Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4229-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-4229-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Maximilian Maahn
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
Physical Sciences Lab, NOAA Earth System Research Laboratory, Boulder, CO, USA
now at: Leipzig Institute for Meteorology, Leipzig University, Leipzig, Germany
Stefan Kneifel
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Davide Ori
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Emiliano Orlandi
Radiometer-Physics GmbH, Meckenheim, Germany
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Pavlos Kollias
School of Marine and Atmospheric Sciences, Stony Brook University, NY, USA
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Vera Schemann
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Susanne Crewell
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
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Manuel Moser, Christiane Voigt, Oliver Eppers, Johannes Lucke, Elena De La Torre Castro, Johanna Mayer, Regis Dupuy, Guillaume Mioche, Olivier Jourdan, Hans-Christian Clemen, Johannes Schneider, Philipp Joppe, Stephan Mertes, Bruno Wetzel, Stephan Borrmann, Marcus Klingebiel, Mario Mech, Christof Lüpkes, Susanne Crewell, André Ehrlich, Andreas Herber, and Manfred Wendisch
EGUsphere, https://doi.org/10.5194/egusphere-2025-3876, https://doi.org/10.5194/egusphere-2025-3876, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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In this study we analyzed Arctic mixed-phase clouds using airborne in-situ measurements in spring 2022. Based on microphysical properties, we show that within these clouds a distinction must be made between classic mixed-phase clouds and a mixed-phase haze regime. Instead of supercooled droplets, the haze regime contains large wet sea salt aerosols. These findings improve our understanding of Arctic low-level cloud processes.
Henning Dorff, Florian Ewald, Heike Konow, Mario Mech, Davide Ori, Vera Schemann, Andreas Walbröl, Manfred Wendisch, and Felix Ament
Atmos. Chem. Phys., 25, 8329–8354, https://doi.org/10.5194/acp-25-8329-2025, https://doi.org/10.5194/acp-25-8329-2025, 2025
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Using observations of an Arctic atmospheric river (AR) from a long-range research aircraft, we analyse how moisture transported into the Arctic by the AR is transformed and how it interacts with the Arctic environment. The moisture transport divergence is the main driver of local moisture change over time. Surface precipitation and evaporation are rather weak when averaged over extended AR sectors, although considerable heterogeneity of precipitation within the AR is observed.
Kerstin Ebell, Christian Buhren, Rosa Gierens, Giovanni Chellini, Melanie Lauer, Andreas Walbröl, Sandro Dahlke, Pavel Krobot, and Mario Mech
Atmos. Chem. Phys., 25, 7315–7342, https://doi.org/10.5194/acp-25-7315-2025, https://doi.org/10.5194/acp-25-7315-2025, 2025
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Ground-based observations of precipitation are rare in the Arctic. Since 2017, additional temporally highly resolved precipitation measurements have been carried out by a precipitation gauge and an optical precipitation sensor at Ny-Ålesund, Svalbard. These new data facilitate the distinction between liquid and solid precipitation. Using reanalysis data, we also find that water vapor transport contributes strongly to precipitation and especially to extreme precipitation events.
André Ehrlich, Susanne Crewell, Andreas Herber, Marcus Klingebiel, Christof Lüpkes, Mario Mech, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Matthias Buschmann, Hans-Christian Clemen, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Andreas Giez, Sarah Grawe, Christophe Gourbeyre, Jörg Hartmann, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsófia Jurányi, Benjamin Kirbus, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Christian Mallaun, Johanna Mayer, Stephan Mertes, Guillaume Mioche, Manuel Moser, Hanno Müller, Veronika Pörtge, Nils Risse, Greg Roberts, Sophie Rosenburg, Johannes Röttenbacher, Michael Schäfer, Jonas Schaefer, Andreas Schäfler, Imke Schirmacher, Johannes Schneider, Sabrina Schnitt, Frank Stratmann, Christian Tatzelt, Christiane Voigt, Andreas Walbröl, Anna Weber, Bruno Wetzel, Martin Wirth, and Manfred Wendisch
Earth Syst. Sci. Data, 17, 1295–1328, https://doi.org/10.5194/essd-17-1295-2025, https://doi.org/10.5194/essd-17-1295-2025, 2025
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This paper provides an overview of the HALO–(AC)3 aircraft campaign data sets, the campaign-specific instrument operation, data processing, and data quality. The data set comprises in situ and remote sensing observations from three research aircraft: HALO, Polar 5, and Polar 6. All data are published in the PANGAEA database by instrument-separated data subsets. It is highlighted how the scientific analysis of the HALO–(AC)3 data benefits from the coordinated operation of three aircraft.
Marcus Klingebiel, André Ehrlich, Micha Gryschka, Nils Risse, Nina Maherndl, Imke Schirmacher, Sophie Rosenburg, Sabine Hörnig, Manuel Moser, Evelyn Jäkel, Michael Schäfer, Hartwig Deneke, Mario Mech, Christiane Voigt, and Manfred Wendisch
EGUsphere, https://doi.org/10.5194/egusphere-2025-201, https://doi.org/10.5194/egusphere-2025-201, 2025
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Our study is using aircraft measurements from the HALO-(𝒜𝒞)³ campaign to investigate the transition from organized Arctic cloud street structures to more scattered cloud shapes. We show that lower wind speeds cause this transition. In addition we look at the changes of the cloud coverage, the height of the clouds, the cloud particles and the radiative properties.
Imke Schirmacher, Sabrina Schnitt, Marcus Klingebiel, Nina Maherndl, Benjamin Kirbus, André Ehrlich, Mario Mech, and Susanne Crewell
Atmos. Chem. Phys., 24, 12823–12842, https://doi.org/10.5194/acp-24-12823-2024, https://doi.org/10.5194/acp-24-12823-2024, 2024
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During Arctic marine cold-air outbreaks, cold air flows from sea ice over open water. Roll circulations evolve, forming cloud streets. We investigate the initial circulation and cloud development using high-resolution airborne measurements. We compute the distance an air mass traveled over water (fetch) from back trajectories. Cloud streets form at 15 km fetch, cloud cover strongly increases at around 20 km, and precipitation forms at around 30 km.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
The Cryosphere, 18, 4137–4163, https://doi.org/10.5194/tc-18-4137-2024, https://doi.org/10.5194/tc-18-4137-2024, 2024
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Passive microwave observations from satellites are crucial for monitoring Arctic sea ice and atmosphere. To do this effectively, it is important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we improved our understanding, identified four distinct emission types, and expanded current knowledge to include higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
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The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
Nina Maherndl, Manuel Moser, Johannes Lucke, Mario Mech, Nils Risse, Imke Schirmacher, and Maximilian Maahn
Atmos. Meas. Tech., 17, 1475–1495, https://doi.org/10.5194/amt-17-1475-2024, https://doi.org/10.5194/amt-17-1475-2024, 2024
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In some clouds, liquid water droplets can freeze onto ice crystals (riming). Riming leads to the formation of snowflakes. We show two ways to quantify riming using aircraft data collected in the Arctic. One aircraft had a cloud radar, while the other aircraft was measuring directly in cloud. The first method compares radar and direct observations. The second looks at snowflake shape. Both methods agree, except when there were gaps in the cloud. This improves our ability to understand riming.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Marcus Klingebiel, André Ehrlich, Elena Ruiz-Donoso, Nils Risse, Imke Schirmacher, Evelyn Jäkel, Michael Schäfer, Kevin Wolf, Mario Mech, Manuel Moser, Christiane Voigt, and Manfred Wendisch
Atmos. Chem. Phys., 23, 15289–15304, https://doi.org/10.5194/acp-23-15289-2023, https://doi.org/10.5194/acp-23-15289-2023, 2023
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In this study we explain how we use aircraft measurements from two Arctic research campaigns to identify cloud properties (like droplet size) over sea-ice and ice-free ocean. To make sure that our measurements make sense, we compare them with other observations. Our results show, e.g., larger cloud droplets in early summer than in spring. Moreover, the cloud droplets are also larger over ice-free ocean than compared to sea ice. In the future, our data can be used to improve climate models.
Imke Schirmacher, Pavlos Kollias, Katia Lamer, Mario Mech, Lukas Pfitzenmaier, Manfred Wendisch, and Susanne Crewell
Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, https://doi.org/10.5194/amt-16-4081-2023, 2023
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CloudSat’s relatively coarse spatial resolution, low sensitivity, and blind zone limit its assessment of Arctic low-level clouds, which affect the surface energy balance. We compare cloud fractions from CloudSat and finely resolved airborne radar observations to determine CloudSat’s limitations. Cloudsat overestimates cloud fractions above its blind zone, especially during cold-air outbreaks over open water, and misses a cloud fraction of 32 % and half of the precipitation inside its blind zone.
Melanie Lauer, Annette Rinke, Irina Gorodetskaya, Michael Sprenger, Mario Mech, and Susanne Crewell
Atmos. Chem. Phys., 23, 8705–8726, https://doi.org/10.5194/acp-23-8705-2023, https://doi.org/10.5194/acp-23-8705-2023, 2023
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We present a new method to analyse the influence of atmospheric rivers (ARs), cyclones, and fronts on the precipitation in the Arctic, based on two campaigns: ACLOUD (early summer 2017) and AFLUX (early spring 2019). There are differences between both campaign periods: in early summer, the precipitation is mostly related to ARs and fronts, especially when they are co-located, while in early spring, cyclones isolated from ARs and fronts contributed most to the precipitation.
Manuel Moser, Christiane Voigt, Tina Jurkat-Witschas, Valerian Hahn, Guillaume Mioche, Olivier Jourdan, Régis Dupuy, Christophe Gourbeyre, Alfons Schwarzenboeck, Johannes Lucke, Yvonne Boose, Mario Mech, Stephan Borrmann, André Ehrlich, Andreas Herber, Christof Lüpkes, and Manfred Wendisch
Atmos. Chem. Phys., 23, 7257–7280, https://doi.org/10.5194/acp-23-7257-2023, https://doi.org/10.5194/acp-23-7257-2023, 2023
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This study provides a comprehensive microphysical and thermodynamic phase analysis of low-level clouds in the northern Fram Strait, above the sea ice and the open ocean, during spring and summer. Using airborne in situ cloud data, we show that the properties of Arctic low-level clouds vary significantly with seasonal meteorological situations and surface conditions. The observations presented in this study can help one to assess the role of clouds in the Arctic climate system.
Jan Chylik, Dmitry Chechin, Regis Dupuy, Birte S. Kulla, Christof Lüpkes, Stephan Mertes, Mario Mech, and Roel A. J. Neggers
Atmos. Chem. Phys., 23, 4903–4929, https://doi.org/10.5194/acp-23-4903-2023, https://doi.org/10.5194/acp-23-4903-2023, 2023
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Arctic low-level clouds play an important role in the ongoing warming of the Arctic. Unfortunately, these clouds are not properly represented in weather forecast and climate models. This study tries to cover this gap by focusing on clouds over open water during the spring, observed by research aircraft near Svalbard. The study combines the high-resolution model with sets of observational data. The results show the importance of processes that involve both ice and the liquid water in the clouds.
Annakaisa von Lerber, Mario Mech, Annette Rinke, Damao Zhang, Melanie Lauer, Ana Radovan, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 7287–7317, https://doi.org/10.5194/acp-22-7287-2022, https://doi.org/10.5194/acp-22-7287-2022, 2022
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Snowfall is an important climate indicator. However, microphysical snowfall processes are challenging for atmospheric models. In this study, the performance of a regional climate model is evaluated in modeling the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations. Excellent agreement in averaged annual snowfall rates is found, and the shown methodology offers a promising diagnostic tool to investigate the shown differences further.
Hélène Bresson, Annette Rinke, Mario Mech, Daniel Reinert, Vera Schemann, Kerstin Ebell, Marion Maturilli, Carolina Viceto, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 173–196, https://doi.org/10.5194/acp-22-173-2022, https://doi.org/10.5194/acp-22-173-2022, 2022
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Arctic warming is pronounced, and one factor in this is the poleward atmospheric transport of heat and moisture. This study assesses the 4D structure of an Arctic moisture intrusion event which occurred in June 2017. For the first time, high-resolution pan-Arctic ICON simulations are performed and compared with global models, reanalysis, and observations. Results show the added value of high resolution in the event representation and the impact of the intrusion on the surface energy fluxes.
Heike Konow, Florian Ewald, Geet George, Marek Jacob, Marcus Klingebiel, Tobias Kölling, Anna E. Luebke, Theresa Mieslinger, Veronika Pörtge, Jule Radtke, Michael Schäfer, Hauke Schulz, Raphaela Vogel, Martin Wirth, Sandrine Bony, Susanne Crewell, André Ehrlich, Linda Forster, Andreas Giez, Felix Gödde, Silke Groß, Manuel Gutleben, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Theresa Lang, Bernhard Mayer, Mario Mech, Marc Prange, Sabrina Schnitt, Jessica Vial, Andreas Walbröl, Manfred Wendisch, Kevin Wolf, Tobias Zinner, Martin Zöger, Felix Ament, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 5545–5563, https://doi.org/10.5194/essd-13-5545-2021, https://doi.org/10.5194/essd-13-5545-2021, 2021
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The German research aircraft HALO took part in the research campaign EUREC4A in January and February 2020. The focus area was the tropical Atlantic east of the island of Barbados. We describe the characteristics of the 15 research flights, provide auxiliary information, derive combined cloud mask products from all instruments that observe clouds on board the aircraft, and provide code examples that help new users of the data to get started.
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.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
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Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Kevin Ohneiser, Markus Hartmann, Heike Wex, Patric Seifert, Anja Hardt, Anna Miller, Katharina Baudrexl, Werner Thomas, Veronika Ettrichrätz, Maximilian Maahn, Tom Gaudek, Willi Schimmel, Fabian Senf, Hannes Griesche, Martin Radenz, and Jan Henneberger
EGUsphere, https://doi.org/10.5194/egusphere-2025-3675, https://doi.org/10.5194/egusphere-2025-3675, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study highlights the efficiency of supercooled stratus clouds to remove ice-nucleating particles (INPs). In our measurement scenarios within the planetary boundary layer lower concentrations of INP under supercooled stratus conditions were found than with temperatures above freezing. Within the free troposphere a lot more INPs were found to be available which means that the free troposphere must be taken into account as an important source of INPs.
Manuel Moser, Christiane Voigt, Oliver Eppers, Johannes Lucke, Elena De La Torre Castro, Johanna Mayer, Regis Dupuy, Guillaume Mioche, Olivier Jourdan, Hans-Christian Clemen, Johannes Schneider, Philipp Joppe, Stephan Mertes, Bruno Wetzel, Stephan Borrmann, Marcus Klingebiel, Mario Mech, Christof Lüpkes, Susanne Crewell, André Ehrlich, Andreas Herber, and Manfred Wendisch
EGUsphere, https://doi.org/10.5194/egusphere-2025-3876, https://doi.org/10.5194/egusphere-2025-3876, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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In this study we analyzed Arctic mixed-phase clouds using airborne in-situ measurements in spring 2022. Based on microphysical properties, we show that within these clouds a distinction must be made between classic mixed-phase clouds and a mixed-phase haze regime. Instead of supercooled droplets, the haze regime contains large wet sea salt aerosols. These findings improve our understanding of Arctic low-level cloud processes.
Susmitha Sasikumar, Alessandro Battaglia, Bernat Puigdomènech Treserras, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2025-3573, https://doi.org/10.5194/egusphere-2025-3573, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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The study present a method to estimate how much the radar signal is weakened as it passes through rain or clouds, designed to implement in the new EarthCARE satellite cloud profiling radar data. The approach builds on the method used in the CloudSat mission, with key improvements that make it robust under non-ideal instrument conditions in the early mission phase. This leads to more reliable retrieval of clouds and rainfall during initial satellite operations.
Henning Dorff, Florian Ewald, Heike Konow, Mario Mech, Davide Ori, Vera Schemann, Andreas Walbröl, Manfred Wendisch, and Felix Ament
Atmos. Chem. Phys., 25, 8329–8354, https://doi.org/10.5194/acp-25-8329-2025, https://doi.org/10.5194/acp-25-8329-2025, 2025
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Using observations of an Arctic atmospheric river (AR) from a long-range research aircraft, we analyse how moisture transported into the Arctic by the AR is transformed and how it interacts with the Arctic environment. The moisture transport divergence is the main driver of local moisture change over time. Surface precipitation and evaporation are rather weak when averaged over extended AR sectors, although considerable heterogeneity of precipitation within the AR is observed.
Nina Maherndl, Alessandro Battaglia, Anton Kötsche, and Maximilian Maahn
Atmos. Meas. Tech., 18, 3287–3304, https://doi.org/10.5194/amt-18-3287-2025, https://doi.org/10.5194/amt-18-3287-2025, 2025
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Accurate measurements of ice water content (IWC) and snowfall rate (SR) are challenging due to high spatial variability and limitations of our measurement techniques. Here, we present a novel method to derive IWC and SR from W-band cloud radar observations, considering the degree of riming. We also investigate the use of the liquid water path (LWP) as a proxy for the occurrence of riming. LWP is easier to measure, so that the method can be applied to both ground-based and space-based instruments.
Kerstin Ebell, Christian Buhren, Rosa Gierens, Giovanni Chellini, Melanie Lauer, Andreas Walbröl, Sandro Dahlke, Pavel Krobot, and Mario Mech
Atmos. Chem. Phys., 25, 7315–7342, https://doi.org/10.5194/acp-25-7315-2025, https://doi.org/10.5194/acp-25-7315-2025, 2025
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Ground-based observations of precipitation are rare in the Arctic. Since 2017, additional temporally highly resolved precipitation measurements have been carried out by a precipitation gauge and an optical precipitation sensor at Ny-Ålesund, Svalbard. These new data facilitate the distinction between liquid and solid precipitation. Using reanalysis data, we also find that water vapor transport contributes strongly to precipitation and especially to extreme precipitation events.
Zackary Mages, Pavlos Kollias, Bernat Puigdomènech Treserras, Paloma Borque, and Mariko Oue
Atmos. Chem. Phys., 25, 6025–6045, https://doi.org/10.5194/acp-25-6025-2025, https://doi.org/10.5194/acp-25-6025-2025, 2025
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Convective clouds are a key component of the climate system. Using remote sensing observations during two field experiments in Houston, Texas, we identify four diurnal patterns of shallow convective clouds. We find areas more frequently experiencing shallow convective clouds, and we find areas where the vertical extent of shallow convective clouds is higher and where they are more likely to precipitate. This provides insight into the complicated environment that forms these clouds in Houston.
Kevin Ohneiser, Patric Seifert, Willi Schimmel, Fabian Senf, Tom Gaudek, Martin Radenz, Audrey Teisseire, Veronika Ettrichrätz, Teresa Vogl, Nina Maherndl, Nils Pfeifer, Jan Henneberger, Anna J. Miller, Nadja Omanovic, Christopher Fuchs, Huiying Zhang, Fabiola Ramelli, Robert Spirig, Anton Kötsche, Heike Kalesse-Los, Maximilian Maahn, Heather Corden, Alexis Berne, Majid Hajipour, Hannes Griesche, Julian Hofer, Ronny Engelmann, Annett Skupin, Albert Ansmann, and Holger Baars
EGUsphere, https://doi.org/10.5194/egusphere-2025-2482, https://doi.org/10.5194/egusphere-2025-2482, 2025
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This study focuses on a seeder-feeder cloud system on 8 Jan 2024 in Eriswil, Switzerland. It is shown how the interaction of these cloud systems changes the cloud microphysical properties and the precipitation patterns. A big set of advanced remote-sensing techniques and retrieval algorithms are applied, so that a detailed view on the seeder-feeder cloud system is available. The gained knowledge can be used to improve weather models and weather forecasts.
Francesco Manconi, Alessandro Battaglia, and Pavlos Kollias
Atmos. Meas. Tech., 18, 2295–2310, https://doi.org/10.5194/amt-18-2295-2025, https://doi.org/10.5194/amt-18-2295-2025, 2025
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The paper aims to study the ground reflection, or clutter, of the signal from a spaceborne radar in the context of ESA's WIVERN (WInd VElocity Radar Nephoscop) mission, which will observe in-cloud winds. Using topography and land type data, with a model of the satellite orbit and rotating antenna, simulations of scans have been run over the Piedmont region of Italy. These measurements cover the full range of the ground clutter over land for WIVERN and have allowed for analyses of the precision and accuracy of velocity observations.
Jialin Yan, Mariko Oue, Pavlos Kollias, Edward Luke, and Fan Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-2149, https://doi.org/10.5194/egusphere-2025-2149, 2025
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In this study, we analyzed over six years of ground-based radar and weather balloon data collected in northern Alaska. We found that ice particle changes depend strongly on temperature, humidity conditions and turbulence. We also found that turbulence and the presence of supercooled liquid water often occur together, and when they do, ice particle growth is especially strong. These findings help scientists to improve weather models.
Manfred Wendisch, Benjamin Kirbus, Davide Ori, Matthew D. Shupe, Susanne Crewell, Harald Sodemann, and Vera Schemann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2062, https://doi.org/10.5194/egusphere-2025-2062, 2025
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Aircraft observations of air parcels moving into and out of the Arctic are reported. From the data, heating and cooling as well as drying and moistening of the air masses along their way into and out of the Arctic could be measured for the first time. These data enable to evaluate if numerical weather prediction models are able to accurately represent these air mass transformations. This work helps to model the future climate changes in the Arctic, which are important for mid-latitude weather.
Aida Galfione, Alessandro Battaglia, Bernat Puigdomènech Treserras, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2025-1914, https://doi.org/10.5194/egusphere-2025-1914, 2025
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Convection drives atmospheric circulation but is difficult to observe and model. EarthCARE's radar provides the first space-based vertical wind data, capturing updrafts and downdrafts. Combined with satellite imagery from other sensors, it offers a broader view of convective storms. While resolution limits detail, cloud-top cooling helps track storm development. This combined approach improves understanding and modeling of convection.
André Ehrlich, Susanne Crewell, Andreas Herber, Marcus Klingebiel, Christof Lüpkes, Mario Mech, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Matthias Buschmann, Hans-Christian Clemen, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Andreas Giez, Sarah Grawe, Christophe Gourbeyre, Jörg Hartmann, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsófia Jurányi, Benjamin Kirbus, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Christian Mallaun, Johanna Mayer, Stephan Mertes, Guillaume Mioche, Manuel Moser, Hanno Müller, Veronika Pörtge, Nils Risse, Greg Roberts, Sophie Rosenburg, Johannes Röttenbacher, Michael Schäfer, Jonas Schaefer, Andreas Schäfler, Imke Schirmacher, Johannes Schneider, Sabrina Schnitt, Frank Stratmann, Christian Tatzelt, Christiane Voigt, Andreas Walbröl, Anna Weber, Bruno Wetzel, Martin Wirth, and Manfred Wendisch
Earth Syst. Sci. Data, 17, 1295–1328, https://doi.org/10.5194/essd-17-1295-2025, https://doi.org/10.5194/essd-17-1295-2025, 2025
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This paper provides an overview of the HALO–(AC)3 aircraft campaign data sets, the campaign-specific instrument operation, data processing, and data quality. The data set comprises in situ and remote sensing observations from three research aircraft: HALO, Polar 5, and Polar 6. All data are published in the PANGAEA database by instrument-separated data subsets. It is highlighted how the scientific analysis of the HALO–(AC)3 data benefits from the coordinated operation of three aircraft.
Nitika Yadlapalli Yurk, Matthew Lebsock, Juan Socuellamos, Raquel Rodriguez Monje, Ken Cooper, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2025-618, https://doi.org/10.5194/egusphere-2025-618, 2025
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Current knowledge of the link between clouds and climate is limited by lack of observations of the drop size distribution (DSD) within clouds, especially for the smallest drops. We demonstrate a method of retrieving DSDs down to small drop sizes using observations of drizzling marine layer clouds captured by the CloudCube millimeter-wave Doppler radar. We compare the shape of the observed spectra to theoretical expectations of radar echoes to solve for DSDs at each time and elevation.
Anton Kötsche, Alexander Myagkov, Leonie von Terzi, Maximilian Maahn, Veronika Ettrichrätz, Teresa Vogl, Alexander Ryzhkov, Petar Bukovcic, Davide Ori, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2025-734, https://doi.org/10.5194/egusphere-2025-734, 2025
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Our study combines radar observations of snowf with snowfall camera observations on the ground to enhance our understanding of radar variables and snowfall properties. We found that values of an important radar variable (KDP) can be related to many different snow particle properties and number concentrations. We were able to constrain which particle sizes contribute to KDP by using computer models of snowflakes and showed which microphysical processes during snow formation can influence KDP.
Sarah Wugofski, Matthew R. Kumjian, Mariko Oue, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2025-671, https://doi.org/10.5194/egusphere-2025-671, 2025
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Doppler spectral data inform on how particles of varying vertical velocities contribute to total backscattered power observed. Through examining three case studies, consistent features in radar moment data were found to be characteristic of multi-modal spectra. We quantified how spectrum width and mean Doppler velocity can be used to determine whether or not a layer is multi-modal. The identification criteria and methods are described in Part 1 and assessed in Part 2.
Marco Coppola, Alessandro Battaglia, Frederic Tridon, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2025-416, https://doi.org/10.5194/egusphere-2025-416, 2025
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The WIVERN conically scanning Doppler W-band radar, has the potential, for the first time, to map the mesoscale and synoptic variability of cloud dynamics, and precipitation microphysics. This study shows that the oblique angle of incidence will be advantageous compared to standard nadir-looking radars due to substantial clutter suppression over ocean surface. This feature will enable the detection and quantification of light and moderate precipitation, with improved proximity to the surface.
Marcus Klingebiel, André Ehrlich, Micha Gryschka, Nils Risse, Nina Maherndl, Imke Schirmacher, Sophie Rosenburg, Sabine Hörnig, Manuel Moser, Evelyn Jäkel, Michael Schäfer, Hartwig Deneke, Mario Mech, Christiane Voigt, and Manfred Wendisch
EGUsphere, https://doi.org/10.5194/egusphere-2025-201, https://doi.org/10.5194/egusphere-2025-201, 2025
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Our study is using aircraft measurements from the HALO-(𝒜𝒞)³ campaign to investigate the transition from organized Arctic cloud street structures to more scattered cloud shapes. We show that lower wind speeds cause this transition. In addition we look at the changes of the cloud coverage, the height of the clouds, the cloud particles and the radiative properties.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Nina Maherndl, Manuel Moser, Imke Schirmacher, Aaron Bansemer, Johannes Lucke, Christiane Voigt, and Maximilian Maahn
Atmos. Chem. Phys., 24, 13935–13960, https://doi.org/10.5194/acp-24-13935-2024, https://doi.org/10.5194/acp-24-13935-2024, 2024
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It is not clear why ice crystals in clouds occur in clusters. Here, airborne measurements of clouds in mid-latitudes and high latitudes are used to study the spatial variability of ice. Further, we investigate the influence of riming, which occurs when liquid droplets freeze onto ice crystals. We find that riming enhances the occurrence of ice clusters. In the Arctic, riming leads to ice clustering at spatial scales of 3–5 km. This is due to updrafts and not higher amounts of liquid water.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias
Atmos. Meas. Tech., 17, 6965–6981, https://doi.org/10.5194/amt-17-6965-2024, https://doi.org/10.5194/amt-17-6965-2024, 2024
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This article presents a novel technique to estimate liquid water content (LWC) profiles 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 retrieving the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
Imke Schirmacher, Sabrina Schnitt, Marcus Klingebiel, Nina Maherndl, Benjamin Kirbus, André Ehrlich, Mario Mech, and Susanne Crewell
Atmos. Chem. Phys., 24, 12823–12842, https://doi.org/10.5194/acp-24-12823-2024, https://doi.org/10.5194/acp-24-12823-2024, 2024
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During Arctic marine cold-air outbreaks, cold air flows from sea ice over open water. Roll circulations evolve, forming cloud streets. We investigate the initial circulation and cloud development using high-resolution airborne measurements. We compute the distance an air mass traveled over water (fetch) from back trajectories. Cloud streets form at 15 km fetch, cloud cover strongly increases at around 20 km, and precipitation forms at around 30 km.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
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The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Theresa Kiszler, Davide Ori, and Vera Schemann
Atmos. Chem. Phys., 24, 10039–10053, https://doi.org/10.5194/acp-24-10039-2024, https://doi.org/10.5194/acp-24-10039-2024, 2024
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Microphysical processes impact the phase-partitioning of clouds. In this study we evaluate these processes while focusing on low-level Arctic clouds. To achieve this we used an extensive simulation set in combination with a new diagnostic tool. This study presents our findings on the relevance of these processes and their behaviour under different thermodynamic regimes.
Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
The Cryosphere, 18, 4137–4163, https://doi.org/10.5194/tc-18-4137-2024, https://doi.org/10.5194/tc-18-4137-2024, 2024
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Passive microwave observations from satellites are crucial for monitoring Arctic sea ice and atmosphere. To do this effectively, it is important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we improved our understanding, identified four distinct emission types, and expanded current knowledge to include higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
Filippo Emilio Scarsi, Alessandro Battaglia, Maximilian Maahn, and Stef Lhermitte
EGUsphere, https://doi.org/10.5194/egusphere-2024-1917, https://doi.org/10.5194/egusphere-2024-1917, 2024
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Snowfall measurements at high latitudes are crucial for estimating ice sheet mass balance. Spaceborne radar and radiometer missions help estimate snowfall but face uncertainties. This work evaluates uncertainties in snowfall estimates from a fixed near-nadir radar (CloudSat-like) and a conically scanning radar (WIVERN-like), determining that WIVERN will provide much better estimates than CloudSat, and at much smaller spatial and temporal scales.
Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna E. Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona M. Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schaefer, Vera Schemann, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
Atmos. Chem. Phys., 24, 8865–8892, https://doi.org/10.5194/acp-24-8865-2024, https://doi.org/10.5194/acp-24-8865-2024, 2024
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The Arctic is warming faster than the rest of the globe. Warm-air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold-air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to mid-latitude weather. In our article, we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented with state-of-the-art remote-sensing and in situ measurement devices.
Henning Dorff, Heike Konow, Vera Schemann, and Felix Ament
Atmos. Chem. Phys., 24, 8771–8795, https://doi.org/10.5194/acp-24-8771-2024, https://doi.org/10.5194/acp-24-8771-2024, 2024
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Using synthetic dropsondes, we assess how discrete spatial sampling and temporal evolution during flight affect the accuracy of real sonde-based moisture transport divergence in Arctic atmospheric rivers (ARs). Non-instantaneous sampling during temporal AR evolution deteriorates the divergence values more than spatial undersampling. Moisture advection is the dominating factor but most sensitive to the sampling method. We suggest a minimum of seven sondes to resolve the AR divergence components.
Andreas Walbröl, Janosch Michaelis, Sebastian Becker, Henning Dorff, Kerstin Ebell, Irina Gorodetskaya, Bernd Heinold, Benjamin Kirbus, Melanie Lauer, Nina Maherndl, Marion Maturilli, Johanna Mayer, Hanno Müller, Roel A. J. Neggers, Fiona M. Paulus, Johannes Röttenbacher, Janna E. Rückert, Imke Schirmacher, Nils Slättberg, André Ehrlich, Manfred Wendisch, and Susanne Crewell
Atmos. Chem. Phys., 24, 8007–8029, https://doi.org/10.5194/acp-24-8007-2024, https://doi.org/10.5194/acp-24-8007-2024, 2024
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To support the interpretation of the data collected during the HALO-(AC)3 campaign, which took place in the North Atlantic sector of the Arctic from 7 March to 12 April 2022, we analyze how unusual the weather and sea ice conditions were with respect to the long-term climatology. From observations and ERA5 reanalysis, we found record-breaking warm air intrusions and a large variety of marine cold air outbreaks. Sea ice concentration was mostly within the climatological interquartile range.
Robin J. Hogan, Anthony J. Illingworth, Pavlos Kollias, Hajime Okamoto, and Ulla Wandinger
Atmos. Meas. Tech., 17, 3081–3083, https://doi.org/10.5194/amt-17-3081-2024, https://doi.org/10.5194/amt-17-3081-2024, 2024
Junghwa Lee, Patric Seifert, Tempei Hashino, Maximilian Maahn, Fabian Senf, and Oswald Knoth
Atmos. Chem. Phys., 24, 5737–5756, https://doi.org/10.5194/acp-24-5737-2024, https://doi.org/10.5194/acp-24-5737-2024, 2024
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Spectral bin model simulations of an idealized supercooled stratiform cloud were performed with the AMPS model for variable CCN and INP concentrations. We performed radar forward simulations with PAMTRA to transfer the simulations into radar observational space. The derived radar reflectivity factors were compared to observational studies of stratiform mixed-phase clouds. These studies report a similar response of the radar reflectivity factor to aerosol perturbations as we found in our study.
Kristofer S. Tuftedal, Bernat Puigdomènech Treserras, Mariko Oue, and Pavlos Kollias
Atmos. Chem. Phys., 24, 5637–5657, https://doi.org/10.5194/acp-24-5637-2024, https://doi.org/10.5194/acp-24-5637-2024, 2024
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This study analyzed coastal convective cells from June through September 2018–2021. The cells were classified and their lifecycles were analyzed to better understand their characteristics. Features such as convective-core growth, for example, are shown. The study found differences in the initiation location of shallow convection and in the aerosol loading in deep convective environments. This work provides a foundation for future analyses of convection or other tracked events elsewhere.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Nina Maherndl, Manuel Moser, Johannes Lucke, Mario Mech, Nils Risse, Imke Schirmacher, and Maximilian Maahn
Atmos. Meas. Tech., 17, 1475–1495, https://doi.org/10.5194/amt-17-1475-2024, https://doi.org/10.5194/amt-17-1475-2024, 2024
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In some clouds, liquid water droplets can freeze onto ice crystals (riming). Riming leads to the formation of snowflakes. We show two ways to quantify riming using aircraft data collected in the Arctic. One aircraft had a cloud radar, while the other aircraft was measuring directly in cloud. The first method compares radar and direct observations. The second looks at snowflake shape. Both methods agree, except when there were gaps in the cloud. This improves our ability to understand riming.
Zeen Zhu, Fan Yang, Pavlos Kollias, Raymond A. Shaw, Alex B. Kostinski, Steve Krueger, Katia Lamer, Nithin Allwayin, and Mariko Oue
Atmos. Meas. Tech., 17, 1133–1143, https://doi.org/10.5194/amt-17-1133-2024, https://doi.org/10.5194/amt-17-1133-2024, 2024
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In this article, we demonstrate the feasibility of applying advanced radar technology to detect liquid droplets generated in the cloud chamber. Specifically, we show that using radar with centimeter-scale resolution, single drizzle drops with a diameter larger than 40 µm can be detected. This study demonstrates the applicability of remote sensing instruments in laboratory experiments and suggests new applications of ultrahigh-resolution radar for atmospheric sensing.
Maximilian Maahn, Dmitri Moisseev, Isabelle Steinke, Nina Maherndl, and Matthew D. Shupe
Atmos. Meas. Tech., 17, 899–919, https://doi.org/10.5194/amt-17-899-2024, https://doi.org/10.5194/amt-17-899-2024, 2024
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The open-source Video In Situ Snowfall Sensor (VISSS) is a novel instrument for characterizing particle shape, size, and sedimentation velocity in snowfall. It combines a large observation volume with relatively high resolution and a design that limits wind perturbations. The open-source nature of the VISSS hardware and software invites the community to contribute to the development of the instrument, which has many potential applications in atmospheric science and beyond.
Shannon L. Mason, Howard W. Barker, 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
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, 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 European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024, https://doi.org/10.5194/essd-16-681-2024, 2024
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This publication describes the microwave radiometric measurements performed during the EUREC4A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.
Marcus Klingebiel, André Ehrlich, Elena Ruiz-Donoso, Nils Risse, Imke Schirmacher, Evelyn Jäkel, Michael Schäfer, Kevin Wolf, Mario Mech, Manuel Moser, Christiane Voigt, and Manfred Wendisch
Atmos. Chem. Phys., 23, 15289–15304, https://doi.org/10.5194/acp-23-15289-2023, https://doi.org/10.5194/acp-23-15289-2023, 2023
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In this study we explain how we use aircraft measurements from two Arctic research campaigns to identify cloud properties (like droplet size) over sea-ice and ice-free ocean. To make sure that our measurements make sense, we compare them with other observations. Our results show, e.g., larger cloud droplets in early summer than in spring. Moreover, the cloud droplets are also larger over ice-free ocean than compared to sea ice. In the future, our data can be used to improve climate models.
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
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We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
David P. Donovan, Pavlos Kollias, Almudena Velázquez Blázquez, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5327–5356, https://doi.org/10.5194/amt-16-5327-2023, https://doi.org/10.5194/amt-16-5327-2023, 2023
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The Earth Cloud, Aerosol and Radiation Explorer mission (EarthCARE) is a multi-instrument cloud–aerosol–radiation-oriented satellite for climate and weather applications. For this satellite mission to be successful, the development and implementation of new techniques for turning the measured raw signals into useful data is required. This paper describes how atmospheric model data were used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
Imke Schirmacher, Pavlos Kollias, Katia Lamer, Mario Mech, Lukas Pfitzenmaier, Manfred Wendisch, and Susanne Crewell
Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, https://doi.org/10.5194/amt-16-4081-2023, 2023
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CloudSat’s relatively coarse spatial resolution, low sensitivity, and blind zone limit its assessment of Arctic low-level clouds, which affect the surface energy balance. We compare cloud fractions from CloudSat and finely resolved airborne radar observations to determine CloudSat’s limitations. Cloudsat overestimates cloud fractions above its blind zone, especially during cold-air outbreaks over open water, and misses a cloud fraction of 32 % and half of the precipitation inside its blind zone.
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.
Melanie Lauer, Annette Rinke, Irina Gorodetskaya, Michael Sprenger, Mario Mech, and Susanne Crewell
Atmos. Chem. Phys., 23, 8705–8726, https://doi.org/10.5194/acp-23-8705-2023, https://doi.org/10.5194/acp-23-8705-2023, 2023
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We present a new method to analyse the influence of atmospheric rivers (ARs), cyclones, and fronts on the precipitation in the Arctic, based on two campaigns: ACLOUD (early summer 2017) and AFLUX (early spring 2019). There are differences between both campaign periods: in early summer, the precipitation is mostly related to ARs and fronts, especially when they are co-located, while in early spring, cyclones isolated from ARs and fronts contributed most to the precipitation.
Manuel Moser, Christiane Voigt, Tina Jurkat-Witschas, Valerian Hahn, Guillaume Mioche, Olivier Jourdan, Régis Dupuy, Christophe Gourbeyre, Alfons Schwarzenboeck, Johannes Lucke, Yvonne Boose, Mario Mech, Stephan Borrmann, André Ehrlich, Andreas Herber, Christof Lüpkes, and Manfred Wendisch
Atmos. Chem. Phys., 23, 7257–7280, https://doi.org/10.5194/acp-23-7257-2023, https://doi.org/10.5194/acp-23-7257-2023, 2023
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This study provides a comprehensive microphysical and thermodynamic phase analysis of low-level clouds in the northern Fram Strait, above the sea ice and the open ocean, during spring and summer. Using airborne in situ cloud data, we show that the properties of Arctic low-level clouds vary significantly with seasonal meteorological situations and surface conditions. The observations presented in this study can help one to assess the role of clouds in the Arctic climate system.
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.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Jan Chylik, Dmitry Chechin, Regis Dupuy, Birte S. Kulla, Christof Lüpkes, Stephan Mertes, Mario Mech, and Roel A. J. Neggers
Atmos. Chem. Phys., 23, 4903–4929, https://doi.org/10.5194/acp-23-4903-2023, https://doi.org/10.5194/acp-23-4903-2023, 2023
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Arctic low-level clouds play an important role in the ongoing warming of the Arctic. Unfortunately, these clouds are not properly represented in weather forecast and climate models. This study tries to cover this gap by focusing on clouds over open water during the spring, observed by research aircraft near Svalbard. The study combines the high-resolution model with sets of observational data. The results show the importance of processes that involve both ice and the liquid water in the clouds.
Pavlos Kollias, Bernat Puidgomènech Treserras, Alessandro Battaglia, Paloma C. Borque, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 1901–1914, https://doi.org/10.5194/amt-16-1901-2023, https://doi.org/10.5194/amt-16-1901-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission developed by the European Space Agency (ESA) and Japan Aerospace Exploration Agency (JAXA) features the first spaceborne 94 GHz Doppler cloud-profiling radar (CPR) with Doppler capability. Here, we describe the post-processing algorithms that apply quality control and corrections to CPR measurements and derive key geophysical variables such as hydrometeor locations and best estimates of particle sedimentation fall velocities.
Samuel Kwakye, Heike Kalesse-Los, Maximilian Maahn, Patric Seifert, Roel van Klink, Christian Wirth, and Johannes Quaas
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-69, https://doi.org/10.5194/amt-2023-69, 2023
Publication in AMT not foreseen
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Insect numbers in the atmosphere can be calculated using polarimetric weather radar but they have to be identified and separated from other echoes, especially weather phenomena. Here, the separation is demonstrated using three machine-learning algorithms and insect count data from suction traps and the nature of radar measurements of different radar echoes is revealed. Random forest is the best separating algorithm and insect echoes radar measurements are distinct.
Zackary Mages, Pavlos Kollias, Zeen Zhu, and Edward P. Luke
Atmos. Chem. Phys., 23, 3561–3574, https://doi.org/10.5194/acp-23-3561-2023, https://doi.org/10.5194/acp-23-3561-2023, 2023
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Cold-air outbreaks (when cold air is advected over warm water and creates low-level convection) are a dominant cloud regime in the Arctic, and we capitalized on ground-based observations, which did not previously exist, from the COMBLE field campaign to study them. We characterized the extent and strength of the convection and turbulence and found evidence of secondary ice production. This information is useful for model intercomparison studies that will represent cold-air outbreak processes.
Frederic Tridon, Israel Silber, Alessandro Battaglia, Stefan Kneifel, Ann Fridlind, Petros Kalogeras, and Ranvir Dhillon
Atmos. Chem. Phys., 22, 12467–12491, https://doi.org/10.5194/acp-22-12467-2022, https://doi.org/10.5194/acp-22-12467-2022, 2022
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The role of ice precipitation in the Earth water budget is not well known because ice particles are complex, and their formation involves intricate processes. Riming of ice crystals by supercooled water droplets is an efficient process, but little is known about its importance at high latitudes. In this work, by exploiting the deployment of an unprecedented number of remote sensing systems in Antarctica, we find that riming occurs at much lower temperatures compared with the mid-latitudes.
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
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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.
Leonie von Terzi, José Dias Neto, Davide Ori, Alexander Myagkov, and Stefan Kneifel
Atmos. Chem. Phys., 22, 11795–11821, https://doi.org/10.5194/acp-22-11795-2022, https://doi.org/10.5194/acp-22-11795-2022, 2022
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We present a statistical analysis of ice microphysical processes (IMP) in mid-latitude clouds. Combining various radar approaches, we find that the IMP active at −20 to −10 °C seems to be the main driver of ice particle size, shape and concentration. The strength of aggregation at −20 to −10 °C correlates with the increase in concentration and aspect ratio of locally formed ice particles. Despite ongoing aggregation, the concentration of ice particles stays enhanced until −4 °C.
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
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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.
Zeen Zhu, Pavlos Kollias, Edward Luke, and Fan Yang
Atmos. Chem. Phys., 22, 7405–7416, https://doi.org/10.5194/acp-22-7405-2022, https://doi.org/10.5194/acp-22-7405-2022, 2022
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Drizzle (small rain droplets) is an important component of warm clouds; however, its existence is poorly understood. In this study, we capitalized on a machine-learning algorithm to develop a drizzle detection method. We applied this algorithm to investigate drizzle occurrence and found out that drizzle is far more ubiquitous than previously thought. This study demonstrates the ubiquitous nature of drizzle in clouds and will improve understanding of the associated microphysical process.
Annakaisa von Lerber, Mario Mech, Annette Rinke, Damao Zhang, Melanie Lauer, Ana Radovan, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 7287–7317, https://doi.org/10.5194/acp-22-7287-2022, https://doi.org/10.5194/acp-22-7287-2022, 2022
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Snowfall is an important climate indicator. However, microphysical snowfall processes are challenging for atmospheric models. In this study, the performance of a regional climate model is evaluated in modeling the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations. Excellent agreement in averaged annual snowfall rates is found, and the shown methodology offers a promising diagnostic tool to investigate the shown differences further.
Alessandro Battaglia, Paolo Martire, Eric Caubet, Laurent Phalippou, Fabrizio Stesina, Pavlos Kollias, and Anthony Illingworth
Atmos. Meas. Tech., 15, 3011–3030, https://doi.org/10.5194/amt-15-3011-2022, https://doi.org/10.5194/amt-15-3011-2022, 2022
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We present an instrument simulator for a new sensor, WIVERN (WInd VElocity Radar Nephoscope), a conically scanning radar payload with Doppler capabilities, recently down-selected as one of the four candidates for the European Space Agency Earth Explorer 11 program. The mission aims at measuring horizontal winds in cloudy areas. The simulator is instrumental in the definition and consolidation of the mission requirements and the evaluation of mission performances.
Alexander Myagkov and Davide Ori
Atmos. Meas. Tech., 15, 1333–1354, https://doi.org/10.5194/amt-15-1333-2022, https://doi.org/10.5194/amt-15-1333-2022, 2022
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This study provides equations to characterize random errors of spectral polarimetric observations from cloud radars. The results can be used for a broad spectrum of applications. For instance, accurate error characterization is essential for advanced retrievals of microphysical properties of clouds and precipitation. Moreover, error characterization allows for the use of measurements from polarimetric cloud radars to potentially improve weather forecasts.
Teresa Vogl, Maximilian Maahn, Stefan Kneifel, Willi Schimmel, Dmitri Moisseev, and Heike Kalesse-Los
Atmos. Meas. Tech., 15, 365–381, https://doi.org/10.5194/amt-15-365-2022, https://doi.org/10.5194/amt-15-365-2022, 2022
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We are using machine learning techniques, a type of artificial intelligence, to detect graupel formation in clouds. The measurements used as input to the machine learning framework were performed by cloud radars. Cloud radars are instruments located at the ground, emitting radiation with wavelenghts of a few millimeters vertically into the cloud and measuring the back-scattered signal. Our novel technique can be applied to different radar systems and different weather conditions.
Carolina Viceto, Irina V. Gorodetskaya, Annette Rinke, Marion Maturilli, Alfredo Rocha, and Susanne Crewell
Atmos. Chem. Phys., 22, 441–463, https://doi.org/10.5194/acp-22-441-2022, https://doi.org/10.5194/acp-22-441-2022, 2022
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We focus on anomalous moisture transport events known as atmospheric rivers (ARs). During ACLOUD and PASCAL, three AR events were identified: 30 May, 6 June, and 9 June 2017. We explore their spatio-temporal evolution and precipitation patterns using measurements, reanalyses, and a model. We show the importance of the following: Atlantic and Siberian pathways during spring–summer in the Arctic, AR-associated heat/moisture increase, precipitation phase transition, and high-resolution datasets.
Claudia Acquistapace, Richard Coulter, Susanne Crewell, Albert Garcia-Benadi, Rosa Gierens, Giacomo Labbri, Alexander Myagkov, Nils Risse, and Jan H. Schween
Earth Syst. Sci. Data, 14, 33–55, https://doi.org/10.5194/essd-14-33-2022, https://doi.org/10.5194/essd-14-33-2022, 2022
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This publication describes the unprecedented high-resolution cloud and precipitation dataset collected by two radars deployed on the Maria S. Merian research vessel. The ship operated in the west Atlantic Ocean during the measurement campaign called EUREC4A, between 19 January and 19 February 2020. The data collected are crucial to investigate clouds and precipitation and understand how they form and change over the ocean, where it is so difficult to measure them.
Hélène Bresson, Annette Rinke, Mario Mech, Daniel Reinert, Vera Schemann, Kerstin Ebell, Marion Maturilli, Carolina Viceto, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 173–196, https://doi.org/10.5194/acp-22-173-2022, https://doi.org/10.5194/acp-22-173-2022, 2022
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Arctic warming is pronounced, and one factor in this is the poleward atmospheric transport of heat and moisture. This study assesses the 4D structure of an Arctic moisture intrusion event which occurred in June 2017. For the first time, high-resolution pan-Arctic ICON simulations are performed and compared with global models, reanalysis, and observations. Results show the added value of high resolution in the event representation and the impact of the intrusion on the surface energy fluxes.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Heike Konow, Florian Ewald, Geet George, Marek Jacob, Marcus Klingebiel, Tobias Kölling, Anna E. Luebke, Theresa Mieslinger, Veronika Pörtge, Jule Radtke, Michael Schäfer, Hauke Schulz, Raphaela Vogel, Martin Wirth, Sandrine Bony, Susanne Crewell, André Ehrlich, Linda Forster, Andreas Giez, Felix Gödde, Silke Groß, Manuel Gutleben, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Theresa Lang, Bernhard Mayer, Mario Mech, Marc Prange, Sabrina Schnitt, Jessica Vial, Andreas Walbröl, Manfred Wendisch, Kevin Wolf, Tobias Zinner, Martin Zöger, Felix Ament, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 5545–5563, https://doi.org/10.5194/essd-13-5545-2021, https://doi.org/10.5194/essd-13-5545-2021, 2021
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The German research aircraft HALO took part in the research campaign EUREC4A in January and February 2020. The focus area was the tropical Atlantic east of the island of Barbados. We describe the characteristics of the 15 research flights, provide auxiliary information, derive combined cloud mask products from all instruments that observe clouds on board the aircraft, and provide code examples that help new users of the data to get started.
Markus Karrer, Axel Seifert, Davide Ori, and Stefan Kneifel
Atmos. Chem. Phys., 21, 17133–17166, https://doi.org/10.5194/acp-21-17133-2021, https://doi.org/10.5194/acp-21-17133-2021, 2021
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Modeling precipitation is of great relevance, e.g., for mitigating damage caused by extreme weather. A key component in accurate precipitation modeling is aggregation, i.e., sticking together of snowflakes. Simulating aggregation is difficult due to multiple parameters that are not well-known. Knowing how these parameters affect aggregation can help its simulation. We put new parameters in the model and select a combination of parameters with which the model can simulate observations better.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 21, 14039–14058, https://doi.org/10.5194/acp-21-14039-2021, https://doi.org/10.5194/acp-21-14039-2021, 2021
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This numerical study provides insights into the sensitivity of shallow-cumulus dilution to geostrophic vertical wind profile. The cumulus dilution is strongly sensitive to vertical wind shear in the cloud layer, with shallow cumuli being more diluted in sheared environments. On the other hand, wind shear in the subcloud layer leads to less diluted cumuli. The sensitivities are explained by jointly considering the impacts of vertical velocity and the properties of the entrained air.
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.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
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Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
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Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Katia Lamer, Mariko Oue, Alessandro Battaglia, Richard J. Roy, Ken B. Cooper, Ranvir Dhillon, and Pavlos Kollias
Atmos. Meas. Tech., 14, 3615–3629, https://doi.org/10.5194/amt-14-3615-2021, https://doi.org/10.5194/amt-14-3615-2021, 2021
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Observations collected during the 25 February 2020 deployment of the VIPR at the Stony Brook Radar Observatory clearly demonstrate the potential of G-band radars for cloud and precipitation research. The field experiment, which coordinated an X-, Ka-, W- and G-band radar, revealed that the differential reflectivity from Ka–G band pair provides larger signals than the traditional Ka–W pairing underpinning an increased sensitivity to smaller amounts of liquid and ice water mass and sizes.
Davide Ori, Leonie von Terzi, Markus Karrer, and Stefan Kneifel
Geosci. Model Dev., 14, 1511–1531, https://doi.org/10.5194/gmd-14-1511-2021, https://doi.org/10.5194/gmd-14-1511-2021, 2021
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Snowflakes have very complex shapes, and modeling their properties requires vast computing power. We produced a large number of realistic snowflakes and modeled their average properties by leveraging their fractal structure. Our approach allows modeling the properties of big ensembles of snowflakes, taking into account their natural variability, at a much lower cost. This enables the usage of remote sensing instruments, such as radars, to monitor the evolution of clouds and precipitation.
Kamil Mróz, Alessandro Battaglia, Stefan Kneifel, Leonie von Terzi, Markus Karrer, and Davide Ori
Atmos. Meas. Tech., 14, 511–529, https://doi.org/10.5194/amt-14-511-2021, https://doi.org/10.5194/amt-14-511-2021, 2021
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The article examines the relationship between the characteristics of rain and the properties of the ice cloud from which the rain originated. Our results confirm the widely accepted assumption that the mass flux through the melting zone is well preserved with an exception of extreme aggregation and riming conditions. Moreover, it is shown that the mean (mass-weighted) size of particles above and below the melting zone is strongly linked, with the former being on average larger.
Marek Jacob, Pavlos Kollias, Felix Ament, Vera Schemann, and Susanne Crewell
Geosci. Model Dev., 13, 5757–5777, https://doi.org/10.5194/gmd-13-5757-2020, https://doi.org/10.5194/gmd-13-5757-2020, 2020
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We compare clouds in different cloud-resolving atmosphere simulations with airborne remote sensing observations. The focus is on warm shallow clouds in the Atlantic trade wind region. Those clouds are climatologically important but challenging for climate models. We use forward operators to apply instrument-specific thresholds for cloud detection to model outputs. In this comparison, the higher-resolution model better reproduces the layered cloud structure.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 20, 13217–13239, https://doi.org/10.5194/acp-20-13217-2020, https://doi.org/10.5194/acp-20-13217-2020, 2020
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This numerical study provides insights into selected environmental sensitivities of shallow-cumulus dilution. Among the parameters under consideration, the dilution of the cloud cores is strongly sensitive to continentality and cloud-layer relative humidity and weakly sensitive to subcloud- and cloud-layer depths. The impacts of all four parameters are interpreted using a similarity theory of shallow cumulus and buoyancy-sorting arguments.
Jie Gong, Xiping Zeng, Dong L. Wu, S. Joseph Munchak, Xiaowen Li, Stefan Kneifel, Davide Ori, Liang Liao, and Donifan Barahona
Atmos. Chem. Phys., 20, 12633–12653, https://doi.org/10.5194/acp-20-12633-2020, https://doi.org/10.5194/acp-20-12633-2020, 2020
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This work provides a novel way of using polarized passive microwave measurements to study the interlinked cloud–convection–precipitation processes. The magnitude of differences between polarized radiances is found linked to ice microphysics (shape, size, orientation and density), mesoscale dynamic and thermodynamic structures, and surface precipitation. We conclude that passive sensors with multiple polarized channel pairs may serve as cheaper and useful substitutes for spaceborne radar sensors.
Alexander Myagkov, Stefan Kneifel, and Thomas Rose
Atmos. Meas. Tech., 13, 5799–5825, https://doi.org/10.5194/amt-13-5799-2020, https://doi.org/10.5194/amt-13-5799-2020, 2020
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This study shows two methods for evaluating the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first method is based on spectral polarimetric observations and requires a polarimetric cloud radar with a scanner. The second method utilizes disdrometer observations and can be applied to scanning and vertically pointed radars. Both methods show consistent results and can be applied for operational monitoring of measurement quality.
Frédéric Tridon, Alessandro Battaglia, and Stefan Kneifel
Atmos. Meas. Tech., 13, 5065–5085, https://doi.org/10.5194/amt-13-5065-2020, https://doi.org/10.5194/amt-13-5065-2020, 2020
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The droplets and ice crystals composing clouds and precipitation interact with microwaves and can therefore be observed by radars, but they can also attenuate the signal they emit. By combining the observations made by two ground-based radars, this study describes an original approach for estimating such attenuation. As a result, the latter can be not only corrected in the radar observations but also exploited for providing an accurate characterization of droplet and ice crystal properties.
Alessandro Battaglia, Pavlos Kollias, Ranvir Dhillon, Katia Lamer, Marat Khairoutdinov, and Daniel Watters
Atmos. Meas. Tech., 13, 4865–4883, https://doi.org/10.5194/amt-13-4865-2020, https://doi.org/10.5194/amt-13-4865-2020, 2020
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Warm rain accounts for slightly more than 30 % of the total rain amount and 70 % of the total rain area in the tropical belt and usually appears in kilometer-size cells. Spaceborne radars adopting millimeter wavelengths are excellent tools for detecting such precipitation types and for separating between the cloud and rain components. Our work highlights the benefits of operating multifrequency radars and discusses the impact of antenna footprints in quantitative estimates of liquid water paths.
Cited articles
Acquistapace, C., Kneifel, S., Löhnert, U., Kollias, P., Maahn, M., and Bauer-Pfundstein, M.: Optimizing observations of drizzle onset with millimeter-wavelength radars, Atmos. Meas. Tech., 10, 1783–1802, https://doi.org/10.5194/amt-10-1783-2017, 2017. a
Acquistapace, C., Löhnert, U., Maahn, M., and Kollias, P.: A New Criterion
to Improve Operational Drizzle Detection with Ground-Based Remote Sensing,
J. Atmos. Ocean. Tech., 36, 781–801,
https://doi.org/10.1175/jtech-d-18-0158.1, 2019. a
Aires, F., Prigent, C., Bernardo, F., Jiménez, C., Saunders, R., and
Brunel, P.: A Tool to Estimate Land-Surface Emissivities at
Microwave Frequencies (TELSEM) for Use in Numerical Weather
Prediction, Q. J. Roy. Meteor. Soc., 137,
690–699, https://doi.org/10.1002/qj.803, 2011. a
Battaglia, A. and Tanelli, S.: DOMUS: DOppler MUltiple-Scattering
Simulator, IEEE T. Geosci. Remote S., 49, 442–450,
https://doi.org/10.1109/TGRS.2010.2052818, 2011. a
Battaglia, A., Tanelli, S., Kobayashi, S., Zrnic, D., Hogan, R. J., and Simmer,
C.: Multiple-Scattering in Radar Systems: A Review, J.
Quant. Spectrosc. Ra., 111, 917–947,
https://doi.org/10.1016/j.jqsrt.2009.11.024, 2010. a
Bennartz, R. and Petty, G. W.: The Sensitivity of Microwave Remote Sensing
Observations of Precipitation to Ice Particle Size Distributions, J.
Appl. Meteorol., 40, 345–364,
https://doi.org/10.1175/1520-0450(2001)040<0345:tsomrs>2.0.co;2, 2002. a
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L. L.,
Klein, S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John,
V. O.: COSP: Satellite Simulation Software for Model Assessment,
B. Am. Meteorol. Soc., 92, 1023–1043,
https://doi.org/10.1175/2011BAMS2856.1, 2011. a
Borque, P., Luke, E., and Kollias, P.: On the Unified Estimation of Turbulence
Eddy Dissipation Rate Using Doppler Cloud Radars and Lidars, J.
Geophys. Res., 121, 5972–5989, https://doi.org/10.1002/2015JD024543, 2016. a
Brdar, S. and Seifert, A.: McSnow: A Monte-Carlo Particle Model for
Riming and Aggregation of Ice Particles in a Multidimensional Microphysical
Phase Space, J. Adv. Model. Earth Sy., 10, 187–206,
https://doi.org/10.1002/2017MS001167, 2018. a, b
Buehler, S. A., Eriksson, P., Kuhn, T., von Engeln, A., and Verdes, C.:
ARTS, the Atmospheric Radiative Transfer Simulator, J.
Quant. Spectrosc. Ra., 91, 65–93,
https://doi.org/10.1016/j.jqsrt.2004.05.051, 2005. a
Buehler, S. A., Mendrok, J., Eriksson, P., Perrin, A., Larsson, R., and Lemke, O.: ARTS, the Atmospheric Radiative Transfer Simulator – version 2.2, the planetary toolbox edition, Geosci. Model Dev., 11, 1537–1556, https://doi.org/10.5194/gmd-11-1537-2018, 2018. a, b
Cadeddu, M. P. and Turner, D. D.: Evaluation of Water Permittivity Models from
Ground-Based Observations of Cold Clouds at Frequencies between 23 and 170
GHz, IEEE T. Geosci. Remote S., 49, 2999–3008,
https://doi.org/10.1109/TGRS.2011.2121074, 2011. a
Cadeddu, M. P., Marchand, R., Orlandi, E., Turner, D. D., and Mech, M.:
Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path
in Drizzling Clouds: Challenges and Possibilities, IEEE T.
Geosci. Remote S., 55, 6468–6481,
https://doi.org/10.1109/TGRS.2017.2728699, 2017. a
Cadeddu, M. P., Ghate, V. P., and Mech, M.: Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds, Atmos. Meas. Tech., 13, 1485–1499, https://doi.org/10.5194/amt-13-1485-2020, 2020. a, b
Chaboureau, J.-P. P., Söhne, N., Pinty, J.-P. P., Meirold-Mautner, I.,
Defer, E., Prigent, C., Pardo, J. R., Mech, M., and Crewell, S.: A
Midlatitude Precipitating Cloud Database Validated with Satellite
Observations, J. Appl. Meteorol. Clim., 47, 1337–1353,
https://doi.org/10.1175/2007JAMC1731.1, 2008. a, b
De Angelis, F., Cimini, D., Hocking, J., Martinet, P., and Kneifel, S.: RTTOV-gb – adapting the fast radiative transfer model RTTOV for the assimilation of ground-based microwave radiometer observations, Geosci. Model Dev., 9, 2721–2739, https://doi.org/10.5194/gmd-9-2721-2016, 2016. a
Deiveegan, M., Balaji, C., and Venkateshan, S. P.: A Polarized Microwave
Radiative Transfer Model for Passive Remote Sensing, Atmos. Res.,
88, 277–293, https://doi.org/10.1016/j.atmosres.2007.11.023, 2008. a
Dias Neto, J., Kneifel, S., Ori, D., Trömel, S., Handwerker, J., Bohn, B., Hermes, N., Mühlbauer, K., Lenefer, M., and Simmer, C.: The TRIple-frequency and Polarimetric radar Experiment for improving process observations of winter precipitation, Earth Syst. Sci. Data, 11, 845–863, https://doi.org/10.5194/essd-11-845-2019, 2019. a, b, c
Ding, S., Yang, P., Weng, F., Liu, Q., Han, Y., van Delst, P., Li, J., and
Baum, B.: Validation of the Community Radiative Transfer Model, J.
Quant. Spectrosc. Ra., 112, 1050–1064,
https://doi.org/10.1016/J.JQSRT.2010.11.009, 2011. a
Doms, G., Forstner, J., Heise, E., Herzog, H.-J., Raschendorfer, M., Reinhardt,
T., Ritter, B., Schrodin, R., Schulz, J.-P., and Vogel, G.: A Description of
the Nonhydrostatic Regional Model LM. Part 2: Physical
Parameterizations, Tech. rep., DWD, 2005. a
Doviak, R. J. and Zrnic, D. S.: Doppler Radar & Weather Observations, Second
Edition, Academic Press, 2nd Edn., 1993. a
Ebell, K., Orlandi, E., Hünerbein, A., Löhnert, U., and Crewell, S.:
Combining Ground-Based with Satellite-Based Measurements in the Atmospheric
State Retrieval: Assessment of the Information Content, J.
Geophys. Res.-Atmos., 118, 6940–6956, https://doi.org/10.1002/jgrd.50548,
2013. a
Ellison, W.: Dielectric Properties of Natural Media, in: Thermal Microwave
Radiation: Applications for Remote Sensing, edited by: Mätzler, C.,
The Institution of Engineering and Technology (IET),
London, 427–506, https://doi.org/10.1049/pbew052e_ch5, 2006. a, b, c
Ellison, W. J.: Permittivity of Pure Water, at Standard Atmospheric Pressure,
over the Frequency Range 0–25 THz and the Temperature Range 0–100 ∘C, J. Phys. Chem. Ref. Data, 36, 1–18,
https://doi.org/10.1063/1.2360986, 2007. a
Eriksson, P., Buehler, S. A., Davis, C. P., Emde, C., and Lemke, O.: ARTS,
the Atmospheric Radiative Transfer Simulator, Version 2, J.
Quant. Spectrosc. Ra., 112, 1551–1558,
https://doi.org/10.1016/j.jqsrt.2011.03.001, 2011. a
Evans, K. F. and Stephens, G. L.: A New Polarized Atmospheric Radiative
Transfer Model, J.
Quant. Spectrosc. Ra.,
46, 413–423, https://doi.org/10.1016/0022-4073(91)90043-P, 1991. a, b
Evans, K. F. and Stephens, G. L.: Microwave Remote Sensing Algorithms for
Cirrus Clouds and Precipitation., Tech. Rep. 540, Dept. of Atmospheric
Science,Colorade State University, Fort Collins, CO, 1993. a
Evans, K. F. and Stephens, G. L.: Microwave Radiative Transfer through Clouds
Composed of Realistically Shaped Ice Crystals. Part II. Remote
Sensing of Ice Clouds, J. Atmos. Sci., 52, 2058–2072,
https://doi.org/10.1175/1520-0469(1995)052<2058:mrttcc>2.0.co;2, 1995. a, b, c
Evans, K. F. and Stephens, G. L.: Many Polarized Radiative Transfer Models,
J. Quant. Spectrosc. Ra., 111, 1686–1688,
https://doi.org/10.1016/j.jqsrt.2010.01.029, 2010. a
Feist, D. G.: The BErnese Atmospheric Multiple Catalog Access Tool
(BEAMCAT): A Tool for Users of Popular Spectral Line Catalogs,
J. Quant. Spectrosc. Ra., 85, 57–97,
https://doi.org/10.1016/S0022-4073(03)00196-1, 2004. a
Field, P. R., Hogan, R. J., Brown, P. R. A., Illingworth, A. J., Choularton,
T. W., and Cotton, R. J.: Parametrization of Ice-Particle Size Distributions
for Mid-Latitude Stratiform Cloud, Q. J. Roy.
Meteorol. Soc., 131, 1997–2017, https://doi.org/10.1256/qj.04.134, 2005. a
Fixsen, D. J.: The Temperature of the Cosmic Microwave Background,
Astrophys. J., 707, 916–920, https://doi.org/10.1088/0004-637X/707/2/916,
2009. a
Geer, A. J. and Baordo, F.: Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies, Atmos. Meas. Tech., 7, 1839–1860, https://doi.org/10.5194/amt-7-1839-2014, 2014. a, b, c
Gossard, E. E. and Strauch, R. G.: Further Guide for the Retrieval of Dropsize
Distributions in Water Clouds with a Ground-Based Clear-Air-Sensing Doppler
Radar, NASA STI/Recon Technical Report n, U.S. Department of
Commerce, National Oceanic and Atmospheric Administration, Environmental
Research Laboratories, 1989. a
Han, M., Braun, S. A., Matsui, T., and Williams, C. R.: Evaluation of Cloud
Microphysics Schemes in Simulations of a Winter Storm Using Radar and
Radiometer Measurements, J. Geophys. Res.-Atmos., 118,
1401–1419, https://doi.org/10.1002/jgrd.50115, 2013. a
Hande, L. B., Engler, C., Hoose, C., and Tegen, I.: Parameterizing cloud condensation nuclei concentrations during HOPE, Atmos. Chem. Phys., 16, 12059–12079, https://doi.org/10.5194/acp-16-12059-2016, 2016. a
Haynes, J. M., Marchand, R. T., Luo, Z., Bodas-Salcedo, A., and Stephens,
G. L.: A Multipurpose Radar Simulation Package: QuickBeam, B.
Am. Meteorol. Soc., 88, 1723–1728, https://doi.org/10.1175/BAMS-88-11-1723, 2007. a, b
Heinze, R., Dipankar, A., Henken, C. C., Moseley, C., Sourdeval, O.,
Trömel, S., Xie, X., Adamidis, P., Ament, F., Baars, H., Barthlott, C.,
Behrendt, A., Blahak, U., Bley, S., Brdar, S., Brueck, M., Crewell, S.,
Deneke, H., Di Girolamo, P., Evaristo, R., Fischer, J., Frank, C.,
Friederichs, P., Göcke, T., Gorges, K., Hande, L., Hanke, M., Hansen, A.,
Hege, H. C., Hoose, C., Jahns, T., Kalthoff, N., Klocke, D., Kneifel, S.,
Knippertz, P., Kuhn, A., van Laar, T., Macke, A., Maurer, V., Mayer, B.,
Meyer, C. I., Muppa, S. K., Neggers, R. A., Orlandi, E., Pantillon, F.,
Pospichal, B., Röber, N., Scheck, L., Seifert, A., Seifert, P., Senf, F.,
Siligam, P., Simmer, C., Steinke, S., Stevens, B., Wapler, K., Weniger, M.,
Wulfmeyer, V., Zängl, G., Zhang, D., and Quaas, J.: Large-Eddy
Simulations over Germany Using ICON: A Comprehensive Evaluation,
Q. J. Roy. Meteor. Soc., 143, 69–100,
https://doi.org/10.1002/qj.2947, 2017. a, b
Heymsfield, A. J. and Westbrook, C. D.: Advances in the Estimation of Ice
Particle Fall Speeds Using Laboratory and Field Measurements, J.
Atmos. Sci., 67, 2469–2482, https://doi.org/10.1175/2010jas3379.1, 2010. a
Hildebrand, P. H., Sekhon, R. S., Hildebrand, P. H., and Sekhon, R. S.:
Objective Determination of the Noise Level in Doppler Spectra, J.
Appl. Meteorol., 13, 808–811,
https://doi.org/10.1175/1520-0450(1974)013<0808:odotnl>2.0.co;2, 2002. a
Hoffmann, F., Noh, Y., and Raasch, S.: The Route to Raindrop Formation in a
Shallow Cumulus Cloud Simulated by a Lagrangian Cloud Model, Jo.
Atmos. Sci., 74, 2125–2142, https://doi.org/10.1175/JAS-D-16-0220.1,
2017. a, b
Hogan, R. J. and Westbrook, C. D.: Equation for the Microwave Backscatter Cross
Section of Aggregate Snowflakes Using the Self-Similar
Rayleigh–Gans Approximation, J. Atmos.
Sci., 71, 3292–3301, https://doi.org/10.1175/jas-d-13-0347.1, 2014. a, b
Hogan, R. J., Tian, L., Brown, P. R., Westbrook, C. D., Heymsfield, A. J., and
Eastment, J. D.: Radar Scattering from Ice Aggregates Using the Horizontally
Aligned Oblate Spheroid Approximation, J. Appl. Meteorol.
Clim., 51, 655–671, https://doi.org/10.1175/JAMC-D-11-074.1, 2012. a
Hogan, R. J., Honeyager, R., Tyynelä, J., and Kneifel, S.: Calculating the
Millimetre-Wave Scattering Phase Function of Snowflakes Using the
Self-Similar Rayleigh–Gans Approximation, Q. J.
Roy. Meteor. Soc., 143, 834–844, https://doi.org/10.1002/qj.2968,
2017. a, b, c, d
Honeyager, R., Liu, G., and Nowell, H.: Voronoi Diagram-Based Spheroid Model
for Microwave Scattering of Complex Snow Aggregates, J. Quant.
Spectrosc. Ra., 170, 28–44,
https://doi.org/10.1016/j.jqsrt.2015.10.025, 2016. a
Hong, G.: Radar Backscattering Properties of Nonspherical Ice Crystals at 94 GHz, J. Geophys. Res.-Atmos., 112, D22203,
https://doi.org/10.1029/2007JD008839, 2007. a
Hong, G., Yang, P., Baum, B. A., Heymsfield, A. J., Weng, F., Liu, Q.,
Heygster, G., and Buehler, S. A.: Scattering Database in the Millimeter and
Submillimeter Wave Range of 100–1000 GHz for Nonspherical Ice Particles,
J. Geophys. Res.-Atmos., 114, D06201,
https://doi.org/10.1029/2008JD010451, 2009. a
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D.,
Kojima, M., Oki, R., Nakamura, K., and Iguchi, T.: The Global Precipitation
Measurement Mission, B. Am. Meteorol. Soc., 95, 701–722,
https://doi.org/10.1175/BAMS-D-13-00164.1, 2014. a
Illingworth, A. J., Barker, H. W., 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, B. Am.
Meteorol. Soc., 96, 1311–1332, https://doi.org/10.1175/BAMS-D-12-00227.1, 2015. a
Johnson, B. T., Petty, G. W., and Skofronick-Jackson, G.: Microwave
Properties of Ice-Phase Hydrometeors for Radar and Radiometers:
Sensitivity to Model Assumptions, J. Appl. Meteorol.
Clim., 51, 2152–2171, https://doi.org/10.1175/JAMC-D-11-0138.1, 2012. a
Kalesse, H., Szyrmer, W., Kneifel, S., Kollias, P., and Luke, E.: Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling, Atmos. Chem. Phys., 16, 2997–3012, https://doi.org/10.5194/acp-16-2997-2016, 2016. a, b
Kangas, V., D'Addio, S., Klein, U., Loiselet, M., Mason, G., Orlhac, J. C.,
Gonzalez, R., Bergada, M., Brandt, M., and Thomas, B.: Ice Cloud Imager
Instrument for MetOp Second Generation, in: 13th Specialist Meeting on
Microwave Radiometry and Remote Sensing of the Environment, MicroRad 2014
– Proceedings, 228–231, https://doi.org/10.1109/MicroRad.2014.6878946, 2014. a
Khvorostyanov, V. I. and Curry, J. A.: Terminal Velocities of Droplets and
Crystals: Power Laws with Continuous Parameters over the Size Spectrum,
J. Atmos. Sci., 59, 1872–1884,
https://doi.org/10.1175/1520-0469(2002)059<1872:TVODAC>2.0.CO;2, 2002. a
Kidder, S. Q., Goldberg, M. D., Zehr, R. M., DeMaria, M., Purdom, J. F.,
Velden, C. S., Grody, N. C., and Kusselson, S. J.: Satellite Analysis of
Tropical Cyclones Using the Advanced Microwave Sounding Unit (AMSU),
B. Am. Meteorol. Soc., 81, 1241–1259,
https://doi.org/10.1175/1520-0477(2000)081<1241:SAOTCU>2.3.CO;2, 2000. a
Kneifel, S., Löhnert, U., Battaglia, A., Crewell, S., and Siebler, D.: Snow
Scattering Signals in Ground-Based Passive Microwave Radiometer Measurements,
J. Geophys. Res.-Atmos., 115, D16214,
https://doi.org/10.1029/2010JD013856, 2010. a, b
Kneifel, S., Redl, S., Orlandi, E., Löhnert, U., Cadeddu, M. P., Turner,
D. D., and Chen, M. T.: Absorption Properties of Supercooled Liquid Water
between 31 and 225 GHz: Evaluation of Absorption Models Using
Ground-Based Observations, J. Appl. Meteorol. Clim.,
53, 1028–1045, https://doi.org/10.1175/JAMC-D-13-0214.1, 2014. a, b
Kneifel, S., von Lerber, A., Tiira, J., Moisseev, D., Kollias, P., and
Leinonen, J.: Observed Relations between Snowfall Microphysics and
Triple-Frequency Radar Measurements, J. Geophys. Res., 120,
6034–6055, https://doi.org/10.1002/2015JD023156, 2015. a
Kneifel, S., Kollias, P., Battaglia, A., Leinonen, J., Maahn, M., Kalesse, H.,
and Tridon, F.: First Observations of Triple-Frequency Radar Doppler
Spectra in Snowfall: Interpretation and Applications, Geophys.
Res. Lett., 43, 2225–2233, https://doi.org/10.1002/2015GL067618, 2016. a
Kneifel, S., Neto, J. D., Ori, D., Moisseev, D., Tyynelä, J., Adams, I. S.,
Kuo, K. S., Bennartz, R., Berne, A., Clothiaux, E. E., Eriksson, P., Geer,
A. J., Honeyager, R., Leinonen, J., and Westbrook, C. D.: Summer Snowfall
Workshop: Scattering Properties of Realistic Frozen Hydrometeors from
Simulations and Observations, as Well as Defining a New Standard for
Scattering Databases, B. Am. Meteorol. Soc., 99,
ES55–ES58, https://doi.org/10.1175/BAMS-D-17-0208.1, 2018. a, b, c
Kollias, P., Albrecht, B. A., and Marks Jr., F.: Why Mie?: Accurate
Observations of Vertical Air Velocities and Raindrops Using a Cloud Radar,
B. Am. Meteorol. Soc., 83, 1471–1483,
https://doi.org/10.1175/BAMS-83-10-1471, 2002. a
Kollias, P., Clothiaux, E. E., Miller, M. A., Albrecht, B. A., Stephens, G. L.,
and Ackerman, T. P.: Millimeter-Wavelength Radars: New Frontier in
Atmospheric Cloud and Precipitation Research, B. Am.
Meteorol. Soc., 88, 1608–1624, https://doi.org/10.1175/BAMS-88-10-1608, 2007. a
Kollias, P., Rémillard, J., Luke, E., and Szyrmer, W.: Cloud Radar
Doppler Spectra in Drizzling Stratiform Clouds: 1. Forward Modeling
and Remote Sensing Applications, J. Geophys. Res.-Atmos.,
116, D13201, https://doi.org/10.1029/2010JD015237, 2011. a
Kollias, P., Tanelli, S., Battaglia, A., and Tatarevic, A.: Evaluation of
EarthCARE Cloud Profiling Radar Doppler Velocity Measurements in Particle
Sedimentation Regimes, J. Atmos. Ocean. Tech., 31,
366–386, https://doi.org/10.1175/JTECH-D-11-00202.1, 2014. a
Küchler, N., Kneifel, S., Kollias, P., and Löhnert, U.: Revisiting
Liquid Water Content Retrievals in Warm Stratified Clouds: The Modified
Frisch, Geophys. Res. Lett., 45, 9323–9330,
https://doi.org/10.1029/2018GL079845, 2018. a, b, c
Kummerow, C., Barnes, W., Kozu, T., Shine, J., and Simpson, J.: The Tropical
Rainfall Measuring Mission (TRMM) Sensor Package, J. Atmos.
Ocean. Tech., 15, 808–816, 1998. a
L'Ecuyer, T. S. and Jiang, J. H.: Touring the Atmosphere Aboard the
A-Train, AIP Conference Proceedings, 1401, 245–256,
https://doi.org/10.1063/1.3653856, 2011. a
Leinonen, J., Kneifel, S., and Hogan, R. J.: Evaluation of the
Rayleigh–Gans Approximation for Microwave Scattering by
Rimed Snowflakes, Q. J. Roy. Meteor. Soc., 144,
77–88, https://doi.org/10.1002/qj.3093, 2018. a
Li, H. and Moisseev, D.: Melting Layer Attenuation at Ka- and W-Bands
as Derived from Multifrequency Radar Doppler Spectra Observations, J.
Geophys. Res.-Atmos., 124, 9520–9533,
https://doi.org/10.1029/2019JD030316, 2019. a
Liebe, H. J., Hufford, G. A., and Manabe, T.: A Model for the Complex
Permittivity of Water at Frequencies below 1 THz, Int. J.
Infrared Milli., 12, 659–675, https://doi.org/10.1007/BF01008897,
1991. a, b, c
Liebe, H. J., Hufford, G. A., and Cotton, M. G.: Propagation modeling of moist air and suspended water/ice particles at frequencies below 1000 GHz, Specialist Meeting of the Electromagnetic Wave Propagation Panel, Adv. Group for Aerosp. Res. and Dev., Palma de Mallorca, Spain, 1993. a, b, c, d, e, f, g
Liljegren, J. C., Boukabara, S. A., Cady-Pereira, K., and Clough, S. A.: The
Effect of the Half-Width of the 22-GHz Water Vapor Line on Retrievals of
Temperature and Water Vapor Profiles with a 12-Channel Microwave
Radiometer, IEEE T. Geosci. Remote S., 43,
1102–1108, https://doi.org/10.1109/TGRS.2004.839593, 2005. a
Liou, K.-N. N.: An Introduction to Atmospheric Radiation, Academic Press,
2002. a
Liu, A. Q., Moore, G. W. K., Tsuboki, K., and Renfrew, I. A.: The Effect of the
Sea-Ice Zone on the Development of Boundary-Layer Roll Clouds during Cold Air
Outbreaks, Bound.-Lay. Meteorol., 118, 557–581,
https://doi.org/10.1007/s10546-005-6434-4, 2006. a
Liu, G.: A Database of Microwave Single-Scattering Properties for Nonspherical
Ice Particles, B. Am. Meteorol. Soc., 89,
1563–1570, https://doi.org/10.1175/2008BAMS2486.1, 2008. a, b
Liu, Q., Weng, F., and English, S. J.: An Improved Fast Microwave Water
Emissivity Model, IEEE T. Geosci. Remote S., 49,
1238–1250, https://doi.org/10.1109/TGRS.2010.2064779, 2011. a
Löhnert, U., Schween, J. H., Acquistapace, C., Ebell, K., Maahn, M.,
Barrera-Verdejo, M., Hirsikko, A., Bohn, B., Knaps, A., O'Connor, E.,
Simmer, C., Wahner, A., and Crewell, S.: JOYCE: Jülich Observatory
for Cloud Evolution, B. Am. Meteorol. Soc., 96,
1157–1174, https://doi.org/10.1175/BAMS-D-14-00105.1, 2015. a, b
Maahn, M. and Kollias, P.: Improved Micro Rain Radar snow measurements using Doppler spectra post-processing, Atmos. Meas. Tech., 5, 2661–2673, https://doi.org/10.5194/amt-5-2661-2012, 2012. a
Maahn, M. and Löhnert, U.: Potential of Higher-Order Moments and Slopes of
the Radar Doppler Spectrum for Retrieving Microphysical and Kinematic
Properties of Arctic Ice Clouds, J. Appl. Meteorol.
Clim., 56, 263–282, https://doi.org/10.1175/JAMC-D-16-0020.1, 2017. a, b, c
Maahn, M., Löhnert, U., Kollias, P., Jackson, R. C., and McFarquhar, G. M.:
Developing and Evaluating Ice Cloud Parameterizations for Forward Modeling of
Radar Moments Using in Situ Aircraft Observations, J. Atmos.
Ocean. Tech., 32, 880–903, https://doi.org/10.1175/JTECH-D-14-00112.1, 2015. a
Maahn, M., de Boer, G., Creamean, J. M., Feingold, G., McFarquhar, G. M., Wu, W., and Mei, F.: The observed influence of local anthropogenic pollution on northern Alaskan cloud properties, Atmos. Chem. Phys., 17, 14709–14726, https://doi.org/10.5194/acp-17-14709-2017, 2017. a
Maahn, M., Hoffmann, F., Shupe, M. D., de Boer, G., Matrosov, S. Y., and Luke, E. P.: Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration?, Atmos. Meas. Tech., 12, 3151–3171, https://doi.org/10.5194/amt-12-3151-2019, 2019. a, b
Mason, S. L., Hogan, R. J., Westbrook, C. D., Kneifel, S., Moisseev, D., and von Terzi, L.: The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow, Atmos. Meas. Tech., 12, 4993–5018, https://doi.org/10.5194/amt-12-4993-2019, 2019. a
Mather, J. H. and Voyles, J. W.: The ARM Climate Research Facility: A
Review of Structure and Capabilities, B. Am. Meteorol.
Soc., 94, 377–392, https://doi.org/10.1175/BAMS-D-11-00218.1, 2013. a
Matrosov, S. Y.: Evaluations of the Spheroidal Particle Model for Describing
Cloud Radar Depolarization Ratios of Ice Hydrometeors, J. Atmos.
Ocean. Tech., 32, 865–879, https://doi.org/10.1175/JTECH-D-14-00115.1, 2015. a
Matrosov, S. Y. and Battaglia, A.: Influence of Multiple Scattering on
CloudSat Measurements in Snow: A Model Study, Geophys. Res.
Lett., 36, L12806, https://doi.org/10.1029/2009GL038704, 2009. a
Matsui, T., Iguchi, T., Li, X., Han, M., Tao, W.-K., Petersen, W., L'Ecuyer,
T., Meneghini, R., Olson, W., Kummerow, C. D., Hou, A. Y., Schwaller, M. R.,
Stocker, E. F., and Kwiatkowski, J.: GPM Satellite Simulator over Ground
Validation Sites, B. Am. Meteorol. Soc., 94,
1653–1660, https://doi.org/10.1175/bams-d-12-00160.1, 2013. a, b
Matsui, T., Dolan, B., Rutledge, S. A., Tao, W.-K. K., Iguchi, T., Barnum, J.,
and Lang, S. E.: POLARRIS: A POLArimetric Radar Retrieval and
Instrument Simulator, J. Geophys. Res.-Atmos., 124,
4634–4657, https://doi.org/10.1029/2018JD028317, 2019. a
Mattioli, V., Accadia, C., Prigent, C., Crewell, S., Geer, A., Eriksson, P.,
Fox, S., Pardo, J. R., Mlawer, E. J., Cadeddu, M., Bremer, M., De Breuck, C.,
Smette, A., Cimini, D., Turner, E., Mech, M., Marzano, F. S., Brunel, P.,
Vidot, J., Bennartz, R., Wehr, T., Di Michele, S., and John, V. O.:
Atmospheric Gas Absorption Knowledge in the Submillimeter: Modeling,
Field Measurements, and Uncertainty Quantification, B. Am.
Meteorol. Soc., 100, ES291–ES295, https://doi.org/10.1175/BAMS-D-19-0074.1,
2019. a
Mätzler, C.: Thermal Microwave Radiation: Applications for Remote
Sensing, IET Digital Library, https://doi.org/10.1049/PBEW052E, 2006. a, b
Mech, M., Orlandi, E., Crewell, S., Ament, F., Hirsch, L., Hagen, M., Peters, G., and Stevens, B.: HAMP – the microwave package on the High Altitude and LOng range research aircraft (HALO), Atmos. Meas. Tech., 7, 4539–4553, https://doi.org/10.5194/amt-7-4539-2014, 2014. a
Mech, M., Kliesch, L.-L., Anhäuser, A., Rose, T., Kollias, P., and Crewell, S.: Microwave Radar/radiometer for Arctic Clouds (MiRAC): first insights from the ACLOUD campaign, Atmos. Meas. Tech., 12, 5019–5037, https://doi.org/10.5194/amt-12-5019-2019, 2019a. a
Mech, M., Maahn, M., Ori, D., and Orlandi, E.: PAMTRA: Passive and
Active Microwave TRAnsfer Tool v1.0, Zenodo,
https://doi.org/10.5281/ZENODO.3582992, 2019b. a
Mech, M., Maahn, M., Ori, D., Kneifel, S., and Orlandi, E.: PAMTRA Package – Passive and Active Microwave TRANsfer, available at: https://github.com/igmk/pamtra (last access: 6 September 2020), 2019c. a
Meunier, V., Löhnert, U., Kollias, P., and Crewell, S.: Biases caused by the instrument bandwidth and beam width on simulated brightness temperature measurements from scanning microwave radiometers, Atmos. Meas. Tech., 6, 1171–1187, https://doi.org/10.5194/amt-6-1171-2013, 2013. a
Mie, G.: Beiträge Zur Optik Trüber Medien, Speziell Kolloidaler
Metallösungen, Ann. Phys., 330, 377–445,
https://doi.org/10.1002/andp.19083300302, 1908. a, b
Mishchenko, M. I. and Travis, L. D.: T-Matrix Computations of Light Scattering
by Large Spheroidal Particles, Opt. Commun., 109, 16–21,
https://doi.org/10.1016/0030-4018(94)90731-5, 1994. a
Morrison, H. and Milbrandt, J. A.: Parameterization of Cloud Microphysics Based
on the Prediction of Bulk Ice Particle Properties. Part I: Scheme
Description and Idealized Tests, J. Atmos. Sci., 72,
287–311, https://doi.org/10.1175/JAS-D-14-0065.1, 2015. a, b, c
Oue, M., Tatarevic, A., Kollias, P., Wang, D., Yu, K., and Vogelmann, A. M.: The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory, Geosci. Model Dev., 13, 1975–1998, https://doi.org/10.5194/gmd-13-1975-2020, 2020. a, b
Petty, G. W.: Physical and Microwave Radiative Properties of Precipitating
Clouds. Part II: A Parametric 1D Rain-Cloud Model for Use in
Microwave Radiative Transfer Simulations, J. Appl. Meteorol., 40,
2115–2129, https://doi.org/10.1175/1520-0450(2001)040<2115:PAMRPO>2.0.CO;2, 2001. a, b
Petty, G. W. and Huang, W.: Microwave Backscatter and Extinction by Soft Ice
Spheres and Complex Snow Aggregates, J. Atmos. Sci., 67,
769–787, https://doi.org/10.1175/2009jas3146.1, 2009. a
Petty, G. W. and Huang, W.: The Modified Gamma Size Distribution Applied to
Inhomogeneous and Nonspherical Particles: Key Relationships and
Conversions, J. Atmos. Sci., 68, 1460–1473,
https://doi.org/10.1175/2011JAS3645.1, 2011. a
Phillips, V. T. J., DeMott, P. J., and Andronache, C.: An Empirical
Parameterization of Heterogeneous Ice Nucleation for Multiple Chemical
Species of Aerosol, J. Atmos. Sci., 65, 2757–2783,
https://doi.org/10.1175/2007JAS2546.1, 2008. a
Prigent, C., Aires, F., Wang, D., Fox, S., and Harlow, C.: Sea-Surface
Emissivity Parametrization from Microwaves to Millimetre Waves, Q.
J. Roy. Meteor. Soc., 143, 596–605,
https://doi.org/10.1002/qj.2953, 2017. a
Purcell, E. M. and Pennypacker, C. R.: Scattering and Absorption of Light by
Nonspherical Dielectric Grains, Astrophys. J., 186, 705–714,
https://doi.org/10.1086/152538, 1973. a
Ray, P. S.: Broadband Complex Refractive Indices of Ice and Water, Appl.
Optics, 11, 1836, https://doi.org/10.1364/ao.11.001836, 1972. a
Rose, T., Crewell, S., Löhnert, U., and Simmer, C.: A Network Suitable
Microwave Radiometer for Operational Monitoring of the Cloudy Atmosphere,
Atmos. Res., 75, 183–200, https://doi.org/10.1016/j.atmosres.2004.12.005,
2005. a
Rosenkranz, P. W.: Water Vapor Microwave Continuum Absorption: A Comparison
of Measurements and Models, Radio Sci., 33, 919–928,
https://doi.org/10.1029/98RS01182, 1998. a
Rosenkranz, P. W.: A Model for the Complex Dielectric Constant of Supercooled
Liquid Water at Microwave Frequencies, IEEE T. Geosci.
Remote S., 53, 1387–1393, https://doi.org/10.1109/TGRS.2014.2339015, 2015. a, b, c
Ryan, B. F.: A Bulk Parameterization of the Ice Particle Size Distribution and
the Optical Properties in Ice Clouds, J. Atmos. Sci.,
57, 1436–1451, https://doi.org/10.1175/1520-0469(2000)057<1436:abpoti>2.0.co;2, 2002. a
Saunders, R., Matricardi, M., and Brunel, P.: An Improved Fast Radiative
Transfer Model for Assimilation of Satellite Radiance Observations, Q.
J. Roy. Meteor. Soc., 125, 1407–1425,
https://doi.org/10.1002/qj.1999.49712555615, 1999. a
Saunders, R., Hocking, J., Turner, E., Rayer, P., Rundle, D., Brunel, P., Vidot, J., Roquet, P., Matricardi, M., Geer, A., Bormann, N., and Lupu, C.: An update on the RTTOV fast radiative transfer model (currently at version 12), Geosci. Model Dev., 11, 2717–2737, https://doi.org/10.5194/gmd-11-2717-2018, 2018. a
Schäfler, A., Craig, G., Wernli, H., Arbogast, P., Doyle, J. D.,
Mctaggart-Cowan, R., Methven, J., Rivière, G., Ament, F., Boettcher,
M., Bramberger, M., Cazenave, Q., Cotton, R., Crewell, S., Delanoë, J.,
Dörnbrack, A., Ehrlich, A., Ewald, F., Fix, A., Grams, C. M., Gray,
S. L., Grob, H., Groß, S., Hagen, M., Harvey, B., Hirsch, L., Jacob, M.,
Kölling, T., Konow, H., Lemmerz, C., Lux, O., Magnusson, L., Mayer, B.,
Mech, M., Moore, R., Pelon, J., Quinting, J., Rahm, S., Rapp, M., Rautenhaus,
M., Reitebuch, O., Reynolds, C. A., Sodemann, H., Spengler, T., Vaughan, G.,
Wendisch, M., Wirth, M., Witschas, B., Wolf, K., and Zinner, T.: The North
Atlantic Waveguide and Downstream Impact EXperiment, B.
Am. Meteorol. Soc., 99, 1607–1637,
https://doi.org/10.1175/BAMS-D-17-0003.1, 2018. a
Schemann, V. and Ebell, K.: Simulation of mixed-phase clouds with the ICON large-eddy model in the complex Arctic environment around Ny-Ålesund, Atmos. Chem. Phys., 20, 475–485, https://doi.org/10.5194/acp-20-475-2020, 2020. a, b
Schmid, B., Tomlinson, J. M., Hubbe, J. M., Comstock, J. M., Mei, F., Chand,
D., Pekour, M. S., Kluzek, C. D., Andrews, E., Biraud, S. C., and McFarquhar,
G. M.: The DOE ARM Aerial Facility, B. Am.
Meteorol. Soc., 95, 723–742, https://doi.org/10.1175/BAMS-D-13-00040.1, 2014. a
Schmid, B., Ellingson, R. G., and McFarquhar, G. M.: ARM Aircraft
Measurements, Meteor. Mon., 57, 10.1–10.13,
https://doi.org/10.1175/AMSMONOGRAPHS-D-15-0042.1, 2016. a
Schrom, R. S. and Kumjian, M. R.: Bulk-Density Representations of
Branched Planar Ice Crystals: Errors in the Polarimetric Radar
Variables, J. Appl. Meteorol. Clim., 57, 333–346,
https://doi.org/10.1175/JAMC-D-17-0114.1, 2017. a
Seifert, A. and Beheng, K. D.: A Two-Moment Cloud Microphysics Parameterization
for Mixed-Phase Clouds. Part 1: Model Description, Meteorol.
Atmos. Phys., 92, 45–66, https://doi.org/10.1007/s00703-005-0112-4, 2006. a, b, c
Sihvola, A. H. and Shivola, A.: Self-Consistency Aspects of Dielectric Mixing
Theories, IEEE T. Geosci. Remote S., 27, 403–415,
https://doi.org/10.1109/36.29560, 1989. a
Skofronick-Jackson, G. and Johnson, B. T.: Surface and Atmospheric
Contributions to Passive Microwave Brightness Temperatures for Falling Snow
Events, J. Geophys. Res.-Atmos., 116, D02213,
https://doi.org/10.1029/2010JD014438, 2011. a, b
Tridon, F., Battaglia, A., Chase, R. J., Turk, F. J., Leinonen, J., Kneifel,
S., Mroz, K., Finlon, J., Bansemer, A., Tanelli, S., Heymsfield, A. J., and
Nesbitt, S. W.: The Microphysics of Stratiform Precipitation during
OLYMPEX: Compatibility between Triple-Frequency Radar and
Airborne in Situ Observations, J. Geophys. Res.-Atmos., 124, 8764–8792,
https://doi.org/10.1029/2018jd029858, 2019. a
Turner, D. D., Cadeddu, M. P., Lohnert, U., Crewell, S., and Vogelmann, A. M.:
Modifications to the Water Vapor Continuum in the Microwave Suggested by
Ground-Based 150-GHz Observations, IEEE T. Geosci.
Remote S., 47, 3326–3337, https://doi.org/10.1109/TGRS.2009.2022262, 2009. a
Turner, D. D., Kneifel, S., and Cadeddu, M. P.: An Improved Liquid Water
Absorption Model at Microwave Frequencies for Supercooled Liquid Water
Clouds, J. Atmos. Ocean. Tech., 33, 33–44,
https://doi.org/10.1175/JTECH-D-15-0074.1, 2016. a, b, c
Turner, E., Rayer, P., and Saunders, R.: AMSUTRAN: A Microwave
Transmittance Code for Satellite Remote Sensing, J. Quant. Spectrosc. Ra., 227, 117–129,
https://doi.org/10.1016/j.jqsrt.2019.02.013, 2019. a, b
Tyynela, J., Leinonen, J., Moisseev, D., and Nousiainen, T.: Radar
Backscattering from Snowflakes: Comparison of Fractal, Aggregate, and
Soft Spheroid Models, J. Atmos. Ocean. Tech., 28,
1365–1372, https://doi.org/10.1175/JTECH-D-11-00004.1, 2011. a
Ulaby, F. T., Moore, R. K., and Fung, A. K.: Microwave Remote Sensing:
Active and Passive, Artech House, London, 1981. a
Wang, D., Prigent, C., Kilic, L., Fox, S., Harlow, C., Jimenez, C., Aires, F.,
Grassotti, C., and Karbou, F.: Surface Emissivity at Microwaves to Millimeter
Waves over Polar Regions: Parameterization and Evaluation with Aircraft
Experiments, J. Atmos. Ocean. Tech., 34, 1039–1059,
https://doi.org/10.1175/JTECH-D-16-0188.1, 2017. a
Wang, Z., French, J., Vali, G., Wechsler, P., Haimov, S., Rodi, A., Deng, M.,
Leon, D., Snider, J., Peng, L., and Pazmany, A. L.: Single Aircraft
Integration of Remote Sensing and in Situ Sampling for the Study of Cloud
Microphysics and Dynamics, B. Am. Meteorol. Soc.,
93, 653–668, https://doi.org/10.1175/BAMS-D-11-00044.1, 2012. a
Wendisch, M., Macke, A., Ehrlich, A., Lüpkes, C., Mech, M.,
Chechin, D., Dethloff, K., Velasco, C. B., Bozem, H., Brückner, M.,
Clemen, H. C., Crewell, S., Donth, T., Dupuy, R., Ebell, K., Egerer, U.,
Engelmann, R., Engler, C., Eppers, O., Gehrmann, M., Gong, X., Gottschalk,
M., Gourbeyre, C., Griesche, H., Hartmann, J., Hartmann, M., Heinold, B.,
Herber, A., Herrmann, H., Heygster, G., Hoor, P., Jafariserajehlou, S.,
Jäkel, E., Järvinen, E., Jourdan, O., Kästner, U., Kecorius, S.,
Knudsen, E. M., Köllner, F., Kretzschmar, J., Lelli, L., Leroy, D.,
Maturilli, M., Mei, L., Mertes, S., Mioche, G., Neuber, R., Nicolaus, M.,
Nomokonova, T., Notholt, J., Palm, M., Van Pinxteren, M., Quaas, J., Richter,
P., Ruiz-Donoso, E., Schäfer, M., Schmieder, K., Schnaiter, M.,
Schneider, J., Schwarzenböck, A., Seifert, P., Shupe, M. D., Siebert, H.,
Spreen, G., Stapf, J., Stratmann, F., Vogl, T., Welti, A., Wex, H.,
Wiedensohler, A., Zanatta, M., Zeppenfeld, and Sebastian: The Arctic
Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform Observations to
Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification,
B. Am. Meteorol. Soc., 100, 841–871,
https://doi.org/10.1175/BAMS-D-18-0072.1, 2019. a
Westbrook, C. D. and Sephton, E. K.: Using 3-D-Printed Analogues to
Investigate the Fall Speeds and Orientations of Complex Ice Particles,
Geophys. Res. Lett., 44, 7994–8001, https://doi.org/10.1002/2017GL074130,
2017. a
Williams, C. R., Maahn, M., Hardin, J. C., and de Boer, G.: Clutter mitigation, multiple peaks, and high-order spectral moments in 35 GHz vertically pointing radar velocity spectra, Atmos. Meas. Tech., 11, 4963–4980, https://doi.org/10.5194/amt-11-4963-2018, 2018. a
Wu, W. and McFarquhar, G. M.: On the Impacts of Different Definitions of
Maximum Dimension for Nonspherical Particles Recorded by 2D Imaging
Probes, J. Atmos. Ocean. Tech., 33, 1057–1072,
https://doi.org/10.1175/JTECH-D-15-0177.1, 2016.
a
Yang, J. and Min, Q.: A Passive and Active Microwave-Vector Radiative Transfer
(PAM-VRT) Model, J. Quant. Spectrosc. Ra., 165, 123–133, https://doi.org/10.1016/J.JQSRT.2015.06.028, 2015. a
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-Hydrostatic) Modelling Framework of DWD and
MPI-M: Description of the Non-Hydrostatic Dynamical Core,
Q. J. Roy. Meteor. Soc., 141, 563–579,
https://doi.org/10.1002/qj.2378, 2015. a
Zrnić, D. S.: Simulation of Weatherlike Doppler Spectra and Signals,
J. Appl. Meteorol., 14, 619–620,
https://doi.org/10.1175/1520-0450(1975)014<0619:SOWDSA>2.0.CO;2, 1975. a
Short summary
The Passive and Active Microwave TRAnsfer tool (PAMTRA) is a public domain software package written in Python and Fortran for the simulation of microwave remote sensing observations. PAMTRA models the interaction of radiation with gases, clouds, precipitation, and the surface using either in situ observations or model output as input parameters. The wide range of applications is demonstrated for passive (radiometer) and active (radar) instruments on ground, airborne, and satellite platforms.
The Passive and Active Microwave TRAnsfer tool (PAMTRA) is a public domain software package...