Articles | Volume 17, issue 5
https://doi.org/10.5194/amt-17-1475-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-17-1475-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Mar 2024
Research article |
| 11 Mar 2024
| 11 Mar 2024
Quantifying riming from airborne data during the HALO-(AC)3 campaign
Nina Maherndl
CORRESPONDING AUTHOR
Leipzig Institute of Meteorology (LIM), Leipzig University, Leipzig, Germany
Manuel Moser
Institute for Physics of the Atmosphere, Johannes Gutenberg University, Mainz, Germany
Institute for Physics of the Atmosphere, German Aerospace Center (DLR), Weßling, Germany
Johannes Lucke
Institute for Physics of the Atmosphere, German Aerospace Center (DLR), Weßling, Germany
Faculty of Aerospace Engineering, Delft University of Technology, Delft 2629, the Netherlands
Mario Mech
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Nils Risse
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Imke Schirmacher
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Maximilian Maahn
Leipzig Institute of Meteorology (LIM), Leipzig University, Leipzig, Germany
Related authors
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
Atmos. Chem. Phys., 25, 9787–9801, https://doi.org/10.5194/acp-25-9787-2025, https://doi.org/10.5194/acp-25-9787-2025, 2025
Short summary
Short summary
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 clouds, which we call isotropic cloud patterns. We show that lower wind speeds cause this transition. In addition, we look at the changes in the cloud coverage, the height of the clouds, the cloud particles, and the radiative properties.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Audrey Teisseire, Patric Seifert, Kevin Ohneiser, Maximilian Maahn, Robert Spirig, and Jan Henneberger
EGUsphere, https://doi.org/10.5194/egusphere-2025-3923, https://doi.org/10.5194/egusphere-2025-3923, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
This study evaluates the vertical distribution of particle shape (VDPS) method for identifying particle shapes and riming/aggregation using in-situ and multi-frequency radar data from the CLOUDLAB campaign. Despite non-Rayleigh scattering effects, results show that the VDPS method using a Ka-band scanning cloud radar in slanted depolarization ratio (SLDR) mode is effective for hydrometeor classification.
Nils Risse, Mario Mech, Catherine Prigent, Joshua Jeremias Müller, and Susanne Crewell
EGUsphere, https://doi.org/10.5194/egusphere-2025-3311, https://doi.org/10.5194/egusphere-2025-3311, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Clouds play a crucial role in the Arctic climate system, particularly cloud liquid water droplets. However, there is currently a measurement gap for cloud liquid water over sea ice. We present a method to estimate cloud liquid water over Arctic sea ice using airborne passive microwave observations from the HALO-(𝒜𝒞)3 campaign. Evaluation with other airborne sensors highlights both the limitations and potential of the retrieval. This approach is promising for future applications to satellites.
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
Atmos. Chem. Phys., 25, 9787–9801, https://doi.org/10.5194/acp-25-9787-2025, https://doi.org/10.5194/acp-25-9787-2025, 2025
Short summary
Short summary
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 clouds, which we call isotropic cloud patterns. We show that lower wind speeds cause this transition. In addition, we look at the changes in the cloud coverage, the height of the clouds, the cloud particles, and the radiative properties.
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).
Short summary
Short summary
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).
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Denghui Ji, Christoph Ritter, Xiaoyu Sun, Manuel Moser, Christiane Voigt, Mathias Palm, and Justus Notholt
EGUsphere, https://doi.org/10.5194/egusphere-2025-1932, https://doi.org/10.5194/egusphere-2025-1932, 2025
Short summary
Short summary
We discovered a process where large aerosols help small water droplets in Arctic clouds grow, even when conditions normally favor ice. Unlike the traditional view, this process may explain how liquid and ice can coexist in cold clouds. Based on theory and aircraft data, our findings provide new insight into the microphysics of mixed-phase clouds, which could improve understanding of how Arctic clouds affect climate.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Benjamin Kirbus, Imke Schirmacher, Marcus Klingebiel, Michael Schäfer, André Ehrlich, Nils Slättberg, Johannes Lucke, Manuel Moser, Hanno Müller, and Manfred Wendisch
Atmos. Chem. Phys., 24, 3883–3904, https://doi.org/10.5194/acp-24-3883-2024, https://doi.org/10.5194/acp-24-3883-2024, 2024
Short summary
Short summary
A research aircraft is used to track the changes in air temperature, moisture, and cloud properties for air that moves from cold Arctic sea ice onto warmer oceanic waters. The measurements are compared to two reanalysis models named ERA5 and CARRA. The biggest differences are found for air temperature over the sea ice and moisture over the ocean. CARRA data are more accurate than ERA5 because they better simulate the sea ice, the transition from sea ice to open ocean, and the forming clouds.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Elena De La Torre Castro, Tina Jurkat-Witschas, Armin Afchine, Volker Grewe, Valerian Hahn, Simon Kirschler, Martina Krämer, Johannes Lucke, Nicole Spelten, Heini Wernli, Martin Zöger, and Christiane Voigt
Atmos. Chem. Phys., 23, 13167–13189, https://doi.org/10.5194/acp-23-13167-2023, https://doi.org/10.5194/acp-23-13167-2023, 2023
Short summary
Short summary
In this study, we show the differences in the microphysical properties between high-latitude (HL) cirrus and mid-latitude (ML) cirrus over the Arctic, North Atlantic, and central Europe during summer. The in situ measurements are combined with backward trajectories to investigate the influence of the region on cloud formation. We show that HL cirrus are characterized by a lower concentration of larger ice crystals when compared to ML cirrus.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Valerian Hahn, Ralf Meerkötter, Christiane Voigt, Sonja Gisinger, Daniel Sauer, Valéry Catoire, Volker Dreiling, Hugh Coe, Cyrille Flamant, Stefan Kaufmann, Jonas Kleine, Peter Knippertz, Manuel Moser, Philip Rosenberg, Hans Schlager, Alfons Schwarzenboeck, and Jonathan Taylor
Atmos. Chem. Phys., 23, 8515–8530, https://doi.org/10.5194/acp-23-8515-2023, https://doi.org/10.5194/acp-23-8515-2023, 2023
Short summary
Short summary
During the DACCIWA campaign in West Africa, we found a 35 % increase in the cloud droplet concentration that formed in a polluted compared with a less polluted environment and a decrease of 17 % in effective droplet diameter. Radiative transfer simulations, based on the measured cloud properties, reveal that these low-level polluted clouds radiate only 2.6 % more energy back to space, compared with a less polluted cloud. The corresponding additional decrease in temperature is rather small.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
Short summary
Short summary
We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
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
Short summary
Short summary
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.
Johannes Lucke, Tina Jurkat-Witschas, Romy Heller, Valerian Hahn, Matthew Hamman, Wolfgang Breitfuss, Venkateshwar Reddy Bora, Manuel Moser, and Christiane Voigt
Atmos. Meas. Tech., 15, 7375–7394, https://doi.org/10.5194/amt-15-7375-2022, https://doi.org/10.5194/amt-15-7375-2022, 2022
Short summary
Short summary
Flight testing in icing conditions requires instruments that are able to accurately measure the liquid water content of supercooled large droplets (SLDs). This work finds that the 12 mm cone of the Nevzorov hot-wire probe has excellent collection properties for SLDs. We also derive a correction to compensate for the low collision efficiency of small droplets with the cone. The results provide a procedure to evaluate LWC measurements of the 12 mm cone during wind tunnel and airborne experiments.
Laura Tomsche, Andreas Marsing, Tina Jurkat-Witschas, Johannes Lucke, Stefan Kaufmann, Katharina Kaiser, Johannes Schneider, Monika Scheibe, Hans Schlager, Lenard Röder, Horst Fischer, Florian Obersteiner, Andreas Zahn, Martin Zöger, Jos Lelieveld, and Christiane Voigt
Atmos. Chem. Phys., 22, 15135–15151, https://doi.org/10.5194/acp-22-15135-2022, https://doi.org/10.5194/acp-22-15135-2022, 2022
Short summary
Short summary
The detection of sulfur compounds in the upper troposphere (UT) and lower stratosphere (LS) is a challenge. In-flight measurements of SO2 and sulfate aerosol were performed during the BLUESKY mission in spring 2020 under exceptional atmospheric conditions. Reduced sinks in the dry UTLS and lower but still significant air traffic influenced the enhanced SO2 in the UT, and aged volcanic plumes enhanced the LS sulfate aerosol impacting the atmospheric radiation budget and global climate.
Willi Schimmel, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert
Atmos. Meas. Tech., 15, 5343–5366, https://doi.org/10.5194/amt-15-5343-2022, https://doi.org/10.5194/amt-15-5343-2022, 2022
Short summary
Short summary
This study introduces the novel Doppler radar spectra-based machine learning approach VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn). VOODOO is a powerful probability-based extension to the existing Cloudnet hydrometeor target classification, enabling the detection of liquid-bearing cloud layers beyond complete lidar attenuation via user-defined p* threshold. VOODOO performs best for (multi-layer) stratiform and deep mixed-phase clouds with liquid water path > 100 g m−2.
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
Short summary
Short summary
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.
Mireia Papke Chica, Valerian Hahn, Tiziana Braeuer, Elena de la Torre Castro, Florian Ewald, Mathias Gergely, Simon Kirschler, Luca Bugliaro Goggia, Stefanie Knobloch, Martina Kraemer, Johannes Lucke, Johanna Mayer, Raphael Maerkl, Manuel Moser, Laura Tomsche, Tina Jurkat-Witschas, Martin Zoeger, Christian von Savigny, and Christiane Voigt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-255, https://doi.org/10.5194/acp-2022-255, 2022
Preprint withdrawn
Short summary
Short summary
The mixed-phase temperature regime in convective clouds challenges our understanding of microphysical and radiative cloud properties. We provide a rare and unique dataset of aircraft in situ measurements in a strong mid-latitude convective system. We find that mechanisms initiating ice nucleation and growth strongly depend on temperature, relative humidity, and vertical velocity and variate within the measured system, resulting in altitude dependent changes of the cloud liquid and ice fraction.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
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
Short summary
Short summary
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.
Claudia Christine Stephan, Sabrina Schnitt, Hauke Schulz, Hugo Bellenger, Simon P. de Szoeke, Claudia Acquistapace, Katharina Baier, Thibaut Dauhut, Rémi Laxenaire, Yanmichel Morfa-Avalos, Renaud Person, Estefanía Quiñones Meléndez, Gholamhossein Bagheri, Tobias Böck, Alton Daley, Johannes Güttler, Kevin C. Helfer, Sebastian A. Los, Almuth Neuberger, Johannes Röttenbacher, Andreas Raeke, Maximilian Ringel, Markus Ritschel, Pauline Sadoulet, Imke Schirmacher, M. Katharina Stolla, Ethan Wright, Benjamin Charpentier, Alexis Doerenbecher, Richard Wilson, Friedhelm Jansen, Stefan Kinne, Gilles Reverdin, Sabrina Speich, Sandrine Bony, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 491–514, https://doi.org/10.5194/essd-13-491-2021, https://doi.org/10.5194/essd-13-491-2021, 2021
Short summary
Short summary
The EUREC4A field campaign took place in the western tropical Atlantic during January and February 2020. A total of 811 radiosondes, launched regularly (usually 4-hourly) from Barbados, and 4 ships measured wind, temperature, and relative humidity. They sampled atmospheric variability associated with different ocean surface conditions, synoptic variability, and mesoscale convective organization. The methods of data collection and post-processing for the radiosonde data are described here.
Cited articles
Avramov, A., Ackerman, A. S., Fridlind, A. M., van Diedenhoven, B., Botta, G., Aydin, K., Verlinde, J., Korolev, A. V., Strapp, J. W., McFarquhar, G. M., Jackson, R., Brooks, S. D., Glen, A., and Wolde, M.: Toward Ice Formation Closure in Arctic Mixed-Phase Boundary Layer Clouds during ISDAC, J. Geophys. Res.-Atmos., 116, D00T08, https://doi.org/10.1029/2011JD015910, 2011. a
Baumgardner, D., Brenguier, J. L., Bucholtz, A., Coe, H., DeMott, P., Garrett, T. J., Gayet, J. F., Hermann, M., Heymsfield, A., Korolev, A., Krämer, M., Petzold, A., Strapp, W., Pilewskie, P., Taylor, J., Twohy, C., Wendisch, M., Bachalo, W., and Chuang, P.: Airborne Instruments to Measure Atmospheric Aerosol Particles, Clouds and Radiation: A Cook's Tour of Mature and Emerging Technology, Atmos. Res., 102, 10–29, https://doi.org/10.1016/j.atmosres.2011.06.021, 2011. a, b
Blanke, A., Heymsfield, A. J., Moser, M., and Trömel, S.: Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data, Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, 2023. a
Chase, R. J., Finlon, J. A., Borque, P., McFarquhar, G. M., Nesbitt, S. W., Tanelli, S., Sy, O. O., Durden, S. L., and Poellot, M. R.: Evaluation of Triple-Frequency Radar Retrieval of Snowfall Properties Using Coincident Airborne In Situ Observations During OLYMPEX, Geophys. Res. Lett., 45, 5752–5760, https://doi.org/10.1029/2018GL077997, 2018. a
Crosier, J., Bower, K. N., Choularton, T. W., Westbrook, C. D., Connolly, P. J., Cui, Z. Q., Crawford, I. P., Capes, G. L., Coe, H., Dorsey, J. R., Williams, P. I., Illingworth, A. J., Gallagher, M. W., and Blyth, A. M.: Observations of ice multiplication in a weakly convective cell embedded in supercooled mid-level stratus, Atmos. Chem. Phys., 11, 257–273, https://doi.org/10.5194/acp-11-257-2011, 2011. a
Ehrlich, A., Wendisch, M., Lüpkes, C., Buschmann, M., Bozem, H., Chechin, D., Clemen, H.-C., Dupuy, R., Eppers, O., Hartmann, J., Herber, A., Jäkel, E., Järvinen, E., Jourdan, O., Kästner, U., Kliesch, L.-L., Köllner, F., Mech, M., Mertes, S., Neuber, R., Ruiz-Donoso, E., Schnaiter, M., Schneider, J., Stapf, J., and Zanatta, M.: A comprehensive in situ and remote sensing data set from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign, Earth Syst. Sci. Data, 11, 1853–1881, https://doi.org/10.5194/essd-11-1853-2019, 2019. a
Erfani, E. and Mitchell, D. L.: Growth of ice particle mass and projected area during riming, Atmos. Chem. Phys., 17, 1241–1257, https://doi.org/10.5194/acp-17-1241-2017, 2017. a
Field, P. R., Heymsfield, A. J., and Bansemer, A.: Shattering and Particle Interarrival Times Measured by Optical Array Probes in Ice Clouds, J. Atmos. Ocean. Tech., 23, 1357–1371, https://doi.org/10.1175/JTECH1922.1, 2006. a
Fitch, K. E. and Garrett, T. J.: Graupel Precipitating From Thin Arctic Clouds With Liquid Water Paths Less Than 50 g m−2, Geophys. Res. Lett., 49, e2021GL094075, https://doi.org/10.1029/2021GL094075, 2022. a, b, c
Garrett, T. J. and Yuter, S. E.: Observed Influence of Riming, Temperature, and Turbulence on the Fallspeed of Solid Precipitation, Geophys. Res. Lett., 41, 6515–6522, https://doi.org/10.1002/2014GL061016, 2014. a, b, c
Gergely, M., Cooper, S. J., and Garrett, T. J.: Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures, Atmos. Chem. Phys., 17, 12011–12030, https://doi.org/10.5194/acp-17-12011-2017, 2017. a
Gierens, R., Kneifel, S., Shupe, M. D., Ebell, K., Maturilli, M., and Löhnert, U.: Low-level mixed-phase clouds in a complex Arctic environment, Atmos. Chem. Phys., 20, 3459–3481, https://doi.org/10.5194/acp-20-3459-2020, 2020. a
Heymsfield, A. J.: A Comparative Study of the Rates of Development of Potential Graupel and Hail Embryos in High Plains Storms, J. Atmos. Sci., 39, 2867–2897, https://doi.org/10.1175/1520-0469(1982)039<2867:ACSOTR>2.0.CO;2, 1982. a
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
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
Intrieri, J. M. and Shupe, M. D.: Characteristics and Radiative Effects of Diamond Dust over the Western Arctic Ocean Region, J. Climate, 17, 2953–2960, https://doi.org/10.1175/1520-0442(2004)017<2953:CAREOD>2.0.CO;2, 2004. a
Kay, J. E. and L'Ecuyer, T.: Observational Constraints on Arctic Ocean Clouds and Radiative Fluxes during the Early 21st Century, J. Geophys. Res.-Atmos., 118, 7219–7236, https://doi.org/10.1002/jgrd.50489, 2013. a
Kneifel, S. and Moisseev, D.: Long-Term Statistics of Riming in Nonconvective Clouds Derived from Ground-Based Doppler Cloud Radar Observations, J. Atmos. Sci., 77, 3495–3508, https://doi.org/10.1175/JAS-D-20-0007.1, 2020. a
Korolev, A., McFarquhar, G., Field, P. R., Franklin, C., Lawson, P., Wang, Z., Williams, E., Abel, S. J., Axisa, D., Borrmann, S., Crosier, J., Fugal, J., Krämer, M., Lohmann, U., Schlenczek, O., Schnaiter, M., and Wendisch, M.: Mixed-Phase Clouds: Progress and Challenges, Meteor. Mon., 58, 5.1–5.50, https://doi.org/10.1175/AMSMONOGRAPHS-D-17-0001.1, 2017. a
Korolev, A. V., Strapp, J. W., Isaac, G. A., and Nevzorov, A. N.: The Nevzorov Airborne Hot-Wire LWC–TWC Probe: Principle of Operation and Performance Characteristics, J. Atmos. Ocean. Tech., 15, 1495–1510, https://doi.org/10.1175/1520-0426(1998)015<1495:TNAHWL>2.0.CO;2, 1998. a
Lance, S., Brock, C. A., Rogers, D., and Gordon, J. A.: Water droplet calibration of the Cloud Droplet Probe (CDP) and in-flight performance in liquid, ice and mixed-phase clouds during ARCPAC, Atmos. Meas. Tech., 3, 1683–1706, https://doi.org/10.5194/amt-3-1683-2010, 2010. a
Leinonen, J. and Moisseev, D.: What Do Triple-Frequency Radar Signatures Reveal about Aggregate Snowflakes?, J. Geophys. Res.-Atmos., 120, 229–239, https://doi.org/10.1002/2014JD022072, 2015. a
Leinonen, J. and Szyrmer, W.: Radar Signatures of Snowflake Riming: A Modeling Study, Earth Space Sci., 2, 346–358, https://doi.org/10.1002/2015EA000102, 2015. a
Leinonen, J., Moisseev, D., and Nousiainen, T.: Linking Snowflake Microstructure to Multi-Frequency Radar Observations, J. Geophys. Res.-Atmos., 118, 3259–3270, https://doi.org/10.1002/jgrd.50163, 2013. a
Lucke, J., Jurkat-Witschas, T., Heller, R., Hahn, V., Hamman, M., Breitfuss, W., Bora, V. R., Moser, M., and Voigt, C.: Icing wind tunnel measurements of supercooled large droplets using the 12 mm total water content cone of the Nevzorov probe, Atmos. Meas. Tech., 15, 7375–7394, https://doi.org/10.5194/amt-15-7375-2022, 2022. a, b
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., Turner, D. D., Löhnert, U., Posselt, D. J., Ebell, K., Mace, G. G., and Comstock, J. M.: Optimal Estimation Retrievals and Their Uncertainties: What Every Atmospheric Scientist Should Know, B. Am. Meteorol. Soc., 101, E1512–E1523, https://doi.org/10.1175/BAMS-D-19-0027.1, 2020. a, b
Maherndl, N., Maahn, M., Tridon, F., Leinonen, J., Ori, D., and Kneifel, S.: A riming-dependent parameterization of scattering by snowflakes using the self-similar Rayleigh–Gans Approximation, Q. J. Roy. Meteor. Soc., 149, 3562–3581, https://doi.org/10.1002/qj.4573, 2023a. a, b, c, d, e, f, g, h, i, j, k, l
Maherndl, N., Maahn, M., Tridon, F., Leinonen, J., Ori, D., and Kneifel, S.: Data set of simulated rimed aggregates for “A riming-dependent parameterization of scattering by snowflakes using the self-similar Rayleigh-Gans approximation”, Zenodo [data set], https://doi.org/10.5281/zenodo.7757034, 2023b.
Mason, S. L., Chiu, C. J., Hogan, R. J., Moisseev, D., and Kneifel, S.: Retrievals of Riming and Snow Density From Vertically Pointing Doppler Radars, J. Geophys. Res.-Atmos., 123, 13807–13834, https://doi.org/10.1029/2018JD028603, 2018. a
McFarquhar, G. M., Zhang, G., Poellot, M. R., Kok, G. L., McCoy, R., Tooman, T., Fridlind, A., and Heymsfield, A. J.: Ice Properties of Single-Layer Stratocumulus during the Mixed-Phase Arctic Cloud Experiment: 1. Observations, J. Geophys. Res.-Atmos., 112, D24201, https://doi.org/10.1029/2007JD008633, 2007. 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, 2019. a, b, c, d
Mech, M., Maahn, M., Kneifel, S., Ori, D., Orlandi, E., Kollias, P., Schemann, V., and Crewell, S.: PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere, Geosci. Model Dev., 13, 4229–4251, https://doi.org/10.5194/gmd-13-4229-2020, 2020. a, b
Mech, M., Ehrlich, A., Herber, A., Lüpkes, C., Wendisch, M., Becker, S., Boose, Y., Chechin, D., Crewell, S., Dupuy, R., Gourbeyre, C., Hartmann, J., Jäkel, E., Jourdan, O., Kliesch, L.-L., Klingebiel, M., Kulla, B. S., Mioche, G., Moser, M., Risse, N., Ruiz-Donoso, E., Schäfer, M., Stapf, J., and Voigt, C.: MOSAiC-ACA and AFLUX - Arctic Airborne Campaigns Characterizing the Exit Area of MOSAiC, Scientific Data, 9, 790, https://doi.org/10.1038/s41597-022-01900-7, 2022a. a, b, c
Mech, M., Risse, N., Marrollo, G., and Paul, D.: ac3airborne, Zenodo [data set], https://doi.org/10.5281/zenodo.7305586, 2022b.
Mech, M., Risse, N., Krobot, P., Paul, D., Schirmacher, I., Schnitt, S., and Crewell, S.: Radar reflectivities at 94 GHz and microwave brightness temperature measurements at 89 GHz during the HALO-AC3 Arctic airborne campaign, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.964977, 2024a. a
Mech, M., Risse, N., Ritter, C., Schirmacher, I., and Schween, J. H.: Cloud mask and cloud top altitude from the AMALi airborne lidar on Polar 5 during HALO-AC3 in spring 2022, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.964985, 2024b. 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
Mitchell, D. L.: Use of Mass- and Area-Dimensional Power Laws for Determining Precipitation Particle Terminal Velocities, J. Atmos. Sci., 53, 1710–1723, https://doi.org/10.1175/1520-0469(1996)053<1710:UOMAAD>2.0.CO;2, 1996. a
Moisseev, D., von Lerber, A., and Tiira, J.: Quantifying the Effect of Riming on Snowfall Using Ground-Based Observations, J. Geophys. Res.-Atmos., 122, 4019–4037, https://doi.org/10.1002/2016JD026272, 2017. a
Morrison, H., de Boer, G., Feingold, G., Harrington, J., Shupe, M. D., and Sulia, K.: Resilience of Persistent Arctic Mixed-Phase Clouds, Nat. Geosci., 5, 11–17, https://doi.org/10.1038/ngeo1332, 2012. a
Morrison, H., van Lier-Walqui, M., Fridlind, A. M., Grabowski, W. W., Harrington, J. Y., Hoose, C., Korolev, A., Kumjian, M. R., Milbrandt, J. A., Pawlowska, H., Posselt, D. J., Prat, O. P., Reimel, K. J., Shima, S.-I., van Diedenhoven, B., and Xue, L.: Confronting the Challenge of Modeling Cloud and Precipitation Microphysics, J. Adv. Model. Earth Syst., 12, e2019MS001689, https://doi.org/10.1029/2019MS001689, 2020. a
Moser, M. and Voigt, C.: DLR in-situ cloud measurements during AFLUX Arctic airborne campaign, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.940564, 2022. a
Moser, M., Voigt, C., and Hahn, V.: DLR in-situ cloud measurements during MOSAiC-ACA Arctic airborne campaign, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.940557, 2022. a
Moser, M., Lucke, J., De La Torre Castro, E., Mayer, J., and Voigt, C.: DLR in situ cloud measurements during HALO-(AC)3 Arctic airborne campaign, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.963247, 2023a. a
Moser, M., Voigt, C., Jurkat-Witschas, T., Hahn, V., Mioche, G., Jourdan, O., Dupuy, R., Gourbeyre, C., Schwarzenboeck, A., Lucke, J., Boose, Y., Mech, M., Borrmann, S., Ehrlich, A., Herber, A., Lüpkes, C., and Wendisch, M.: Microphysical and thermodynamic phase analyses of Arctic low-level clouds measured above the sea ice and the open ocean in spring and summer, Atmos. Chem. Phys., 23, 7257–7280, https://doi.org/10.5194/acp-23-7257-2023, 2023b. a, b
Mosimann, L.: An Improved Method for Determining the Degree of Snow Crystal Riming by Vertical Doppler Radar, Atmos. Res., 37, 305–323, https://doi.org/10.1016/0169-8095(94)00050-N, 1995. a
Mosimann, L., Weingartner, E., and Waldvogel, A.: An Analysis of Accreted Drop Sizes and Mass on Rimed Snow Crystals, J. Atmos. Sci., 51, 1548–1558, https://doi.org/10.1175/1520-0469(1994)051<1548:AAOADS>2.0.CO;2, 1994. a
Müller, G., Brümmer, B., and Alpers, W.: Roll Convection within an Arctic Cold-Air Outbreak: Interpretation of In Situ Aircraft Measurements and Spaceborne SAR Imagery by a Three-Dimensional Atmospheric Model, Mon. Weather Rev., 127, 363–380, https://doi.org/10.1175/1520-0493(1999)127<0363:RCWAAC>2.0.CO;2, 1999. a
NASA Worldview: MODIS Terra, NASA Worldview, https://worldview.earthdata.nasa.gov, last access: 23 January 2024. a
Nguyen, C. M., Wolde, M., Battaglia, A., Nichman, L., Bliankinshtein, N., Haimov, S., Bala, K., and Schuettemeyer, D.: Coincident in situ and triple-frequency radar airborne observations in the Arctic, Atmos. Meas. Tech., 15, 775–795, https://doi.org/10.5194/amt-15-775-2022, 2022. a, b, c
Ori, D., von Terzi, L., Karrer, M., and Kneifel, S.: snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation, Geosci. Model Dev., 14, 1511–1531, https://doi.org/10.5194/gmd-14-1511-2021, 2021. a
Oue, M., Galletti, M., Verlinde, J., Ryzhkov, A., and Lu, Y.: Use of X-Band Differential Reflectivity Measurements to Study Shallow Arctic Mixed-Phase Clouds, J. Appl. Meteorol. Clim., 55, 403–424, https://doi.org/10.1175/JAMC-D-15-0168.1, 2016. a
Praz, C., Roulet, Y.-A., and Berne, A.: Solid hydrometeor classification and riming degree estimation from pictures collected with a Multi-Angle Snowflake Camera, Atmos. Meas. Tech., 10, 1335–1357, https://doi.org/10.5194/amt-10-1335-2017, 2017. a
Rantanen, M., Karpechko, A. Y., Lipponen, A., Nordling, K., Hyvärinen, O., Ruosteenoja, K., Vihma, T., and Laaksonen, A.: The Arctic Has Warmed Nearly Four Times Faster than the Globe since 1979, Communications Earth & Environment, 3, 1–10, https://doi.org/10.1038/s43247-022-00498-3, 2022. a
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding: Theory and Practice, World Scientific, https://doi.org/10.1142/3171, 2000. a, b
Rosenkranz, P. W.: Water vapor microwave continuum absorption: A comparison of measurements and models, Radio Sci., 33, 919–928, 1998.
Ruiz-Donoso, E., Ehrlich, A., Schäfer, M., Jäkel, E., Schemann, V., Crewell, S., Mech, M., Kulla, B. S., Kliesch, L.-L., Neuber, R., and Wendisch, M.: Small-scale structure of thermodynamic phase in Arctic mixed-phase clouds observed by airborne remote sensing during a cold air outbreak and a warm air advection event, Atmos. Chem. Phys., 20, 5487–5511, https://doi.org/10.5194/acp-20-5487-2020, 2020. a
Seifert, A., Leinonen, J., Siewert, C., and Kneifel, S.: The Geometry of Rimed Aggregate Snowflakes: A Modeling Study, J. Adv. Model. Earth Syst., 11, 712–731, https://doi.org/10.1029/2018MS001519, 2019. a, b, c
Shupe, M. D.: Clouds at Arctic Atmospheric Observatories. Part II: Thermodynamic Phase Characteristics, J. Appl. Meteorol. Clim., 50, 645–661, https://doi.org/10.1175/2010JAMC2468.1, 2011. a
Shupe, M. D. and Intrieri, J. M.: Cloud Radiative Forcing of the Arctic Surface: The Influence of Cloud Properties, Surface Albedo, and Solar Zenith Angle, J. Climate, 17, 616–628, https://doi.org/10.1175/1520-0442(2004)017<0616:CRFOTA>2.0.CO;2, 2004. a
Shupe, M. D., Matrosov, S. Y., and Uttal, T.: Arctic Mixed-Phase Cloud Properties Derived from Surface-Based Sensors at SHEBA, J. Atmos. Sci., 63, 697–711, https://doi.org/10.1175/JAS3659.1, 2006. a
Stachlewska, I. S., Neuber, R., Lampert, A., Ritter, C., and Wehrle, G.: AMALi – the Airborne Mobile Aerosol Lidar for Arctic research, Atmos. Chem. Phys., 10, 2947–2963, https://doi.org/10.5194/acp-10-2947-2010, 2010. a
Takahashi, T.: Influence of Liquid Water Content and Temperature on the Form and Growth of Branched Planar Snow Crystals in a Cloud, J. Atmos. Sci., 71, 4127–4142, https://doi.org/10.1175/JAS-D-14-0043.1, 2014. a, b
Takahashi, T., Endoh, T., Wakahama, G., and Fukuta, N.: Vapor Diffusional Growth of Free-Falling Snow Crystals between −3 and −23 °C, J. Meteorol. Soc. Jpn. Ser. II, 69, 15–30, https://doi.org/10.2151/jmsj1965.69.1_15, 1991. a, b
Tian, J., Dong, X., Xi, B., Wang, J., Homeyer, C. R., McFarquhar, G. M., and Fan, J.: Retrievals of ice cloud microphysical properties of deep convective systems using radar measurements, J. Geophys. Res.-Atmos., 121, 10820–10839, https://doi.org/10.1002/2015jd024686, 2016. a
Trömel, S., Simmer, C., Blahak, U., Blanke, A., Doktorowski, S., Ewald, F., Frech, M., Gergely, M., Hagen, M., Janjic, T., Kalesse-Los, H., Kneifel, S., Knote, C., Mendrok, J., Moser, M., Köcher, G., Mühlbauer, K., Myagkov, A., Pejcic, V., Seifert, P., Shrestha, P., Teisseire, A., von Terzi, L., Tetoni, E., Vogl, T., Voigt, C., Zeng, Y., Zinner, T., and Quaas, J.: Overview: Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes, Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, 2021. a
Vogl, T., Maahn, M., Kneifel, S., Schimmel, W., Moisseev, D., and Kalesse-Los, H.: Using artificial neural networks to predict riming from Doppler cloud radar observations, Atmos. Meas. Tech., 15, 365–381, https://doi.org/10.5194/amt-15-365-2022, 2022. a
Waitz, F., Schnaiter, M., Leisner, T., and Järvinen, E.: In situ observation of riming in mixed-phase clouds using the PHIPS probe, Atmos. Chem. Phys., 22, 7087–7103, https://doi.org/10.5194/acp-22-7087-2022, 2022. a, b, c
Walbröl, A., Michaelis, J., Becker, S., Dorff, H., Gorodetskaya, I., Kirbus, B., Lauer, M., Maherndl, N., Maturilli, M., Mayer, J., Müller, H., Neggers, R. A. J., Paulus, F. M., Röttenbacher, J., Rückert, J. E., Schirmacher, I., Slättberg, N., Ehrlich, A., Wendisch, M., and Crewell, S.: Environmental conditions in the North Atlantic sector of the Arctic during the HALO–(AC)3 campaign, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-668, 2023. a, b
Wendisch, M., Keil, A., and Korolev, A. V.: FSSP Characterization with Monodisperse Water Droplets, J. Atmos. Ocean. Tech., 13, 1152–1165, https://doi.org/10.1175/1520-0426(1996)013<1152:FCWMWD>2.0.CO;2, 1996. 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., and Zeppenfeld, S.: 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
Wendisch, M., Brückner, M., Crewell, S., Ehrlich, A., Notholt, J., Lüpkes, C., Macke, A., Burrows, J. P., Rinke, A., Quaas, J., Maturilli, M., Schemann, V., Shupe, M. D., Akansu, E. F., Barrientos-Velasco, C., Bärfuss, K., Blechschmidt, A.-M., Block, K., Bougoudis, I., Bozem, H., Böckmann, C., Bracher, A., Bresson, H., Bretschneider, L., Buschmann, M., Chechin, D. G., Chylik, J., Dahlke, S., Deneke, H., Dethloff, K., Donth, T., Dorn, W., Dupuy, R., Ebell, K., Egerer, U., Engelmann, R., Eppers, O., Gerdes, R., Gierens, R., Gorodetskaya, I. V., Gottschalk, M., Griesche, H., Gryanik, V. M., Handorf, D., Harm-Altstädter, B., Hartmann, J., Hartmann, M., Heinold, B., Herber, A., Herrmann, H., Heygster, G., Höschel, I., Hofmann, Z., Hölemann, J., Hünerbein, A., Jafariserajehlou, S., Jäkel, E., Jacobi, C., Janout, M., Jansen, F., Jourdan, O., Jurányi, Z., Kalesse-Los, H., Kanzow, T., Käthner, R., Kliesch, L. L., Klingebiel, M., Knudsen, E. M., Kovács, T., Körtke, W., Krampe, D., Kretzschmar, J., Kreyling, D., Kulla, B., Kunkel, D., Lampert, A., Lauer, M., Lelli, L., von Lerber, A., Linke, O., Löhnert, U., Lonardi, M., Losa, S. N., Losch, M., Maahn, M., Mech, M., Mei, L., Mertes, S., Metzner, E., Mewes, D., Michaelis, J., Mioche, G., Moser, M., Nakoudi, K., Neggers, R., Neuber, R., Nomokonova, T., Oelker, J., Papakonstantinou-Presvelou, I., Pätzold, F., Pefanis, V., Pohl, C., van Pinxteren, M., Radovan, A., Rhein, M., Rex, M., Richter, A., Risse, N., Ritter, C., Rostosky, P., Rozanov, V. V., Donoso, E. R., Garfias, P. S., Salzmann, M., Schacht, J., Schäfer, M., Schneider, J., Schnierstein, N., Seifert, P., Seo, S., Siebert, H., Soppa, M. A., Spreen, G., Stachlewska, I. S., Stapf, J., Stratmann, F., Tegen, I., Viceto, C., Voigt, C., Vountas, M., Walbröl, A., Walter, M., Wehner, B., Wex, H., Willmes, S., Zanatta, M., and Zeppenfeld, S.: Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project, B. Am. Meteorol. Soc., 104, E208–E242, https://doi.org/10.1175/BAMS-D-21-0218.1, 2023. a
Wendisch M., Crewell S., Ehrlich, A., Herber, A., Kirbus, B., Lüpkes, C., Mech, M., Akansu, E. F., Ament, F., Aubry, C., Becker, S., Borrmann, S., Bozem, H., Marlen Brückner, M., Clemen, H., Dahlke, S., Dekoutsidis, G., Delanoë, J., De La Torre Castro, E., Dorff, H., Dupuy, R., Eppers, O., Ewald, F., George, G., Gorodetskaya, I. V., Grawe, S., Groß, S., Hartmann, J., Henning, S., Jäkel, E., Joppe, P., Jourdan, O., Jurányi, Z., Karalis, M., Kellermann, M., Klingebiel, M., Lonardi, M., Lucke, J., Maahn, M., Maherndl, N., Maturilli, M., Mayer, B., Mayer, J., Mertes, S., Michaelis, J., Michalkov, M., Mioche, G., Moser, M., Müller, H., Neggers, R., Ori, D., Paul, D., Paulus, F., Pilz, C., Pithan, F., Pörtge, V., Risse, N., Roberts, G. C., Rosenburg, S., Röttenbacher, J., Rückert, J., Schäfer, M., Schaefer, J., Schemann, V., Schirmacher, I., Schmidt, S., Schneider, J., Schnitt, S., Schwarz, A., Siebert, H., Sperzel, T., Spreen, G., Stevens, B., Stratmann, F., Svensson, G., Tatzelt, C., Tuch, T., Vihma, T., Voigt, C., Volkmer, L., Walbröl, A., Weber, A., Wehner, B., Wetzel, B., Wirth, M., and Zinner, T.: Quasi-Lagrangian observations of Arctic air mass transformations: Introduction and first results of the HALO–(AC)3 airborne campaign, in preparation, 2024. a, b
Wesche, C., Steinhage, D., and Nixdorf, U.: Polar Aircraft Polar5 and Polar6 Operated by the Alfred Wegener Institute, Journal of Large-Scale Research Facilities JLSRF, 2, A87–A87, https://doi.org/10.17815/jlsrf-2-153, 2016. a
Wolde, M., Korolev, A., Schüttemeyer, D., Baibakov, K., Barker, H., Bastian, M., Battaglia, A., Blanchet, J., Haimov, S., Heckman, I., Hudak, D., Mariani, Z., Michelson, D., Nguyen, C., Nichman, L., and Rodriguez, P.: Radar Snow Experiment for future precipitation mission (RadSnowExp), Living Planet Symposium, Milan, Italia, 13–17 May 2019. a
Yang, F., Ovchinnikov, M., and Shaw, R. A.: Minimalist Model of Ice Microphysics in Mixed-Phase Stratiform Clouds, Geophys. Res. Lett., 40, 3756–3760, https://doi.org/10.1002/grl.50700, 2013. a
Zuidema, P., Baker, B., Han, Y., Intrieri, J., Key, J., Lawson, P., Matrosov, S., Shupe, M., Stone, R., and Uttal, T.: An Arctic Springtime Mixed-Phase Cloudy Boundary Layer Observed during SHEBA, J. Atmos. Sci., 62, 160–176, https://doi.org/10.1175/JAS-3368.1, 2005. a
Short summary
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.
In some clouds, liquid water droplets can freeze onto ice crystals (riming). Riming leads to the...
Special issue