Articles | Volume 17, issue 24
https://doi.org/10.5194/amt-17-7143-2024
© Author(s) 2024. 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-17-7143-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Dec 2024
Research article |
| 20 Dec 2024
| 20 Dec 2024
Double-moment normalization of hail size number distributions over Switzerland
Alfonso Ferrone
Hydro-Meteo-Climate Structure, Agency for Prevention, Environment and Energy of Emilia-Romagna (Arpae), Bologna, Italy
Jérôme Kopp
Oeschger Centre for Climate Change Research and Institute of Geography, University of Bern, Bern, Switzerland
Martin Lainer
Federal Office of Meteorology and Climatology MeteoSwiss, Locarno-Monti, Switzerland
Marco Gabella
Federal Office of Meteorology and Climatology MeteoSwiss, Locarno-Monti, Switzerland
Urs Germann
Federal Office of Meteorology and Climatology MeteoSwiss, Locarno-Monti, Switzerland
Environmental Remote Sensing Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Matteo Guidicelli, Matthias Huss, Marco Gabella, and Nadine Salzmann
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Anne-Claire Billault-Roux, Gionata Ghiggi, Louis Jaffeux, Audrey Martini, Nicolas Viltard, and Alexis Berne
Atmos. Meas. Tech., 16, 911–940, https://doi.org/10.5194/amt-16-911-2023, https://doi.org/10.5194/amt-16-911-2023, 2023
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Atmos. Chem. Phys., 22, 13551–13568, https://doi.org/10.5194/acp-22-13551-2022, https://doi.org/10.5194/acp-22-13551-2022, 2022
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We determined over the course of 8 winter months the phase of clouds associated with snowfall in Northern Finland using radiosondes and observations of ice particle habits at ground level. We found that precipitating clouds were extending from near ground to at least 2.7 km altitude and approximately three-quarters of them were likely glaciated. Possible moisture sources and ice formation processes are discussed.
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
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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.
Alfonso Ferrone, Anne-Claire Billault-Roux, and Alexis Berne
Atmos. Meas. Tech., 15, 3569–3592, https://doi.org/10.5194/amt-15-3569-2022, https://doi.org/10.5194/amt-15-3569-2022, 2022
Short summary
Short summary
The Micro Rain Radar PRO (MRR-PRO) is a meteorological radar, with a relevant set of features for deployment in remote locations. We developed an algorithm, named ERUO, for the processing of its measurements of snowfall. The algorithm addresses typical issues of the raw spectral data, such as interference lines, but also improves the quality and sensitivity of the radar variables. ERUO has been evaluated over four different datasets collected in Antarctica and in the Swiss Jura.
Jeong-Su Ko, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, Gregory Thompson, and Alexis Berne
Geosci. Model Dev., 15, 4529–4553, https://doi.org/10.5194/gmd-15-4529-2022, https://doi.org/10.5194/gmd-15-4529-2022, 2022
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This study evaluates the performance of the four microphysics parameterizations, the WDM6, WDM7, Thompson, and Morrison schemes, in simulating snowfall events during the ICE-POP 2018 field campaign. Eight snowfall events are selected and classified into three categories (cold-low, warm-low, and air–sea interaction cases). The evaluation focuses on the simulated hydrometeors, microphysics budgets, wind fields, and precipitation using the measurement data.
Jussi Leinonen, Ulrich Hamann, Urs Germann, and John R. Mecikalski
Nat. Hazards Earth Syst. Sci., 22, 577–597, https://doi.org/10.5194/nhess-22-577-2022, https://doi.org/10.5194/nhess-22-577-2022, 2022
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We evaluate the usefulness of different data sources and variables to the short-term prediction (
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Paraskevi Georgakaki, Georgia Sotiropoulou, Étienne Vignon, Anne-Claire Billault-Roux, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 22, 1965–1988, https://doi.org/10.5194/acp-22-1965-2022, https://doi.org/10.5194/acp-22-1965-2022, 2022
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The modelling study focuses on the importance of ice multiplication processes in orographic mixed-phase clouds, which is one of the least understood cloud types in the climate system. We show that the consideration of ice seeding and secondary ice production through ice–ice collisional breakup is essential for correct predictions of precipitation in mountainous terrain, with important implications for radiation processes.
Monika Feldmann, Urs Germann, Marco Gabella, and Alexis Berne
Weather Clim. Dynam., 2, 1225–1244, https://doi.org/10.5194/wcd-2-1225-2021, https://doi.org/10.5194/wcd-2-1225-2021, 2021
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Mesocyclones are the rotating updraught of supercell thunderstorms that present a particularly hazardous subset of thunderstorms. A first-time characterisation of the spatiotemporal occurrence of mesocyclones in the Alpine region is presented, using 5 years of Swiss operational radar data. We investigate parallels to hailstorms, particularly the influence of large-scale flow, daily cycles and terrain. Improving understanding of mesocyclones is valuable for risk assessment and warning purposes.
Hélène Barras, Olivia Martius, Luca Nisi, Katharina Schroeer, Alessandro Hering, and Urs Germann
Weather Clim. Dynam., 2, 1167–1185, https://doi.org/10.5194/wcd-2-1167-2021, https://doi.org/10.5194/wcd-2-1167-2021, 2021
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In Switzerland hail may occur several days in a row. Such multi-day hail events may cause significant damage, and understanding and forecasting these events is important. Using reanalysis data we show that weather systems over Europe move slower before and during multi-day hail events compared to single hail days. Surface temperatures are typically warmer and the air more humid over Switzerland and winds are slower on multi-day hail clusters. These results may be used for hail forecasting.
Jussi Leinonen, Jacopo Grazioli, and Alexis Berne
Atmos. Meas. Tech., 14, 6851–6866, https://doi.org/10.5194/amt-14-6851-2021, https://doi.org/10.5194/amt-14-6851-2021, 2021
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Measuring the shape, size and mass of a large number of snowflakes is a challenging task; it is hard to achieve in an automatic and instrumented manner. We present a method to retrieve these properties of individual snowflakes using as input a triplet of images/pictures automatically collected by a multi-angle snowflake camera (MASC) instrument. Our method, based on machine learning, is trained on artificially generated snowflakes and evaluated on 3D-printed snowflake replicas.
Marc Schwaerzel, Dominik Brunner, Fabian Jakub, Claudia Emde, Brigitte Buchmann, Alexis Berne, and Gerrit Kuhlmann
Atmos. Meas. Tech., 14, 6469–6482, https://doi.org/10.5194/amt-14-6469-2021, https://doi.org/10.5194/amt-14-6469-2021, 2021
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NO2 maps from airborne imaging remote sensing often appear much smoother than one would expect from high-resolution model simulations of NO2 over cities, despite the small ground-pixel size of the sensors. Our case study over Zurich, using the newly implemented building module of the MYSTIC radiative transfer solver, shows that the 3D effect can explain part of the smearing and that building shadows cause a noticeable underestimation and noise in the measured NO2 columns.
Jérôme Kopp, Pauline Rivoire, S. Mubashshir Ali, Yannick Barton, and Olivia Martius
Hydrol. Earth Syst. Sci., 25, 5153–5174, https://doi.org/10.5194/hess-25-5153-2021, https://doi.org/10.5194/hess-25-5153-2021, 2021
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Episodes of extreme rainfall events happening in close temporal succession can lead to floods with dramatic impacts. We developed a novel method to individually identify those episodes and deduced the regions where they occur frequently and where their impact is substantial. Those regions are the east and northeast of the Asian continent, central Canada and the south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and north of Argentina and south of Bolivia.
Anna Špačková, Vojtěch Bareš, Martin Fencl, Marc Schleiss, Joël Jaffrain, Alexis Berne, and Jörg Rieckermann
Earth Syst. Sci. Data, 13, 4219–4240, https://doi.org/10.5194/essd-13-4219-2021, https://doi.org/10.5194/essd-13-4219-2021, 2021
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An original dataset of microwave signal attenuation and rainfall variables was collected during 1-year-long field campaign. The monitored 38 GHz dual-polarized commercial microwave link with a short sampling resolution (4 s) was accompanied by five disdrometers and three rain gauges along its path. Antenna radomes were temporarily shielded for approximately half of the campaign period to investigate antenna wetting impacts.
Paraskevi Georgakaki, Aikaterini Bougiatioti, Jörg Wieder, Claudia Mignani, Fabiola Ramelli, Zamin A. Kanji, Jan Henneberger, Maxime Hervo, Alexis Berne, Ulrike Lohmann, and Athanasios Nenes
Atmos. Chem. Phys., 21, 10993–11012, https://doi.org/10.5194/acp-21-10993-2021, https://doi.org/10.5194/acp-21-10993-2021, 2021
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Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol–cloud droplet link in alpine mixed-phase clouds. Predicted droplet number, Nd, agrees with observations and never exceeds a characteristic “limiting droplet number”, Ndlim, which depends solely on σw. Nd becomes velocity limited when it is within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol–cloud interactions.
Noémie Planat, Josué Gehring, Étienne Vignon, and Alexis Berne
Atmos. Meas. Tech., 14, 4543–4564, https://doi.org/10.5194/amt-14-4543-2021, https://doi.org/10.5194/amt-14-4543-2021, 2021
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We implement a new method to identify microphysical processes during cold precipitation events based on the sign of the vertical gradient of polarimetric radar variables. We analytically asses the meteorological conditions for this vertical analysis to hold, apply it on two study cases and successfully compare it with other methods informing about the microphysics. Finally, we are able to obtain the main vertical structure and characteristics of the different processes during these study cases.
Martin Lainer, Jordi Figueras i Ventura, Zaira Schauwecker, Marco Gabella, Montserrat F.-Bolaños, Reto Pauli, and Jacopo Grazioli
Atmos. Meas. Tech., 14, 3541–3560, https://doi.org/10.5194/amt-14-3541-2021, https://doi.org/10.5194/amt-14-3541-2021, 2021
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We show results from two unique measurement campaigns aimed at better understanding effects of large wind turbines on radar returns by deploying a mobile X-band weather radar system in the proximity of a small wind park. Measurements were taken in 24/7 operation with dedicated scan strategies to retrieve the variability and most extreme values of reflectivity and radar cross-section of the wind turbines. The findings are useful for wind turbine interference mitigation measures in radar systems.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193, https://doi.org/10.5194/amt-14-3169-2021, https://doi.org/10.5194/amt-14-3169-2021, 2021
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In this work, we present a novel quantitative precipitation estimation method for Switzerland that uses random forests, an ensemble-based machine learning technique. The estimator has been trained with a database of 4 years of ground and radar observations. The results of an in-depth evaluation indicate that, compared with the more classical method in use at MeteoSwiss, this novel estimator is able to reduce both the average error and bias of the predictions.
Anne-Claire Billault-Roux and Alexis Berne
Atmos. Meas. Tech., 14, 2749–2769, https://doi.org/10.5194/amt-14-2749-2021, https://doi.org/10.5194/amt-14-2749-2021, 2021
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In the context of climate studies, understanding the role of clouds on a global and local scale is of paramount importance. One aspect is the quantification of cloud liquid water, which impacts the Earth’s radiative balance. This is routinely achieved with radiometers operating at different frequencies. In this study, we propose an approach that uses a single-frequency radiometer and that can be applied at any location to retrieve vertically integrated quantities of liquid water and water vapor.
Maxi Boettcher, Andreas Schäfler, Michael Sprenger, Harald Sodemann, Stefan Kaufmann, Christiane Voigt, Hans Schlager, Donato Summa, Paolo Di Girolamo, Daniele Nerini, Urs Germann, and Heini Wernli
Atmos. Chem. Phys., 21, 5477–5498, https://doi.org/10.5194/acp-21-5477-2021, https://doi.org/10.5194/acp-21-5477-2021, 2021
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Warm conveyor belts (WCBs) are important airstreams in extratropical cyclones, often leading to the formation of intense precipitation. We present a case study that involves aircraft, lidar and radar observations of water and clouds in a WCB ascending from western Europe across the Alps towards the Baltic Sea during the field campaigns HyMeX and T-NAWDEX-Falcon in October 2012. A probabilistic trajectory measure and an airborne tracer experiment were used to confirm the long pathway of the WCB.
Cited articles
American Meteorological Society: Hail. Glossary of Meteorology, https://glossary.ametsoc.org/wiki/Hail (last access: 18 December 2024), 2023. a
Barras, H., Hering, A., Martynov, A., Noti, P.-A., Germann, U., and Martius, O.: Experiences with > 50,000 Crowdsourced Hail Reports in Switzerland, B. Am. Meteorol. Soc., 100, 1429–440, https://doi.org/10.1175/BAMS-D-18-0090.1, 2019. a
Brown, T. M., Pogorzelski, W. H., and Giammanco, I. M.: Evaluating Hail Damage Using Property Insurance Claims Data, Weather Clim. Soc., 7, 197–210, https://doi.org/10.1175/WCAS-D-15-0011.1, 2015. a
Changnon, S. A.: Hail Measurement Techniques for Evaluating Suppression Projects, J. Appl. Meteorol. Clim., 8, 596–603, https://doi.org/10.1175/1520-0450(1969)008<0596:HMTFES>2.0.CO;2, 1969. a
Cheng, L. and English, M.: A Relationship Between Hailstone Concentration and Size, J. Atmos. Sci., 40, 204–213, https://doi.org/10.1175/1520-0469(1983)040<0204:ARBHCA>2.0.CO;2, 1983. a
Douglas, R.: Size distributions of Alberta hail samples, McGill University Stormy Weather Research Group Sci. Rep. MW-36, 55–70, 1963. a
ETH Zurich: scClim: Seamless coupling of kilometer-resolution weather predictions and climate simulations with hail impact assessments for multiple sectors, https://scclim.ethz.ch/ (last access: 18 December 2024), 2023. a
Federal Office of Topography Swisstopo: The light version of the digital height model of Switzerland, https://www.swisstopo.admin.ch/en/geodata/height/dhm25.html (last access: 18 December 2024), 2021. a
Federer, B. and Waldvogel, A.: Hail and Raindrop Size Distributions from a Swiss Multicell Storm, J. Appl. Meteorol. Clim., 14, 91–97, https://doi.org/10.1175/1520-0450(1975)014<0091:HARSDF>2.0.CO;2, 1975. a
Federer, B., Waldvogel, A., Schmid, W., Schiesser, H. H., Hampel, F., Schweingruber, M., Stahel, W., Bader, J., Mezeix, J. F., Doras, N., D'Aubigny, G., DerMegreditchian, G., and Vento, D.: Main Results of Grossversuch IV, J. Appl. Meteorol. Clim., 25, 917–957, https://doi.org/10.1175/1520-0450(1986)025<0917:MROGI>2.0.CO;2, 1986. a
Feldmann, M., Hering, A., Gabella, M., and Berne, A.: Hailstorms and rainstorms versus supercells – a regional analysis of convective storm types in the Alpine region, npj Climate and Atmospheric Science, 6, 19, https://doi.org/10.1038/s41612-023-00352-z, 2023. a
Field, P. R., Heymsfield, A. J., Detwiler, A. G., and Wilkinson, J. M.: Normalized Hail Particle Size Distributions from the T-28 Storm-Penetrating Aircraft, J. Appl. Meteorol. Clim., 58, 231–245, https://doi.org/10.1175/JAMC-D-18-0118.1, 2019. a, b
Grieser, J. and Hill, M.: How to Express Hail Intensity–Modeling the Hailstone Size Distribution, J. Appl. Meteorol. Clim., 58, 2329 – 2345, https://doi.org/10.1175/JAMC-D-18-0334.1, 2019. a
Kopp, J., Manzato, A., Hering, A., Germann, U., and Martius, O.: How observations from automatic hail sensors in Switzerland shed light on local hailfall duration and compare with hailpad measurements, Atmos. Meas. Tech., 16, 3487–3503, https://doi.org/10.5194/amt-16-3487-2023, 2023a. a, b, c, d, e, f
Kopp, J., Schröer, K., Schwierz, C., Hering, A., Germann, U., and Martius, O.: The summer 2021 Switzerland hailstorms: weather situation, major impacts and unique observational data, Weather, 78, 184–191, https://doi.org/10.1002/wea.4306, 2023b. a
Lainer, M.: Hail Event on 2021-06-20 in Entlebuch (LU), Switzerland: Drone Photogrammetry Imagery, Hail Sensor Recordings, Mask R-CNN Model and Analysis Data of Hailstones, Zenodo [data set], https://doi.org/10.5281/zenodo.10609730, 2024. a
Lainer, M., Brennan, K. P., Hering, A., Kopp, J., Monhart, S., Wolfensberger, D., and Germann, U.: Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground, Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024, 2024. a, b, c
Lee, G., Bringi, V., and Thurai, M.: The Retrieval of Drop Size Distribution Parameters Using a Dual-Polarimetric Radar, Remote Sensing, 15, 1063, https://doi.org/10.3390/rs15041063, 2023. a
Löffler-Mang, M., Schön, D., and Landry, M.: Characteristics of a new automatic hail recorder, Atmos. Res., 100, 439–446, https://doi.org/10.1016/j.atmosres.2010.10.026, 2011. a
Marshall, J. S. and Palmer, W. M.: The distribution of raindrops with size, J. Atmos. Sci., 5, 165–166, https://doi.org/10.1175/1520-0469(1948)005<0165:TDORWS>2.0.CO;2, 1948. a
Mason, B. J.: On the melting of hailstones, Q. J. Roy. Meteor. Soc., 82, 209–216, https://doi.org/10.1002/qj.49708235207, 1956. a
NCCS: National Centre for Climate Services: Hail climatology Switzerland, https://www.nccs.admin.ch/nccs/en/home/the-nccs/priority-themes/hail-climate-switzerland.html (last access: 21 December 2023), 2021. a
Nisi, L., Martius, O., Hering, A., Kunz, M., and Germann, U.: Spatial and temporal distribution of hailstorms in the Alpine region: a long-term, high resolution, radar-based analysis, Q. J. Roy. Meteor. Soc., 142, 1590–1604, https://doi.org/10.1002/qj.2771, 2016. a
Nisi, L., Hering, A., Germann, U., and Martius, O.: A 15-year hail streak climatology for the Alpine region, Q. J. Roy. Meteor. Soc., 144, 1429–1449, https://doi.org/10.1002/qj.3286, 2018. a
Python Software Foundation: random – Generate pseudo-random numbers, https://docs.python.org/3/library/random.html (last access: 18 December 2024), 2023. a
Púčik, T., Castellano, C., Groenemeijer, P., Kühne, T., Rädler, A. T., Antonescu, B., and Faust, E.: Large Hail Incidence and Its Economic and Societal Impacts across Europe, Mon. Weather Rev., 147, 3901–3916, https://doi.org/10.1175/MWR-D-19-0204.1, 2019. a
Raupach, T. H. and Berne, A.: Retrieval of the raindrop size distribution from polarimetric radar data using double-moment normalisation, Atmos. Meas. Tech., 10, 2573–2594, https://doi.org/10.5194/amt-10-2573-2017, 2017. a, b, c, d
Sempere-Torres, D., Porrà, J. M., and Creutin, J.-D.: A General Formulation for Raindrop Size Distribution, J. Appl. Meteorol. Clim., 33, 1494–1502, https://doi.org/10.1175/1520-0450(1994)033<1494:AGFFRS>2.0.CO;2, 1994. a
Sempere-Torres, D., Porrà, J. M., and Creutin, J.-D.: Experimental evidence of a general description for raindrop size distribution properties, J. Geophys. Res.-Atmos., 103, 1785–1797, https://doi.org/10.1029/97JD02065, 1998. a, b
Ulbrich, C. W. and Atlas, D.: Hail Parameter Relations: A Comprehensive Digest, J. Appl. Meteorol. Clim., 21, 22–43, https://doi.org/10.1175/1520-0450(1982)021<0022:HPRACD>2.0.CO;2, 1982. a
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C. J., Polat, İ., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F., van Mulbregt, P., and SciPy 1.0 Contributors: SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python, Nat. Methods, 17, 261–272, https://doi.org/10.1038/s41592-019-0686-2, 2020. a
Waldvogel, A., Schmid, W., and Federer, B.: The Kinetic Energy of Hailfalls. Part I: Hailstone Spectra, J. Appl. Meteorol. Clim., 17, 515–520, https://doi.org/10.1175/1520-0450(1978)017<0515:TKEOHP>2.0.CO;2, 1978. a
Warren, R. A., Ramsay, H. A., Siems, S. T., Manton, M. J., Peter, J. R., Protat, A., and Pillalamarri, A.: Radar-based climatology of damaging hailstorms in Brisbane and Sydney, Australia, Q. J. Roy. Meteor. Soc., 146, 505–530, https://doi.org/10.1002/qj.3693, 2020. a
Wetzel, E.: Made to measure, https://www.innetag.ch/wp-content/uploads/2020/10/HailSens-MTI_2018_09.pdf (last access: 18 December 2024), 2018. a
Short summary
Estimates of hail size have been collected by a network of hail sensors, installed in three regions of Switzerland, since September 2018. In this study, we use a technique called “double-moment normalization” to model the distribution of diameter sizes. The parameters of the method have been defined over 70 % of the dataset and tested over the remaining 30 %. An independent distribution of hail sizes, collected by a drone, has also been used to evaluate the method.
Estimates of hail size have been collected by a network of hail sensors, installed in three...
