Articles | Volume 17, issue 8
https://doi.org/10.5194/amt-17-2539-2024
© 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-17-2539-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 May 2024
Research article |
| 02 May 2024
| 02 May 2024
Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground
Martin Lainer
CORRESPONDING AUTHOR
Federal Office of Meteorology and Climatology, MeteoSwiss, Locarno-Monti, Switzerland
Killian P. Brennan
Federal Office of Meteorology and Climatology, MeteoSwiss, Locarno-Monti, Switzerland
now at: Institute for Atmospheric and Climate Science, ETH Zurich, 8092 Zurich, Switzerland
Alessandro Hering
Federal Office of Meteorology and Climatology, MeteoSwiss, Locarno-Monti, Switzerland
Jérôme Kopp
Oeschger Centre for Climate Change Research, Bern, Switzerland
Institute of Geography, University of Bern, Bern, Switzerland
Samuel Monhart
CORRESPONDING AUTHOR
Federal Office of Meteorology and Climatology, MeteoSwiss, Locarno-Monti, Switzerland
Daniel Wolfensberger
Federal Office of Meteorology and Climatology, MeteoSwiss, Locarno-Monti, Switzerland
Urs Germann
Federal Office of Meteorology and Climatology, MeteoSwiss, Locarno-Monti, Switzerland
Related authors
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
Short summary
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.
Marco Gabella, Martin Lainer, Daniel Wolfensberger, and Jacopo Grazioli
Atmos. Meas. Tech., 16, 4409–4422, https://doi.org/10.5194/amt-16-4409-2023, https://doi.org/10.5194/amt-16-4409-2023, 2023
Short summary
Short summary
A still wind turbine observed with a fixed-pointing radar antenna has shown distinctive polarimetric signatures: the correlation coefficient between the two orthogonal polarization states was persistently equal to 1. The differential reflectivity and the radar reflectivity factors were also stable in time. Over 2 min (2000 Hz, 128 pulses were used; consequently, the sampling time was 64 ms), the standard deviation of the differential backscattering phase shift was only a few degrees.
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
Short summary
Short summary
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.
Martin Lainer, Klemens Hocke, Ellen Eckert, and Niklaus Kämpfer
Atmos. Chem. Phys., 19, 6611–6620, https://doi.org/10.5194/acp-19-6611-2019, https://doi.org/10.5194/acp-19-6611-2019, 2019
Short summary
Short summary
A middle atmospheric water vapor time series of more than 11 years (April 2007 to May 2018) from the NDACC microwave remote sensing site at Bern (Switzerland) is investigated to estimate the trend by means of a robust multilinear parametric trend model. Between 61 and 72 km altitude a significant decline in water vapor could be detected. The reduction of water vapor maximizes to about −12 % per decade at 72 km altitude.
Martin Lainer, Klemens Hocke, and Niklaus Kämpfer
Atmos. Chem. Phys., 18, 12061–12074, https://doi.org/10.5194/acp-18-12061-2018, https://doi.org/10.5194/acp-18-12061-2018, 2018
Short summary
Short summary
A long continuous record (in total 7 years) of middle atmospheric water vapor at the midlatitude NDACC station in Bern is investigated to study quasi 2-day wave oscillations (Q2DWs). We present monthly climatologies of the wave amplitudes and show the periods that the Q2DWs developed. What we observe is very-high-frequency variability. An autobicoherence analysis revealed nonlinear phase couplings between Q2DWs and other atmospheric waves. Our results are useful for model validation purposes.
Martin Lainer, Klemens Hocke, Rolf Rüfenacht, and Niklaus Kämpfer
Atmos. Chem. Phys., 17, 14905–14917, https://doi.org/10.5194/acp-17-14905-2017, https://doi.org/10.5194/acp-17-14905-2017, 2017
Short summary
Short summary
We report on middle-atmospheric water vapor measurements above Bern from the ground-based microwave radiometer MIAWARA (NDACC affiliated) during two winter periods of 6 months. Quasi 18 h oscillations of mesospheric water vapor above 0.1 hPa are observed. Further, the 18 h wave is seen in a zonal wind data set from the Doppler wind radiometer WIRA. Inertia-gravity-wave-induced fluctuations or a nonlinear coupling between tides and quasi 2-day waves are considered as possible drivers.
Gerald E. Nedoluha, Michael Kiefer, Stefan Lossow, R. Michael Gomez, Niklaus Kämpfer, Martin Lainer, Peter Forkman, Ole Martin Christensen, Jung Jin Oh, Paul Hartogh, John Anderson, Klaus Bramstedt, Bianca M. Dinelli, Maya Garcia-Comas, Mark Hervig, Donal Murtagh, Piera Raspollini, William G. Read, Karen Rosenlof, Gabriele P. Stiller, and Kaley A. Walker
Atmos. Chem. Phys., 17, 14543–14558, https://doi.org/10.5194/acp-17-14543-2017, https://doi.org/10.5194/acp-17-14543-2017, 2017
Short summary
Short summary
As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. In the lower mesosphere, we quantify instrumental differences in the observed trends and annual variations at six sites. We then present a range of observed trends in water vapor over the past 20 years.
Klemens Hocke, Martin Lainer, Lorena Moreira, Jonas Hagen, Susana Fernandez Vidal, and Franziska Schranz
Ann. Geophys., 34, 781–788, https://doi.org/10.5194/angeo-34-781-2016, https://doi.org/10.5194/angeo-34-781-2016, 2016
Short summary
Short summary
The dense horizontal sampling of atmospheric temperature profiles by the microwave limb sounder MLS on the NASA satellite AURA permit the estimation of global distributions of inertia-gravity waves (IGWs) in the middle atmosphere. We present and discuss the estimated global distributions of IGWs for July 2015 and January 2016. A dependence on the zonal wind distribution is obvious. The distributions of IGWs are a bit similar to the global distributions of small-scale gravity waves.
M. Lainer, N. Kämpfer, B. Tschanz, G. E. Nedoluha, S. Ka, and J. J. Oh
Atmos. Chem. Phys., 15, 9711–9730, https://doi.org/10.5194/acp-15-9711-2015, https://doi.org/10.5194/acp-15-9711-2015, 2015
Short summary
Short summary
We use water vapor profiles from ground-based microwave radiometers at five locations distributed over the Northern Hemisphere and operated in the frame of NDACC (Network for the Detection of Atmospheric Composition Change) to generate hemispheric water vapor maps based on the so-called trajectory mapping technique. The novelty is to show that a mini network of instruments is capable of providing information about the hemispheric distribution of water vapor under most conditions.
K. Hocke, M. Lainer, and A. Schanz
Ann. Geophys., 33, 783–788, https://doi.org/10.5194/angeo-33-783-2015, https://doi.org/10.5194/angeo-33-783-2015, 2015
Short summary
Short summary
The composite analysis of major sudden stratospheric warmings (SSW) showed changes in atmospheric parameters at mid-latitudes about 1-2 months before the central date of the SSW. Polar ozone is enhanced during the half year after the SSW event.
Killian P. Brennan, Michael Sprenger, André Walser, Marco Arpagaus, and Heini Wernli
Weather Clim. Dynam., 6, 645–668, https://doi.org/10.5194/wcd-6-645-2025, https://doi.org/10.5194/wcd-6-645-2025, 2025
Short summary
Short summary
We studied severe hailstorms that occurred in Switzerland on 28 June 2021 using a weather prediction model to understand how they evolved. We found that the storms moved toward areas with more storm energy. Hailfall was quickly followed by heavy rain. Just before the storms died out, the air feeding them stopped coming from near the ground. We also observed a delay between different types of precipitation forming in the incoming air.
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
Killian P. Brennan, Iris Thurnherr, Michael Sprenger, and Heini Wernli
EGUsphere, https://doi.org/10.5194/egusphere-2025-918, https://doi.org/10.5194/egusphere-2025-918, 2025
Short summary
Short summary
Hailstorms can cause severe damage to homes, crops, and infrastructure. Using high-resolution climate simulations, we tracked thousands of hailstorms across Europe to study future changes. Large hail will become more frequent, hail-covered areas will expand, and extreme hail combined with heavy rain will double. These shifts could increase risks for communities and businesses, highlighting the need for better preparedness and adaptation.
Alexandre Bugnard, Martine Collaud Coen, Maxime Hervo, Daniel Leuenberger, Marco Arpagaus, and Samuel Monhart
Atmos. Meas. Tech., 18, 1039–1061, https://doi.org/10.5194/amt-18-1039-2025, https://doi.org/10.5194/amt-18-1039-2025, 2025
Short summary
Short summary
Temperature (T) and wind profiles were measured by a Doppler wind lidar and a microwave radiometer in Meiringen in a medium-sized Alpine valley. Ground-based T inversions and thermal winds were studied during the 10 months of the campaign. The comparison between the observations and the COSMO-1E model provides good model performance for monthly climatologies. T inversions are however frequently missed, and important differences for particular cases are found, especially for foehn events.
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
Short summary
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.
Killian P. Brennan and Lena Wilhelm
EGUsphere, https://doi.org/10.5194/egusphere-2024-3924, https://doi.org/10.5194/egusphere-2024-3924, 2024
Short summary
Short summary
In this study, we discovered that natural dust carried into Europe significantly increases the likelihood of hailstorms. By analyzing dust data, weather records, and hail reports, we found that moderate dust levels lead to more frequent hail, while very high or low dust amounts reduce it. Adding dust information into statistical models improved forecasting skills. We aimed to understand how dust affects hailstorms.
Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius
Atmos. Meas. Tech., 17, 4529–4552, https://doi.org/10.5194/amt-17-4529-2024, https://doi.org/10.5194/amt-17-4529-2024, 2024
Short summary
Short summary
We present a verification of two products based on weather radars to detect the presence of hail and estimate its size. Radar products are remote detection of hail, so they must be verified against ground-based observations. We use reports from users of the Swiss Weather Services phone app to do the verification. We found that the product estimating the presence of hail provides fair results but that it should be recalibrated and that estimating the hail size with radar is more challenging.
Loris Foresti, Bernat Puigdomènech Treserras, Daniele Nerini, Aitor Atencia, Marco Gabella, Ioannis V. Sideris, Urs Germann, and Isztar Zawadzki
Nonlin. Processes Geophys., 31, 259–286, https://doi.org/10.5194/npg-31-259-2024, https://doi.org/10.5194/npg-31-259-2024, 2024
Short summary
Short summary
We compared two ways of defining the phase space of low-dimensional attractors describing the evolution of radar precipitation fields. The first defines the phase space by the domain-scale statistics of precipitation fields, such as their mean, spatial and temporal correlations. The second uses principal component analysis to account for the spatial distribution of precipitation. To represent different climates, radar archives over the United States and the Swiss Alpine region were used.
Marco Gabella, Martin Lainer, Daniel Wolfensberger, and Jacopo Grazioli
Atmos. Meas. Tech., 16, 4409–4422, https://doi.org/10.5194/amt-16-4409-2023, https://doi.org/10.5194/amt-16-4409-2023, 2023
Short summary
Short summary
A still wind turbine observed with a fixed-pointing radar antenna has shown distinctive polarimetric signatures: the correlation coefficient between the two orthogonal polarization states was persistently equal to 1. The differential reflectivity and the radar reflectivity factors were also stable in time. Over 2 min (2000 Hz, 128 pulses were used; consequently, the sampling time was 64 ms), the standard deviation of the differential backscattering phase shift was only a few degrees.
Jérôme Kopp, Agostino Manzato, Alessandro Hering, Urs Germann, and Olivia Martius
Atmos. Meas. Tech., 16, 3487–3503, https://doi.org/10.5194/amt-16-3487-2023, https://doi.org/10.5194/amt-16-3487-2023, 2023
Short summary
Short summary
We present the first study of extended field observations made by a network of 80 automatic hail sensors from Switzerland. The sensors record the exact timing of hailstone impacts, providing valuable information about the local duration of hailfall. We found that the majority of hailfalls lasts just a few minutes and that most hailstones, including the largest, fall during a first phase of high hailstone density, while a few remaining and smaller hailstones fall in a second low-density phase.
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
Short summary
Short summary
We evaluate the usefulness of different data sources and variables to the short-term prediction (
nowcasting) of severe thunderstorms using machine learning. Machine-learning models are trained with data from weather radars, satellite images, lightning detection and weather forecasts and with terrain elevation data. We analyze the benefits provided by each of the data sources to predicting hazards (heavy precipitation, lightning and hail) caused by the thunderstorms.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Timothy H. Raupach, Andrey Martynov, Luca Nisi, Alessandro Hering, Yannick Barton, and Olivia Martius
Geosci. Model Dev., 14, 6495–6514, https://doi.org/10.5194/gmd-14-6495-2021, https://doi.org/10.5194/gmd-14-6495-2021, 2021
Short summary
Short summary
When simulated thunderstorms are compared to observations or other simulations, a match between overall storm properties is often more important than exact matches to individual storms. We tested a comparison method that uses a thunderstorm tracking algorithm to characterise simulated storms. For May 2018 in Switzerland, the method produced reasonable matches to independent observations for most storm properties, showing its feasibility for summarising simulated storms over mountainous terrain.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
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.
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
Short summary
Short summary
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.
Floor van den Heuvel, Loris Foresti, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 13, 2481–2500, https://doi.org/10.5194/amt-13-2481-2020, https://doi.org/10.5194/amt-13-2481-2020, 2020
Short summary
Short summary
In areas with reduced visibility at the ground level, radar precipitation measurements higher up in the atmosphere need to be extrapolated to the ground and be corrected for the vertical change (i.e. growth and transformation) of precipitation. This study proposes a method based on hydrometeor proportions and machine learning (ML) to apply these corrections at smaller spatiotemporal scales. In comparison with existing techniques, the ML methods can make predictions from higher altitudes.
Jordi Figueras i Ventura, Nicolau Pineda, Nikola Besic, Jacopo Grazioli, Alessandro Hering, Oscar A. van der Velde, David Romero, Antonio Sunjerga, Amirhossein Mostajabi, Mohammad Azadifar, Marcos Rubinstein, Joan Montanyà, Urs Germann, and Farhad Rachidi
Atmos. Meas. Tech., 12, 5573–5591, https://doi.org/10.5194/amt-12-5573-2019, https://doi.org/10.5194/amt-12-5573-2019, 2019
Short summary
Short summary
This paper presents an analysis of the lightning production of convective cells. Polarimetric weather radar data were used to identify and characterize the convective cells while lightning was detected using the EUCLID network and a lightning mapping array deployed during the summer of 2017 in the northeastern part of Switzerland. In it we show that there is a good correlation between the height of the rimed-particle column and the intensity of the lightning activity in the convective cell.
Seppo Pulkkinen, Daniele Nerini, Andrés A. Pérez Hortal, Carlos Velasco-Forero, Alan Seed, Urs Germann, and Loris Foresti
Geosci. Model Dev., 12, 4185–4219, https://doi.org/10.5194/gmd-12-4185-2019, https://doi.org/10.5194/gmd-12-4185-2019, 2019
Short summary
Short summary
Reliable precipitation forecasts are vital for the society, as water-related hazards can cause economic losses and loss of lives. Pysteps is an open-source Python library for radar-based precipitation forecasting. It aims to be a well-documented platform for development of new methods as well as an easy-to-use tool for practitioners. The potential of the library is demonstrated by case studies and scientific experiments using radar data from Finland, Switzerland, the United States and Australia.
Jordi Figueras i Ventura, Nicolau Pineda, Nikola Besic, Jacopo Grazioli, Alessandro Hering, Oscar A. van der Velde, David Romero, Antonio Sunjerga, Amirhossein Mostajabi, Mohammad Azadifar, Marcos Rubinstein, Joan Montanyà, Urs Germann, and Farhad Rachidi
Atmos. Meas. Tech., 12, 2881–2911, https://doi.org/10.5194/amt-12-2881-2019, https://doi.org/10.5194/amt-12-2881-2019, 2019
Short summary
Short summary
This paper presents an analysis of a large dataset of lightning and polarimetric weather radar data collected over the course of a lightning measurement campaign that took place in the summer of 2017 in the area surrounding Säntis in northeastern Switzerland. We show that polarimetric weather radar data can be helpful in determining regions where lightning is more likely to occur, which is a first step towards a lightning nowcasting system.
Martin Lainer, Klemens Hocke, Ellen Eckert, and Niklaus Kämpfer
Atmos. Chem. Phys., 19, 6611–6620, https://doi.org/10.5194/acp-19-6611-2019, https://doi.org/10.5194/acp-19-6611-2019, 2019
Short summary
Short summary
A middle atmospheric water vapor time series of more than 11 years (April 2007 to May 2018) from the NDACC microwave remote sensing site at Bern (Switzerland) is investigated to estimate the trend by means of a robust multilinear parametric trend model. Between 61 and 72 km altitude a significant decline in water vapor could be detected. The reduction of water vapor maximizes to about −12 % per decade at 72 km altitude.
Samuel Monhart, Massimiliano Zappa, Christoph Spirig, Christoph Schär, and Konrad Bogner
Hydrol. Earth Syst. Sci., 23, 493–513, https://doi.org/10.5194/hess-23-493-2019, https://doi.org/10.5194/hess-23-493-2019, 2019
Short summary
Short summary
Subseasonal streamflow forecasts have received increasing attention during the past decade, but their performance in alpine catchments is still largely unknown. We analyse the effect of a statistical correction technique applied to the driving meteorological forecasts on the performance of the resulting streamflow forecasts. The study shows the benefits of such hydrometeorological ensemble prediction systems and highlights the importance of snow-related processes for subseasonal predictions.
Franziska Gerber, Nikola Besic, Varun Sharma, Rebecca Mott, Megan Daniels, Marco Gabella, Alexis Berne, Urs Germann, and Michael Lehning
The Cryosphere, 12, 3137–3160, https://doi.org/10.5194/tc-12-3137-2018, https://doi.org/10.5194/tc-12-3137-2018, 2018
Short summary
Short summary
A comparison of winter precipitation variability in operational radar measurements and high-resolution simulations reveals that large-scale variability is well captured by the model, depending on the event. Precipitation variability is driven by topography and wind. A good portion of small-scale variability is captured at the highest resolution. This is essential to address small-scale precipitation processes forming the alpine snow seasonal snow cover – an important source of water.
Floor van den Heuvel, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 11, 5181–5198, https://doi.org/10.5194/amt-11-5181-2018, https://doi.org/10.5194/amt-11-5181-2018, 2018
Short summary
Short summary
The paper aims at characterising and quantifying the spatio-temporal variability of the melting layer (ML; transition zone from solid to liquid precipitation). A method based on the Fourier transform is found to accurately describe different ML signatures. Hence, it is applied to characterise the ML variability in a relatively flat area and in an inner Alpine valley in Switzerland, where the variability at smaller spatial scales is found to be relatively more important.
Martin Lainer, Klemens Hocke, and Niklaus Kämpfer
Atmos. Chem. Phys., 18, 12061–12074, https://doi.org/10.5194/acp-18-12061-2018, https://doi.org/10.5194/acp-18-12061-2018, 2018
Short summary
Short summary
A long continuous record (in total 7 years) of middle atmospheric water vapor at the midlatitude NDACC station in Bern is investigated to study quasi 2-day wave oscillations (Q2DWs). We present monthly climatologies of the wave amplitudes and show the periods that the Q2DWs developed. What we observe is very-high-frequency variability. An autobicoherence analysis revealed nonlinear phase couplings between Q2DWs and other atmospheric waves. Our results are useful for model validation purposes.
Nikola Besic, Josué Gehring, Christophe Praz, Jordi Figueras i Ventura, Jacopo Grazioli, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 11, 4847–4866, https://doi.org/10.5194/amt-11-4847-2018, https://doi.org/10.5194/amt-11-4847-2018, 2018
Short summary
Short summary
In this paper we propose an innovative approach for hydrometeor de-mixing, i.e., to identify and quantify the presence of mixtures of different hydrometeor types in a radar sampling volume. It is a bin-based approach, inspired by conventional decomposition methods and evaluated using C- and X-band radar measurements compared with synchronous ground observations. The paper also investigates the potential influence of incoherency in the backscattering from hydrometeor mixtures in a radar volume.
Daniel Wolfensberger and Alexis Berne
Atmos. Meas. Tech., 11, 3883–3916, https://doi.org/10.5194/amt-11-3883-2018, https://doi.org/10.5194/amt-11-3883-2018, 2018
Short summary
Short summary
This work presents a polarimetric forward operator for the COSMO weather prediction model. This tool is able to simulate radar observables from the state of the atmosphere simulated by the model, taking into account most physical aspects of radar beam propagation and backscattering. This operator was validated with a large dataset of radar observations from several instruments and it was shown that is able to simulate a realistic radar signature in liquid precipitation.
Martin Lainer, Klemens Hocke, Rolf Rüfenacht, and Niklaus Kämpfer
Atmos. Chem. Phys., 17, 14905–14917, https://doi.org/10.5194/acp-17-14905-2017, https://doi.org/10.5194/acp-17-14905-2017, 2017
Short summary
Short summary
We report on middle-atmospheric water vapor measurements above Bern from the ground-based microwave radiometer MIAWARA (NDACC affiliated) during two winter periods of 6 months. Quasi 18 h oscillations of mesospheric water vapor above 0.1 hPa are observed. Further, the 18 h wave is seen in a zonal wind data set from the Doppler wind radiometer WIRA. Inertia-gravity-wave-induced fluctuations or a nonlinear coupling between tides and quasi 2-day waves are considered as possible drivers.
Gerald E. Nedoluha, Michael Kiefer, Stefan Lossow, R. Michael Gomez, Niklaus Kämpfer, Martin Lainer, Peter Forkman, Ole Martin Christensen, Jung Jin Oh, Paul Hartogh, John Anderson, Klaus Bramstedt, Bianca M. Dinelli, Maya Garcia-Comas, Mark Hervig, Donal Murtagh, Piera Raspollini, William G. Read, Karen Rosenlof, Gabriele P. Stiller, and Kaley A. Walker
Atmos. Chem. Phys., 17, 14543–14558, https://doi.org/10.5194/acp-17-14543-2017, https://doi.org/10.5194/acp-17-14543-2017, 2017
Short summary
Short summary
As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. In the lower mesosphere, we quantify instrumental differences in the observed trends and annual variations at six sites. We then present a range of observed trends in water vapor over the past 20 years.
Daniel Wolfensberger, Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer, and Alexis Berne
Atmos. Chem. Phys., 17, 14253–14273, https://doi.org/10.5194/acp-17-14253-2017, https://doi.org/10.5194/acp-17-14253-2017, 2017
Short summary
Short summary
Precipitation intensities simulated by the COSMO weather prediction model are compared to radar observations over a range of spatial and temporal scales using the universal multifractal framework. Our results highlight the strong influence of meteorological and topographical features on the multifractal characteristics of precipitation. Moreover, the influence of the subgrid parameterizations of COSMO is clearly visible by a break in the scaling properties that is absent from the radar data.
Daniele Nerini, Nikola Besic, Ioannis Sideris, Urs Germann, and Loris Foresti
Hydrol. Earth Syst. Sci., 21, 2777–2797, https://doi.org/10.5194/hess-21-2777-2017, https://doi.org/10.5194/hess-21-2777-2017, 2017
Short summary
Short summary
Stochastic generators are effective tools for the quantification of uncertainty in a number of applications with weather radar data, including quantitative precipitation estimation and very short-term forecasting. However, most of the current stochastic rainfall field generators cannot handle spatial non-stationarity. We propose an approach based on the short-space Fourier transform, which aims to reproduce the local spatial structure of the observed rainfall fields.
Klemens Hocke, Martin Lainer, Lorena Moreira, Jonas Hagen, Susana Fernandez Vidal, and Franziska Schranz
Ann. Geophys., 34, 781–788, https://doi.org/10.5194/angeo-34-781-2016, https://doi.org/10.5194/angeo-34-781-2016, 2016
Short summary
Short summary
The dense horizontal sampling of atmospheric temperature profiles by the microwave limb sounder MLS on the NASA satellite AURA permit the estimation of global distributions of inertia-gravity waves (IGWs) in the middle atmosphere. We present and discuss the estimated global distributions of IGWs for July 2015 and January 2016. A dependence on the zonal wind distribution is obvious. The distributions of IGWs are a bit similar to the global distributions of small-scale gravity waves.
Nikola Besic, Jordi Figueras i Ventura, Jacopo Grazioli, Marco Gabella, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, https://doi.org/10.5194/amt-9-4425-2016, 2016
Short summary
Short summary
In this paper we propose a novel semi-supervised method for hydrometeor classification, which takes into account both the specificities of acquired polarimetric radar measurements and the presumed electromagnetic behavior of different hydrometeor types. The method has been applied on three datasets, each acquired by different C-band radar from the Swiss network, and on two X-band research radar datasets. The obtained classification is found to be of high quality.
Luca Panziera, Marco Gabella, Stefano Zanini, Alessandro Hering, Urs Germann, and Alexis Berne
Hydrol. Earth Syst. Sci., 20, 2317–2332, https://doi.org/10.5194/hess-20-2317-2016, https://doi.org/10.5194/hess-20-2317-2016, 2016
Short summary
Short summary
This paper presents a novel system to issue heavy rainfall alerts for predefined geographical regions by evaluating the sum of precipitation fallen in the immediate past and expected in the near future. In order to objectively define the thresholds for the alerts, an extreme rainfall analysis for the 159 regions used for official warnings in Switzerland was developed. It is shown that the system has additional lead time with respect to thunderstorm tracking tools targeted for convective storms.
M. Lainer, N. Kämpfer, B. Tschanz, G. E. Nedoluha, S. Ka, and J. J. Oh
Atmos. Chem. Phys., 15, 9711–9730, https://doi.org/10.5194/acp-15-9711-2015, https://doi.org/10.5194/acp-15-9711-2015, 2015
Short summary
Short summary
We use water vapor profiles from ground-based microwave radiometers at five locations distributed over the Northern Hemisphere and operated in the frame of NDACC (Network for the Detection of Atmospheric Composition Change) to generate hemispheric water vapor maps based on the so-called trajectory mapping technique. The novelty is to show that a mini network of instruments is capable of providing information about the hemispheric distribution of water vapor under most conditions.
K. Hocke, M. Lainer, and A. Schanz
Ann. Geophys., 33, 783–788, https://doi.org/10.5194/angeo-33-783-2015, https://doi.org/10.5194/angeo-33-783-2015, 2015
Short summary
Short summary
The composite analysis of major sudden stratospheric warmings (SSW) showed changes in atmospheric parameters at mid-latitudes about 1-2 months before the central date of the SSW. Polar ozone is enhanced during the half year after the SSW event.
J. Grazioli, D. Tuia, S. Monhart, M. Schneebeli, T. Raupach, and A. Berne
Atmos. Meas. Tech., 7, 2869–2882, https://doi.org/10.5194/amt-7-2869-2014, https://doi.org/10.5194/amt-7-2869-2014, 2014
K. Liechti, L. Panziera, U. Germann, and M. Zappa
Hydrol. Earth Syst. Sci., 17, 3853–3869, https://doi.org/10.5194/hess-17-3853-2013, https://doi.org/10.5194/hess-17-3853-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Combining commercial microwave links and weather radar for classification of dry snow and rainfall
Improved consistency in solar-induced fluorescence retrievals from GOME-2A with the SIFTER v3 algorithm
An information content approach to diagnosing and improving CLIMCAPS retrieval consistency across instruments and satellites
Characterizing urban planetary boundary layer dynamics using 3-year Doppler wind lidar measurements in a western Yangtze River Delta city, China
Radar-based high-resolution ensemble precipitation analyses over the French Alps
Gravity waves above the northern Atlantic and Europe during streamer events using Aeolus
Observations of tall-building wakes using a scanning Doppler lidar
A new method to retrieve relative humidity profiles from a synergy of Raman lidar, microwave radiometer and satellite
Mid-Atlantic nocturnal low-level jet characteristics: a machine learning analysis of radar wind profiles
Mitigating radome-induced bias in X-band weather radar polarimetric moments using an adaptive discrete Fourier transform algorithm
GNSS-RO residual ionospheric error (RIE): a new method and assessment
Best Estimate of the Planetary Boundary Layer Height from Multiple Remote Sensing Measurements
Benchmarking KDP in rainfall: a quantitative assessment of estimation algorithms using C-band weather radar observations
Comparative experimental validation of microwave hyperspectral atmospheric soundings in clear-sky conditions
Propagating Information Content: An Example with Advection
Global Navigation Satellite System (GNSS) radio occultation climatologies mapped by machine learning and Bayesian interpolation
Use of commercial microwave links as scintillometers: potential and limitations towards evaporation estimation
Determination of low-level temperature profiles from microwave radiometer observations during rain
Aeolus lidar surface return (LSR) at 355 nm as a new Aeolus Level-2A product
Sampling the diurnal and annual cycles of the Earth's energy imbalance with constellations of satellite-borne radiometers
Retrieval of top-of-atmosphere fluxes from combined EarthCARE lidar, imager, and broadband radiometer observations: the BMA-FLX product
Analysis of the measurement uncertainty for a 3D wind lidar
Improving solution availability and temporal consistency of an optimal-estimation physical retrieval for ground-based thermodynamic boundary layer profiling
Reconstruction of 3D precipitation measurements from FY-3G MWRI-RM imaging and sounding channels
An improved geolocation methodology for spaceborne radar and lidar systems
Combining low- and high-frequency microwave radiometer measurements from the MOSAiC expedition for enhanced water vapour products
An LES Exploration of the Assumptions used in Retrieving Entrainment from a Mixing Diagram Approach with Ground-Based Remote Sensors
HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and TEmporal Resolution
Retrieving Tropospheric Refractivity Structure using Interferometry of Aircraft Radio Transmissions
TanSat-2: a new satellite for mapping solar-induced chlorophyll fluorescence at both red and far-red bands with high spatio-temporal resolution
Global-scale gravity wave analysis methodology for the ESA Earth Explorer 11 candidate CAIRT
Evolution of Wind Field in the Atmospheric Boundary Layer with using of Multiple Sources Observations during the Transit of Super Typhoon Doksuri (2305)
Retrieval of pseudo-BRDF-adjusted surface reflectance at 440 nm from the Geostationary Environmental Monitoring Spectrometer (GEMS)
Drop size distribution retrieval using dual-polarization radar at C-band and S-band
Thermal tides in the middle atmosphere at mid-latitudes measured with a ground-based microwave radiometer
Global sensitivity analysis of simulated remote sensing polarimetric observations over snow
Improving the Gaussianity of radar reflectivity departures between observations and simulations using symmetric rain rates
On the temperature stability requirements of free-running Nd:YAG lasers for atmospheric temperature profiling through the rotational Raman technique
Limitations in wavelet analysis of non-stationary atmospheric gravity wave signatures in temperature profiles
A new non-linearity correction method for the spectrum from the Geostationary Inferometric Infrared Sounder on board Fengyun-4 satellites and its preliminary assessments
Observing atmospheric rivers using multi-GNSS airborne radio occultation: system description and data evaluation
Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data
Unfiltering of the EarthCARE Broadband Radiometer (BBR) observations: the BM-RAD product
Variance estimations in the presence of intermittent interference and their applications to incoherent scatter radar signal processing
A clustering-based method for identifying and tracking squall lines
A multi-instrument fuzzy logic boundary-layer-top detection algorithm
Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models
Scale separation for gravity wave analysis from 3D temperature observations in the mesosphere and lower thermosphere (MLT) region
A Machine-learning Based Marine Planetary Boundary Layer (MPBL) Moisture Profile Retrieval Product from GNSS-RO Deep Refraction Signals
Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere
Erlend Øydvin, Renaud Gaban, Jafet Andersson, Remco (C. Z.) van de Beek, Mareile Astrid Wolff, Nils-Otto Kitterød, Christian Chwala, and Vegard Nilsen
Atmos. Meas. Tech., 18, 2279–2293, https://doi.org/10.5194/amt-18-2279-2025, https://doi.org/10.5194/amt-18-2279-2025, 2025
Short summary
Short summary
We present a novel method for classifying rain and snow by combining data from commercial microwave links (CMLs) with weather radar. We compare this to a reference method using dew point temperature for precipitation type classification. Evaluations with nearby disdrometers show that CMLs improve the classification of dry snow and rainfall, outperforming the reference method.
Juliëtte C. S. Anema, K. Folkert Boersma, Lieuwe G. Tilstra, Olaf N. E. Tuinder, and Willem W. Verstraeten
Atmos. Meas. Tech., 18, 1961–1979, https://doi.org/10.5194/amt-18-1961-2025, https://doi.org/10.5194/amt-18-1961-2025, 2025
Short summary
Short summary
Long-term records of plant fluorescence offer vital insights into changing vegetation activity. The GOME-2A sensor provides extensive global observations but suffers from calibration and instrument degradation, which affects data consistency. This study presents the SIFTER v3 algorithm, which effectively resolves these issues and includes other improvements, resulting in robust, accurate, and consistent GOME-2A fluorescence measurements from 2007 to 2017.
Nadia Smith and Christopher D. Barnet
Atmos. Meas. Tech., 18, 1823–1839, https://doi.org/10.5194/amt-18-1823-2025, https://doi.org/10.5194/amt-18-1823-2025, 2025
Short summary
Short summary
CLIMCAPS extends the Aqua AIRS+AMSU record with retrievals from CrIS+ATMS on Suomi National Polar-orbiting Partnership (SNPP) and Joint Polar Satellite System series (JPSS-1 to JPSS-4). With “continuous”, we mean a data record that is consistent in its characterization of natural variation despite changes in source instrumentation. Here we investigate how sounding continuity can improve across the full CLIMCAPS record (2002 to the present day), spanning multiple instruments and satellites.
Tianwen Wei, Mengya Wang, Kenan Wu, Jinlong Yuan, Haiyun Xia, and Simone Lolli
Atmos. Meas. Tech., 18, 1841–1857, https://doi.org/10.5194/amt-18-1841-2025, https://doi.org/10.5194/amt-18-1841-2025, 2025
Short summary
Short summary
This study analyzes three years of wind lidar measurements to explore the dynamics of the urban planetary boundary layer in Hefei, China. Results reveal that nocturnal low-level jets are most frequent in spring and intensify in summer, significantly enhancing turbulence and shear near the surface, particularly at night. Additionally, cloud cover raises the mixing layer height by approximately 100 m at night due to the greenhouse effect but reduces it by up to 200 m in the afternoon.
Matthieu Vernay, Matthieu Lafaysse, and Clotilde Augros
Atmos. Meas. Tech., 18, 1731–1755, https://doi.org/10.5194/amt-18-1731-2025, https://doi.org/10.5194/amt-18-1731-2025, 2025
Short summary
Short summary
This paper provides a comprehensive evaluation of the quality of radar-based precipitation estimation in mountainous areas and presents a method to mitigate the main shortcomings identified. It then compares three different ensemble analysis methods that combine radar-based precipitation estimates with forecasts from an ensemble numerical weather prediction model.
Sabine Wüst, Lisa Küchelbacher, Franziska Trinkl, and Michael Bittner
Atmos. Meas. Tech., 18, 1591–1607, https://doi.org/10.5194/amt-18-1591-2025, https://doi.org/10.5194/amt-18-1591-2025, 2025
Short summary
Short summary
Information on the energy transported by atmospheric gravity waves (GWs) is crucial for improving atmosphere models. Most space-based studies report the potential energy. We use Aeolus wind data to estimate the kinetic energy (density). However, the data quality is a challenge for such analyses, as the accuracy of the data is in the range of typical GW amplitudes. We find a temporal coincidence between enhanced or breaking planetary waves and enhanced gravity wave kinetic energy density.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025, https://doi.org/10.5194/amt-18-1355-2025, 2025
Short summary
Short summary
A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Chengli Ji, Qiankai Jin, Feilong Li, Yuyang Liu, Zhicheng Wang, Jiajia Mao, Xiaoyu Ren, Yan Xiang, Wanlin Jian, Peitao Zhao, and Zhenyi Chen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1171, https://doi.org/10.5194/egusphere-2025-1171, 2025
Short summary
Short summary
This study presents the humidity measurements with a synergetic algorithm combining Raman lidar, MVR, and satellite. The results from 47 sites in China show the best correlation over 0.9 concerning the radiosonde measurements. It validates the RH accuracy with various data integrations. Three representative sites present the different seasonal characteristics indicating the geographic and height influences on the RH vertical distribution.
Maurice Roots, John T. Sullivan, and Belay Demoz
Atmos. Meas. Tech., 18, 1269–1282, https://doi.org/10.5194/amt-18-1269-2025, https://doi.org/10.5194/amt-18-1269-2025, 2025
Short summary
Short summary
This paper presents a supervised-machine-learning approach for the automatic isolation of nocturnal low-level jets (NLLJs) using observations from a radar wind profiler. This analysis isolated 90 southwesterly NLLJs observed from May to September 2017–2021, highlighting key features in the evolution and morphology of the mid-Atlantic NLLJ.
Padmanabhan Thiruvengadam, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, and Joël Van Baelen
Atmos. Meas. Tech., 18, 1185–1191, https://doi.org/10.5194/amt-18-1185-2025, https://doi.org/10.5194/amt-18-1185-2025, 2025
Short summary
Short summary
This study explores how the joints in a weather radar's protective cover affect its measurements. We developed a new method to correct these errors, improving the accuracy of the radar's data. Our method was tested during an intense cyclone on Réunion Island, demonstrating significant improvements in data accuracy. This research is crucial for enhancing weather predictions and understanding, particularly in challenging terrains.
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae N. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech., 18, 843–863, https://doi.org/10.5194/amt-18-843-2025, https://doi.org/10.5194/amt-18-843-2025, 2025
Short summary
Short summary
Global Navigation Satellite System radio occultation data help monitor climate and weather prediction but are affected by residual ionospheric errors (RIEs). A new excess-phase-gradient method detects and corrects RIEs, showing both positive and negative values, varying by latitude, time, and solar activity. Tests show that RIE impacts polar stratosphere temperatures in models, with differences up to 3–4 K. This highlights the need for RIE correction to improve the accuracy of data assimilation.
Damao Zhang, Jennifer Comstock, Chitra Sivaraman, Kefei Mo, Raghavendra Krishnamurthy, Jingjing Tian, Tianning Su, Zhanqing Li, and Natalia Roldán-Henao
EGUsphere, https://doi.org/10.5194/egusphere-2024-3959, https://doi.org/10.5194/egusphere-2024-3959, 2025
Short summary
Short summary
Planetary boundary layer height (PBLHT) is an important parameter in atmospheric process studies and numerical model simulations. We use machine learning methods to produce a best-estimate planetary boundary layer height (PBLHT-BE-ML) by integrating four PBLHT estimates derived from remote sensing measurements. We demonstrated that PBLHT-BE-ML greatly improved the comparisons against sounding-derived PBLHT.
Miguel Aldana, Seppo Pulkkinen, Annakaisa von Lerber, Matthew R. Kumjian, and Dmitri Moisseev
Atmos. Meas. Tech., 18, 793–816, https://doi.org/10.5194/amt-18-793-2025, https://doi.org/10.5194/amt-18-793-2025, 2025
Short summary
Short summary
Accurate KDP estimates are crucial in radar-based applications. We quantify the uncertainties of several publicly available KDP estimation methods for multiple rainfall intensities. We use C-band weather radar observations and employed a self-consistency KDP, estimated from reflectivity and differential reflectivity, as a framework for the examination. Our study provides guidance for the performance, uncertainties, and optimisation of the methods, focusing mainly on accuracy and robustness.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 18, 471–485, https://doi.org/10.5194/amt-18-471-2025, https://doi.org/10.5194/amt-18-471-2025, 2025
Short summary
Short summary
This study evaluates and compares a new microwave hyperspectrometer with an infrared hyperspectrometer for clear-sky temperature and water vapor retrievals. The analysis reveals that the information content of the infrared hyperspectrometer exceeds that of the microwave hyperspectrometer and provides higher vertical resolution in ground-based zenith measurements. Leveraging the ground–airborne synergy between the two instruments yielded optimal sounding results.
David D. Turner, Maria P. Cadeddu, Julia Simonson, and Timothy J. Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2024-4124, https://doi.org/10.5194/egusphere-2024-4124, 2025
Short summary
Short summary
When deriving a geophysical variable from remote sensors, the uncertainty and information content are critical. The latter quantify specifies what fraction of a real perturbation would be observed in the derived variable. This paper outlines, for the first time, a methodology for propagating the information content from multiple remote sensors into a derived product, using horizontal advection as an example.
Endrit Shehaj, Stephen Leroy, Kerri Cahoy, Alain Geiger, Laura Crocetti, Gregor Moeller, Benedikt Soja, and Markus Rothacher
Atmos. Meas. Tech., 18, 57–72, https://doi.org/10.5194/amt-18-57-2025, https://doi.org/10.5194/amt-18-57-2025, 2025
Short summary
Short summary
This work investigates whether machine learning (ML) can offer an alternative to existing methods to map radio occultation (RO) products, allowing the extraction of information not visible in direct observations. ML can further improve the results of Bayesian interpolation, a state-of-the-art method to map RO observations. The results display improvements in horizontal and temporal domains, at heights ranging from the planetary boundary layer up to the lower stratosphere, and for all seasons.
Luuk D. van der Valk, Oscar K. Hartogensis, Miriam Coenders-Gerrits, Rolf W. Hut, Bas Walraven, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-2974, https://doi.org/10.5194/egusphere-2024-2974, 2025
Short summary
Short summary
Commercial microwave links (CMLs), part of mobile phone networks, transmit comparable signals as instruments specially designed to estimate evaporation. Therefore, we investigate if CMLs could be used to estimate evaporation, even though they have not been designed for this purpose. Our results illustrate the potential of using CMLs to estimate evaporation, especially given their global coverage, but also outline some major drawbacks, often a consequence of unfavourable design choices for CMLs.
Andreas Foth, Moritz Lochmann, Pablo Saavedra Garfias, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 7169–7181, https://doi.org/10.5194/amt-17-7169-2024, https://doi.org/10.5194/amt-17-7169-2024, 2024
Short summary
Short summary
Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. We present a method based on a selection of specific frequencies and elevation angles from microwave radiometer observations. A comparison with a numerical weather prediction model shows the presented method allows low-level temperature profiles during rain to be resolved, with rain rates of up to 2.5 mm h−1,, which was not possible before with state-of-the-art retrievals.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
Atmos. Meas. Tech., 17, 7183–7208, https://doi.org/10.5194/amt-17-7183-2024, https://doi.org/10.5194/amt-17-7183-2024, 2024
Short summary
Short summary
The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm that produces Aeolus lidar surface returns (LSRs), containing useful information for measuring UV reflectivity. Aeolus LSRs matched well with existing UV reflectivity data from other satellites, like GOME-2 and TROPOMI, and demonstrated excellent sensitivity to modeled snow cover.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024, https://doi.org/10.5194/amt-17-7077-2024, 2024
Short summary
Short summary
The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
Atmos. Meas. Tech., 17, 7007–7026, https://doi.org/10.5194/amt-17-7007-2024, https://doi.org/10.5194/amt-17-7007-2024, 2024
Short summary
Short summary
This paper focuses on the BMA-FLX processor, in which thermal and solar top-of-atmosphere radiative fluxes are obtained from longwave and shortwave radiances measured along track by the EarthCARE Broadband Radiometer (BBR). The BBR measurements, at three fixed viewing angles (fore, nadir, aft), are co-registered either at the surface or at a reference level. A combined flux from the three BRR views is obtained. The algorithm has been successfully validated against test scenes.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech., 17, 6913–6931, https://doi.org/10.5194/amt-17-6913-2024, https://doi.org/10.5194/amt-17-6913-2024, 2024
Short summary
Short summary
Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose optimized post-processing for error reduction.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
Short summary
Short summary
Continuous profile observations of temperature and humidity in the lowest part of the atmosphere are essential for the evaluation of numerical weather prediction models and data assimilation for better weather forecasts. Such profiles can be retrieved from passive ground-based remote sensing instruments like infrared spectrometers and microwave radiometers. In this study, we describe three recent modifications to the retrieval framework TROPoe for improved temperature and humidity profiles.
Yunfan Yang, Wei Han, Haofei Sun, Jun Li, Jiapeng Yan, and Zhiqiu Gao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-175, https://doi.org/10.5194/amt-2024-175, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Our research improves satellite-based precipitation monitoring by using deep learning to reconstruct radar observations from passive microwave radiances. Active radar is costly, so we focus on a more accessible approach. Using data from the FengYun-3G satellite, we successfully tracked severe weather like Typhoon Khanun and heavy rainfall in Beijing in 2023. This method enhances global precipitation data and helps better understand extreme weather.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
Short summary
Short summary
The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
Short summary
Short summary
We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Tessa E. Rosenberger, Thijs Heus, Girish N. Raghunathan, David D. Turner, Timothy J. Wagner, and Julia M. Simonson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2894, https://doi.org/10.5194/egusphere-2024-2894, 2024
Short summary
Short summary
Entrainment is key in understanding temperature and moisture changes within the boundary layer, but it is difficult to observe using ground-based observations. This work used simulations to verify an assumption that simplifies entrainment estimations from ground-based observational data, recognizing that entrainment is the combination of the transfer of heat and moisture from above the boundary layer into it and the change in concentration of heat and moisture as boundary layer depth changes.
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
Atmos. Meas. Tech., 17, 6025–6046, https://doi.org/10.5194/amt-17-6025-2024, https://doi.org/10.5194/amt-17-6025-2024, 2024
Short summary
Short summary
The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.
Ollie Lewis, Chris Brunt, Malcolm Kitchen, Neill E. Bowler, and Edmund K. Stone
EGUsphere, https://doi.org/10.5194/egusphere-2024-2273, https://doi.org/10.5194/egusphere-2024-2273, 2024
Short summary
Short summary
Humidity observations are crucial for an accurate weather forecast. We propose a new way to measure humidity by measuring how radio signals from commercial aircraft are refracted by the atmosphere. Humidity affects the refractive index of air, allowing its presence to be detected. With thousands of flights in the airspace over the United Kingdom every day, there is the potential for a large increase in the number of humidity measurements for use in weather forecasting models.
Dianrun Zhao, Shanshan Du, Chu Zou, Longfei Tian, Meng Fan, Yulu Du, and Liangyun Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3118, https://doi.org/10.5194/egusphere-2024-3118, 2024
Short summary
Short summary
The TanSat-2 satellite is designed for global carbon monitoring. It provides high-resolution, dual-band observations of solar-induced chlorophyll fluorescence, a key indicator of plant photosynthesis. Through simulations, we optimized the satellite's data processing and found it can retrieve this fluorescence with great accuracy. These findings suggest that TanSat-2 will enhance global monitoring of carbon cycles and vegetation health, offering valuable insights for climate change research.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
Short summary
Short summary
We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Xiaoye Wang, Jing Xu, Songhua Wu, Qichao Wang, Guangyao Dai, Peizhi Zhu, Zhizhong Su, Sai Chen, Xiaomeng Shi, and Mengqi Fan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-156, https://doi.org/10.5194/amt-2024-156, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
In this paper, we proposed a data fusion method to obtain the no-blind zone wind speed profiles covering the whole Atmospheric Boundary Layer based on the joint measurements of coherent Doppler lidar (CDL), radar wind profiler (RWP) and automatic weather station (AWS). Since above instruments are widely deployed in China, we believe this method has broad application prospects on the improvement of the boundary layer parameterization scheme in numerical forecast models.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
Short summary
Short summary
This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024, https://doi.org/10.5194/amt-17-5397-2024, 2024
Short summary
Short summary
A method for determining drop size distributions (DSDs) for rain using radar measurements from two frequencies at two polarizations is presented. Following some preprocessing and quality control, radar measurements are incorporated into a model that uses swarm intelligence to seek the most suitable DSD to produce the input measurements.
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, https://doi.org/10.5194/amt-17-5015-2024, 2024
Short summary
Short summary
Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024, https://doi.org/10.5194/amt-17-4737-2024, 2024
Short summary
Short summary
We analyze simulated polarization observations over snow to investigate the capabilities of remote sensing to determine surface and atmospheric properties in snow-covered regions. Polarization measurements are demonstrated to aid in the determination of snow grain shape, ice crystal roughness, and the vertical distribution of impurities in the snow–atmosphere system, data that are critical for estimating snow albedo for use in climate models.
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, https://doi.org/10.5194/amt-17-4675-2024, 2024
Short summary
Short summary
A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, https://doi.org/10.5194/amt-17-4687-2024, 2024
Short summary
Short summary
We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Robert Reichert, Natalie Kaifler, and Bernd Kaifler
Atmos. Meas. Tech., 17, 4659–4673, https://doi.org/10.5194/amt-17-4659-2024, https://doi.org/10.5194/amt-17-4659-2024, 2024
Short summary
Short summary
Imagine you want to determine how quickly the pitch of a passing ambulance’s siren changes. If the vehicle is traveling slowly, the pitch changes only slightly, but if it is traveling fast, the pitch also changes rapidly. In a similar way, the wind in the middle atmosphere modulates the wavelength of atmospheric gravity waves. We have investigated the question of how strong the maximum wind may be so that the change in wavelength can still be determined with the help of wavelet transformation.
Qiang Guo, Yuning Liu, Xin Wang, and Wen Hui
Atmos. Meas. Tech., 17, 4613–4627, https://doi.org/10.5194/amt-17-4613-2024, https://doi.org/10.5194/amt-17-4613-2024, 2024
Short summary
Short summary
Non-linearity (NL) correction is a critical procedure to guarantee that the calibration accuracy of a spaceborne sensor approaches a reasonable level. Different from the classical method, a new NL correction method for a spaceborne Fourier transform spectrometer is proposed. To overcome the inaccurate linear coefficient from two-point calibration influencing NL correction, an iteration algorithm is established that is suitable for NL correction of both infrared and microwave sensors.
Bing Cao, Jennifer S. Haase, Michael J. Murphy Jr., and Anna M. Wilson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-119, https://doi.org/10.5194/amt-2024-119, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
This paper describes an Airborne Radio Occultation (ARO) observation system installed on reconnaissance aircraft that uses GPS signal refraction in the atmosphere to retrieve information about the temperature and moisture in the storm environment as far away as 400 km surrounding the flight track. The characteristics and quality of 1700 ARO refractivity profiles were assessed. These observations are collected to help understand atmospheric rivers and improve their forecasting.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
Short summary
Short summary
Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech., 17, 4245–4256, https://doi.org/10.5194/amt-17-4245-2024, https://doi.org/10.5194/amt-17-4245-2024, 2024
Short summary
Short summary
The Broadband Radiometer measures shortwave and total-wave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, the effect of the spectral response needs to be corrected for, done within the BM-RAD processor. Errors in the unfiltering are propagated into fluxes; thus, accurate unfiltering is required for their proper estimation (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the shortwave and <0.1 % for the longwave.
Qihou Zhou, Yanlin Li, and Yun Gong
Atmos. Meas. Tech., 17, 4197–4209, https://doi.org/10.5194/amt-17-4197-2024, https://doi.org/10.5194/amt-17-4197-2024, 2024
Short summary
Short summary
We discuss several robust estimators to compute the variance of a normally distributed random variable to deal with interference. Compared to rank-based estimators, the methods based on the geometric mean are more accurate and are computationally more efficient. We apply three robust estimators to incoherent scatter power and velocity processing, along with the traditional sample mean estimator. The best estimator is a hybrid estimator that combines the sample mean and a robust estimator.
Zhao Shi, Yuxiang Wen, and Jianxin He
Atmos. Meas. Tech., 17, 4121–4135, https://doi.org/10.5194/amt-17-4121-2024, https://doi.org/10.5194/amt-17-4121-2024, 2024
Short summary
Short summary
The squall line is a type of convective system. Squall lines are often associated with damaging weather, so identifying and tracking squall lines plays an important role in early meteorological disaster warnings. A clustering-based method is proposed in this article. It can identify the squall lines within the radar scanning range with an accuracy rate of 95.93 %. It can also provide the three-dimensional structure and movement tracking results for each squall line.
Elizabeth N. Smith and Jacob T. Carlin
Atmos. Meas. Tech., 17, 4087–4107, https://doi.org/10.5194/amt-17-4087-2024, https://doi.org/10.5194/amt-17-4087-2024, 2024
Short summary
Short summary
Boundary-layer height observations remain sparse in time and space. In this study we create a new fuzzy logic method for synergistically combining boundary-layer height estimates from a suite of instruments. These estimates generally compare well to those from radiosondes; plus, the approach offers near-continuous estimates through the entire diurnal cycle. Suspected reasons for discrepancies are discussed. The code for the newly presented fuzzy logic method is provided for the community to use.
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, https://doi.org/10.5194/amt-17-3933-2024, 2024
Short summary
Short summary
The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
Atmos. Meas. Tech., 17, 3829–3841, https://doi.org/10.5194/amt-17-3829-2024, https://doi.org/10.5194/amt-17-3829-2024, 2024
Short summary
Short summary
The Swedish research satellite MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is designed to study atmospheric waves in the mesosphere and lower thermosphere. These waves perturb the temperature field, and thus, by observing three-dimensional temperature fluctuations, their properties can be quantified. This pre-study uses synthetic MATS data generated from a general circulation model to investigate how well wave properties can be retrieved.
Jie Gong, Dong Liang Wu, Michelle Badalov, Manisha Ganeshan, and Minghua Zheng
EGUsphere, https://doi.org/10.5194/egusphere-2024-973, https://doi.org/10.5194/egusphere-2024-973, 2024
Short summary
Short summary
Marine boundary layer water vapor is among the key factors to couple the ocean and atmosphere, but it is also among the hardest to retrieve from satellite remote sensing perspective. Here we propose a novel way to retrieve MPBL specific humidity profiles using the GNSS Level-1 signal-to-noise ratio. Using a machine learning approach, we successfully obtained a retrieval product that outperforms the ERA-5 reanalysis and operational Level-2 retrievals globally except in the deep tropics.
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024, https://doi.org/10.5194/amt-17-3605-2024, 2024
Short summary
Short summary
This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and its dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We propose methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the refractivity bias under different atmospheric conditions and thus improve the applications of the GNSS RO data in the deep troposphere.
Cited articles
Allen, J. T., Giammanco, I. M., Kumjian, M. R., Jurgen Punge, H., Zhang, Q., Groenemeijer, P., Kunz, M., and Ortega, K.: Understanding Hail in the Earth System, Rev. Geophys., 58, e2019RG000665, https://doi.org/10.1029/2019RG000665, 2020. 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, 1429–1440, https://doi.org/10.1175/BAMS-D-18-0090.1, 2019. a, b
Bemis, S. P., Micklethwaite, S., Turner, D., James, M. R., Akciz, S., Thiele, S. T., and Bangash, H. A.: Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology, J. Struct. Geol., 69, 163–178, https://doi.org/10.1016/j.jsg.2014.10.007, 2014. a
Brook, J. P., Protat, A., Soderholm, J., Carlin, J. T., McGowan, H., and Warren, R. A.: HailTrack – Improving Radar-Based Hailfall Estimates by Modeling Hail Trajectories, J. Appl. Meteorol. Clim., 60, 237–254, https://doi.org/10.1175/JAMC-D-20-0087.1, 2021. a
Bunkers, M. J., Klimowski, B. A., Zeitler, J. W., Thompson, R. L., and Weisman, M. L.: Predicting Supercell Motion Using a New Hodograph Technique, Weather Forecast., 15, 61–79, https://doi.org/10.1175/1520-0434(2000)015<0061:PSMUAN>2.0.CO;2, 2000. a
Chronis, T., Carey, L. D., Schultz, C. J., Schultz, E. V., Calhoun, K. M., and Goodman, S. J.: Exploring Lightning Jump Characteristics, Weather Forecast., 30, 23–37, https://doi.org/10.1175/WAF-D-14-00064.1, 2015. a
Fawcett, D., Azlan, B., Hill, T. C., Kho, L. K., Bennie, J., and Anderson, K.: Unmanned aerial vehicle (UAV) derived structure-from-motion photogrammetry point clouds for oil palm (Elaeis guineensis) canopy segmentation and height estimation, Int. J. Remote Sens., 40, 7538–7560, https://doi.org/10.1080/01431161.2019.1591651, 2019. 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 Clim. Atmos. Sci., 6, 19, https://doi.org/10.1038/s41612-023-00352-z, 2023. a
Fraile, R., Castro, A., and Sánchez, J.: Analysis of hailstone size distributions from a hailpad network, Atmos. Res., 28, 311–326, https://doi.org/10.1016/0169-8095(92)90015-3, 1992. a
Fraile, R., Castro, A., López, L., Sánchez, J. L., and Palencia, C.: The influence of melting on hailstone size distribution, Atmos. Res., 67–68, 203–213, https://doi.org/10.1016/S0169-8095(03)00052-8, 2003. a
Germann, U., Boscacci, M., Clementi, L., Gabella, M., Hering, A., Sartori, M., Sideris, I. V., and Calpini, B.: Weather Radar in Complex Orography, Remote Sens., 14, 503, https://doi.org/10.3390/rs14030503, 2022. a, b
Goutte, C. and Gaussier, E.: A Probabilistic Interpretation of Precision, Recall and F-Score, with Implication for Evaluation, in: Advances in Information Retrieval, edited by: Losada, D. E. and Fernández-Luna, J. M., Springer Berlin Heidelberg, Berlin, Heidelberg, 345–359, https://doi.org/10.1007/978-3-540-31865-1_25, 2005. a
Guidi, G., Shafqat Malik, U., and Micoli, L. L.: Optimal Lateral Displacement in Automatic Close-Range Photogrammetry, Sensors, 20, 6280, https://doi.org/10.3390/s20216280, 2020. a
He, K., Zhang, X., Ren, S., and Sun, J.: Deep Residual Learning for Image Recognition, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 27–30 June 2016, IEEE, 770–778, https://doi.org/10.1109/CVPR.2016.90, 2016. a
He, K., Gkioxari, G., Dollár, P., and Girshick, R.: Mask R-CNN, IEEE T. Pattern Anal., 42, 386–397, https://doi.org/10.1109/TPAMI.2018.2844175, 2020. a
Hering, A., Morel, C., Galli, G., Sénési, S., Ambrosetti, P., and Boscacci, M.: Nowcasting thunderstorms in the Alpine region using a radar based adaptive thresholding scheme, in: Proceedings of the 3rd European Conference on Radar in Meteorology and Hydrology, Visby, Island of Gotland, Sweden, 6–10 September 2004, Copernicus GmbH, ISBN 3936586292, ISBN 9783936586299, 2004. a
Houze, R. A., Schmid, W., Fovell, R. G., and Schiesser, H.-H.: Hailstorms in Switzerland: Left Movers, Right Movers, and False Hooks, Mon. Weather Rev., 121, 3345–3370, https://doi.org/10.1175/1520-0493(1993)121<3345:HISLMR>2.0.CO;2, 1993. a
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, 2022. a, b
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, 2023. a, b
Kumjian, M. R. and Lombardo, K.: A Hail Growth Trajectory Model for Exploring the Environmental Controls on Hail Size: Model Physics and Idealized Tests, J. Atmos. Sci., 77, 2765–2791, https://doi.org/10.1175/JAS-D-20-0016.1, 2020. a
Kumjian, M. R. and Ryzhkov, A. V.: Polarimetric Signatures in Supercell Thunderstorms, J. Appl. Meteorol. Clim., 47, 1940–1961, https://doi.org/10.1175/2007JAMC1874.1, 2008. 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
la Mobilière: 2021 Annual Report in brief, Tech. rep., Mobilière Holding Ltd., Berne, https://report.mobiliar.ch/2021/app/uploads/2022/03/mobiliar_ar21_in-brief.pdf (last access: 26 April 2024), 2021. a
Lin, T.-Y., Maire, M., Belongie, S., Bourdev, L., Girshick, R., Hays, J., Perona, P., Ramanan, D., Zitnick, C. L., and Dollár, P.: Microsoft COCO: Common Objects in Context, arXiv [preprint], https://doi.org/10.48550/arxiv.1405.0312, 1 May 2014. 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
mapillary: OpenSfM, GitHub [code], https://github.com/mapillary/OpenSfM (last access: 15 April 2024), 2020. a
mapillary: OpenSFM, GitHub [code], https://github.com/mapillary/OpenSfM/blob/main/README.md (last access: 15 April 2024), 2023. a
May, R. M., Arms, S. C., Marsh, P., Bruning, E., Leeman, J. R., Goebbert, K., Thielen, J. E., Bruick, Z. S., and Camron, M. D.: MetPy: A Python Package for Meteorological Data, Unidata [data set], https://doi.org/10.5065/D6WW7G29, 2023. a
Najman, L. and Schmitt, M.: Watershed of a continuous function, Signal Process., 38, 99–112, https://doi.org/10.1016/0165-1684(94)90059-0, 1994. 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
Nisi, L., Hering, A., Germann, U., Schroeer, K., Barras, H., Kunz, M., and Martius, O.: Hailstorms in the Alpine region: Diurnal cycle, 4D-characteristics, and the nowcasting potential of lightning properties, Q. J. Roy. Meteor. Soc., 146, 4170–4194, https://doi.org/10.1002/qj.3897, 2020. a
OpenDroneMap: ODM – A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images, GitHub [code], https://github.com/OpenDroneMap/ODM (last access: 1 April 2024), 2020. a
Powers, D. M. W.: Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation, CoRR, arXiv [preprint], https://doi.org/10.48550/arXiv.2010.16061, 11 October 2020. a
Rasmussen, R. and Pruppacher, H. R.: A Wind Tunnel and Theoretical Study of the Melting Behavior of Atmospheric Ice Particles. I: A Wind Tunnel Study of Frozen Drops of Radius < 500 µm, J. Atmos. Sci., 39, 152–158, https://doi.org/10.1175/1520-0469(1982)039<0152:AWTATS>2.0.CO;2, 1982. a
Rasmussen, R. M. and Heymsfield, A. J.: Melting and Shedding of Graupel and Hail. Part I: Model Physics, J. Atmos. Sci., 44, 2754–2763, https://doi.org/10.1175/1520-0469(1987)044<2754:MASOGA>2.0.CO;2, 1987. a
Romppainen-Martius, O.: The Swiss Hail Network, Mobiliar Lab for Natural Risks, University of Bern, https://www.mobiliarlab.unibe.ch/research/applied_research_on_hail_and_wind_gusts/the_swiss_hail_network/index_eng.html (last access: 26 February 2024), 2022. a
Schmidhuber, J.: Deep learning in neural networks: An overview, Neural Networks, 61, 85–117, https://doi.org/10.1016/j.neunet.2014.09.003, 2015. a
Schultz, C. J., Petersen, W. A., and Carey, L. D.: Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather, J. Appl. Meteorol. Clim., 48, 2543–2563, https://doi.org/10.1175/2009JAMC2237.1, 2009. a
Sekachev, B., Manovich, N., Zhiltsov, M., Zhavoronkov, A., Kalinin, D., Hoff, B., TOsmanov, Kruchinin, D., Zankevich, A., DmitriySidnev, Markelov, M., Johannes222, Chenuet, M., a andre, telenachos, Melnikov, A., Kim, J., Ilouz, L., Glazov, N., Priya4607, Tehrani, R., Jeong, S., Skubriev, V., Yonekura, S., vugia truong, zliang7, lizhming, and Truong, T.: opencv/cvat: v1.1.0, Zenodo [code], https://doi.org/10.5281/zenodo.4009388, 2020. a
SwissGeoportal: https://map.geo.admin.ch/ (last access: 15 April 2024), 2023. a
Treloar, A.: Vertically integrated radar reflectivity as an indicator of hail size in the greater Sydney region of Australia, in: Preprints, 19th Conf. on Severe Local Storms, Minneapolis, MN, USA, 14–18 September 1998, Amer. Meteor. Soc, 48–51, 1998. a
Van Rijsbergen, C. J.: Information retrieval, 2nd edn., Butterworths, Newton, Ma, ISBN 9780408709293, 1979. a
Waldvogel, A., Federer, B., and Grimm, P.: Criteria for the Detection of Hail Cells, J. Appl. Meteorol. Clim., 18, 1521–1525, https://doi.org/10.1175/1520-0450(1979)018<1521:CFTDOH>2.0.CO;2, 1979. a
Wilks, D. S.: Statistical methods in the atmospheric sciences, vol. 100, Academic press, ISBN 9780123850225, 2011. a
Wu, Y., Kirillov, A., Massa, F., Lo, W.-Y., and Girshick, R.: Detectron2, GitHub [code], https://github.com/facebookresearch/detectron2 (last access: 20 March 2024), 2019. a
Wu, Y., Kirillov, A., Massa, F., Lo, W.-Y., and Girshick, R.: Detectron2, GitHub [code], https://github.com/facebookresearch/detectron2/blob/main/detectron2/config/defaults.py (last access: 20 March 2024), 2023. a
Ziegler, C. L., Ray, P. S., and Knight, N. C.: Hail Growth in an Oklahoma Multicell Storm, J. Atmos. Sci., 40, 1768–1791, https://doi.org/10.1175/1520-0469(1983)040<1768:HGIAOM>2.0.CO;2, 1983. a
Zou, Z., Shi, Z., Guo, Y., and Ye, J.: Object Detection in 20 Years: A Survey, arXiv [preprint], https://doi.org/10.48550/arxiv.1905.05055, 13 May 2019. a
Short summary
This study uses deep learning (the Mask R-CNN model) on drone-based photogrammetric data of hail on the ground to estimate hail size distributions (HSDs). Traditional hail sensors' limited areas complicate the full HSD retrieval. The HSD of a supercell event on 20 June 2021 is retrieved and contains > 18 000 hailstones. The HSD is compared to automatic hail sensor measurements and those of weather-radar-based MESHS. Investigations into ground hail melting are performed by five drone flights.
This study uses deep learning (the Mask R-CNN model) on drone-based photogrammetric data of hail...
