Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-441-2024
© 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-17-441-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Jan 2024
Research article |
| 23 Jan 2024
| 23 Jan 2024
Real-time pollen identification using holographic imaging and fluorescence measurements
Sophie Erb
CORRESPONDING AUTHOR
Federal Office of Meteorology and Climatology MeteoSwiss, 1530 Payerne, Switzerland
Environmental Remote Sensing Laboratory (LTE), École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
Elias Graf
Swisens AG, 6048 Horw, Switzerland
Yanick Zeder
Swisens AG, 6048 Horw, Switzerland
Simone Lionetti
Algorithmic Business Research Lab (ABIZ), Lucerne University of Applied Sciences and Arts, 6002 Lucerne, Switzerland
Alexis Berne
Environmental Remote Sensing Laboratory (LTE), École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
Bernard Clot
Federal Office of Meteorology and Climatology MeteoSwiss, 1530 Payerne, Switzerland
Gian Lieberherr
Federal Office of Meteorology and Climatology MeteoSwiss, 1530 Payerne, Switzerland
Fiona Tummon
Federal Office of Meteorology and Climatology MeteoSwiss, 1530 Payerne, Switzerland
Pascal Wullschleger
Algorithmic Business Research Lab (ABIZ), Lucerne University of Applied Sciences and Arts, 6002 Lucerne, Switzerland
Benoît Crouzy
Federal Office of Meteorology and Climatology MeteoSwiss, 1530 Payerne, Switzerland
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Marilena Gidarakou, Alexandros Papayannis, Kunfeng Gao, Panagiotis Gidarakos, Benoit Crouzy, Romanos Foskinis, Sophie Erb, Cuiqi Zhang, Gian Lieberherr, Martine Collaud Coen, Branko Sikoparija, Zamin A. Kanji, Bernard Clot, Bertrand Calpini, Eugenia Giagka, and Athanasios Nenes
EGUsphere, https://doi.org/10.5194/egusphere-2025-2978, https://doi.org/10.5194/egusphere-2025-2978, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Vertical profiles of pollen and biomass burning particles were obtained at a semi-rural site at the MeteoSwiss station near Payerne (Switzerland) using a novel multi-channel elastic-fluorescence lidar system combined with in situ measurements during the spring 2023 wildfires and pollination season during the PERICLES (PayernE lidaR and Insitu detection of fluorescent bioaerosol and dust partiCLES and their cloud impacts) campaign.
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
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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.
Valentin Wiener, Étienne Vignon, Thomas Caton Harrison, Christophe Genthon, Felipe Toledo, Guylaine Canut-Rocafort, Yann Meurdesoif, and Alexis Berne
EGUsphere, https://doi.org/10.5194/egusphere-2025-2046, https://doi.org/10.5194/egusphere-2025-2046, 2025
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Katabatic winds are a key feature of the climate of Antarctica, but substantial biases remain in their representation in atmospheric models. This study investigates a katabatic wind event in the ICOLMDZ model using in-situ observations. The framework allows to disentangle which part of the bias is due to horizontal resolution, to parameter calibration and to structural deficiencies in the model. We underline in particular the need to refine the physics of the model snow cover.
Marc Schneebeli, Andreas Leuenberger, Philipp J. Schmid, Jacopo Grazioli, Heather Corden, Alexis Berne, Patrick Kennedy, Jim George, Francesc Junyent, and V. Chandrasekar
EGUsphere, https://doi.org/10.5194/egusphere-2025-1702, https://doi.org/10.5194/egusphere-2025-1702, 2025
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A new technique for the end-to-end calibration of weather radars is introduced. Highly precise artificial radar targets are generated with a radar target simulator and serve as a calibration reference for weather radar observables like reflectivity and Doppler velocity. The system allows to investigate and correct any biases associated with weather radar observations.
Frédéric G. Jordan, Clément Cosson, Marco Gabella, Ioannis V. Sideris, Adrien Liernur, Alexis Berne, and Urs Germann
Abstr. Int. Cartogr. Assoc., 9, 19, https://doi.org/10.5194/ica-abs-9-19-2025, https://doi.org/10.5194/ica-abs-9-19-2025, 2025
Alfonso Ferrone, Jérôme Kopp, Martin Lainer, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 17, 7143–7168, https://doi.org/10.5194/amt-17-7143-2024, https://doi.org/10.5194/amt-17-7143-2024, 2024
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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.
Nicholas D. Beres, Julia Burkart, Elias Graf, Yanick Zeder, Lea Ann Dailey, and Bernadett Weinzierl
Atmos. Meas. Tech., 17, 6945–6964, https://doi.org/10.5194/amt-17-6945-2024, https://doi.org/10.5194/amt-17-6945-2024, 2024
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We tested a method to identify airborne microplastics (MPs), merging imaging, fluorescence, and machine learning of single particles. We examined whether combining imaging and fluorescence data enhances classification accuracy compared to using each method separately and tested these methods with other particle types. The tested MPs have distinct fluorescence, and a combined imaging and fluorescence method improves their detection, making meaningful progress in monitoring MPs in the atmosphere.
Kunfeng Gao, Franziska Vogel, Romanos Foskinis, Stergios Vratolis, Maria I. Gini, Konstantinos Granakis, Anne-Claire Billault-Roux, Paraskevi Georgakaki, Olga Zografou, Prodromos Fetfatzis, Alexis Berne, Alexandros Papayannis, Konstantinos Eleftheridadis, Ottmar Möhler, and Athanasios Nenes
Atmos. Chem. Phys., 24, 9939–9974, https://doi.org/10.5194/acp-24-9939-2024, https://doi.org/10.5194/acp-24-9939-2024, 2024
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Ice nucleating particle (INP) concentrations are required for correct predictions of clouds and precipitation in a changing climate, but they are poorly constrained in climate models. We unravel source contributions to INPs in the eastern Mediterranean and find that biological particles are important, regardless of their origin. The parameterizations developed exhibit superior performance and enable models to consider biological-particle effects on INPs.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
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This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
Alfonso Ferrone, Étienne Vignon, Andrea Zonato, and Alexis Berne
The Cryosphere, 17, 4937–4956, https://doi.org/10.5194/tc-17-4937-2023, https://doi.org/10.5194/tc-17-4937-2023, 2023
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In austral summer 2019/2020, three K-band Doppler profilers were deployed across the Sør Rondane Mountains, south of the Belgian base Princess Elisabeth Antarctica. Their measurements, along with atmospheric simulations and reanalyses, have been used to study the spatial variability in precipitation over the region, as well as investigate the interaction between the complex terrain and the typical flow associated with precipitating systems.
Anne-Claire Billault-Roux, Paraskevi Georgakaki, Josué Gehring, Louis Jaffeux, Alfons Schwarzenboeck, Pierre Coutris, Athanasios Nenes, and Alexis Berne
Atmos. Chem. Phys., 23, 10207–10234, https://doi.org/10.5194/acp-23-10207-2023, https://doi.org/10.5194/acp-23-10207-2023, 2023
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Secondary ice production plays a key role in clouds and precipitation. In this study, we analyze radar measurements from a snowfall event in the Jura Mountains. Complex signatures are observed, which reveal that ice crystals were formed through various processes. An analysis of multi-sensor data suggests that distinct ice multiplication processes were taking place. Both the methods used and the insights gained through this case study contribute to a better understanding of snowfall microphysics.
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data, 15, 1115–1132, https://doi.org/10.5194/essd-15-1115-2023, https://doi.org/10.5194/essd-15-1115-2023, 2023
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This article presents the datasets collected between November 2019 and February 2020 in the vicinity of the Belgian research base Princess Elisabeth Antarctica. Five meteorological radars, a multi-angle snowflake camera, three weather stations, and two radiometers have been deployed at five sites, up to a maximum distance of 30 km from the base. Their varied locations allow the study of spatial variability in snowfall and its interaction with the complex terrain in the region.
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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Better understanding and modeling snowfall properties and processes is relevant to many fields, ranging from weather forecasting to aircraft safety. Meteorological radars can be used to gain insights into the microphysics of snowfall. In this work, we propose a new method to retrieve snowfall properties from measurements of radars with different frequencies. It relies on an original deep-learning framework, which incorporates knowledge of the underlying physics, i.e., electromagnetic scattering.
Claudia Mignani, Lukas Zimmermann, Rigel Kivi, Alexis Berne, and Franz Conen
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
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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.
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.
Gian Lieberherr, Kevin Auderset, Bertrand Calpini, Bernard Clot, Benoît Crouzy, Martin Gysel-Beer, Thomas Konzelmann, José Manzano, Andrea Mihajlovic, Alireza Moallemi, David O'Connor, Branko Sikoparija, Eric Sauvageat, Fiona Tummon, and Konstantina Vasilatou
Atmos. Meas. Tech., 14, 7693–7706, https://doi.org/10.5194/amt-14-7693-2021, https://doi.org/10.5194/amt-14-7693-2021, 2021
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Today there is no standard procedure to validate bioaerosol and pollen monitors. Three instruments were tested, focusing on detecting particles of different sizes. Only one instrument was able to detect the smallest particles (0.5 µm Ø), whereas the others performed best at the largest tested particles (10 µm Ø). These results are the first step towards a standardised validation procedure. The need for a reference counting method for larger particles (pollen grains: 10–200 µm Ø) was emphasised.
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.
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.
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.
Josué Gehring, Alfonso Ferrone, Anne-Claire Billault-Roux, Nikola Besic, Kwang Deuk Ahn, GyuWon Lee, and Alexis Berne
Earth Syst. Sci. Data, 13, 417–433, https://doi.org/10.5194/essd-13-417-2021, https://doi.org/10.5194/essd-13-417-2021, 2021
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This article describes a dataset of precipitation and cloud measurements collected from November 2017 to March 2018 in Pyeongchang, South Korea. The dataset includes weather radar data and images of snowflakes. It allows for studying the snowfall intensity; wind conditions; and shape, size and fall speed of snowflakes. Classifications of the types of snowflakes show that aggregates of ice crystals were dominant. This dataset represents a unique opportunity to study snowfall in this region.
Georgia Sotiropoulou, Étienne Vignon, Gillian Young, Hugh Morrison, Sebastian J. O'Shea, Thomas Lachlan-Cope, Alexis Berne, and Athanasios Nenes
Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, https://doi.org/10.5194/acp-21-755-2021, 2021
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Summer clouds have a significant impact on the radiation budget of the Antarctic surface and thus on ice-shelf melting. However, these are poorly represented in climate models due to errors in their microphysical structure, including the number of ice crystals that they contain. We show that breakup from ice particle collisions can substantially magnify the ice crystal number concentration with significant implications for surface radiation. This process is currently missing in climate models.
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Short summary
In this study, we focus on an automatic bioaerosol measurement instrument and investigate the impact of using its fluorescence measurement for pollen identification. The fluorescence signal is used together with a pair of images from the same instrument to identify single pollen grains via neural networks. We test whether considering fluorescence as a supplementary input improves the pollen identification performance by comparing three different neural networks.
In this study, we focus on an automatic bioaerosol measurement instrument and investigate the...
