Articles | Volume 12, issue 5
Atmos. Meas. Tech., 12, 2881–2911, 2019
https://doi.org/10.5194/amt-12-2881-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 12, 2881–2911, 2019
https://doi.org/10.5194/amt-12-2881-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 27 May 2019
Research article | 27 May 2019
Polarimetric radar characteristics of lightning initiation and propagating channels
Jordi Figueras i Ventura et al.
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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.
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
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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.
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
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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.
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
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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.
Jussi Leinonen, Ulrich Hamann, Urs Germann, and John R. Mecikalski
Nat. Hazards Earth Syst. Sci., 22, 577–597, https://doi.org/10.5194/nhess-22-577-2022, https://doi.org/10.5194/nhess-22-577-2022, 2022
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We evaluate the usefulness of different data sources and variables to the short-term prediction (
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
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Mesocyclones are the rotating updraught of supercell thunderstorms that present a particularly hazardous subset of thunderstorms. A first-time characterisation of the spatiotemporal occurrence of mesocyclones in the Alpine region is presented, using 5 years of Swiss operational radar data. We investigate parallels to hailstorms, particularly the influence of large-scale flow, daily cycles and terrain. Improving understanding of mesocyclones is valuable for risk assessment and warning purposes.
Hélène Barras, Olivia Martius, Luca Nisi, Katharina Schroeer, Alessandro Hering, and Urs Germann
Weather Clim. Dynam., 2, 1167–1185, https://doi.org/10.5194/wcd-2-1167-2021, https://doi.org/10.5194/wcd-2-1167-2021, 2021
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In Switzerland hail may occur several days in a row. Such multi-day hail events may cause significant damage, and understanding and forecasting these events is important. Using reanalysis data we show that weather systems over Europe move slower before and during multi-day hail events compared to single hail days. Surface temperatures are typically warmer and the air more humid over Switzerland and winds are slower on multi-day hail clusters. These results may be used for hail forecasting.
Francisco J. Pérez-Invernón, Heidi Huntrieser, Sergio Soler, Francisco J. Gordillo-Vázquez, Nicolau Pineda, Javier Navarro-González, Víctor Reglero, Joan Montanyà, Oscar van der Velde, and Nikos Koutsias
Atmos. Chem. Phys., 21, 17529–17557, https://doi.org/10.5194/acp-21-17529-2021, https://doi.org/10.5194/acp-21-17529-2021, 2021
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Lightning-ignited fires tend to occur in remote areas and can spread significantly before suppression. Long continuing current (LCC) lightning, preferably taking place in dry thunderstorms, is believed to be the main precursor of lightning-ignited fires. We analyze fire databases of lightning-ignited fires in the Mediterranean basin and report the shared meteorological conditions of fire- and LCC-lightning-producing thunderstorms. These results can be useful to improve fire forecasting methods.
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
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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.
Jussi Leinonen, Jacopo Grazioli, and Alexis Berne
Atmos. Meas. Tech., 14, 6851–6866, https://doi.org/10.5194/amt-14-6851-2021, https://doi.org/10.5194/amt-14-6851-2021, 2021
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Measuring the shape, size and mass of a large number of snowflakes is a challenging task; it is hard to achieve in an automatic and instrumented manner. We present a method to retrieve these properties of individual snowflakes using as input a triplet of images/pictures automatically collected by a multi-angle snowflake camera (MASC) instrument. Our method, based on machine learning, is trained on artificially generated snowflakes and evaluated on 3D-printed snowflake replicas.
Martin Lainer, Jordi Figueras i Ventura, Zaira Schauwecker, Marco Gabella, Montserrat F.-Bolaños, Reto Pauli, and Jacopo Grazioli
Atmos. Meas. Tech., 14, 3541–3560, https://doi.org/10.5194/amt-14-3541-2021, https://doi.org/10.5194/amt-14-3541-2021, 2021
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We show results from two unique measurement campaigns aimed at better understanding effects of large wind turbines on radar returns by deploying a mobile X-band weather radar system in the proximity of a small wind park. Measurements were taken in 24/7 operation with dedicated scan strategies to retrieve the variability and most extreme values of reflectivity and radar cross-section of the wind turbines. The findings are useful for wind turbine interference mitigation measures in radar systems.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193, https://doi.org/10.5194/amt-14-3169-2021, https://doi.org/10.5194/amt-14-3169-2021, 2021
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In this work, we present a novel quantitative precipitation estimation method for Switzerland that uses random forests, an ensemble-based machine learning technique. The estimator has been trained with a database of 4 years of ground and radar observations. The results of an in-depth evaluation indicate that, compared with the more classical method in use at MeteoSwiss, this novel estimator is able to reduce both the average error and bias of the predictions.
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.
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
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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
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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
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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.
Claudio Durán-Alarcón, Brice Boudevillain, Christophe Genthon, Jacopo Grazioli, Niels Souverijns, Nicole P. M. van Lipzig, Irina V. Gorodetskaya, and Alexis Berne
The Cryosphere, 13, 247–264, https://doi.org/10.5194/tc-13-247-2019, https://doi.org/10.5194/tc-13-247-2019, 2019
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Precipitation is the main input in the surface mass balance of the Antarctic ice sheet, but it is still poorly understood due to a lack of observations in this region. We analyzed the vertical structure of the precipitation using multiyear observation of vertically pointing micro rain radars (MRRs) at two stations located in East Antarctica. The use of MRRs showed the potential to study the effect of climatology and hydrometeor microphysics on the vertical structure of Antarctic precipitation.
Niels Souverijns, Alexandra Gossart, Stef Lhermitte, Irina V. Gorodetskaya, Jacopo Grazioli, Alexis Berne, Claudio Duran-Alarcon, Brice Boudevillain, Christophe Genthon, Claudio Scarchilli, and Nicole P. M. van Lipzig
The Cryosphere, 12, 3775–3789, https://doi.org/10.5194/tc-12-3775-2018, https://doi.org/10.5194/tc-12-3775-2018, 2018
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Snowfall observations over Antarctica are scarce and currently limited to information from the CloudSat satellite. Here, a first evaluation of the CloudSat snowfall record is performed using observations of ground-based precipitation radars. Results indicate an accurate representation of the snowfall climatology over Antarctica, despite the low overpass frequency of the satellite, outperforming state-of-the-art model estimates. Individual snowfall events are however not well represented.
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
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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
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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.
Christophe Genthon, Alexis Berne, Jacopo Grazioli, Claudio Durán Alarcón, Christophe Praz, and Brice Boudevillain
Earth Syst. Sci. Data, 10, 1605–1612, https://doi.org/10.5194/essd-10-1605-2018, https://doi.org/10.5194/essd-10-1605-2018, 2018
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Antarctica suffers from a severe shortage of in situ observations of precipitation. The APRES3 program contributes to improving observation from both the surface and from space. A field campaign with various instruments was deployed at the coast of Adélie Land, with an intensive observing period in austral summer 2015–16, then continuous radar monitoring through 2016 and beyond. This paper provides a compact presentation of the APRES3 dataset, which is now made open to the scientific community.
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
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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.
Jacopo Grazioli, Christophe Genthon, Brice Boudevillain, Claudio Duran-Alarcon, Massimo Del Guasta, Jean-Baptiste Madeleine, and Alexis Berne
The Cryosphere, 11, 1797–1811, https://doi.org/10.5194/tc-11-1797-2017, https://doi.org/10.5194/tc-11-1797-2017, 2017
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We present medium and long-term measurements of precipitation in a coastal region of Antarctica. These measurements are among the first of their kind on the Antarctic continent and combine remote sensing with in situ observations. The benefits of this synergy are demonstrated and the lessons learned from this measurements, which are still ongoing, are very important for the creation of similar observatories elsewhere on the continent.
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
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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.
Guillaume Nord, Brice Boudevillain, Alexis Berne, Flora Branger, Isabelle Braud, Guillaume Dramais, Simon Gérard, Jérôme Le Coz, Cédric Legoût, Gilles Molinié, Joel Van Baelen, Jean-Pierre Vandervaere, Julien Andrieu, Coralie Aubert, Martin Calianno, Guy Delrieu, Jacopo Grazioli, Sahar Hachani, Ivan Horner, Jessica Huza, Raphaël Le Boursicaud, Timothy H. Raupach, Adriaan J. Teuling, Magdalena Uber, Béatrice Vincendon, and Annette Wijbrans
Earth Syst. Sci. Data, 9, 221–249, https://doi.org/10.5194/essd-9-221-2017, https://doi.org/10.5194/essd-9-221-2017, 2017
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A high space–time resolution dataset linking hydrometeorological forcing and hydro-sedimentary response in a mesoscale catchment (Auzon, 116 km2) of the Ardèche region (France) is presented. This region is subject to precipitating systems of Mediterranean origin, which can result in significant rainfall amount. The data presented cover a period of 4 years (2011–2014) and aim at improving the understanding of processes triggering flash floods.
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
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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.
Joan Montanyà, Ferran Fabró, Oscar van der Velde, Víctor March, Earle Rolfe Williams, Nicolau Pineda, David Romero, Glòria Solà, and Modesto Freijo
Nat. Hazards Earth Syst. Sci., 16, 1465–1472, https://doi.org/10.5194/nhess-16-1465-2016, https://doi.org/10.5194/nhess-16-1465-2016, 2016
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Lightning is one of the major threats to modern multi-megawatt wind turbines and a concern for new generation of aircraft. Both wind turbines and aircraft can initiate lightning and very favourable conditions for lightning initiation occur in winter thunderstorms. Moreover, winter thunderstorms are characterized for producing very energetic lightning. In this paper we present the global winter lightning activity. Japan, US, Mediterranean, Argentina and New Zealand are the most active areas.
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
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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.
J. Grazioli, G. Lloyd, L. Panziera, C. R. Hoyle, P. J. Connolly, J. Henneberger, and A. Berne
Atmos. Chem. Phys., 15, 13787–13802, https://doi.org/10.5194/acp-15-13787-2015, https://doi.org/10.5194/acp-15-13787-2015, 2015
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This study investigates the microphysics of winter alpine snowfall occurring in mixed-phase clouds in an inner-Alpine valley during CLACE2014. From polarimetric radar and in situ observations, riming is shown to be an important process leading to more intense snowfall. Riming is usually associated with more intense turbulence providing supercooled liquid water. Distinct features are identified in the vertical structure of polarimetric radar variables.
J. Grazioli, D. Tuia, and A. Berne
Atmos. Meas. Tech., 8, 149–170, https://doi.org/10.5194/amt-8-149-2015, https://doi.org/10.5194/amt-8-149-2015, 2015
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A new approach for hydrometeor classification from polarimetric radar measurements is proposed. It takes adavantage of clustering techniques to objectively determine the number of hydrometeor classes that can be reliably identified. The proposed method is tested using observations from an X-band polarimetric radar in different regions and evaluated by comparison with existing algorithms and with measurements from a ground-based 2D video disdrometer (providing 2-D views of falling hydrometeors).
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
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Terhikki Manninen, Emmihenna Jääskeläinen, Niilo Siljamo, Aku Riihelä, and Karl-Göran Karlsson
Atmos. Meas. Tech., 15, 879–893, https://doi.org/10.5194/amt-15-879-2022, https://doi.org/10.5194/amt-15-879-2022, 2022
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A new method for cloud-correcting observations of surface albedo is presented for AVHRR data. Instead of a binary cloud mask, it applies cloud probability values smaller than 20% of the A3 edition of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record provided by the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT. According to simulations, the 90% quantile was 1.1% for the absolute albedo error and 2.2% for the relative error.
Shihan Chen, Yuanjian Yang, Fei Deng, Yanhao Zhang, Duanyang Liu, Chao Liu, and Zhiqiu Gao
Atmos. Meas. Tech., 15, 735–756, https://doi.org/10.5194/amt-15-735-2022, https://doi.org/10.5194/amt-15-735-2022, 2022
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This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. The spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. The present RF model framework for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII.
Brian J. Carroll, Amin R. Nehrir, Susan A. Kooi, James E. Collins, Rory A. Barton-Grimley, Anthony Notari, David B. Harper, and Joseph Lee
Atmos. Meas. Tech., 15, 605–626, https://doi.org/10.5194/amt-15-605-2022, https://doi.org/10.5194/amt-15-605-2022, 2022
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HALO is a recently developed lidar system that demonstrates new technologies and advanced algorithms for profiling water vapor as well as aerosol and cloud properties. The high-resolution, high-accuracy measurements have unique advantages within the suite of atmospheric instrumentation, such as directly trading water vapor measurement resolution for precision. This paper provides the methodology and first water vapor results, showing agreement with in situ and spaceborne sounder measurements.
Irina V. Djalalova, David D. Turner, Laura Bianco, James M. Wilczak, James Duncan, Bianca Adler, and Daniel Gottas
Atmos. Meas. Tech., 15, 521–537, https://doi.org/10.5194/amt-15-521-2022, https://doi.org/10.5194/amt-15-521-2022, 2022
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In this paper we investigate the synergy obtained by combining active (radio acoustic sounding system – RASS) and passive (microwave radiometer) remote sensing observations to obtain temperature vertical profiles through a radiative transfer model. Inclusion of the RASS observations leads to more accurate temperature profiles from the surface to 5 km above ground, well above the maximum height of the RASS observations themselves (2000 m), when compared to the microwave radiometer used alone.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 15, 503–520, https://doi.org/10.5194/amt-15-503-2022, https://doi.org/10.5194/amt-15-503-2022, 2022
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In this work, we review the use of quasi-vertical profiles for monitoring the calibration of the radar differential reflectivity ZDR. We validate the proposed method by comparing its results against the traditional approach based on measurements taken at 90°; we observed good agreement as the errors are within 0.2 dB. Additionally, we compare the results of the proposed method with ZDR derived from disdrometers; the errors are reasonable considering factors discussed in the paper.
Katarzyna Ośródka and Jan Szturc
Atmos. Meas. Tech., 15, 261–277, https://doi.org/10.5194/amt-15-261-2022, https://doi.org/10.5194/amt-15-261-2022, 2022
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Weather radar data are used in weather monitoring and forecasting, but they are affected by numerous errors and require advanced corrections. Different systems are designed and implemented to suit specific local conditions, like the RADVOL-QC system. The radar errors are divided into several groups: disturbance by non-meteorological echoes (from the mountains, RLAN signals, wind turbines, etc.), beam blockage, attenuation, etc. Each of them has different properties and is corrected differently.
Biao Tong, Xiangfei Sun, Jiyang Fu, Yuncheng He, and Pakwai Chan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-405, https://doi.org/10.5194/amt-2021-405, 2021
Revised manuscript accepted for AMT
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In recent years, there has been numerous research on Tropical Cyclone (TC) observation based on satellite cloud images (SCIs), but most methods are limited by low efficiency and subjectivity. To overcome subjectivity and improve efficiency of traditional methods, this paper uses deep learning technology to do further research on fingerprint identification of TC. Results provide an automatic and objective method to distinguish TCs from SCIs, and bring great convenience for subsequent research.
Richard Müller and Uwe Pfeifroth
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-351, https://doi.org/10.5194/amt-2021-351, 2021
Revised manuscript accepted for AMT
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The great works of physics teach us that a central paradigm of science should be make methods and theories as easy as possible and as complex as needed. This manuscript provides a brief review of Remote Sensing of solar surface irradiance based on this paradigma.
Xingou Xu and Ad Stoffelen
Atmos. Meas. Tech., 14, 7435–7451, https://doi.org/10.5194/amt-14-7435-2021, https://doi.org/10.5194/amt-14-7435-2021, 2021
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The support vector machine can effectively represent the increasing effect of rain affecting wind speeds. This research provides a correction of deviations that are skew- to Gaussian-like features caused by rain in Ku-band scatterometer wind. It demonstrates the effectiveness of a machine learning method when used based on elaborate analysis of the model establishment and result validation procedures. The corrected winds provide information previously lacking, which is vital for nowcasting.
Anna Franck, Dmitri Moisseev, Ville Vakkari, Matti Leskinen, Janne Lampilahti, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Meas. Tech., 14, 7341–7353, https://doi.org/10.5194/amt-14-7341-2021, https://doi.org/10.5194/amt-14-7341-2021, 2021
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We proposed a method to derive a convective boundary layer height, using insects in radar observations, and we investigated the consistency of these retrievals among different radar frequencies (5, 35 and 94 GHz). This method can be applied to radars at other measurement stations and serve as additional way to estimate the boundary layer height during summer. The entrainment zone was also observed by the 5 GHz radar above the boundary layer in the form of a Bragg scatter layer.
Ryan Volz, Jorge L. Chau, Philip J. Erickson, Juha P. Vierinen, J. Miguel Urco, and Matthias Clahsen
Atmos. Meas. Tech., 14, 7199–7219, https://doi.org/10.5194/amt-14-7199-2021, https://doi.org/10.5194/amt-14-7199-2021, 2021
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We introduce a new way of estimating winds in the upper atmosphere (about 80 to 100 km in altitude) from the observed Doppler shift of meteor trails using a statistical method called Gaussian process regression. Wind estimates and, critically, the uncertainty of those estimates can be evaluated smoothly (i.e., not gridded) in space and time. The effective resolution is set by provided parameters, which are limited in practice by the number density of the observed meteors.
Fabian Weiler, Michael Rennie, Thomas Kanitz, Lars Isaksen, Elena Checa, Jos de Kloe, Ngozi Okunde, and Oliver Reitebuch
Atmos. Meas. Tech., 14, 7167–7185, https://doi.org/10.5194/amt-14-7167-2021, https://doi.org/10.5194/amt-14-7167-2021, 2021
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This paper summarizes the identification and correction of one of the most important systematic error sources for the wind measurements of the ESA satellite Aeolus. It depicts the effects of small temperature variations in the primary telescope mirror on the quality of the wind products and describes the approach to correct for it in the near-real-time processing. Moreover, the performance of the correction approach is assessed, and alternative approaches are discussed.
Xinyan Li, Yuanjian Yang, Jiaqin Mi, Xueyan Bi, You Zhao, Zehao Huang, Chao Liu, Lian Zong, and Wanju Li
Atmos. Meas. Tech., 14, 7007–7023, https://doi.org/10.5194/amt-14-7007-2021, https://doi.org/10.5194/amt-14-7007-2021, 2021
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A random forest (RF) model framework for Fengyun-4A (FY-4A) daytime and nighttime quantitative precipitation estimation (QPE) is established using FY-4A multi-band spectral information, cloud parameters, high-density precipitation observations and physical quantities from reanalysis data. The RF model of FY-4A QPE has a high accuracy in estimating precipitation at the heavy-rain level or below, which has advantages for quantitative estimation of summer precipitation over East Asia in future.
Clayton Cantrall and Tomoko Matsuo
Atmos. Meas. Tech., 14, 6917–6928, https://doi.org/10.5194/amt-14-6917-2021, https://doi.org/10.5194/amt-14-6917-2021, 2021
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This paper presents a new technique to determine temperature in the thermosphere from observations of far ultraviolet radiation emitted by molecular nitrogen. The technique utilizes a ratio of two far ultraviolet spectral channels to capture the thermosphere temperature signal. Applying the technique to NASA GOLD observations results in temperatures that agree well with other thermosphere observations during a geomagnetic disturbance.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Alexander Geiß, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-366, https://doi.org/10.5194/amt-2021-366, 2021
Revised manuscript accepted for AMT
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The article discusses modifications in the wind retrieval of the ALADIN Airborne Demonstrator (A2D) – one of the key instruments for the validation of Aeolus. Thanks to the retrieval refinements, which are demonstrated in the context of two airborne campaigns in 2019, the systematic and random wind errors of the A2D were significantly reduced, thereby enhancing its validation capabilities. Finally, wind comparisons between A2D and Aeolus for the validation of the satellite data are presented.
Marie Bouillon, Sarah Safieddine, Simon Whitburn, Lieven Clarisse, Filipe Aires, Victor Pellet, Olivier Lezeaux, Noëlle A. Scott, Marie Doutriaux-Boucher, and Cathy Clerbaux
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-302, https://doi.org/10.5194/amt-2021-302, 2021
Revised manuscript accepted for AMT
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The IASI instruments have been observing Earth since 2007. We use a neural network to retrieve atmopsheric temperatures. This new temperature data record is validated against other datasets and shows good agreement. We use this new dataset to compute trends over the 2008–2020 period. We found a warming of the troposphere, more important at the poles. In the stratosphere, we found that temperatures decrease everywhere except at the South pole. The cooling is more pronounced at the South pole.
Gunter Stober, Alexander Kozlovsky, Alan Liu, Zishun Qiao, Masaki Tsutsumi, Chris Hall, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, Patrick J. Espy, Robert E. Hibbins, and Nicholas Mitchell
Atmos. Meas. Tech., 14, 6509–6532, https://doi.org/10.5194/amt-14-6509-2021, https://doi.org/10.5194/amt-14-6509-2021, 2021
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Wind observations at the edge to space, 70–110 km altitude, are challenging. Meteor radars have become a widely used instrument to obtain mean wind profiles above an instrument for these heights. We describe an advanced mathematical concept and present a tomographic analysis using several meteor radars located in Finland, Sweden and Norway, as well as Chile, to derive the three-dimensional flow field. We show an example of a gravity wave decelerating the mean flow.
Matthew A. Miller, Sandra E. Yuter, Nicole P. Hoban, Laura M. Tomkins, and Brian A. Colle
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-256, https://doi.org/10.5194/amt-2021-256, 2021
Revised manuscript accepted for AMT
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Apparent waves in the atmosphere and similar features in storm winds can be detected by taking the difference between successive Doppler weather radar scans measuring radar-relative storm air motions. Applying image filtering to the difference data better isolates the detected signal. This technique is a useful tool in weather research and forecasting since such waves can trigger or enhance precipitation.
Maya Ben-Yami, Hilke Oetjen, Helen Brindley, William Cossich, Dulce Lajas, Tiziano Maestri, Davide Magurno, Piera Raspollini, Luca Sgheri, and Laura Warwick
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-232, https://doi.org/10.5194/amt-2021-232, 2021
Revised manuscript accepted for AMT
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Spectral emissivity is a key property of the Earth surface. Few measurements exist in the far-infrared, despite recent work showing its contribution is important for accurate modelling of global climate. In preparation for ESA’s EE9 FORUM mission (launch 2026), this study takes first steps towards the development of an operational emissivity retrieval for FORUM by investigating the sensitivity of the emissivity product to different physical and operational parameters.
S. Joseph Munchak, Robert S. Schrom, Charles N. Helms, and Ali Tokay
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-264, https://doi.org/10.5194/amt-2021-264, 2021
Revised manuscript accepted for AMT
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The ability to measure snowfall with weather radar has greatly advanced with the development of techniques that utilize dual-polarization measurements, which provide information about the snow particle shape and orientation, and multi-frequency measurements, which provide information about size and density. This study combines these techniques with the NASA D3R radar, which provides dual-frequency polarimetric measurements, with data that was observed during the 2018 Winter Olympics.
Corwin J. Wright, Neil P. Hindley, M. Joan Alexander, Laura A. Holt, and Lars Hoffmann
Atmos. Meas. Tech., 14, 5873–5886, https://doi.org/10.5194/amt-14-5873-2021, https://doi.org/10.5194/amt-14-5873-2021, 2021
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Measuring atmospheric gravity waves in low vertical-resolution data is technically challenging, especially when the waves are significantly longer in the vertical than in the length of the measurement domain. We introduce and demonstrate a modification to the existing Stockwell transform methods of characterising these waves that address these problems, with no apparent reduction in the other capabilities of the technique.
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech., 14, 5593–5605, https://doi.org/10.5194/amt-14-5593-2021, https://doi.org/10.5194/amt-14-5593-2021, 2021
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We have estimated horizontal gradients of the propagation delay caused by water vapour in the atmosphere using two independent techniques, namely global navigation satellite systems (GNSS) and microwave radiometry. The highest resolution was 5 min. We found that the sampling of the atmosphere in different directions is an important factor for high correlations between the two techniques and that GNSS data can be used to detect large short-lived gradients, however, with increased formal errors.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
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Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Benjamin Männel, Florian Zus, Galina Dick, Susanne Glaser, Maximilian Semmling, Kyriakos Balidakis, Jens Wickert, Marion Maturilli, Sandro Dahlke, and Harald Schuh
Atmos. Meas. Tech., 14, 5127–5138, https://doi.org/10.5194/amt-14-5127-2021, https://doi.org/10.5194/amt-14-5127-2021, 2021
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Within the MOSAiC expedition, GNSS was used to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked data, coordinates and hourly zenith total delays (ZTDs) were determined using kinematic precise point positioning. The derived ZTD values agree within few millimeters with ERA5 and terrestrial GNSS and VLBI stations. The derived integrated water vapor corresponds to the frequently launched radiosondes (0.08 ± 0.04 kg m−2, rms of the differences of 1.47 kg m−2).
Joel P. Younger, Iain M. Reid, Chris L. Adami, Chris M. Hall, and Masaki Tsutsumi
Atmos. Meas. Tech., 14, 5015–5027, https://doi.org/10.5194/amt-14-5015-2021, https://doi.org/10.5194/amt-14-5015-2021, 2021
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A radar in Svalbard usually used to study meteor trails was used to observe a thin icy layer in the upper atmosphere. New methods used the layer to measure wind speed over short periods of time and found that the layer is most reflective within 6.8 ± 3.3° of vertical. Analysis of meteor trail radar echo durations found that the layer may shorten meteor trail echoes, but more data are needed. This study shows new uses for data collected by meteor radars for other purposes.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
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Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Andreas Foth, Janek Zimmer, Felix Lauermann, and Heike Kalesse-Los
Atmos. Meas. Tech., 14, 4565–4574, https://doi.org/10.5194/amt-14-4565-2021, https://doi.org/10.5194/amt-14-4565-2021, 2021
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In this paper, we present two micro rain radar-based approaches to discriminate between stratiform and convective precipitation. One is based on probability density functions and the other one is an artificial neural network classification. Both methods agree well, giving similar results. However, the results of the artificial neural network are more reasonable since it is also able to distinguish an inconclusive class, in turn making the stratiform and convective classes more reliable.
Raghavendra Krishnamurthy, Rob K. Newsom, Larry K. Berg, Heng Xiao, Po-Lun Ma, and David D. Turner
Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, https://doi.org/10.5194/amt-14-4403-2021, 2021
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Planetary boundary layer (PBL) height is a critical parameter in atmospheric models. Continuous PBL height measurements from remote sensing measurements are important to understand various boundary layer mechanisms, especially during daytime and evening transition periods. Due to several limitations in existing methodologies to detect PBL height from a Doppler lidar, in this study, a machine learning (ML) approach is tested. The ML model is observed to improve the accuracy by over 50 %.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Anne Kleinert, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, Daniel R. Marsh, and Gabriele P. Stiller
Atmos. Meas. Tech., 14, 4111–4138, https://doi.org/10.5194/amt-14-4111-2021, https://doi.org/10.5194/amt-14-4111-2021, 2021
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An improved dataset of vertical temperature profiles of the Earth's atmosphere in the altitude range 5–70 km is presented. These profiles are derived from measurements of the MIPAS instrument onboard ESA's Envisat satellite. The overall improvements are based on upgrades in the input data and several improvements in the data processing approach. Both of these are discussed, and an extensive error discussion is included. Enhancements of the new dataset are demonstrated by means of examples.
Daniel Kastinen, Johan Kero, Alexander Kozlovsky, and Mark Lester
Atmos. Meas. Tech., 14, 3583–3596, https://doi.org/10.5194/amt-14-3583-2021, https://doi.org/10.5194/amt-14-3583-2021, 2021
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When a meteor enters the atmosphere, it causes a trail of diffusing plasma that moves with the neutral wind. An interferometric radar system can measure such trails and determine its location. However, there is a chance of determining the wrong position due to noise. We simulate this behaviour and use the simulations to successfully determine the true location of ambiguous events. We also successfully test two simple temporal integration methods for avoiding such erroneous determinations.
Ting-Yu Cha and Michael M. Bell
Atmos. Meas. Tech., 14, 3523–3539, https://doi.org/10.5194/amt-14-3523-2021, https://doi.org/10.5194/amt-14-3523-2021, 2021
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Doppler radar provides high-resolution wind measurements within tropical cyclones (TCs) for real-time monitoring and weather forecasting. Hurricane Matthew (2016) was observed by the ground-based single-Doppler and NOAA P-3 Hurricane Hunter airborne radar simultaneously, providing a novel opportunity to compare single- and multiple-Doppler wind retrieval techniques. Here, we improve the single-Doppler wind retrieval algorithm and show the pros and cons of each method for studying TC structure.
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.
Pavel Alekseychik, Gabriel Katul, Ilkka Korpela, and Samuli Launiainen
Atmos. Meas. Tech., 14, 3501–3521, https://doi.org/10.5194/amt-14-3501-2021, https://doi.org/10.5194/amt-14-3501-2021, 2021
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Drones with thermal cameras are powerful new tools with the potential to provide new insights into atmospheric turbulence and heat fluxes. In a pioneering experiment, a Matrice 210 drone with a Zenmuse XT2 thermal camera was used to record 10–20 min thermal videos at 500 m a.g.l. over the Siikaneva peatland in southern Finland. A method to visualize the turbulent structures and derive their parameters from thermal videos is developed. The study provides a novel approach for turbulence analysis.
Svetla Hristova-Veleva, Sara Q. Zhang, F. Joseph Turk, Ziad S. Haddad, and Randy C. Sawaya
Atmos. Meas. Tech., 14, 3333–3350, https://doi.org/10.5194/amt-14-3333-2021, https://doi.org/10.5194/amt-14-3333-2021, 2021
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The assimilation of airborne-based three-dimensional winds into a mesoscale weather forecast model resulted in better agreement with airborne radar-derived precipitation 3-D structure at later model time steps. More importantly, there was also a discernible impact on the resultant wind and moisture structure, in accord with independent analysis of the wind structure and external satellite observations.
Julian Gröbner, Herbert Schill, Luca Egli, and René Stübi
Atmos. Meas. Tech., 14, 3319–3331, https://doi.org/10.5194/amt-14-3319-2021, https://doi.org/10.5194/amt-14-3319-2021, 2021
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The world's longest continuous total column ozone time series was initiated in 1926 at the Lichtklimatisches Observatorium (LKO), at Arosa, in the Swiss Alps. The measurements between Dobson and Brewer spectroradiometers have shown seasonal variations of the order of 2 %. The results of the study show that the consistency between the two instrument types can be significantly improved when the ozone cross-sections from Serdyuchenko et al. (2013) and the measured slit functions are used.
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193, https://doi.org/10.5194/amt-14-3169-2021, https://doi.org/10.5194/amt-14-3169-2021, 2021
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In this work, we present a novel quantitative precipitation estimation method for Switzerland that uses random forests, an ensemble-based machine learning technique. The estimator has been trained with a database of 4 years of ground and radar observations. The results of an in-depth evaluation indicate that, compared with the more classical method in use at MeteoSwiss, this novel estimator is able to reduce both the average error and bias of the predictions.
David D. Turner and Ulrich Löhnert
Atmos. Meas. Tech., 14, 3033–3048, https://doi.org/10.5194/amt-14-3033-2021, https://doi.org/10.5194/amt-14-3033-2021, 2021
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Temperature and humidity profiles in the lowest couple of kilometers near the surface are very important for many applications. Passive spectral radiometers are commercially available, and observations from these instruments have been used to get these profiles. However, new active lidar systems are able to measure partial profiles of water vapor. This paper investigates how the derived profiles of water vapor and temperature are improved when the active and passive observations are combined.
Mingzhe Li and Xinan Yue
Atmos. Meas. Tech., 14, 3003–3013, https://doi.org/10.5194/amt-14-3003-2021, https://doi.org/10.5194/amt-14-3003-2021, 2021
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In this study, we statistically analyzed the correlation between the ionospheric irregularity and the quality of the GNSS atmospheric radio occultation (RO) products. The results show that the ionospheric irregularity could affect the GNSS atmospheric RO in terms of causing failed inverted RO events and the bending angle oscillation. Awareness of the ionospheric irregularity effect on RO could be beneficial to improve the RO data quality for weather and climate research.
Daniel Sanchez-Rivas and Miguel A. Rico-Ramirez
Atmos. Meas. Tech., 14, 2873–2890, https://doi.org/10.5194/amt-14-2873-2021, https://doi.org/10.5194/amt-14-2873-2021, 2021
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In our paper, we propose a robust and operational algorithm to determine the height of the melting level that can be applied to either quasi-vertical profiles (QVPs) or vertical profiles (VPs) of polarimetric radar variables. The algorithm is applied to 1 year of rainfall events that occurred over southeast England and validated using radiosonde data. The algorithm proves to be accurate as the errors (mean absolute error and root mean square error) are close to 200 m.
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.
Ayham Alyosef, Domenico Cimini, Lorenzo Luini, Carlo Riva, Frank S. Marzano, Marianna Biscarini, Luca Milani, Antonio Martellucci, Sabrina Gentile, Saverio T. Nilo, Francesco Di Paola, Ayman Alkhateeb, and Filomena Romano
Atmos. Meas. Tech., 14, 2737–2748, https://doi.org/10.5194/amt-14-2737-2021, https://doi.org/10.5194/amt-14-2737-2021, 2021
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Telecommunication is based on the propagation of radio signals through the atmosphere. The signal power diminishes along the path due to atmospheric attenuation, which needs to be estimated to be accounted for. In a study funded by the European Space Agency, we demonstrate an innovative method improving atmospheric attenuation estimates from ground-based radiometric measurements by 10–30 %. More accurate atmospheric attenuation estimates imply better telecommunication services in the future.
Peng Sun, Suqin Wu, Kefei Zhang, Moufeng Wan, and Ren Wang
Atmos. Meas. Tech., 14, 2529–2542, https://doi.org/10.5194/amt-14-2529-2021, https://doi.org/10.5194/amt-14-2529-2021, 2021
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In GPS or Global navigation satellite systems (GNSS) meteorology, precipitable water vapor (PWV) at a station is obtained from a conversion of the GNSS signal zenith wet delay (ZWD) using a conversion factor which is a function of weighted mean temperature (Tm) over the site. We developed a new global grid-based empirical Tm model using ERA5 reanalysis data. The model-predicted Tm value has significance for applications needing real-time or near real-time PWV converted from GNSS signals.
Ying Li, Gottfried Kirchengast, Marc Schwärz, Florian Ladstädter, and Yunbin Yuan
Atmos. Meas. Tech., 14, 2327–2343, https://doi.org/10.5194/amt-14-2327-2021, https://doi.org/10.5194/amt-14-2327-2021, 2021
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We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known Jan.–Feb. 2009 event. We found that RO data are capable of SSW monitoring. Based on our method, a SSW event can be detected and tracked, and the duration and the strength of the event can be recorded. The results are consistent with other research on the 2009 event.
Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 2065–2093, https://doi.org/10.5194/amt-14-2065-2021, https://doi.org/10.5194/amt-14-2065-2021, 2021
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A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of lidar scans and retrieval of velocity statistics is proposed. The LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. The optimal design of lidar scans is formulated as a two-cost-function optimization problem, including the minimization of the volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field.
Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 2095–2113, https://doi.org/10.5194/amt-14-2095-2021, https://doi.org/10.5194/amt-14-2095-2021, 2021
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The LiDAR Statistical Barnes Objective Analysis (LiSBOA) is applied to lidar data collected in the wake of wind turbines to reconstruct mean wind speed and turbulence intensity. Various lidar scans performed during a field campaign for a wind farm in complex terrain are analyzed. The results endorse the application of the LiSBOA for lidar-based wind resource assessment and farm diagnosis.
Viktor A. Banakh, Igor N. Smalikho, and Andrey V. Falits
Atmos. Meas. Tech., 14, 1511–1524, https://doi.org/10.5194/amt-14-1511-2021, https://doi.org/10.5194/amt-14-1511-2021, 2021
Matteo Puccioni and Giacomo Valerio Iungo
Atmos. Meas. Tech., 14, 1457–1474, https://doi.org/10.5194/amt-14-1457-2021, https://doi.org/10.5194/amt-14-1457-2021, 2021
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A procedure for correcting the turbulent-energy damping connected with spatial averaging of wind lidars is proposed. This effect of the lidar measuring process is modeled through a low-pass filter, whose order and cut-off frequency are estimated directly from the lidar data. The proposed procedure is first assessed through simultaneous and colocated lidar and sonic-anemometer measurements. Then it is applied to several datasets collected at sites with different terrain roughness.
E. Eva Borbas, Elisabeth Weisz, Chris Moeller, W. Paul Menzel, and Bryan A. Baum
Atmos. Meas. Tech., 14, 1191–1203, https://doi.org/10.5194/amt-14-1191-2021, https://doi.org/10.5194/amt-14-1191-2021, 2021
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As the VIIRS satellite sensor has no infrared (IR) H2O absorption bands, we construct the missing bands through the fusion of imager (VIIRS) and sounder (CrIS) data in an attempt to improve derivation of moisture products. This study clearly demonstrates the positive impact by adding fusion IR absorption spectral bands and the potential for continuing the moisture record from MODIS and the previous generations of polar-orbiting satellite sensors.
Maryna Lukach, David Dufton, Jonathan Crosier, Joshua M. Hampton, Lindsay Bennett, and Ryan R. Neely III
Atmos. Meas. Tech., 14, 1075–1098, https://doi.org/10.5194/amt-14-1075-2021, https://doi.org/10.5194/amt-14-1075-2021, 2021
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This paper presents a novel technique of data-driven hydrometeor classification (HC) from quasi-vertical profiles, where the hydrometeor types are identified from an optimal number of hierarchical clusters, obtained recursively. This data-driven HC approach is capable of providing an optimal number of classes from dual-polarimetric weather radar observations. The embedded flexibility in the extent of granularity is the main advantage of this technique.
Andrew Tangborn, Belay Demoz, Brian J. Carroll, Joseph Santanello, and Jeffrey L. Anderson
Atmos. Meas. Tech., 14, 1099–1110, https://doi.org/10.5194/amt-14-1099-2021, https://doi.org/10.5194/amt-14-1099-2021, 2021
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Accurate prediction of the planetary boundary layer is essential to both numerical weather prediction (NWP) and pollution forecasting. This paper presents a methodology to combine these measurements with the models through a statistical data assimilation approach that calculates the correlation between the PBLH and variables like temperature and moisture in the model. The model estimates of these variables can be improved via this method, and this will enable increased forecast accuracy.
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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.
This paper presents an analysis of a large dataset of lightning and polarimetric weather radar...
