these concentrations may increase further, influencing aerosol–cloud interactions and therewith the observed strong warming of the Arctic.
Jamie R. Banks, Kerstin Schepanski, Bernd Heinold, Anja Hünerbein, and Helen E. Brindley
Atmos. Chem. Phys., 18, 9681–9703, https://doi.org/10.5194/acp-18-9681-2018, https://doi.org/10.5194/acp-18-9681-2018, 2018
Short summary
Short summary
Satellite observations are used to visualize dust storms over the Sahara, and specific infrared channel combinations can highlight dust with distinctive pink colours. Using output from a dust-atmosphere model to simulate satellite imagery, we explore the consequences of particle size, shape, and refractive index for the colour of dust in the imagery. Particles with a radius of ~ 1.5 microns perturb the colour the most and an assumption of spherical dust appears to be insufficient.
J. Slobodda, A. Hünerbein, R. Lindstrot, R. Preusker, K. Ebell, and J. Fischer
Atmos. Meas. Tech., 8, 567–578, https://doi.org/10.5194/amt-8-567-2015, https://doi.org/10.5194/amt-8-567-2015, 2015
Short summary
Short summary
In this paper the representativeness of ground-based cloud observatories and their comparability to satellite data and weather prediction models is examined. It is performed by analysing correlation of time series of SEVIRI pixels. The representativeness strongly depends on the used channels and ranges between 1km and over 20km.
Nicole Docter, Anja Hünerbein, David Patrick Donovan, Rene Preusker, Jürgen Fischer, Jan Fokke Meirink, Piet Stammes, and Michael Eisinger
EGUsphere, https://doi.org/10.5194/egusphere-2023-2002, https://doi.org/10.5194/egusphere-2023-2002, 2023
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
MSI is the imaging spectrometer on board EarthCARE and will provide across track information on clouds and aerosol properties. The MSI solar channels exhibit a spectral misalignment effect (SMILE) in the measurements. This paper describes and evaluates how the SMILE will affect the cloud and aerosol retrievals that do not account for it.
James Barry, Stefanie Meilinger, Klaus Pfeilsticker, Anna Herman-Czezuch, Nicola Kimiaie, Christopher Schirrmeister, Rone Yousif, Tina Buchmann, Johannes Grabenstein, Hartwig Deneke, Jonas Witthuhn, Claudia Emde, Felix Gödde, Bernhard Mayer, Leonhard Scheck, Marion Schroedter-Homscheidt, Philipp Hofbauer, and Matthias Struck
Atmos. Meas. Tech., 16, 4975–5007, https://doi.org/10.5194/amt-16-4975-2023, https://doi.org/10.5194/amt-16-4975-2023, 2023
Short summary
Short summary
Measured power data from solar photovoltaic (PV) systems contain information about the state of the atmosphere. In this work, power data from PV systems in the Allgäu region in Germany were used to determine the solar irradiance at each location, using state-of-the-art simulation and modelling. The results were validated using concurrent measurements of the incoming solar radiation in each case. If applied on a wider scale, this algorithm could help improve weather and climate models.
Shannon L. Mason, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-1682, https://doi.org/10.5194/egusphere-2023-1682, 2023
Short summary
Short summary
When the EarthCARE mission enters its operational phase a large number of retrieval data products will be available, many of which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the ESA production model, with the intention of providing a compact guide to users.
Hannes Jascha Griesche, Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Patric Seifert, and Andreas Macke
EGUsphere, https://doi.org/10.5194/egusphere-2023-358, https://doi.org/10.5194/egusphere-2023-358, 2023
Short summary
Short summary
The Arctic is strongly affected by climate change and the role of clouds therein is not yet completely understood. Measurements from the Arctic expedition PS106 were used to simulate radiative fluxes with and without clouds at very low altitudes (below 165 m), and their radiative effect was calculated to be 43 W m-2. The low heights of these clouds make them hard to observe. This study shows the importance of accurate measurements and simulations of clouds and provides suggestions for improvements.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-327, https://doi.org/10.5194/egusphere-2023-327, 2023
Short summary
Short summary
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 benefits of MSI in observing the complete scene besides the satellite track and to extend the lidar information to the swath. The algorithm is validated against simulated test scenes.
Kevin Ohneiser, Albert Ansmann, Jonas Witthuhn, Hartwig Deneke, Alexandra Chudnovsky, Gregor Walter, and Fabian Senf
Atmos. Chem. Phys., 23, 2901–2925, https://doi.org/10.5194/acp-23-2901-2023, https://doi.org/10.5194/acp-23-2901-2023, 2023
Short summary
Short summary
This study shows that smoke layers can reach the tropopause via the self-lofting effect within 3–7 d in the absence of pyrocumulonimbus convection if the
aerosol optical thickness is larger than approximately 2 for a longer time period. When reaching the stratosphere, wildfire smoke can sensitively influence the stratospheric composition on a hemispheric scale and thus can affect the Earth’s climate and the ozone layer.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
EGUsphere, https://doi.org/10.5194/egusphere-2023-305, https://doi.org/10.5194/egusphere-2023-305, 2023
Short summary
Short summary
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 combine the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size, and water path.
Carola Barrientos-Velasco, Hartwig Deneke, Anja Hünerbein, Hannes J. Griesche, Patric Seifert, and Andreas Macke
Atmos. Chem. Phys., 22, 9313–9348, https://doi.org/10.5194/acp-22-9313-2022, https://doi.org/10.5194/acp-22-9313-2022, 2022
Short summary
Short summary
This article describes an intercomparison of radiative fluxes and cloud properties from satellite, shipborne observations, and 1D radiative transfer simulations. The analysis focuses on research for PS106 expedition aboard the German research vessel, Polarstern. The results are presented in detailed case studies, time series for the PS106 cruise and extended to the central Arctic region. The findings illustrate the main periods of agreement and discrepancies of both points of view.
Jonas Witthuhn, Anja Hünerbein, Florian Filipitsch, Stefan Wacker, Stefanie Meilinger, and Hartwig Deneke
Atmos. Chem. Phys., 21, 14591–14630, https://doi.org/10.5194/acp-21-14591-2021, https://doi.org/10.5194/acp-21-14591-2021, 2021
Short summary
Short summary
Knowledge of aerosol–radiation interactions is important for understanding the climate system and for the renewable energy sector. Here, two complementary approaches are used to assess the consistency of the underlying aerosol properties and the resulting radiative effect in clear-sky conditions over Germany in 2015. An approach based on clear-sky models and broadband irradiance observations is contrasted to the use of explicit radiative transfer simulations using CAMS reanalysis data.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
Short summary
Short summary
The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
Short summary
Short summary
Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
James Barry, Dirk Böttcher, Klaus Pfeilsticker, Anna Herman-Czezuch, Nicola Kimiaie, Stefanie Meilinger, Christopher Schirrmeister, Hartwig Deneke, Jonas Witthuhn, and Felix Gödde
Adv. Sci. Res., 17, 165–173, https://doi.org/10.5194/asr-17-165-2020, https://doi.org/10.5194/asr-17-165-2020, 2020
Short summary
Short summary
The power output of solar photovoltaic (PV) modules depends largely upon incident solar radiation as well as PV module temperature. Although irradiance can fluctuate rapidly under broken cloud conditions, module temperature is subject to latency due to the solar panel's heat capacity. In order to reconcile this difference a simple four-parameter model is successfully employed to describe the dynamics of PV module temperature as a function of atmospheric conditions.
Carola Barrientos Velasco, Hartwig Deneke, Hannes Griesche, Patric Seifert, Ronny Engelmann, and Andreas Macke
Atmos. Meas. Tech., 13, 1757–1775, https://doi.org/10.5194/amt-13-1757-2020, https://doi.org/10.5194/amt-13-1757-2020, 2020
Short summary
Short summary
In the changing Arctic, quantifying the resulting variability of incoming solar radiation is important to better elucidate the net radiative effect of clouds. As part of a multidisciplinary expedition in the central Arctic held in early summer 2017, a novel network of pyranometers was deployed over an ice floe to investigate the spatiotemporal variability of solar radiation under different sky conditions. This study presents the collected data and an analysis of the spatiotemporal variability.
Jonas Witthuhn, Anja Hünerbein, and Hartwig Deneke
Atmos. Meas. Tech., 13, 1387–1412, https://doi.org/10.5194/amt-13-1387-2020, https://doi.org/10.5194/amt-13-1387-2020, 2020
Short summary
Short summary
Reliable reference measurements over ocean are essential for the evaluation and improvement of satellite- and model-based aerosol datasets. Here, a uniqe set of shipborne reference aerosol products obtained from Microtops sunphotometer and GUVis-3511 shadowband radiometer observations are compared to aerosol products from the MODIS and SEVIRI satellite sensors, and the CAMS reanalysis over the Atlantic Ocean. The present evaluation highlights the importance of an aerosol-type based analysis.
Frank Werner and Hartwig Deneke
Atmos. Meas. Tech., 13, 1089–1111, https://doi.org/10.5194/amt-13-1089-2020, https://doi.org/10.5194/amt-13-1089-2020, 2020
Short summary
Short summary
The reliability of remotely sensed cloud variables from space depends on the horizontal resolution of the instrument. This study presents and evaluates several candidate approaches for increasing the spatial resolution of observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) from the native 3 km scale to a horizontal resolution of 1 km. It is shown that uncertainties in the derived cloud products can be significantly mitigated by applying an appropriate downscaling scheme.
Diego Villanueva, Bernd Heinold, Patric Seifert, Hartwig Deneke, Martin Radenz, and Ina Tegen
Atmos. Chem. Phys., 20, 2177–2199, https://doi.org/10.5194/acp-20-2177-2020, https://doi.org/10.5194/acp-20-2177-2020, 2020
Short summary
Short summary
Spaceborne retrievals of cloud phase were analysed together with an atmospheric composition model to assess the global frequency of ice and liquid clouds. This analysis showed that at equal temperature the average occurrence of ice clouds increases for higher dust mixing ratios on a day-to-day basis in the middle and high latitudes. This indicates that mineral dust may have a strong impact on the occurrence of ice clouds even in remote areas.
Vasileios Barlakas, Hartwig Deneke, and Andreas Macke
Atmos. Chem. Phys., 20, 303–322, https://doi.org/10.5194/acp-20-303-2020, https://doi.org/10.5194/acp-20-303-2020, 2020
Short summary
Short summary
By means of a high-resolution model, we demonstrated the suitability of the sub-adiabatic cloud model to serve as a conceptual tool for the evaluation of the representation of low-level clouds and to capture the relevant properties that determine the shortwave cloud radiative effect. We also highlighted the differences in cloud radiative effect resulting from different cloud microphysics schemes used in models and pointed to the need to better account for prognostic droplet number concentration.
Jamie R. Banks, Anja Hünerbein, Bernd Heinold, Helen E. Brindley, Hartwig Deneke, and Kerstin Schepanski
Atmos. Chem. Phys., 19, 6893–6911, https://doi.org/10.5194/acp-19-6893-2019, https://doi.org/10.5194/acp-19-6893-2019, 2019
Short summary
Short summary
Saharan dust storms may be observed over the desert using false-colour infrared satellite imagery; in one widely used scheme dust displays characteristic pink colours. Simulating satellite imagery using a dust transport model, we confirm that water vapour is a major control on the apparent colour of dust in the false-colour imagery and that dust displays its deepest colours when it is at a high altitude and when the atmosphere is dry. Water vapour can obscure the presence of low-altitude dust.
Heike Wex, Lin Huang, Wendy Zhang, Hayley Hung, Rita Traversi, Silvia Becagli, Rebecca J. Sheesley, Claire E. Moffett, Tate E. Barrett, Rossana Bossi, Henrik Skov, Anja Hünerbein, Jasmin Lubitz, Mareike Löffler, Olivia Linke, Markus Hartmann, Paul Herenz, and Frank Stratmann
Atmos. Chem. Phys., 19, 5293–5311, https://doi.org/10.5194/acp-19-5293-2019, https://doi.org/10.5194/acp-19-5293-2019, 2019
Short summary
Short summary
We found an annual cycle for ice-nucleating particles in the Arctic. These particles are important for Arctic clouds, as they can change the lifetime of clouds. We suggest that higher concentrations of these particles in summertime originate from the Arctic biosphere (both marine and terrestrial). With a warming Arctic, these concentrations may increase further, influencing aerosol–cloud interactions and therewith the observed strong warming of the Arctic.
Diego Villanueva, Bernd Heinold, Patric Seifert, Hartwig Deneke, Martin Radenz, and Ina Tegen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1074, https://doi.org/10.5194/acp-2018-1074, 2018
Revised manuscript not accepted
Short summary
Short summary
Two different satellite products were analysed together with an atmospheric composition model to assess the global frequency of ice and liquid stratiform clouds. This analysis showed that at equal temperature the average occurrence of fully glaciated stratiform clouds was found to increase for higher dust mixing-ratios on a day-to-day basis in the mid- and high latitudes. This indicates that mineral dust may have a strong impact in the occurrence of ice clouds even in remote areas.
Jamie R. Banks, Kerstin Schepanski, Bernd Heinold, Anja Hünerbein, and Helen E. Brindley
Atmos. Chem. Phys., 18, 9681–9703, https://doi.org/10.5194/acp-18-9681-2018, https://doi.org/10.5194/acp-18-9681-2018, 2018
Short summary
Short summary
Satellite observations are used to visualize dust storms over the Sahara, and specific infrared channel combinations can highlight dust with distinctive pink colours. Using output from a dust-atmosphere model to simulate satellite imagery, we explore the consequences of particle size, shape, and refractive index for the colour of dust in the imagery. Particles with a radius of ~ 1.5 microns perturb the colour the most and an assumption of spherical dust appears to be insufficient.
Andreas Macke, Patric Seifert, Holger Baars, Christian Barthlott, Christoph Beekmans, Andreas Behrendt, Birger Bohn, Matthias Brueck, Johannes Bühl, Susanne Crewell, Thomas Damian, Hartwig Deneke, Sebastian Düsing, Andreas Foth, Paolo Di Girolamo, Eva Hammann, Rieke Heinze, Anne Hirsikko, John Kalisch, Norbert Kalthoff, Stefan Kinne, Martin Kohler, Ulrich Löhnert, Bomidi Lakshmi Madhavan, Vera Maurer, Shravan Kumar Muppa, Jan Schween, Ilya Serikov, Holger Siebert, Clemens Simmer, Florian Späth, Sandra Steinke, Katja Träumner, Silke Trömel, Birgit Wehner, Andreas Wieser, Volker Wulfmeyer, and Xinxin Xie
Atmos. Chem. Phys., 17, 4887–4914, https://doi.org/10.5194/acp-17-4887-2017, https://doi.org/10.5194/acp-17-4887-2017, 2017
Short summary
Short summary
This article provides an overview of the instrumental setup and the main results obtained during the two HD(CP)2 Observational Prototype Experiments HOPE-Jülich and HOPE-Melpitz conducted in Germany in April–May and Sept 2013, respectively. Goal of the field experiments was to provide high-resolution observational datasets for both, improving the understaning of boundary layer and cloud processes, as well as for the evaluation of the new ICON model that is run at 156 m horizontal resolution.
Bomidi Lakshmi Madhavan, Hartwig Deneke, Jonas Witthuhn, and Andreas Macke
Atmos. Chem. Phys., 17, 3317–3338, https://doi.org/10.5194/acp-17-3317-2017, https://doi.org/10.5194/acp-17-3317-2017, 2017
Short summary
Short summary
A method has been introduced to assess the representativeness of the time series of a point measurement compared to results for a larger area centered around the measurement location. This method allows one to determine the optimal accuracy that can be achieved for the validation of satellite products for a given pixel footprint, or the evaluation of an atmospheric model with a given grid-cell resolution.
Shi Song, K. Sebastian Schmidt, Peter Pilewskie, Michael D. King, Andrew K. Heidinger, Andi Walther, Hironobu Iwabuchi, Gala Wind, and Odele M. Coddington
Atmos. Chem. Phys., 16, 13791–13806, https://doi.org/10.5194/acp-16-13791-2016, https://doi.org/10.5194/acp-16-13791-2016, 2016
Short summary
Short summary
The radiative effects of spatially complex cloud fields are notoriously difficult to estimate and are afflicted with errors up to ±50 % of the incident solar radiation. We find that horizontal photon transport, the leading cause for these three-dimensional effects, manifests itself through a spectral fingerprint – a new observable that holds promise for reducing the errors associated with spatial complexity by moving the problem to the spectral dimension.
Holger Baars, Thomas Kanitz, Ronny Engelmann, Dietrich Althausen, Birgit Heese, Mika Komppula, Jana Preißler, Matthias Tesche, Albert Ansmann, Ulla Wandinger, Jae-Hyun Lim, Joon Young Ahn, Iwona S. Stachlewska, Vassilis Amiridis, Eleni Marinou, Patric Seifert, Julian Hofer, Annett Skupin, Florian Schneider, Stephanie Bohlmann, Andreas Foth, Sebastian Bley, Anne Pfüller, Eleni Giannakaki, Heikki Lihavainen, Yrjö Viisanen, Rakesh Kumar Hooda, Sérgio Nepomuceno Pereira, Daniele Bortoli, Frank Wagner, Ina Mattis, Lucja Janicka, Krzysztof M. Markowicz, Peggy Achtert, Paulo Artaxo, Theotonio Pauliquevis, Rodrigo A. F. Souza, Ved Prakesh Sharma, Pieter Gideon van Zyl, Johan Paul Beukes, Junying Sun, Erich G. Rohwer, Ruru Deng, Rodanthi-Elisavet Mamouri, and Felix Zamorano
Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016, https://doi.org/10.5194/acp-16-5111-2016, 2016
Short summary
Short summary
The findings from more than 10 years of global aerosol lidar measurements with Polly systems are summarized, and a data set of optical properties for specific aerosol types is given. An automated data retrieval algorithm for continuous Polly lidar observations is presented and discussed by means of a Saharan dust advection event in Leipzig, Germany. Finally, a statistic on the vertical aerosol distribution including the seasonal variability at PollyNET locations around the globe is presented.
D. Merk, H. Deneke, B. Pospichal, and P. Seifert
Atmos. Chem. Phys., 16, 933–952, https://doi.org/10.5194/acp-16-933-2016, https://doi.org/10.5194/acp-16-933-2016, 2016
Short summary
Short summary
A 2-year data set is analyzed to evaluate the consistency and limitations of current ground-based and satellite-retrieved cloud property data sets. We demonstrate that neither the assumption of a completely adiabatic cloud nor the assumption of a constant sub-adiabatic factor is fulfilled. As cloud adiabaticity is required to estimate the cloud droplet number concentration, but is not available from passive satellite observations, we need an independent method to estimate the adiabatic factor.
J. Slobodda, A. Hünerbein, R. Lindstrot, R. Preusker, K. Ebell, and J. Fischer
Atmos. Meas. Tech., 8, 567–578, https://doi.org/10.5194/amt-8-567-2015, https://doi.org/10.5194/amt-8-567-2015, 2015
Short summary
Short summary
In this paper the representativeness of ground-based cloud observatories and their comparability to satellite data and weather prediction models is examined. It is performed by analysing correlation of time series of SEVIRI pixels. The representativeness strongly depends on the used channels and ranges between 1km and over 20km.
U. Hamann, A. Walther, B. Baum, R. Bennartz, L. Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S. Joro, A. Kniffka, H. Le Gléau, M. Lockhoff, H.-J. Lutz, J. F. Meirink, P. Minnis, R. Palikonda, R. Roebeling, A. Thoss, S. Platnick, P. Watts, and G. Wind
Atmos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7-2839-2014, https://doi.org/10.5194/amt-7-2839-2014, 2014
S. Bley and H. Deneke
Atmos. Meas. Tech., 6, 2713–2723, https://doi.org/10.5194/amt-6-2713-2013, https://doi.org/10.5194/amt-6-2713-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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
Evaluation of Four Ground-based Retrievals of Cloud Droplet Number Concentration in Marine Stratocumulus with Aircraft In Situ Measurements
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Optical and microphysical properties of ice crystals in Arctic clouds from lidar observations
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
Across-track extension of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-3D product
Insights into 3D cloud radiative transfer effects for the Orbiting Carbon Observatory
Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 1: Model description and Jacobian calculation
Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter-wave radar
The Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Near-global distributions of overshooting tops derived from Terra and Aqua MODIS observations
Climatology of estimated liquid water content and scaling factor for warm clouds using radar–microwave radiometer synergy
Optimizing cloud motion estimation on the edge with phase correlation and optical flow
A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission
High-spatial-resolution retrieval of cloud droplet size distribution from polarized observations of the cloudbow
Evaluation of the spectral misalignment on the Earth Clouds, Aerosols and Radiation Explorer/multi-spectral imager cloud product
Retrieval of terahertz ice cloud properties from airborne measurements based on the irregularly shaped Voronoi ice scattering models
Latent heating profiles from GOES-16 and its impacts on precipitation forecasts
A CO2-independent cloud mask from Infrared Atmospheric Sounding Interferometer (IASI) radiances for climate applications
Retrieval of ice water path from the Microwave Humidity Sounder (MWHS) aboard FengYun-3B (FY-3B) satellite polarimetric measurements based on a deep neural network
Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals
Improved spectral processing for a multi-mode pulse compression Ka–Ku-band cloud radar system
Uncertainty-bounded estimates of ash cloud properties using the ORAC algorithm: application to the 2019 Raikoke eruption
Ice water path retrievals from Meteosat-9 using quantile regression neural networks
An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties
Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks
Segmentation-based multi-pixel cloud optical thickness retrieval using a convolutional neural network
Top-of-the-atmosphere reflected shortwave radiative fluxes from GOES-R
Optimizing radar scan strategies for tracking isolated deep convection using observing system simulation experiments
A kriging-based analysis of cloud liquid water content using CloudSat data
High-resolution satellite-based cloud detection for the analysis of land surface effects on boundary layer clouds
Retrievals of ice microphysical properties using dual-wavelength polarimetric radar observations during stratiform precipitation events
The surface longwave cloud radiative effect derived from space lidar observations
Cloud phase and macrophysical properties over the Southern Ocean during the MARCUS field campaign
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Damao Zhang, Andrew Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
EGUsphere, https://doi.org/10.5194/egusphere-2023-1364, https://doi.org/10.5194/egusphere-2023-1364, 2023
Short summary
Short summary
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 to quantify retrieval uncertainties and identify reliable retrieval scenarios.
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
Short summary
Short summary
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.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-122, https://doi.org/10.5194/amt-2023-122, 2023
Revised manuscript accepted for AMT
Short summary
Short summary
The vertical profiles of effective radius 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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Zhipeng Qu, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard
Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, https://doi.org/10.5194/amt-16-2319-2023, 2023
Short summary
Short summary
This paper describes EarthCARE’s L2 product ACM-3D. It includes the scene construction algorithm (SCA) used to produce the indexes for reconstructing 3D atmospheric scene based on satellite nadir retrievals. It also provides the information about the buffer zone sizes of 3D assessment domains and the ranking scores for selecting the best 3D assessment domains. These output variables are needed to run 3D radiative transfer models for the radiative closure assessment of EarthCARE’s L2 retrievals.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Sebastian Schmidt, and Steffen Mauceri
Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
Short summary
Short summary
This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
Short summary
Short summary
We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 1803–1847, https://doi.org/10.5194/amt-16-1803-2023, https://doi.org/10.5194/amt-16-1803-2023, 2023
Short summary
Short summary
We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over 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.
Leilei Kou, Zhengjian Lin, Haiyang Gao, Shujun Liao, and Piman Ding
Atmos. Meas. Tech., 16, 1723–1744, https://doi.org/10.5194/amt-16-1723-2023, https://doi.org/10.5194/amt-16-1723-2023, 2023
Short summary
Short summary
Forward modeling of spaceborne millimeter-wave radar composed of eight submodules is presented. We quantify the uncertainties in radar reflectivity that may be caused by the physical model parameters via a sensitivity analysis. The simulations with improved and conventional settings are compared with CloudSat data, and the simulation results are evaluated and analyzed. The results are instructive to the optimization of forward modeling and microphysical parameter retrieval.
Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn
Atmos. Meas. Tech., 16, 1683–1704, https://doi.org/10.5194/amt-16-1683-2023, https://doi.org/10.5194/amt-16-1683-2023, 2023
Short summary
Short summary
The Virga-Sniffer, a new modular open-source Python package tool to characterize full precipitation evaporation (so-called virga) from ceilometer cloud base height and vertically pointing cloud radar reflectivity time–height fields, is described. Results of its first application to RV Meteor observations during the EUREC4A field experiment in January–February 2020 are shown. About half of all detected clouds with bases below the trade inversion height were found to produce virga.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
EGUsphere, https://doi.org/10.5194/egusphere-2023-327, https://doi.org/10.5194/egusphere-2023-327, 2023
Short summary
Short summary
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 benefits of MSI in observing the complete scene besides the satellite track and to extend the lidar information to the swath. The algorithm is validated against simulated test scenes.
Yulan Hong, Stephen W. Nesbitt, Robert J. Trapp, and Larry Di Girolamo
Atmos. Meas. Tech., 16, 1391–1406, https://doi.org/10.5194/amt-16-1391-2023, https://doi.org/10.5194/amt-16-1391-2023, 2023
Short summary
Short summary
Deep convective updrafts form overshooting tops (OTs) when they extend into the upper troposphere and lower stratosphere. An OT often indicates hazardous weather conditions. The global distribution of OTs is useful for understanding global severe weather conditions. The Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and Terra satellites provides 2 decades of records on the Earth–atmosphere system with stable orbits, which are used in this study to derive 20-year OT climatology.
Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont
Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, https://doi.org/10.5194/amt-16-1211-2023, 2023
Short summary
Short summary
Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.
Bhupendra A. Raut, Paytsar Muradyan, Rajesh Sankaran, Robert C. Jackson, Seongha Park, Sean A. Shahkarami, Dario Dematties, Yongho Kim, Joseph Swantek, Neal Conrad, Wolfgang Gerlach, Sergey Shemyakin, Pete Beckman, Nicola J. Ferrier, and Scott M. Collis
Atmos. Meas. Tech., 16, 1195–1209, https://doi.org/10.5194/amt-16-1195-2023, https://doi.org/10.5194/amt-16-1195-2023, 2023
Short summary
Short summary
We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.
William K. Jones, Matthew W. Christensen, and Philip Stier
Atmos. Meas. Tech., 16, 1043–1059, https://doi.org/10.5194/amt-16-1043-2023, https://doi.org/10.5194/amt-16-1043-2023, 2023
Short summary
Short summary
Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
EGUsphere, https://doi.org/10.5194/egusphere-2023-305, https://doi.org/10.5194/egusphere-2023-305, 2023
Short summary
Short summary
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 combine the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size, and water path.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
Short summary
Short summary
This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
Short summary
Short summary
In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023, https://doi.org/10.5194/amt-16-603-2023, 2023
Short summary
Short summary
SMILE (a spectral misalignment in which a shift in the center wavelength appears as a distortion in the spectral image) was detected during our recent work. To evaluate how it affects the cloud retrieval products, we did a simulation of EarthCARE-MSI forward radiation, evaluating the error in simulated scenes from a global cloud system-resolving model and a satellite simulator. Our results indicated that the error from SMILE was generally small and negligible for oceanic scenes.
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023, https://doi.org/10.5194/amt-16-331-2023, 2023
Short summary
Short summary
Influenced by the representativeness of ice crystal scattering models, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. We developed an ice cloud remote sensing retrieval algorithm of the ice water path and particle size from aircraft-based terahertz radiation measurements based on the Voronoi model. Validation revealed that the Voronoi model performs better than the sphere and hexagonal column models.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022, https://doi.org/10.5194/amt-15-7119-2022, 2022
Short summary
Short summary
Vertical profiles of latent heating are derived from GOES-16 to be used in convective initialization. They are compared with other latent heating products derived from NEXRAD and GPM satellites, and the results show that their values are very similar to the radar-derived products. Finally, using latent heating derived from GOES-16 for convective initialization shows improvements in precipitation forecasts, which are comparable to the results using latent heating derived from NEXRAD.
Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 6653–6668, https://doi.org/10.5194/amt-15-6653-2022, https://doi.org/10.5194/amt-15-6653-2022, 2022
Short summary
Short summary
With more than 15 years of measurements, the IASI radiance dataset is becoming a reference climate data record. Its exploitation for satellite applications requires an accurate and unbiased detection of cloud scenes. Here, we present a new cloud detection algorithm for IASI that is both sensitive and consistent over time. It is based on the use of a neural network, relying on IASI radiance information only and taking as a reference the last version of the operational IASI L2 cloud product.
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022, https://doi.org/10.5194/amt-15-6489-2022, 2022
Short summary
Short summary
This paper uses a neural network approach to retrieve the ice water path from FY-3B/MWHS polarimetric measurements, focusing on its unique 150 GHz quasi-polarized channels. The Level 2 product of CloudSat is used as the reference value for the neural network. The results show that the polarization information is helpful for the retrieval in scenes with thicker cloud ice, and the 150 GHz channels give a significant improvement compared to using only 183 GHz channels.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
Short summary
Short summary
The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Han Ding, Haoran Li, and Liping Liu
Atmos. Meas. Tech., 15, 6181–6200, https://doi.org/10.5194/amt-15-6181-2022, https://doi.org/10.5194/amt-15-6181-2022, 2022
Short summary
Short summary
In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.
Andrew T. Prata, Roy G. Grainger, Isabelle A. Taylor, Adam C. Povey, Simon R. Proud, and Caroline A. Poulsen
Atmos. Meas. Tech., 15, 5985–6010, https://doi.org/10.5194/amt-15-5985-2022, https://doi.org/10.5194/amt-15-5985-2022, 2022
Short summary
Short summary
Satellite observations are often used to track ash clouds and estimate their height, particle sizes and mass; however, satellite-based techniques are always associated with some uncertainty. We describe advances in a satellite-based technique that is used to estimate ash cloud properties for the June 2019 Raikoke (Russia) eruption. Our results are significant because ash warning centres increasingly require uncertainty information to correctly interpret,
aggregate and utilise the data.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
Short summary
Short summary
Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
Short summary
Short summary
Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, https://doi.org/10.5194/amt-15-5343-2022, 2022
Short summary
Short summary
This study introduces the novel Doppler radar spectra-based machine learning approach VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn). VOODOO is a powerful probability-based extension to the existing Cloudnet hydrometeor target classification, enabling the detection of liquid-bearing cloud layers beyond complete lidar attenuation via user-defined p* threshold. VOODOO performs best for (multi-layer) stratiform and deep mixed-phase clouds with liquid water path > 100 g m−2.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
Short summary
Short summary
A convolutional neural network (CNN) is introduced to retrieve cloud optical thickness (COT) from passive cloud imagery. The CNN, trained on large eddy simulations from the Sulu Sea, learns from spatial information at multiple scales to reduce cloud inhomogeneity effects. By considering the spatial context of a pixel, the CNN outperforms the traditional independent pixel approximation (IPA) across several cloud morphology metrics.
Rachel T. Pinker, Yingtao Ma, Wen Chen, Istvan Laszlo, Hongqing Liu, Hye-Yun Kim, and Jaime Daniels
Atmos. Meas. Tech., 15, 5077–5094, https://doi.org/10.5194/amt-15-5077-2022, https://doi.org/10.5194/amt-15-5077-2022, 2022
Short summary
Short summary
Scene-dependent narrow-to-broadband transformations are developed to facilitate the use of observations from the Advanced Baseline Imager (ABI), the primary instrument on GOES-R, to derive surface shortwave radiative fluxes. This is a first NOAA product at the high resolution of about 5 k over the contiguous United States (CONUS) region. The product is archived and can be downloaded from the NOAA Comprehensive Large Array-data Stewardship System (CLASS).
Mariko Oue, Stephen M. Saleeby, Peter J. Marinescu, Pavlos Kollias, and Susan C. van den Heever
Atmos. Meas. Tech., 15, 4931–4950, https://doi.org/10.5194/amt-15-4931-2022, https://doi.org/10.5194/amt-15-4931-2022, 2022
Short summary
Short summary
This study provides an optimization of radar observation strategies to better capture convective cell evolution in clean and polluted environments as well as a technique for the optimization. The suggested optimized radar observation strategy is to better capture updrafts at middle and upper altitudes and precipitation particle evolution of isolated deep convective clouds. This study sheds light on the challenge of designing remote sensing observation strategies in pre-field campaign periods.
Jean-Marie Lalande, Guillaume Bourmaud, Pierre Minvielle, and Jean-François Giovannelli
Atmos. Meas. Tech., 15, 4411–4429, https://doi.org/10.5194/amt-15-4411-2022, https://doi.org/10.5194/amt-15-4411-2022, 2022
Short summary
Short summary
In this paper we describe the implementation of an interpolation–prediction estimator applied to cloud properties derived from CloudSat observations. The objective is to evaluate the uncertainty associated with the estimated quantity. The model developed in this study can be valuable for satellite applications (GPS, telecommunication) as well as for cloud product comparisons. This paper is didactic and beneficial for anyone interested in kriging estimators.
Julia Fuchs, Hendrik Andersen, Jan Cermak, Eva Pauli, and Rob Roebeling
Atmos. Meas. Tech., 15, 4257–4270, https://doi.org/10.5194/amt-15-4257-2022, https://doi.org/10.5194/amt-15-4257-2022, 2022
Short summary
Short summary
Two cloud-masking approaches, a local and a regional approach, using high-resolution satellite data are developed and validated for the region of Paris to improve applicability for analyses of urban effects on low clouds. We found that cloud masks obtained from the regional approach are more appropriate for the high-resolution analysis of locally induced cloud processes. Its applicability is tested for the analysis of typical fog conditions over different surface types.
Eleni Tetoni, Florian Ewald, Martin Hagen, Gregor Köcher, Tobias Zinner, and Silke Groß
Atmos. Meas. Tech., 15, 3969–3999, https://doi.org/10.5194/amt-15-3969-2022, https://doi.org/10.5194/amt-15-3969-2022, 2022
Short summary
Short summary
We use the C-band POLDIRAD and the Ka-band MIRA-35 to perform snowfall dual-wavelength polarimetric radar measurements. We develop an ice microphysics retrieval for mass, apparent shape, and median size of the particle size distribution by comparing observations to T-matrix ice spheroid simulations while varying the mass–size relationship. We furthermore show how the polarimetric measurements from POLDIRAD help to narrow down ambiguities between ice particle shape and size.
Assia Arouf, Hélène Chepfer, Thibault Vaillant de Guélis, Marjolaine Chiriaco, Matthew D. Shupe, Rodrigo Guzman, Artem Feofilov, Patrick Raberanto, Tristan S. L'Ecuyer, Seiji Kato, and Michael R. Gallagher
Atmos. Meas. Tech., 15, 3893–3923, https://doi.org/10.5194/amt-15-3893-2022, https://doi.org/10.5194/amt-15-3893-2022, 2022
Short summary
Short summary
We proposed new estimates of the surface longwave (LW) cloud radiative effect (CRE) derived from observations collected by a space-based lidar on board the CALIPSO satellite and radiative transfer computations. Our estimate appropriately captures the surface LW CRE annual variability over bright polar surfaces, and it provides a dataset more than 13 years long.
Baike Xi, Xiquan Dong, Xiaojian Zheng, and Peng Wu
Atmos. Meas. Tech., 15, 3761–3777, https://doi.org/10.5194/amt-15-3761-2022, https://doi.org/10.5194/amt-15-3761-2022, 2022
Short summary
Short summary
This study develops an innovative method to determine the cloud phases over the Southern Ocean (SO) using the combination of radar and lidar measurements during the ship-based field campaign of MARCUS. Results from our study show that the low-level, deep, and shallow cumuli are dominant, and the mixed-phase clouds occur more than single phases over the SO. The mixed-phase cloud properties are similar to liquid-phase (ice-phase) clouds in the midlatitudes (polar) region of the SO.
Cited articles
Ackerman, A., Strabala, K., Menzel, P., Frey, R., Moeller, C., Gumley, L., Baum, B., Seemann, S., and Zhang, H.: Discriminating Clear-Sky from Cloud with MODIS—Algorithm Theoretical Basis Document (MOD35), ATBD Reference Number: ATBD-MOD-06, Goddard Space Flight Center, https://atmosphere-imager.gsfc.nasa.gov/sites/default/files/ModAtmo/MOD35_ATBD_Collection6_1.pdf (last access: 31 May 2023), 2002. a, b
Ackerman, S. A., Strabala, K. I., Menzel, W. P., Frey, R. A., Moeller, C. C., and Gumley, L. E.: Discriminating clear sky from clouds with MODIS, J. Geophys. Res.-Atmos., 103, 32141–32157, https://doi.org/10.1029/1998JD200032, 1998. a
Docter, N., Preusker, R., Filipitsch, F., Kritten, L., Schmidt, F., and Fischer, J.: Aerosol optical depth retrieval from the EarthCARE multi-spectral imager: the M-AOT product, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-150, 2023. a
Eumetrain: RGB color guide, https://www.eumetrain.org/index.php/rgb-color-guide (last access: 22 November 2022), 2022. a
Haarig, M., Hünerbein, A., Wandinger, U., Docter, N., Bley, S., Donovan, D., and van Zadelhoff, G.-J.: Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-327, 2023. a
Hamann, U., Walther, A., Baum, B., Bennartz, R., Bugliaro, L., Derrien, M., Francis, P. N., Heidinger, A., Joro, S., Kniffka, A., Le Gléau, H., Lockhoff, M., Lutz, H.-J., Meirink, J. F., Minnis, P., Palikonda, R., Roebeling, R., Thoss, A., Platnick, S., Watts, P., and Wind, G.: Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms, Atmos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7-2839-2014, 2014. a
Hollstein, A., Fischer, J., Carbajal Henken, C., and Preusker, R.: Bayesian cloud detection for MERIS, AATSR, and their combination, Atmos. Meas. Tech., 8, 1757–1771, https://doi.org/10.5194/amt-8-1757-2015, 2015. a
Holmlund, K., Grandell, J., Schmetz, J., Stuhlmann, R., Bojkov, B., Munro, R., Lekouara, M., Coppens, D., Viticchie, B., August, T., Theodore, B., Watts, P., Dobber, M., Fowler, G., Bojinski, S., Schmid, A., Salonen, K., Tjemkes, S., Aminou, D., and Blythe, P.: Meteosat Third Generation (MTG): Continuation and Innovation of Observations from Geostationary Orbit, B. Am. Meteorol. Soc., 102, E990–E1015, https://doi.org/10.1175/BAMS-D-19-0304.1, 2021. a
Hughes, M. J. and Kennedy, R.: High-quality cloud masking of Landsat 8 imagery using convolutional neural networks, Remote Sens., 11, 2591, https://doi.org/10.3390/rs11212591, 2019. a
Hünerbein, A., Bley, S., Deneke, H., Meirink, J. F., van Zadelhoff, G.-J., and Walther, A.: Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-305, 2023. a, b
Illingworth, A. J., Barker, H., Beljaars, A., Ceccaldi, M., Chepfer, H., Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., Donovan, D. P., Fukuda, S., Hirakata, M., Hogan, R. J., Huenerbein, A., Kollias, P., Kubota, T., Nakajima, T., Nakajima, T. Y., Nishizawa, T., Ohno, Y., Okamoto, H., Oki, R., Sato, K., Satoh, M., Shephard, M. W., Velázquez-Blázquez, A., Wandinger, U., Wehr, T., and van Zadelhoff, G.-J.: The EarthCARE satellite: The next step forward in global measurements of clouds, aerosols, precipitation, and radiation, Bulletin of the American Meteorological Society, 96, 1311–1332, 2015. a
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, ISBN: 978-92-9169-158-6, in press, https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_SPM_final.pdf (last access: 31 May 2023), 2021. a
Li, Z., Shen, H., Cheng, Q., Liu, Y., You, S., and He, Z.: Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors, ISPRS J. Photogramm., 150, 197–212, https://doi.org/10.1016/j.isprsjprs.2019.02.017, 2019. a
Liu, Y., Key, J. R., Frey, R. A., Ackerman, S. A., and Menzel, W.: Nighttime polar cloud detection with MODIS, Remote Sens. Environ., 92, 181–194, https://doi.org/10.1016/j.rse.2004.06.004, 2004. a
Mateo-García, G., Gómez-Chova, L., and Camps-Valls, G.: Convolutional neural networks for multispectral image cloud masking, in: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 23–28 July 2017, IEEE, 2255–2258, https://doi.org/10.1109/IGARSS.2017.8127438, 2017. a
Nakajima, T. Y., Tsuchiya, T., Ishida, H., Matsui, T. N., and Shimoda, H.: Cloud detection performance of spaceborne visible-to-infrared multispectral imagers, Appl. Optics, 50, 2601, https://doi.org/10.1364/ao.50.002601, 2011. a
Pinty, B. and Verstraete, M.: GEMI: a non-linear index to monitor global vegetation from satellites, Vegetatio, 101, 15–20, https://doi.org/10.1007/BF00031911, 1992. a
Platnick, S., King, M. D., Ackerman, S. A., Menzel, W. P., Baum, B. A.,
Riedi, J. C., and Frey, R. A.: The MODIS cloud products: Algorithms and examples from Terra, IEEE T. Geosci. Remote, 41, 459–473, 2003. a
Qu, Z., Donovan, D. P., Barker, H. W., Cole, J. N. S., Shephard, M. W., and Huijnen, V.: Numerical Model Generation of Test Frames for Pre-launch Studies of EarthCARE’s Retrieval Algorithms and Data Management System, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2022-300, in review, 2022. a, b
Rossow, W. B. and Schiffer, R. A.: Advances in understanding clouds from ISCCP, B. Am. Meteorol. Soc., 80, 2261–2288, https://doi.org/10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2, 1999. a
Saunders, R. W., Matricardi, M., and Brunel, P.: An Improved Fast Radiative Transfer Model for Assimilation of Satellite Radiances Observations, Q. J. Roy. Meteor. Soc., 125, 1407–1425, 1999. a
Schiffer, R. A. and Rossow, W. B.: The International Satellite Cloud Climatology Project (ISCCP): The First Project of the World Climate Research Programme, B. Am. Meteorol. Soc., 64, 779–784, https://doi.org/10.1175/1520-0477-64.7.779, 1983. a
Skakun, S., Wevers, J., Brockmann, C., Doxani, G., Aleksandrov, M., Batič, M., Frantz, D., Gascon, F., Gómez-Chova, L., Hagolle, O., López-Puigdollers, D., Louis, J., Lubej, M., Mateo-García, G., OSMAN, J., Peressutti, D., Pflug, B., Puc, J., Richter, R., Roger, J.-C., Scaramuzza, P., Vermote, E., Vesel, N., Zupanc, A., and Žust, L.: CMIX: Cloud Mask Intercomparison eXercise, in: Living Planet Symposium, Bonn, Germany, 23–27 May 2022, https://elib.dlr.de/187698/ (last access: 31 May 2023), 2022. a
van Zadelhoff, G.-J., Barker, H. W., Baudrez, E., Bley, S., Clerbaux, N., Cole, J. N. S., de Kloe, J., Docter, N., Domenech, C., Donovan, D. P., Dufresne, J.-L., Eisinger, M., Fischer, J., García-Marañón, R., Haarig, M., Hogan, R. J., Hünerbein, A., Kollias, P., Koopman, R., Madenach, N., Mason, S. L., Preusker, R., Puigdomènech Treserras, B., Qu, Z., Ruiz-Saldaña, M., Shephard, M., Velázquez-Blazquez, A., Villefranque, N., Wandinger, U., Wang, P., and Wehr, T.: EarthCARE level-2 demonstration products from simulated scenes, Zenodo [data set], https://doi.org/10.5281/zenodo.7117116, 2022.
a
Wang, M., Nakajima, T. Y., Roh, W., Satoh, M., Suzuki, K., Kubota, T., and Yoshida, M.: Evaluation of the smile effect on the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE)/Multi-Spectral Imager (MSI) cloud product, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-736, 2022. a
Wehr, T., Kubota, T., Tzeremes, G., Wallace, K., Nakatsuka, H., Ohno, Y., Koopman, R., Rusli, S., Kikuchi, M., Eisinger, M., Tanaka, T., Taga, M., Deghaye, P., Tomita, E., and Bernaerts, D.: The EarthCARE Mission – Science and System Overview, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-1476, 2023. a, b
Wu, D. L., Baum, B. A., Choi, Y.-S., Foster, M. J., Karlsson, K.-G., Heidinger, A., Poulsen, C., Pavolonis, M., Riedi, J., Roebeling, R., Sherwood, S., Thoss, A., and Watts, P.: Toward Global Harmonization of Derived Cloud Products, B. Am. Meteorol. Soc., 98, ES49–ES52, https://doi.org/10.1175/BAMS-D-16-0234.1, 2017. a
Zekoll, V., Main-Knorn, M., Alonso, K., Louis, J., Frantz, D., Richter, R., and Pflug, B.: Comparison of Masking Algorithms for Sentinel-2 Imagery, Remote Sens., 13, 137, https://doi.org/10.3390/rs13010137, 2021. a
Short summary
The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information...
Special issue