Articles | Volume 14, issue 4
https://doi.org/10.5194/amt-14-3169-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-3169-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Apr 2021
Research article |
| 29 Apr 2021
| 29 Apr 2021
RainForest: a random forest algorithm for quantitative precipitation estimation over Switzerland
Daniel Wolfensberger
LTE, Ecole polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
MeteoSwiss, via ai Monti 146, Locarno, Switzerland
Marco Gabella
MeteoSwiss, via ai Monti 146, Locarno, Switzerland
Marco Boscacci
MeteoSwiss, via ai Monti 146, Locarno, Switzerland
Urs Germann
MeteoSwiss, via ai Monti 146, Locarno, Switzerland
LTE, Ecole polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Jussi Leinonen, Ulrich Hamann, Urs Germann, and John R. Mecikalski
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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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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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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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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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Marc Schwaerzel, Dominik Brunner, Fabian Jakub, Claudia Emde, Brigitte Buchmann, Alexis Berne, and Gerrit Kuhlmann
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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.
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.
Rebecca Gugerli, Matteo Guidicelli, Marco Gabella, Matthias Huss, and Nadine Salzmann
Adv. Sci. Res., 18, 7–20, https://doi.org/10.5194/asr-18-7-2021, https://doi.org/10.5194/asr-18-7-2021, 2021
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To obtain reliable snowfall estimates in high mountain remains a challenge. This study uses daily snow water equivalent (SWE) estimates by a cosmic ray sensor on two Swiss glaciers to assess three
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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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Short summary
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.
Cited articles
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Short summary
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.
In this work, we present a novel quantitative precipitation estimation method for Switzerland...
