Articles | Volume 17, issue 23
https://doi.org/10.5194/amt-17-6913-2024
© 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-17-6913-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Dec 2024
Research article |
| 10 Dec 2024
| 10 Dec 2024
Analysis of the measurement uncertainty for a 3D wind lidar
Wolf Knöller
Fraunhofer Institute for Physical Measurement Techniques IPM, Georges-Köhler-Allee 301, 79110 Freiburg, Germany
Gholamhossein Bagheri
Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany
Philipp von Olshausen
CORRESPONDING AUTHOR
Fraunhofer Institute for Physical Measurement Techniques IPM, Georges-Köhler-Allee 301, 79110 Freiburg, Germany
Michael Wilczek
Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany
Theoretical Physics I, University of Bayreuth, Universitätsstraße 30, 95447 Bayreuth, Germany
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Birte Thiede, Oliver Schlenczek, Katja Stieger, Alexander Ecker, Eberhard Bodenschatz, and Gholamhossein Bagheri
EGUsphere, https://doi.org/10.5194/egusphere-2025-612, https://doi.org/10.5194/egusphere-2025-612, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Accurate measurement of cloud particles is crucial for cloud research. While holographic imaging enables detailed analysis of cloud droplet size, shape, and distribution, processing errors remain poorly quantified. To address this, we developed CloudTarget, a patterned photomask that can quantify the detection efficiency and uncertainties. Additionally, our AI-based classification enhances both accuracy and speed, achieving over 90 % precision while accelerating analysis 100-fold.
Viet Le, Konstantinos Matthaios Doulgeris, Mika Komppula, John Backman, Gholamhossein Bagheri, Eberhard Bodenschatz, and David Brus
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-148, https://doi.org/10.5194/essd-2025-148, 2025
Preprint under review for ESSD
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This manuscript presents datasets collected during the Pallas Cloud Experiment in northern Finland during the autumn of 2022. We provide an overview of the payload that measured meteorological, cloud, and aerosol properties, and was deployed on tethered balloon systems across 21 flights. Additionally, we describe the datasets obtained, including details of the instruments on the payload.
Venecia Chávez-Medina, Hossein Khodamoradi, Oliver Schlenczek, Freja Nordsiek, Claudia E. Brunner, Eberhard Bodenschatz, and Gholamhossein Bagheri
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-111, https://doi.org/10.5194/essd-2025-111, 2025
Preprint under review for ESSD
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During the Pallas Cloud Experiment (PaCE) in Finland (September 15–28, 2022), detailed measurements of clouds and boundary layer turbulence were gathered. Using the Max Planck CloudKite platform, WinDarts, and a ground station, data were collected from ground level up to 1510 m. This paper presents the data collection process, structure, and user guidelines.
Oliver Schlenczek, Freja Nordsiek, Claudia E. Brunner, Venecia Chávez-Medina, Birte Thiede, Eberhard Bodenschatz, and Gholamhossein Bagheri
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-112, https://doi.org/10.5194/essd-2025-112, 2025
Preprint under review for ESSD
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During the Pallas Cloud Experiment (PaCE) in Finland (Sept. 19–26, 2022), the Advanced Max Planck CloudKite instrument (MPCK+) gathered turbulence, wind shear, and cloud data from 0–1200 m. Flights lasted 1.5–3 hours, capturing droplet concentrations and size distributions at high resolution (<10 m spacing). The dataset aids studies of Arctic boundary layer clouds above freezing temperatures. This paper details the data collection, structure, and user guidelines.
Alina Sylvia Waltraud Reininger, Daria Tatsii, Taraprasad Bhowmick, Gholamhossein Bagheri, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2025-605, https://doi.org/10.5194/egusphere-2025-605, 2025
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Microplastics are transported over large distances in the atmosphere, but the shape-dependence of their atmospheric transport lacks investigation. We conducted laboratory experiments and atmospheric transport simulations to study the settling of commercially sold microplastics. We found that films settle up to 74 % slower and travel up to ~ 4x further than volume-equivalent spheres. Our work emphasizes the role of the atmosphere as a transport medium for commercial microplastics such as glitter.
Simon Thivet, Gholamhossein Bagheri, Przemyslaw M. Kornatowski, Allan Fries, Jonathan Lemus, Riccardo Simionato, Carolina Díaz-Vecino, Eduardo Rossi, Taishi Yamada, Simona Scollo, and Costanza Bonadonna
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-162, https://doi.org/10.5194/amt-2024-162, 2024
Revised manuscript accepted for AMT
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This work presents an innovative way of sampling and analyzing volcanic clouds using an Unoccupied Aircraft System (UAS). The UAS can reach hazardous environments to sample volcanic particles, and measure in-situ key parameters such as the atmospheric concentration of volcanic aerosols and gases. Acquired data bridge the gap between the existing approaches of ground sampling and remote sensing, hence contributing to the understanding of volcanic cloud dispersion and impact.
Marcel Schröder, Tobias Bätge, Eberhard Bodenschatz, Michael Wilczek, and Gholamhossein Bagheri
Atmos. Meas. Tech., 17, 627–657, https://doi.org/10.5194/amt-17-627-2024, https://doi.org/10.5194/amt-17-627-2024, 2024
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The rate at which energy is dissipated in a turbulent flow is an extremely important quantity. In the atmosphere, it is usually measured by recording a velocity time at a specific location. Our goal is to understand how best to estimate the dissipation rate from such data based on various available methods. Our reference for evaluating the performance of the different methods is data generated with direct numerical simulations and in highly controlled laboratory setups.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Claudia Christine Stephan, Sabrina Schnitt, Hauke Schulz, Hugo Bellenger, Simon P. de Szoeke, Claudia Acquistapace, Katharina Baier, Thibaut Dauhut, Rémi Laxenaire, Yanmichel Morfa-Avalos, Renaud Person, Estefanía Quiñones Meléndez, Gholamhossein Bagheri, Tobias Böck, Alton Daley, Johannes Güttler, Kevin C. Helfer, Sebastian A. Los, Almuth Neuberger, Johannes Röttenbacher, Andreas Raeke, Maximilian Ringel, Markus Ritschel, Pauline Sadoulet, Imke Schirmacher, M. Katharina Stolla, Ethan Wright, Benjamin Charpentier, Alexis Doerenbecher, Richard Wilson, Friedhelm Jansen, Stefan Kinne, Gilles Reverdin, Sabrina Speich, Sandrine Bony, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 491–514, https://doi.org/10.5194/essd-13-491-2021, https://doi.org/10.5194/essd-13-491-2021, 2021
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The EUREC4A field campaign took place in the western tropical Atlantic during January and February 2020. A total of 811 radiosondes, launched regularly (usually 4-hourly) from Barbados, and 4 ships measured wind, temperature, and relative humidity. They sampled atmospheric variability associated with different ocean surface conditions, synoptic variability, and mesoscale convective organization. The methods of data collection and post-processing for the radiosonde data are described here.
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Improved consistency in solar-induced fluorescence retrievals from GOME-2A with the SIFTER v3 algorithm
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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
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
Improving solution availability and temporal consistency of an optimal-estimation physical retrieval for ground-based thermodynamic boundary layer profiling
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
HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and 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)
Combining commercial microwave links and weather radar for classification of dry snow and rainfall
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
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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
Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere
Observed impact of the GNSS clock data rate on Radio Occultation bending angles for Sentinel-6A and COSMIC-2
High Spectral Resolution Lidar – generation 2 (HSRL-2) retrievals of ocean surface wind speed: methodology and evaluation
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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.
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
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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
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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).
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
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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.
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
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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
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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
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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.
Erlend Øydvin, Renaud Gaban, Jafet Andersson, Remco van de Beek, Mareile Astrid Wolff, Nils-Otto Kitterød, Christian Chwala, and Vegard Nilsen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2625, https://doi.org/10.5194/egusphere-2024-2625, 2024
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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.
Sebastiano Padovan, Axel Von Engeln, Saverio Paolella, Yago Andres, Chad R. Galley, Riccardo Notarpietro, Veronica Rivas Boscán, Francisco Sancho, Francisco Martin Alemany, Nicolas Morew, and Christian Marquardt
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-80, https://doi.org/10.5194/amt-2024-80, 2024
Revised manuscript accepted for AMT
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Radio Occultation (RO) measurements are an important contribution to numerical weather predictions and long-term climate studies. Using more than a hundred thousand occultations recorded by instruments onboard the Sentinel-6A and Cosmic-2 satellites, this work studies the effects of the clock data rate of the Global Navigation Satellite System on the RO data quality. GLONASS occultations benefit of high-rate clock data (1 second), GPS occultation have high quality already at 30 seconds.
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024, https://doi.org/10.5194/amt-17-3515-2024, 2024
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This study introduces and evaluates a new ocean surface wind speed product from the NASA Langley Research Center (LARC) airborne High-Spectral-Resolution Lidar – Generation 2 (HSRL-2) during the NASA ACTIVATE mission. We show that HSRL-2 surface wind speed data are accurate when compared to ground-truth dropsonde measurements. Therefore, the HSRL-2 instrument is able obtain accurate, high-resolution surface wind speed data in airborne field campaigns.
Laura M. Tomkins, Sandra E. Yuter, and Matthew A. Miller
Atmos. Meas. Tech., 17, 3377–3399, https://doi.org/10.5194/amt-17-3377-2024, https://doi.org/10.5194/amt-17-3377-2024, 2024
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We have created a new method to better identify enhanced features in radar data from winter storms. Unlike the clear-cut features seen in warm-season storms, features in winter storms are often fuzzier with softer edges. Our technique is unique because it uses two adaptive thresholds that change based on the background radar values. It can identify both strong and subtle features in the radar data and takes into account uncertainties in the detection process.
Eileen Päschke and Carola Detring
Atmos. Meas. Tech., 17, 3187–3217, https://doi.org/10.5194/amt-17-3187-2024, https://doi.org/10.5194/amt-17-3187-2024, 2024
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Little noise in radial velocity Doppler lidar measurements can contribute to large errors in retrieved turbulence variables. In order to distinguish between plausible and erroneous measurements we developed new filter techniques that work independently of the choice of a specific threshold for the signal-to-noise ratio. The performance of these techniques is discussed both by means of assessing the filter results and by comparing retrieved turbulence variables versus independent measurements.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
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Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024, https://doi.org/10.5194/amt-17-2539-2024, 2024
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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.
Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi
Atmos. Meas. Tech., 17, 2195–2217, https://doi.org/10.5194/amt-17-2195-2024, https://doi.org/10.5194/amt-17-2195-2024, 2024
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The paper describes a new machine-learning-based snowfall retrieval algorithm for Advanced Technology Microwave Sounder observations developed to retrieve high-latitude snowfall events. The main novelty of the approach is the radiometric characterization of the background surface at the time of the overpass, which is ancillary to the retrieval process. The algorithm shows a unique capability to retrieve snowfall in the environmental conditions typical of high latitudes.
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Kumer, V. M., Reuder, J., Dorninger, M., Zauner, R., and Grubišić, V.: Turbulent kinetic energy estimates from profiling wind LiDAR measurements and their potential for wind energy applications, Renew. Energ., 99, 898–910, https://doi.org/10.1016/j.renene.2016.07.014, 2016. a
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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.
Three-dimensional (3D) wind velocity measurements are of major importance for the...
