Articles | Volume 22, issue 17
https://doi.org/10.5194/acp-22-11795-2022
© Author(s) 2022. 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-22-11795-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Sep 2022
Research article |
| 13 Sep 2022
| 13 Sep 2022
Ice microphysical processes in the dendritic growth layer: a statistical analysis combining multi-frequency and polarimetric Doppler cloud radar observations
Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany
José Dias Neto
Department of Geosciences and Remote Sensing, Delft University of Technology, Delft, the Netherlands
Davide Ori
Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany
Alexander Myagkov
Radiometer Physics GmbH, Meckenheim, Germany
Stefan Kneifel
Institute of Geophysics and Meteorology, University of Cologne, Cologne, Germany
Meteorological Institute, Ludwig-Maximilians University Munich, Germany
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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
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Modeling precipitation is of great relevance, e.g., for mitigating damage caused by extreme weather. A key component in accurate precipitation modeling is aggregation, i.e., sticking together of snowflakes. Simulating aggregation is difficult due to multiple parameters that are not well-known. Knowing how these parameters affect aggregation can help its simulation. We put new parameters in the model and select a combination of parameters with which the model can simulate observations better.
Davide Ori, Leonie von Terzi, Markus Karrer, and Stefan Kneifel
Geosci. Model Dev., 14, 1511–1531, https://doi.org/10.5194/gmd-14-1511-2021, https://doi.org/10.5194/gmd-14-1511-2021, 2021
Short summary
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Snowflakes have very complex shapes, and modeling their properties requires vast computing power. We produced a large number of realistic snowflakes and modeled their average properties by leveraging their fractal structure. Our approach allows modeling the properties of big ensembles of snowflakes, taking into account their natural variability, at a much lower cost. This enables the usage of remote sensing instruments, such as radars, to monitor the evolution of clouds and precipitation.
Kamil Mróz, Alessandro Battaglia, Stefan Kneifel, Leonie von Terzi, Markus Karrer, and Davide Ori
Atmos. Meas. Tech., 14, 511–529, https://doi.org/10.5194/amt-14-511-2021, https://doi.org/10.5194/amt-14-511-2021, 2021
Short summary
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The article examines the relationship between the characteristics of rain and the properties of the ice cloud from which the rain originated. Our results confirm the widely accepted assumption that the mass flux through the melting zone is well preserved with an exception of extreme aggregation and riming conditions. Moreover, it is shown that the mean (mass-weighted) size of particles above and below the melting zone is strongly linked, with the former being on average larger.
Jie Gong, Xiping Zeng, Dong L. Wu, S. Joseph Munchak, Xiaowen Li, Stefan Kneifel, Davide Ori, Liang Liao, and Donifan Barahona
Atmos. Chem. Phys., 20, 12633–12653, https://doi.org/10.5194/acp-20-12633-2020, https://doi.org/10.5194/acp-20-12633-2020, 2020
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This work provides a novel way of using polarized passive microwave measurements to study the interlinked cloud–convection–precipitation processes. The magnitude of differences between polarized radiances is found linked to ice microphysics (shape, size, orientation and density), mesoscale dynamic and thermodynamic structures, and surface precipitation. We conclude that passive sensors with multiple polarized channel pairs may serve as cheaper and useful substitutes for spaceborne radar sensors.
Alexander Myagkov, Stefan Kneifel, and Thomas Rose
Atmos. Meas. Tech., 13, 5799–5825, https://doi.org/10.5194/amt-13-5799-2020, https://doi.org/10.5194/amt-13-5799-2020, 2020
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This study shows two methods for evaluating the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first method is based on spectral polarimetric observations and requires a polarimetric cloud radar with a scanner. The second method utilizes disdrometer observations and can be applied to scanning and vertically pointed radars. Both methods show consistent results and can be applied for operational monitoring of measurement quality.
Frédéric Tridon, Alessandro Battaglia, and Stefan Kneifel
Atmos. Meas. Tech., 13, 5065–5085, https://doi.org/10.5194/amt-13-5065-2020, https://doi.org/10.5194/amt-13-5065-2020, 2020
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The droplets and ice crystals composing clouds and precipitation interact with microwaves and can therefore be observed by radars, but they can also attenuate the signal they emit. By combining the observations made by two ground-based radars, this study describes an original approach for estimating such attenuation. As a result, the latter can be not only corrected in the radar observations but also exploited for providing an accurate characterization of droplet and ice crystal properties.
Mario Mech, Maximilian Maahn, Stefan Kneifel, Davide Ori, Emiliano Orlandi, Pavlos Kollias, Vera Schemann, and Susanne Crewell
Geosci. Model Dev., 13, 4229–4251, https://doi.org/10.5194/gmd-13-4229-2020, https://doi.org/10.5194/gmd-13-4229-2020, 2020
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The Passive and Active Microwave TRAnsfer tool (PAMTRA) is a public domain software package written in Python and Fortran for the simulation of microwave remote sensing observations. PAMTRA models the interaction of radiation with gases, clouds, precipitation, and the surface using either in situ observations or model output as input parameters. The wide range of applications is demonstrated for passive (radiometer) and active (radar) instruments on ground, airborne, and satellite platforms.
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Short summary
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.
We present a statistical analysis of ice microphysical processes (IMP) in mid-latitude clouds....
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