Articles | Volume 21, issue 22
https://doi.org/10.5194/acp-21-17133-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-17133-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2021
Research article |
| 25 Nov 2021
| 25 Nov 2021
Improving the representation of aggregation in a two-moment microphysical scheme with statistics of multi-frequency Doppler radar observations
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Axel Seifert
Deutscher Wetterdienst, Offenbach, Germany
Davide Ori
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Stefan Kneifel
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
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Leonie von Terzi, Axel Seifert, Christoph Siewert, Fabian Jakub, and Stefan Kneifel
EGUsphere, https://doi.org/10.5194/egusphere-2026-3865, https://doi.org/10.5194/egusphere-2026-3865, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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A distinct temperature layer in clouds promotes growth of dendritic ice crystals, producing characteristic radar signatures whose origin has remained unclear. We combined radar observations with microphysical simulations to identify the dominant microphysical processes. Collisions breaking particles into fragments prove essential to reproducing the signatures, alongside crystal growth and aggregation, clarifying the link between radar signals and ice processes for weather models.
Paul Ockenfuß, Gregor Köcher, Isabel Petit, and Stefan Kneifel
EGUsphere, https://doi.org/10.5194/egusphere-2026-3446, https://doi.org/10.5194/egusphere-2026-3446, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Remote sensing instruments often point vertically, producing time-height cross-sections of the atmosphere. In this case, each particle is observed only once. To learn about particle evolution, we need either assumptions about their distribution or scanning observations to "follow" them. In this work, we do both. To illustrate, we introduce new techniques to reveal the spatial distribution of rimed snowflakes, and we discuss the observed patterns and rimed particle evolution.
Lukas Pieper, Patric Seifert, Hannes Griesche, Albert Ansmann, George McCosh, Florian Ewald, and Stefan Kneifel
EGUsphere, https://doi.org/10.5194/egusphere-2026-3092, https://doi.org/10.5194/egusphere-2026-3092, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Using ground-based cloud Doppler radar observations and aerosol model data, a strong relationship between Saharan dust and enhanced turbulence in cirrus clouds over Europe was identified. Dust-infused cirrus formed mainly within moist, dust-laden air masses and showed strong correlation with in-cloud turbulence. The results provide a baseline observational overview on dust-turbulence-cirrus interactions, informing weather and climate models regarding possible methodological improvements.
Paul Ockenfuß, Gregor Köcher, Matthias Bauer-Pfundstein, and Stefan Kneifel
Atmos. Meas. Tech., 19, 2961–2984, https://doi.org/10.5194/amt-19-2961-2026, https://doi.org/10.5194/amt-19-2961-2026, 2026
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The pointing of scanning weather and cloud radars must be very accurate, to within 0.1°. We present a general method to calibrate the pointing of a scanning radar with an elevation and an azimuth axis. Using the Sun as a reference, we can determine the specific misalignments of the radar pedestal, axes and antenna. Once the misalignments are known, we can correct for them by steering the scanner motors accordingly. We provide recommendations and code to apply this method to any scanning radar.
Paul Ockenfuß, Michael Frech, Mathias Gergely, and Stefan Kneifel
Atmos. Meas. Tech., 19, 2125–2147, https://doi.org/10.5194/amt-19-2125-2026, https://doi.org/10.5194/amt-19-2125-2026, 2026
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The 17 operational German weather radars regularly point vertical for calibration. We proof that this data also contains valuable scientific information. To demonstrate this, we use it to detect the melting level in clouds and strong snowflake riming. Riming is the collision of a snowflake with liquid droplets, which can create precipitation. We analyze the frequency and temperature dependence of riming for all German weather radar sites and relate it to the local precipitation climatology.
Gholam Ali Hoshyaripour, Andreas Baer, Sascha Bierbauer, Julia Bruckert, Dominik Brunner, Jochen Förstner, Arash Hamzehloo, Valentin Hanft, Corina Keller, Martina Klose, Pankaj Kumar, Patrick Ludwig, Enrico Metzner, Lisa Muth, Andreas Pauling, Nikolas Porz, Maryam Ramezani Ziarani, Thomas Reddmann, Luca Reißig, Roland Ruhnke, Khompat Satitkovitchai, Axel Seifert, Miriam Sinnhuber, Michael Steiner, Stefan Versick, Heike Vogel, Michael Weimer, Sven Werchner, and Corinna Hoose
Geosci. Model Dev., 19, 1645–1681, https://doi.org/10.5194/gmd-19-1645-2026, https://doi.org/10.5194/gmd-19-1645-2026, 2026
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This paper presents recent advances in ICON-ART, a modeling system that simulates atmospheric composition – such as gases and particles – and their interactions with weather and climate. By integrating updated chemistry, emissions, and aerosol processes, ICON-ART enables detailed, scale-spanning simulations. It supports both scientific research and operational forecasts, contributing to improved air quality, weather and climate predictions.
Leonie von Terzi, Davide Ori, and Stefan Kneifel
Geosci. Model Dev., 19, 887–910, https://doi.org/10.5194/gmd-19-887-2026, https://doi.org/10.5194/gmd-19-887-2026, 2026
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We present a new database of radar-relevant optical properties for a wide range of ice particle shapes, computed using the Discrete Dipole Approximation (DDA) at 5.6, 9.6, 35.6, and 94 GHz. The database is designed to support habit-evolving microphysical schemes, which predict continuous changes in ice particle properties rather than the traditionally assumed fixed categories. It includes over 2600 individual crystals and 450 aggregates with varying riming degrees and morphology.
Ulrich Schumann and Axel Seifert
Atmos. Chem. Phys., 25, 18571–18597, https://doi.org/10.5194/acp-25-18571-2025, https://doi.org/10.5194/acp-25-18571-2025, 2025
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Contrails caused by aircraft flying in cold and humid air masses, impact weather and climate. For reduction of the climate impact, one should avoid flights forming warming contrails. This requires good weather forecast of contrail formation conditions and contrail effects. We present a two-way coupling of the Contrail Cirrus Prediction model (CoCiP) with the global Icosahedral Non-hydrostatic numerical weather model (ICON). We find that contrails are predictable – but only for a finite period.
Maleen Hanst, Carmen G. Köhler, Axel Seifert, and Linda Schlemmer
Atmos. Chem. Phys., 25, 17253–17274, https://doi.org/10.5194/acp-25-17253-2025, https://doi.org/10.5194/acp-25-17253-2025, 2025
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Persistent condensation trails typically occur due to aircraft flying through certain cold and humid regions. In most cases, these contrails have a warming impact on the climate. Predicting these regions in advance allows flight planners to re-route airplanes. We show that an adaptation of the ice microphysics scheme in a certain weather forecast model improves the prediction of these regions. Running an ensemble of simulations with this scheme improves the prediction quality even further.
Manfred Wendisch, Benjamin Kirbus, Davide Ori, Matthew D. Shupe, Susanne Crewell, Harald Sodemann, and Vera Schemann
Atmos. Chem. Phys., 25, 15047–15076, https://doi.org/10.5194/acp-25-15047-2025, https://doi.org/10.5194/acp-25-15047-2025, 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 are used to evaluate if weather prediction models are able to accurately represent these air mass transformations. This work helps to model the future Arctic climate changes, which may have an impact for mid-latitude weather as well.
Anton Kötsche, Alexander Myagkov, Leonie von Terzi, Maximilian Maahn, Veronika Ettrichrätz, Teresa Vogl, Alexander Ryzhkov, Petar Bukovcic, Davide Ori, and Heike Kalesse-Los
Atmos. Chem. Phys., 25, 14045–14070, https://doi.org/10.5194/acp-25-14045-2025, https://doi.org/10.5194/acp-25-14045-2025, 2025
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Our study combines radar observations of snow 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.
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.
Tim Lüttmer, Peter Spichtinger, and Axel Seifert
Atmos. Chem. Phys., 25, 4505–4529, https://doi.org/10.5194/acp-25-4505-2025, https://doi.org/10.5194/acp-25-4505-2025, 2025
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We investigate ice formation pathways in idealized convective clouds using a novel microphysics scheme that distinguishes between five ice classes each with their own unique formation mechanism. Ice crystals from rime splintering form the lowermost layer of ice crystals around the updraft core. The majority of ice crystals in the anvil of the convective cloud stems from frozen droplets. Ice stemming from homogeneous and deposition nucleation was only relevant in the overshoot.
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.
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.
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.
Axel Seifert, Vanessa Bachmann, Florian Filipitsch, Jochen Förstner, Christian M. Grams, Gholam Ali Hoshyaripour, Julian Quinting, Anika Rohde, Heike Vogel, Annette Wagner, and Bernhard Vogel
Atmos. Chem. Phys., 23, 6409–6430, https://doi.org/10.5194/acp-23-6409-2023, https://doi.org/10.5194/acp-23-6409-2023, 2023
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We investigate how mineral dust can lead to the formation of cirrus clouds. Dusty cirrus clouds lead to a reduction in solar radiation at the surface and, hence, a reduced photovoltaic power generation. Current weather prediction systems are not able to predict this interaction between mineral dust and cirrus clouds. We have developed a new physical description of the formation of dusty cirrus clouds. Overall we can show a considerable improvement in the forecast quality of clouds and radiation.
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.
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.
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.
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.
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Short summary
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.
Modeling precipitation is of great relevance, e.g., for mitigating damage caused by extreme...
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