Articles | Volume 16, issue 8
https://doi.org/10.5194/amt-16-2089-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-2089-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
20 Apr 2023
Research article | Highlight paper |
| 20 Apr 2023
| 20 Apr 2023
Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
Armin Blanke
CORRESPONDING AUTHOR
Department of Meteorology, Institute of Geosciences, University of Bonn, Bonn, 53121, Germany
Andrew J. Heymsfield
Mesoscale and Microscale Meteorology Lab (MMM), National Center for Atmospheric Research, Boulder, Colorado, 80307, USA
Manuel Moser
Institute for Physics of the Atmosphere, University Mainz, Mainz, 55099, Germany
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, 82234, Germany
Silke Trömel
Department of Meteorology, Institute of Geosciences, University of Bonn, Bonn, 53121, Germany
Laboratory for Clouds and Precipitation Exploration, Geoverbund ABC/J, Bonn, 53121, Germany
Related authors
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.
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.
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.
Andrew DeLaFrance, Lynn A. McMurdie, Angela K. Rowe, and Andrew J. Heymsfield
Atmos. Chem. Phys., 25, 8087–8106, https://doi.org/10.5194/acp-25-8087-2025, https://doi.org/10.5194/acp-25-8087-2025, 2025
Short summary
Short summary
Numerical modeling simulations are used to investigate ice crystal growth and decay processes within a banded region of enhanced precipitation rates during a prominent winter storm. We identify robust primary ice growth in the upper portion of the cloud but decay exceeding 70 % during fallout through a subsaturated layer. The ice fall characteristics and decay rate are sensitive to the ambient cloud properties, which has implications for radar-based measurements and precipitation accumulations.
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.
Velibor Pejcic, Kamil Mroz, Kai Mühlbauer, and Silke Trömel
EGUsphere, https://doi.org/10.5194/egusphere-2025-1414, https://doi.org/10.5194/egusphere-2025-1414, 2025
Short summary
Short summary
Estimating the proportions of individual hydrometeor types (hydrometeor partitioning ratios, HPRs) in a mixture of a resolved radar volume and their evaluation is challenging. This study has three objectives, (1) to evaluate HPR retrievals, (2) to exploit the combination of dual-frequency (DF) space-borne radar (SR) and dual-polarisation (DP) ground-based radar (GR) observations for estimating HPRs based on SR DF observations and (3) to further improve HPR estimates based on DP GR observations.
Armin Blanke, Mathias Gergely, and Silke Trömel
Atmos. Chem. Phys., 25, 4167–4184, https://doi.org/10.5194/acp-25-4167-2025, https://doi.org/10.5194/acp-25-4167-2025, 2025
Short summary
Short summary
The area-wide radar-based distinction between riming and aggregation is crucial for model microphysics and data assimilation. This study introduces a discrimination algorithm based on polarimetric radar networks only. Exploiting the unique opportunity to link fall velocities from Doppler spectra to polarimetric variables in an operational setting enables us to set up and evaluate a well-performing machine learning algorithm.
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.
Andrew DeLaFrance, Lynn A. McMurdie, Angela K. Rowe, and Andrew J. Heymsfield
Atmos. Chem. Phys., 24, 11191–11206, https://doi.org/10.5194/acp-24-11191-2024, https://doi.org/10.5194/acp-24-11191-2024, 2024
Short summary
Short summary
Using a numerical model, the process whereby falling ice crystals accumulate supercooled liquid water droplets is investigated to elucidate its effects on radar-based measurements and surface precipitation. We demonstrate that this process accounted for 55% of the precipitation during a wintertime storm and is uniquely discernable from other ice crystal growth processes in Doppler velocity measurements. These results have implications for measurements from airborne and spaceborne platforms.
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.
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.
Nina Maherndl, Manuel Moser, Johannes Lucke, Mario Mech, Nils Risse, Imke Schirmacher, and Maximilian Maahn
Atmos. Meas. Tech., 17, 1475–1495, https://doi.org/10.5194/amt-17-1475-2024, https://doi.org/10.5194/amt-17-1475-2024, 2024
Short summary
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.
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.
Lucas Reimann, Clemens Simmer, and Silke Trömel
Atmos. Chem. Phys., 23, 14219–14237, https://doi.org/10.5194/acp-23-14219-2023, https://doi.org/10.5194/acp-23-14219-2023, 2023
Short summary
Short summary
Polarimetric radar observations were assimilated for the first time in a convective-scale numerical weather prediction system in Germany and their impact on short-term precipitation forecasts was evaluated. The assimilation was performed using microphysical retrievals of liquid and ice water content and yielded slightly improved deterministic 9 h precipitation forecasts for three intense summer precipitation cases with respect to the assimilation of radar reflectivity alone.
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.
Mohamed Saadi, Carina Furusho-Percot, Alexandre Belleflamme, Ju-Yu Chen, Silke Trömel, and Stefan Kollet
Nat. Hazards Earth Syst. Sci., 23, 159–177, https://doi.org/10.5194/nhess-23-159-2023, https://doi.org/10.5194/nhess-23-159-2023, 2023
Short summary
Short summary
On 14 July 2021, heavy rainfall fell over central Europe, causing considerable damage and human fatalities. We analyzed how accurate our estimates of rainfall and peak flow were for these flooding events in western Germany. We found that the rainfall estimates from radar measurements were improved by including polarimetric variables and their vertical gradients. Peak flow estimates were highly uncertain due to uncertainties in hydrological model parameters and rainfall measurements.
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.
Étienne Vignon, Lea Raillard, Christophe Genthon, Massimo Del Guasta, Andrew J. Heymsfield, Jean-Baptiste Madeleine, and Alexis Berne
Atmos. Chem. Phys., 22, 12857–12872, https://doi.org/10.5194/acp-22-12857-2022, https://doi.org/10.5194/acp-22-12857-2022, 2022
Short summary
Short summary
The near-surface atmosphere over the Antarctic Plateau is cold and pristine and resembles to a certain extent the high troposphere where cirrus clouds form. In this study, we use innovative humidity measurements at Concordia Station to study the formation of ice fogs at temperatures <−40°C. We provide observational evidence that ice fogs can form through the homogeneous freezing of solution aerosols, a common nucleation pathway for cirrus clouds.
Prabhakar Shrestha, Silke Trömel, Raquel Evaristo, and Clemens Simmer
Atmos. Chem. Phys., 22, 7593–7618, https://doi.org/10.5194/acp-22-7593-2022, https://doi.org/10.5194/acp-22-7593-2022, 2022
Short summary
Short summary
The study makes use of ensemble numerical simulations with forward operator to evaluate the simulated cloud and precipitation processes with radar observations. While comparing model data with radar has its own challenges due to errors in the forward operator and processed radar measurements, the model was generally found to underestimate the high reflectivity, width/magnitude (value) of ZDR columns and high precipitation.
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.
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022, https://doi.org/10.5194/gmd-15-291-2022, 2022
Short summary
Short summary
The article focuses on the exploitation of radar polarimetry for model evaluation of stratiform precipitation. The model exhibited a low bias in simulated polarimetric moments at lower levels above the melting layer where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models in the forward operator to draw valid conclusions.
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.
Kamil Mroz, Alessandro Battaglia, Cuong Nguyen, Andrew Heymsfield, Alain Protat, and Mengistu Wolde
Atmos. Meas. Tech., 14, 7243–7254, https://doi.org/10.5194/amt-14-7243-2021, https://doi.org/10.5194/amt-14-7243-2021, 2021
Short summary
Short summary
A method for estimating microphysical properties of ice clouds based on radar measurements is presented. The algorithm exploits the information provided by differences in the radar response at different frequency bands in relation to changes in the snow morphology. The inversion scheme is based on a statistical relation between the radar simulations and the properties of snow calculated from in-cloud sampling.
Cited articles
Allabakash, S., Lim, S., Chandrasekar, V., Min, K., Choi, J., and Jang, B.: X-band dual-polarization radar observations of snow growth processes of a severe winter storm: Case of 12 December 2013 in South Korea, J. Atmos. Ocean. Tech., 36, 1217–1235, https://doi.org/10.1175/JTECH-D-18-0076.1, 2019. a
Aydin, K. and Tang, C.: Relationships between IWC and polarimetric radar measurands at 94 and 220 GHz for hexagonal columns and plates, J. Atmos. Ocean. Tech., 14, 1055–1063, https://doi.org/10.1175/1520-0426(1997)014<1055:RBIAPR>2.0.CO;2, 1997. a
Baker, B. and Lawson, R. P.: Improvement in determination of ice water content from two-dimensional particle imagery. Part I: Image-to-mass relationships, J. Appl. Meteorol. Clim., 45, 1282–1290, https://doi.org/10.1175/JAM2398.1, 2006. a
Bansemer, A.: System for OAP Data Analysis, v2.23.0, Zenodo [code],
https://doi.org/10.5281/zenodo.7803116, 2023. a
Baumgardner, D. and Rodi, A.: Laboratory and wind tunnel evaluations of the Rosemount icing detector, J. Atmos. Ocean. Tech., 6, 971–979, https://doi.org/10.1175/1520-0426(1989)006<0971:LAWTEO>2.0.CO;2, 1989. a
Baumgardner, D., Abel, S. J., Axisa, D., Cotton, R., Crosier, J., Field, P., Gurganus, C., Heymsfield, A., Korolev, A., Krämer, M., Lawson, P., McFarquhar, G., Ulanowski, Z., and Um, J.: Cloud Ice Properties: In Situ Measurement Challenges, Meteor. Mon., 58, 9.1–9.23, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0011.1, 2017. a, b
Bernstein, B., DiVito, S., Riley, J. T., Landolt, S., Haggerty, J., Thompson,
G., Adriaansen, D., Serke, D., Kessinger, C., Tessendorf, S., Wolde, M., Korolev, A., Brown, A., Nichman, L., Sims, D., Dumont, C.: The In-Cloud Icing and Large-Drop Experiment Science and Operations Plan, Tech. rep. no. DOT/FAA/TC-21/29, Department of Transportation, Federal Aviation Administration, United States, https://doi.org/10.21949/1524472, 2021. a
Brandes, E. A., Ikeda, K., Zhang, G., Schönhuber, M., and Rasmussen, R. M.: A statistical and physical description of hydrometeor distributions in Colorado snowstorms using a video disdrometer, J. Appl. Meteorol. Clim., 46, 634–650, https://doi.org/10.1175/JAM2489.1, 2007. a
Brown, P. R. A. and Francis, P. N.: Improved Measurements of the Ice Water Content in Cirrus Using a Total-Water Probe, J. Atmos. Ocean. Tech., 12, 410–414, https://doi.org/10.1175/1520-0426(1995)012<0410:imotiw>2.0.co;2, 1995. a, b
Bukovčić, P., Zrnić, D., and Zhang, G.: Winter precipitation liquid–ice phase transitions revealed with polarimetric radar and 2DVD observations in central Oklahoma, J. Appl. Meteorol. Clim., 56, 1345–1363, https://doi.org/10.1175/JAMC-D-16-0239.1, 2017.
a, b
Carlin, J. T., Ryzhkov, A. V., Snyder, J. C., and Khain, A.: Hydrometeor mixing ratio retrievals for storm-scale radar data assimilation: Utility of current relations and potential benefits of polarimetry, Mon. Weather Rev., 144, 2981–3001, https://doi.org/10.1175/MWR-D-15-0423.1, 2016. 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
Davis, C., Atkins, N., Bartels, D., Bosart, L., Coniglio, M., Bryan, G., Cotton, W., Dowell, D., Jewett, B., Johns, R., Jorgensen, D., Knievel, J.,
Knupp, K., Lee, W.-C., McFarquhar, G., Moore, J., Przybylinski, R., Rauber, R., Smull, B., Trapp, R., Trier, S., Wakimoto, R., Weisman, M., and Ziegler, C.: The Bow Echo and MCV experiment: observations and opportunities: observations and opportunities, B. Am. Meteorol. Soc., 85, 1075–1094, https://doi.org/10.1175/BAMS-85-8-1075, 2004. a
Ding, S., McFarquhar, G. M., Nesbitt, S. W., Chase, R. J., Poellot, M. R., and Wang, H.: Dependence of mass–dimensional relationships on median mass diameter, Atmosphere, 11, 756, https://doi.org/10.3390/atmos11070756, 2020. a
Dunnavan, E. L., Carlin, J. T., Hu, J., Bukovčić, P., Ryzhkov, A. V., McFarquhar, G. M., Finlon, J. A., Matrosov, S. Y., and Delene, D. J.: Radar Retrieval Evaluation and Investigation of Dendritic Growth Layer Polarimetric Signatures in a Winter Storm, J. Appl. Meteorol. Clim., 61, 1685–1711, https://doi.org/10.1175/JAMC-D-21-0220.1, 2022. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023. a
Heymsfield, A., Bansemer, A., Heymsfield, G., Noone, D., Grecu, M., and Toohey, D.: Relationship of Multiwavelength Radar Measurements to Ice Microphysics from the IMPACTS Field Program, J. Appl. Meteorol. Clim., 62, 289–315, https://doi.org/10.1175/JAMC-D-22-0057.1, 2023. a
Heymsfield, A. J. and Miloshevich, L. M.: Evaluation of liquid water measuring instruments in cold clouds sampled during FIRE, J. Atmos. Ocean. Tech., 6, 378–388, https://doi.org/10.1175/1520-0426(1989)006<0378:EOLWMI>2.0.CO;2, 1989. a
Heymsfield, A. J., Protat, A., Bouniol, D., Austin, R. T., Hogan, R. J., Delanoë, J., Okamoto, H., Sato, K., van Zadelhoff, G.-J., Donovan, D. P., and Wang, Z.: Testing IWC retrieval methods using radar and ancillary measurements with in situ data, J. Appl. Meteorol. Clim., 47, 135–163, https://doi.org/10.1175/2007JAMC1606.1, 2008. a
Heymsfield, A. J., Schmitt, C., Bansemer, A., and Twohy, C. H.: Improved representation of ice particle masses based on observations in natural clouds, J. Atmos. Sci., 67, 3303–3318, https://doi.org/10.1175/2010JAS3507.1, 2010. a
Hogan, R. J., Tian, L., Brown, P. R. A., Westbrook, C. D., Heymsfield, A. J., and Eastment, J. D.: Radar Scattering from Ice Aggregates Using the Horizontally Aligned Oblate Spheroid Approximation, J. Appl. Meteorol. Clima., 51, 655–671, https://doi.org/10.1175/jamc-d-11-074.1, 2012. a
Holoborodko, P.: Smooth Noise Robust Differentiators,
http://www.holoborodko.com/pavel/numerical-methods/numerical-derivative/smooth-low-noise-differentiators/ (last access: 5 April 2023), 2008. a
Houze, R. A., Wurman, J., Brodzik, S., and Framback, A.: GPM Ground Validation Doppler on Wheels (DOW) OLYMPEX V2, NASA EOSDIS Global Hydrology Resource Center Distributed Active Archive Center (DAAC) [data set], Huntsville, Alabama, U.S.A., https://doi.org/10.5067/GPMGV/OLYMPEX/DOW/DATA201, 2018. a, b, c, d
Houze Jr., R. A., McMurdie, L. A., Petersen, W. A., Schwaller, M. R., Baccus, W., Lundquist, J. D., Mass, C. F., Nijssen, B., Rutledge, S. A., Hudak, D. R., Tanelli, S., Mace, G. G., Poellot, M. R., Lettenmaier, D. P., Zagrodnik, J. P., Rowe, A. K., DeHart, J. C., Madaus, L. E., Barnes, H. C., and
Chandrasekar, V.: The olympic mountains experiment (OLYMPEX), B. Am. Meteorol. Soc., 98, 2167–2188, https://doi.org/10.1175/BAMS-D-16-0182.1, 2017. a, b, c
Hu, J. and Ryzhkov, A.: Climatology of the vertical profiles of polarimetric radar variables and retrieved microphysical parameters in continental/tropical MCSs and landfalling hurricanes, J. Geophys. Res.-Atmos., 127, e2021JD035498, https://doi.org/10.1029/2021JD035498, 2022. a, b, c
Kedzuf, N. J., Chiu, J. C., Chandrasekar, V., Biswas, S., Joshil, S. S., Lu, Y., van Leeuwen, P. J., Westbrook, C., Blanchard, Y., and O'Shea, S.: Retrieving microphysical properties of concurrent pristine ice and snow using polarimetric radar observations, Atmos. Meas. Tech., 14, 6885–6904, https://doi.org/10.5194/amt-14-6885-2021, 2021. a
Kumjian, M. R., Mishra, S., Giangrande, S. E., Toto, T., Ryzhkov, A. V., and Bansemer, A.: Polarimetric radar and aircraft observations of saggy bright bands during MC3E, J. Geophys. Res.-Atmos., 121, 3584–3607, https://doi.org/10.1002/2015JD024446, 2016. a
Lawson, R. P., O'Connor, D., Zmarzly, P., Weaver, K., Baker, B., Mo, Q., and Jonsson, H.: The 2D-S (Stereo) Probe: Design and Preliminary Tests of a New Airborne, High-Speed, High-Resolution Particle Imaging Probe, J. Atmos. Ocean. Tech., 23, 1462–1477, https://doi.org/10.1175/JTECH1927.1, 2006. a
Leinonen, J. and Szyrmer, W.: Radar signatures of snowflake riming: A modeling study, Earth and Space Science, 2, 346–358, https://doi.org/10.1002/2015EA000102, 2015. a
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
Matrosov, S., Ryzhkov, A., Hardin, J., Shupe, M., Maahn, M., de Boer, G., and Uttal, T.: Intercomparisons of CloudSat and ground-based radar measurements during satellite overpasses, in: 39th Int. Conf. on Radar Meteorology, 16–20 September 2019, Nara, Japan, Amer. Meteor. Soc., 11A-02, https://cscenter.co.jp/icrm2019/program/data/abstracts/Session11A-02_2.pdf (last access: 5 April 2023), 2019. a, b, c
Matrosov, S. Y., Ryzhkov, A. V., Maahn, M., and De Boer, G.: Hydrometeor shape variability in snowfall as retrieved from polarimetric radar measurements, J. Appl. Meteorol. Clim., 59, 1503–1517, https://doi.org/10.1175/JAMC-D-20-0052.1, 2020. a
McMurdie, L., Heymsfield, G., Yorks, J., and Braun, S.: Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) Collection, NASA EOSDIS Global Hydrology Resource Center Distributed Active Archive Center [data set], Huntsville, Alabama, U.S.A., https://doi.org/10.5067/IMPACTS/DATA101, 2019. 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. Discuss. [preprint], https://doi.org/10.5194/acp-2023-44, in review, 2023. a
Petersen, W., Houze, R., and McMurdie, L.: GPM Ground Validation OLYMPEX Field Campaign Data Collection, NASA EOSDIS Global Hydrology Resource Center Distributed Active Archive Center (DAAC) [data set], Huntsville, Alabama, U.S.A., https://doi.org/10.5067/GPMGV/OLYMPEX/DATA101, 2018. a, b
Poellot, M. R., Heymsfield, A. J., and Bansemer, A.: GPM Ground Validation UND Citation Cloud Microphysics OLYMPEX, NASA EOSDIS Global Hydrology Resource Center Distributed Active Archive Center (DAAC) [data set], Huntsville, Alabama, U.S.A., https://doi.org/10.5067/GPMGV/OLYMPEX/MULTIPLE/DATA201, 2017. a
Praz, C., Ding, S., McFarquhar, G. M., and Berne, A.: A versatile method for ice particle habit classification using airborne imaging probe data, J. Geophys. Res.-Atmos., 123, 13–472, https://doi.org/10.1029/2018JD029163, 2018. a
Przybylo, V. M., Sulia, K. J., Schmitt, C. G., and Lebo, Z. J.: Classification of cloud particle imagery from aircraft platforms using convolutional neural networks, J. Atmos. Ocean. Tech., 39, 405–424, https://doi.org/10.1175/JTECH-D-21-0094.1, 2022. a, b
Reimann, L., Simmer, C., and Trömel, S.: Dual-polarimetric radar estimators of liquid water content over Germany, Meteorol. Z., 30, 237–249, https://doi.org/10.1127/metz/2021/1072, 2021. a
Ryzhkov, A., Zhang, P., Reeves, H., Kumjian, M., Tschallener, T., Trömel, S., and Simmer, C.: Quasi-vertical profiles—A new way to look at polarimetric radar data, J. Atmos. Ocean. Tech., 33, 551–562, https://doi.org/10.1175/JTECH-D-15-0020.1, 2016. a, b
Ryzhkov, A., Bukovcic, P., Murphy, A., Zhang, P., and McFarquhar, G.: Ice microphysical retrievals using polarimetric radar data, in: 10th European Conference on Radar in Meteorology and Hydrology, 1–6 July 2018, the Netherlands, 494–504, https://doi.org/10.18174/454537, 2018. a, b, c, d, e, f, g, h, i
Ryzhkov, A. V., Snyder, J., Carlin, J. T., Khain, A., and Pinsky, M.: What polarimetric weather radars offer to cloud modelers: forward radar operators and microphysical/thermodynamic retrievals, Atmosphere, 11, 362, https://doi.org/10.3390/atmos11040362, 2020. a, b
Skofronick-Jackson, G., Hudak, D., Petersen, W., Nesbitt, S. W., Chandrasekar, V., Durden, S., Gleicher, K. J., Huang, G.-J., Joe, P., Kollias, P., Reed, K. A., Schwaller, M. R., Stewart, R., Tanelli, S., Tokay, A., Wang, J. R., and Wolde, M.: Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEX): for measurement's sake, let it snow, B. Am. Meteorol. Soc., 96, 1719–1741, https://doi.org/10.1175/BAMS-D-13-00262.1, 2015. a
Skofronick-Jackson, G., Kulie, M., Milani, L., Munchak, S. J., Wood, N. B., and Levizzani, V.: Satellite estimation of falling snow: A global precipitation measurement (GPM) core observatory perspective, J. Appl. Meteorol. Clim., 58, 1429–1448, https://doi.org/10.1175/JAMC-D-18-0124.1, 2019. a, b, c
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
Tobin, D. M. and Kumjian, M. R.: Polarimetric radar and surface-based precipitation-type observations of ice pellet to freezing rain transitions, Weather Forecast., 32, 2065–2082, https://doi.org/10.1175/WAF-D-17-0054.1, 2017. a
Tridon, F., Battaglia, A., Chase, R. J., Turk, F. J., Leinonen, J., Kneifel, S., Mroz, K., Finlon, J., Bansemer, A., Tanelli, S., Heymsfield, A. J.,
and Nesbitt, S. W.: The microphysics of stratiform precipitation during OLYMPEX: Compatibility between triple-frequency radar and airborne in situ observations, J. Geophys. Res.-Atmos., 124, 8764–8792, https://doi.org/10.1029/2018JD029858, 2019. a, b, c
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
Ulbrich, C. W.: Natural variations in the analytical form of the raindrop size distribution, J. Appl. Meteorol. Clim., 22, 1764–1775, 1983. a
Vogel, J. M. and Fabry, F.: Contrasting polarimetric observations of stratiform riming and nonriming events, J. Appl. Meteorol. Clim., 57, 457–476, https://doi.org/10.1175/JAMC-D-16-0370.1, 2018. a
Vulpiani, G., Montopoli, M., Passeri, L. D., Gioia, A. G., Giordano, P., and Marzano, F. S.: On the use of dual-polarized C-band radar for operational rainfall retrieval in mountainous areas, J. Appl. Meteorol. Clim., 51, 405–425, https://doi.org/10.1175/JAMC-D-10-05024.1, 2012. a
Wurman, J., Straka, J., Rasmussen, E., Randall, M., and Zahrai, A.: Design and deployment of a portable, pencil-beam, pulsed, 3-cm Doppler radar, J. Atmos. Ocean. Tech., 14, 1502–1512, https://doi.org/10.1175/1520-0426(1997)014<1502:DADOAP>2.0.CO;2, 1997. a
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a
Executive editor
This study evaluates many currently available conventional and polarimetric radar-based remote-sensing retrievals of ice water content, total number concentration and mean diameter of ice hydrometeors. It has the potential to become a reference for the assessment of measurement uncertainties from radar observations for which no in-situ reference data are available.
This study evaluates many currently available conventional and polarimetric radar-based...
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.
We present an evaluation of current retrieval techniques in the ice phase applied to...
