Articles | Volume 15, issue 24
https://doi.org/10.5194/amt-15-7315-2022
© Author(s) 2022. 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-15-7315-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Dec 2022
Research article |
| 20 Dec 2022
| 20 Dec 2022
Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes
Mathias Gergely
CORRESPONDING AUTHOR
German Meteorological Service (Deutscher Wetterdienst, DWD), Observatorium Hohenpeißenberg, Hohenpeißenberg, Germany
Maximilian Schaper
German Meteorological Service (Deutscher Wetterdienst, DWD), Observatorium Hohenpeißenberg, Hohenpeißenberg, Germany
Matthias Toussaint
GAMIC Weather Radar and Signal Processing, Aachen, Germany
Michael Frech
German Meteorological Service (Deutscher Wetterdienst, DWD), Observatorium Hohenpeißenberg, Hohenpeißenberg, Germany
Related authors
Armin Blanke, Mathias Gergely, and Silke Trömel
Atmos. Chem. Phys., 25, 4167–4184, https://doi.org/10.5194/acp-25-4167-2025, https://doi.org/10.5194/acp-25-4167-2025, 2025
Short summary
Short summary
The area-wide radar-based distinction between riming and aggregation is crucial for model microphysics and data assimilation. This study introduces a discrimination algorithm based on polarimetric radar networks only. Exploiting the unique opportunity to link fall velocities from Doppler spectra to polarimetric variables in an operational setting enables us to set up and evaluate a well-performing machine learning algorithm.
Mireia Papke Chica, Valerian Hahn, Tiziana Braeuer, Elena de la Torre Castro, Florian Ewald, Mathias Gergely, Simon Kirschler, Luca Bugliaro Goggia, Stefanie Knobloch, Martina Kraemer, Johannes Lucke, Johanna Mayer, Raphael Maerkl, Manuel Moser, Laura Tomsche, Tina Jurkat-Witschas, Martin Zoeger, Christian von Savigny, and Christiane Voigt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-255, https://doi.org/10.5194/acp-2022-255, 2022
Preprint withdrawn
Short summary
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The mixed-phase temperature regime in convective clouds challenges our understanding of microphysical and radiative cloud properties. We provide a rare and unique dataset of aircraft in situ measurements in a strong mid-latitude convective system. We find that mechanisms initiating ice nucleation and growth strongly depend on temperature, relative humidity, and vertical velocity and variate within the measured system, resulting in altitude dependent changes of the cloud liquid and ice fraction.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
Short summary
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Armin Blanke, Mathias Gergely, and Silke Trömel
Atmos. Chem. Phys., 25, 4167–4184, https://doi.org/10.5194/acp-25-4167-2025, https://doi.org/10.5194/acp-25-4167-2025, 2025
Short summary
Short summary
The area-wide radar-based distinction between riming and aggregation is crucial for model microphysics and data assimilation. This study introduces a discrimination algorithm based on polarimetric radar networks only. Exploiting the unique opportunity to link fall velocities from Doppler spectra to polarimetric variables in an operational setting enables us to set up and evaluate a well-performing machine learning algorithm.
Alexander Myagkov, Tatiana Nomokonova, and Michael Frech
Atmos. Meas. Tech., 18, 1621–1640, https://doi.org/10.5194/amt-18-1621-2025, https://doi.org/10.5194/amt-18-1621-2025, 2025
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The study examines the use of the spheroidal shape approximation for calculating cloud radar observables in rain and identifies some limitations. To address these, it introduces the empirical scattering model (ESM) based on high-quality Doppler spectra from a 94 GHz radar. The ESM offers improved accuracy and directly incorporates natural rain's microphysical effects. This new model can enhance retrieval and calibration methods, benefiting cloud radar polarimetry experts and scattering modelers.
Cornelius Hald, Maximilian Schaper, Annette Böhm, Michael Frech, Jan Petersen, Bertram Lange, and Benjamin Rohrdantz
Atmos. Meas. Tech., 17, 4695–4707, https://doi.org/10.5194/amt-17-4695-2024, https://doi.org/10.5194/amt-17-4695-2024, 2024
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Weather radars should use lightning protection to be safe from damage, but the rods can reduce the quality of the radar measurements. This study presents three new solutions for lightning protection for weather radars and evaluates their influence on data quality. The results are compared to the current system. All tested ones have very little effect on data, and a new lightning protection system with four rods is recommended for the German Meteorological Service.
Michael Frech, Cornelius Hald, Maximilian Schaper, Bertram Lange, and Benjamin Rohrdantz
Atmos. Meas. Tech., 16, 295–309, https://doi.org/10.5194/amt-16-295-2023, https://doi.org/10.5194/amt-16-295-2023, 2023
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Weather radar data are the backbone of a lot of meteorological products. In order to obtain a better low-level coverage with radar data, additional systems have to be included. The frequency range in which radars are allowed to operate is limited. A potential radar-to-radar interference has to be avoided. The paper derives guidelines on how additional radars can be included into a C-band weather radar network and how interferences can be avoided.
Maximilian Schaper, Michael Frech, David Michaelis, Cornelius Hald, and Benjamin Rohrdantz
Atmos. Meas. Tech., 15, 6625–6642, https://doi.org/10.5194/amt-15-6625-2022, https://doi.org/10.5194/amt-15-6625-2022, 2022
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C-band weather radar data are commonly compromised by radio frequency interference (RFI) from external sources. It is not possible to separate a superimposed interference signal from the radar data. Therefore, the best course of action is to shut down RFI sources as quickly as possible. An automated RFI detection algorithm has been developed. Since its implementation, persistent RFI sources are eliminated much more quickly, while the number of short-lived RFI sources keeps steadily increasing.
Mireia Papke Chica, Valerian Hahn, Tiziana Braeuer, Elena de la Torre Castro, Florian Ewald, Mathias Gergely, Simon Kirschler, Luca Bugliaro Goggia, Stefanie Knobloch, Martina Kraemer, Johannes Lucke, Johanna Mayer, Raphael Maerkl, Manuel Moser, Laura Tomsche, Tina Jurkat-Witschas, Martin Zoeger, Christian von Savigny, and Christiane Voigt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-255, https://doi.org/10.5194/acp-2022-255, 2022
Preprint withdrawn
Short summary
Short summary
The mixed-phase temperature regime in convective clouds challenges our understanding of microphysical and radiative cloud properties. We provide a rare and unique dataset of aircraft in situ measurements in a strong mid-latitude convective system. We find that mechanisms initiating ice nucleation and growth strongly depend on temperature, relative humidity, and vertical velocity and variate within the measured system, resulting in altitude dependent changes of the cloud liquid and ice fraction.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
Short summary
Short summary
The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Michael Frech and John Hubbert
Atmos. Meas. Tech., 13, 1051–1069, https://doi.org/10.5194/amt-13-1051-2020, https://doi.org/10.5194/amt-13-1051-2020, 2020
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The prime source of the temperature sensitivity of ZDR can be attributed to the antenna assembly. This result is based on over 2000 solar box scans. These data also reveal that there is a 0.6 dB decrease in gain for a 10 °C temperature increase, which directly relates to a bias of the radar reflectivity factor Z, which has not been not accounted for previously. The ZDR variability in and ZDR calibration performance of the German weather radar network are shown.
M. Frech and J. Steinert
Hydrol. Earth Syst. Sci., 19, 1141–1152, https://doi.org/10.5194/hess-19-1141-2015, https://doi.org/10.5194/hess-19-1141-2015, 2015
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Gravity waves above the northern Atlantic and Europe during streamer events using Aeolus
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Mid-Atlantic nocturnal low-level jet characteristics: a machine learning analysis of radar wind profiles
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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
Global Navigation Satellite System (GNSS) radio occultation climatologies mapped by machine learning and Bayesian interpolation
Determination of low-level temperature profiles from microwave radiometer observations during rain
Aeolus lidar surface return (LSR) at 355 nm as a new Aeolus Level-2A product
Sampling the diurnal and annual cycles of the Earth's energy imbalance with constellations of satellite-borne radiometers
Retrieval of top-of-atmosphere fluxes from combined EarthCARE lidar, imager, and broadband radiometer observations: the BMA-FLX product
Analysis of the measurement uncertainty for a 3D wind lidar
Improving solution availability and temporal consistency of an optimal-estimation physical retrieval for ground-based thermodynamic boundary layer profiling
An improved geolocation methodology for spaceborne radar and lidar systems
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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
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Improved consistency in solar-induced fluorescence retrievals from GOME-2A with the SIFTER v3 algorithm
Global-scale gravity wave analysis methodology for the ESA Earth Explorer 11 candidate CAIRT
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
An information content approach to diagnosing and improving CLIMCAPS retrievals across instruments and satellites
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
Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data
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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
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Dual adaptive differential threshold method for automated detection of faint and strong echo features in radar observations of winter storms
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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.
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.
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.
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.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech., 17, 6913–6931, https://doi.org/10.5194/amt-17-6913-2024, https://doi.org/10.5194/amt-17-6913-2024, 2024
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Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose optimized post-processing for error reduction.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
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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).
Tianwen Wei, Mengya Wang, Kenan Wu, Jinlong Yuan, Haiyun Xia, and Simone Lolli
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-178, https://doi.org/10.5194/amt-2024-178, 2024
Revised manuscript accepted for AMT
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This study uses three years of wind lidar measurements to investigate the dynamics of the urban PBL in Hefei, China. Results show that nocturnal low-level jets occur most frequently in spring and intensify in summer, significantly increasing turbulence and shear intensity near the ground level, especially during the night. Cloud cover raises the MLH by around 100 m during the night due to the greenhouse effect and decreases it by up to 200 m in the afternoon by obstructing solar radiation.
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.
Juliëtte C. S. Anema, K. Folkert Boersma, Lieuwe G. Tilstra, Olaf N. E. Tuinder, and Willem W. Verstraeten
EGUsphere, https://doi.org/10.5194/egusphere-2024-2666, https://doi.org/10.5194/egusphere-2024-2666, 2024
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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 that affect 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.
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.
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.
Nadia Smith and Christopher D. Barnet
EGUsphere, https://doi.org/10.5194/egusphere-2024-2448, https://doi.org/10.5194/egusphere-2024-2448, 2024
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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 improved across the full CLIMCAPS record (2002 to present day) spanning multiple instruments and satellites.
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.
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.
Lusheng Liang, Wenying Su, Sergio Sejas, Zachary Eitzen, and Norman G. Loeb
Atmos. Meas. Tech., 17, 2147–2163, https://doi.org/10.5194/amt-17-2147-2024, https://doi.org/10.5194/amt-17-2147-2024, 2024
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This paper describes an updated process to obtain unfiltered radiation from CERES satellite instruments by incorporating the most recent developments in radiative transfer modeling and ancillary input datasets (e.g., realistic representation of land surface radiation and climatology of surface temperatures and aerosols) during the past 20 years. The resulting global mean of instantaneous SW and LW fluxes is changed by less than 0.5 W m−2 with regional differences as large as 2.0 W m−2.
Maximilian Graf, Andreas Wagner, Julius Polz, Llorenç Lliso, José Alberto Lahuerta, Harald Kunstmann, and Christian Chwala
Atmos. Meas. Tech., 17, 2165–2182, https://doi.org/10.5194/amt-17-2165-2024, https://doi.org/10.5194/amt-17-2165-2024, 2024
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Commercial microwave links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is a crucial processing step. We investigate the usage of rainfall data from MSG SEVIRI for this task, compare this approach with existing methods, and introduce a novel combined approach. The results show certain advantages for SEVIRI-based methods, particularly for CMLs where existing methods perform poorly. Our novel combination yields the best performance.
Lieuwe G. Tilstra, Martin de Graaf, Victor J. H. Trees, Pavel Litvinov, Oleg Dubovik, and Piet Stammes
Atmos. Meas. Tech., 17, 2235–2256, https://doi.org/10.5194/amt-17-2235-2024, https://doi.org/10.5194/amt-17-2235-2024, 2024
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This paper introduces a new surface albedo climatology of directionally dependent Lambertian-equivalent reflectivity (DLER) observed by TROPOMI on the Sentinel-5 Precursor satellite. The database contains monthly fields of DLER for 21 wavelength bands at a relatively high spatial resolution of 0.125 by 0.125 degrees. The anisotropy of the surface reflection is handled by parameterisation of the viewing angle dependence.
Bing Cao and Alan Z. Liu
Atmos. Meas. Tech., 17, 2123–2146, https://doi.org/10.5194/amt-17-2123-2024, https://doi.org/10.5194/amt-17-2123-2024, 2024
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A narrow-band sodium lidar measures atmospheric waves but is limited to vertical variations. We propose to utilize phase shifts among observations from different laser beams to derive horizontal wave information. Two gravity wave packets were identified by this method. Both waves were found to interact with thin evanescent layers, partially reflected, but transmitted energy to higher altitudes. The method can detect more medium-frequency gravity waves for similar lidar systems worldwide.
Xiaozhen Xiong, Xu Liu, Robert Spurr, Ming Zhao, Qiguang Yang, Wan Wu, and Liqiao Lei
Atmos. Meas. Tech., 17, 1965–1978, https://doi.org/10.5194/amt-17-1965-2024, https://doi.org/10.5194/amt-17-1965-2024, 2024
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The term “hotspot” refers to the sharp increase in reflectance occurring when incident (solar) and reflected (viewing) directions coincide in the backscatter direction. The accurate simulation of hotspot directional signatures is important for many remote sensing applications, but current models typically require large values of computations to represent the hotspot accurately. This paper provides a numerically improved hotspot BRDF model that converges much faster and is used in VLIDORT.
Cited articles
Al-Sakka, H., Boumahmoud, A.-A., Fradon, B., Frasier, S. J., and Tabary, P.: A new fuzzy logic hydrometeor classification scheme applied to the French X-, C-, and S-band polarimetric radars, J. Appl. Meteorol. Clim., 52, 2328–2344, https://doi.org/10.1175/JAMC-D-12-0236.1, 2013. a
Bechini, R. and Chandrasekar, V.: A semisupervised robust hydrometeor
classification method for dual-polarization radar applications, J. Atmos.
Ocean. Tech., 32, 22–47, https://doi.org/10.1175/JTECH-D-14-00097.1, 2014. a
Besic, N., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmos. Meas. Tech., 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, 2016. a, b
Bringi, V. N. and Chandrasekar, V.: Polarimetric Doppler weather radar: principles and applications, Cambridge University Press, ISBN 0-521-62384-7, 2001. a
Bukovcic, P., Ryzhkov, A., Zrnic, D., and Zhang, G.: Polarimetric radar
relations for quantification of snow based on disdrometer data, J. Appl.
Meteorol. Clim., 57, 103–120, https://doi.org/10.1175/JAMC-D-17-0090.1, 2018. a
Campello, R. J. G. B., Moulavi, D., and Sander, J.: Density-based clustering based on hierarchical density estimates, in: Advances in Knowledge Discovery and Data Mining. PAKDD 2013, edited by: Pei, J., Tseng, V. S., Cao, L., Motoda, H., and Xu, G., Lectue Notes in Computer Science, Springer Berlin Heidelberg, 160–172, https://doi.org/10.1007/978-3-642-37456-2_14, 2013. a
Chase, R. J., Finlon, J. A., Borque, P., McFarquhar, G. M., Nesbitt, S. W.,
Tanelli, S., Sy, O. O., Durden, S. L., and Poellot, M. R.: Evaluation of
triple-frequency radar retrieval of snowfall properties using coincident
airborne in situ observations during OLYMPEX, Geophys. Res. Lett., 45,
5752–5760, https://doi.org/10.1029/2018GL077997, 2018. a
Dolan, B. and Rutledge, S. A.: A theory-based hydrometeor identification
algorithm for X-band polarimetric radars, J. Atmos. Ocean. Tech., 26,
2071–2088, https://doi.org/10.1175/2009JTECHA1208.1, 2009. a
Dolan, B., Rutledge, S. A., Lim, S., Chandrasekar, V., and Thurai, M.: A robust C-band hydrometeor identification algorithm and application to a long-term polarimetric radar dataset, J. Appl. Meteorol. Clim., 52, 2162–2186, https://doi.org/10.1175/JAMC-D-12-0275.1, 2013. a
Frech, M. and Hubbert, J.: Monitoring the differential reflectivity and receiver calibration of the German polarimetric weather radar network, Atmos. Meas. Tech., 13, 1051–1069, https://doi.org/10.5194/amt-13-1051-2020, 2020. a, b
Frech, M. and Steinert, J.: Polarimetric radar observations during an orographic rain event, Hydrol. Earth Syst. Sci., 19, 1141–1152, https://doi.org/10.5194/hess-19-1141-2015, 2015. a, b
Frech, M., Lange, B., Mammen, T., Seltmann, J., Morehead, C., and Rowan, J.:
Influence of a radome on antenna performance, J. Atmos. Ocean. Tech., 30,
313–324, https://doi.org/10.1175/JTECH-D-12-00033.1, 2013. a
Frech, M., Hagen, M., and Mammen, T.: Monitoring the absolute calibration of a polarimetric weather radar, J. Atmos. Ocean. Tech., 34, 599–615,
https://doi.org/10.1175/JTECH-D-16-0076.1, 2017. a, b
Frech, M., Mammen, T., and Lange, B.: Pointing accuracy of an operational polarimetric weather radar, Remote Sens., 11, 1115, https://doi.org/10.3390/rs11091115,
2019. a
Garrett, T. J., Fallgatter, C., Shkurko, K., and Howlett, D.: Fall speed measurement and high-resolution multi-angle photography of hydrometeors in free fall, Atmos. Meas. Tech., 5, 2625–2633, https://doi.org/10.5194/amt-5-2625-2012, 2012. a
Gergely, M.: Sensitivity of snowfall radar reflectivity to maximum snowflake
size and implications for snowfall retrievals, J. Quant. Spectrosc. Radiat.
Transfer, 236, 106605, https://doi.org/10.1016/j.jqsrt.2019.106605, 2019. a
Gergely, M., Cooper, S. J., and Garrett, T. J.: Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures, Atmos. Chem. Phys., 17, 12011–12030, https://doi.org/10.5194/acp-17-12011-2017, 2017. a
Grazioli, J., Tuia, D., and Berne, A.: Hydrometeor classification from polarimetric radar measurements: a clustering approach, Atmos. Meas. Tech., 8, 149–170, https://doi.org/10.5194/amt-8-149-2015, 2015. a
Griffin, E. M., Schuur, T. J., and Ryzhkov, A. V.: A polarimetric analysis of ice microphysical processes in snow, using quasi-vertical profiles, J. Appl.
Meteorol. Climatol., 57, 31–50, https://doi.org/10.1175/JAMC-D-17-0033.1, 2018. a
Harris, F. J.: On the use of windows for harmonic analysis with the discrete Fourier transform, Proc. IEEE, 66, 51–83, https://doi.org/10.1109/PROC.1978.10837,
1978. a
Hartigan, J. A. and Hartigan, P. M.: The dip test of unimodality, Ann. Stat., 13, 70–84, https://www.jstor.org/stable/2241144 (last access: 15 December 2022), 1985. a
Illingworth, A. J., Hogan, R. J., O'Connor, E. J., Bouniol, D., Brooks, M. E., Delanoé, J., Donovan, D. P., Eastment, J. D., Gaussiat, N., Goddard, J. W. F., Haeffelin, M., Baltink, H. K., Krasnov, O. A., Pelon, J., Piriou, J.-M., Protat, A., Russchenberg, H. W. J., Seifert, A., Tompkins, A. M., van Zadelhoff, G.-J., Vinit, F., Willén, U., Wilson, D. R., and Wrench, C. L.: CloudNet: continuous evaluation of cloud profiles in seven operational models using ground-based observations, Bull. Am. Meteorol. Soc., 88, 883–898, https://doi.org/10.1175/BAMS-88-6-883, 2007. a
JCGM 100:2008: Evaluation of measurement data – Guide to the expression of uncertainty in measurement, Tech. Rep. 100:2008, Joint Committee for Guides in Metrology, https://www.bipm.org/en/committees/jc/jcgm/publications (last access: 15 December 2022), 2008. a
Kalesse, H., Szyrmer, W., Kneifel, S., Kollias, P., and Luke, E.: Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling, Atmos. Chem. Phys., 16, 2997–3012, https://doi.org/10.5194/acp-16-2997-2016, 2016. a, b
Kaltenboeck, R. and Ryzhkov, A.: A freezing rain storm explored with a C-band polarimetric weather radar using the QVP methodology, Meteorol. Z., 26, 207–222, https://doi.org/10.1127/metz/2016/0807, 2016. a
Kleine, J., Voigt, C., Sauer, D., Schlager, H., Scheibe, M., Kaufmann, S., Jurkat-Witschas, T., Kärcher, B., and Anderson, B.: In situ observations
of ice particle losses in a young persistent contrail, Geophys. Res. Lett.,
45, 13553–13561, https://doi.org/10.1029/2018GL079390, 2018. a
Kneifel, S., von Lerber, A., Tiira, J., Moisseev, D., Kollias, P., and
Leinonen, J.: Observed relations between snowfall microphysics and
triple-frequency radar measurements, J. Geophys. Res.-Atmos., 120,
6034–6055, https://doi.org/10.1002/2015JD023156, 2015. a
Kollias, P., Clothiaux, E. E., Miller, M. A., Luke, E. P., Johnson, K. L., Moran, K. P., Widener, K. B., and Albrecht, B. A.: The Atmospheric Radiation Measurement Program cloud profiling radars: second-generation
sampling strategies, processing, and cloud data products, J. Atmos. Ocean.
Tech., 24, 1199–1214, https://doi.org/10.1175/JTECH2033.1, 2007. a, b, c, d, e
Kumjian, M. R. and Lombardo, K. A.: Insights into the evolving microphysical
and kinematic structure of northeastern U.S. winter storms from
dual-polarization Doppler radar, Mon. Weather Rev., 145, 1033–1061,
https://doi.org/10.1175/MWR-D-15-0451.1, 2017. a
Kumjian, M. R., Rutledge, S. A., Rasmussen, R. M., Kennedy, P. C., and Dixon, M.: High-resolution polarimetric radar observations of snow-generating cells,
J. Appl. Meteorol. Clim., 53, 1636–1658, https://doi.org/10.1175/JAMC-D-13-0312.1,
2014. a
Kumjian, M. R., Mishra, S., Giangrande, S. E., Toto, T., Ryzhkov, A. V., and
Bansemer, A.: Polarimetric radar and aircraft observations of saggy bright
bands during MC3E, J. Geophys. Res.-Atmos., 121, 3584–3607,
https://doi.org/10.1002/2015JD024446, 2016. a
Kumjian, M. R., Tobin, D. M., Oue, M., and Kollias, P.: Microphysical insights into ice pellet formation revealed by fully polarimetric Ka-band Doppler radar, J. Appl. Meteorol. Clim., 59, 1557–1580,
https://doi.org/10.1175/JAMC-D-20-0054.1, 2020. a
Li, H., Moisseev, D., and von Lerber, A.: How does riming affect dual-polarization radar observations and snowflake shape?, J. Geophys. Res.-Atmos., 123, 6070–6081, https://doi.org/10.1029/2017JD028186, 2018. a
Luke, E. P., Kollias, P., and Shupe, M. D.: Detection of supercooled liquid in mixed-phase clouds using radar Doppler spectra, J. Geophys. Res., 115,
D19201, https://doi.org/10.1029/2009JD012884, 2010. a
Maahn, M. and Kollias, P.: Improved Micro Rain Radar snow measurements using Doppler spectra post-processing, Atmos. Meas. Tech., 5, 2661–2673, https://doi.org/10.5194/amt-5-2661-2012, 2012. a
Maahn, M. and Löhnert, U.: Potential of higher-order moments and slopes of the radar Doppler spectrum for retrieving microphysical and kinematic
properties of Arctic ice clouds, J. Appl. Meteorol. Clim., 56,
263–282, https://doi.org/10.1175/JAMC-D-16-0020.1, 2017. a, b, c
Marzano, F. S., Scaranari, D., and Vulpiani, G.: Supervised fuzzy-logic
classification of hydrometeors using C-band weather radars, IEEE T.
Geosci. Remote, 45, 3784–3799, https://doi.org/10.1109/TGRS.2007.903399, 2007. a
Marzano, F. S., Scaranari, D., Montpoli, M., and Vulpiani, G.: Supervised
classification and estimation of hydrometeors from C-band dual-polarized
radars: a Bayesian approach, IEEE T. Geosci. Remote, 46, 85–98,
https://doi.org/10.1109/TGRS.2007.906476, 2008. a
Marzano, F. S., Botta, G., and Montopoli, M.: Iterative Bayesian retrieval of hydrometeor content from X-band polarimetric weather radar, IEEE T.
Geosci. Remote, 48, 3059–3074, https://doi.org/10.1109/TGRS.2010.2045231, 2010. a
Matrosov, S. Y., Reinking, R. F., and Djalalova, I. V.: Inferring fall
attitudes of pristine dendritic crystals from polarimetric radar data, J.
Atmos. Sci., 62, 241–250, https://doi.org/10.1175/JAS-3356.1, 2005. a
Maurus, S. and Plant, C.: Skinny-dip: clustering in a sea of noise, in: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD'16, San Francisco, California, USA, 13–17 August 2016, Association for Computing Machinery, 1055–1064, https://doi.org/10.1145/2939672.2939740, 2016. a
McInnes, L., Healy, J., and Astels, S.: hdbscan: hierarchical density based
clustering, Journal of Open Source Software, 2, 205,
https://doi.org/10.21105/joss.00205, 2017. a
Melnikov, V.: Parameters of cloud ice particles retrieved from radar data, J.
Atmos. Ocean. Tech., 34, 717–728, https://doi.org/10.1175/JTECH-D-16-0123.1, 2017. a
Melnikov, V. and Straka, J. M.: Axis ratios and flutter angles of cloud ice
particles: retrievals from radar data, J. Atmos. Ocean. Tech., 30,
1691–1703, https://doi.org/10.1175/JTECH-D-12-00212.1, 2013. a
Moisseev, D., von Lerber, A., and Tiira, J.: Quantifying the effect of riming
on snowfall using ground-based observations, J. Geophys. Res.-Atmos., 122,
4019–4037, https://doi.org/10.1002/2016JD026272, 2017. a
Moisseev, D. N. and Chandrasekar, V.: Polarimetric spectral filter for adaptive clutter and noise suppression, J. Atmos. Ocean. Tech., 26, 215–228,
https://doi.org/10.1175/2008JTECHA1119.1, 2009. a, b
Moisseev, D. N., Lautaportti, S., Tyynela, J., and Lim, S.: Dual-polarization
radar signatures in snowstorms: role of snowflake aggregation, J. Geophys.
Res.-Atmos., 120, 12644–12655, https://doi.org/10.1002/2015JD023884, 2015. a, b
Myagkov, A., Seifert, P., Bauer-Pfundstein, M., and Wandinger, U.: Cloud radar with hybrid mode towards estimation of shape and orientation of ice crystals, Atmos. Meas. Tech., 9, 469–489, https://doi.org/10.5194/amt-9-469-2016, 2016. a
Nesbitt, S. W., Salio, P. V., Ávila, E., et al.: A storm safari in subtropical South America: proyecto RELAMPAGO, B. Am. Meteorol. Soc., 102, E1621–E1644, https://doi.org/10.1175/BAMS-D-20-0029.1, 2021. a
Oue, M., Kollias, P., Ryzhkov, A., and Luke, E. P.: Toward exploring the
synergy between cloud radar polarimetry and Doppler spectral analysis in
deep cold precipitating systems in the Arctic, J. Geophys. Res.-Atmos.,
123, 2797–2815, https://doi.org/10.1002/2017JD027717, 2018. a, b
Park, H., Ryzhkov, A. V., Zrnic, D. S., and Kim, K.-E.: The hydrometeor
classification algorithm for the polarimetric WSR-88D: description and
application to an MCS, Weather Forecast., 24, 730–748,
https://doi.org/10.1175/2008WAF2222205.1, 2009. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.: Scikit-learn: machine learning in Python, J. Mach. Learn. Res., 12, 2825–2830, https://scikit-learn.org/stable/ (last access: 15 December 2022), 2011. a
Petty, G. W. and Huang, W.: The modified Gamma size distribution applied to inhomogeneous and nonspherical particles: key relationships and conversions,
J. Atmos. Sci., 68, 1460–1473, https://doi.org/10.1175/2011JAS3645.1, 2011. a
Pucik, T., Castellano, C., Groenemeijer, P., Kühne, T., Rädler, A. T.,
Antonescu, B., and Faust, E.: Large hail incidence and its economic and
societal impacts across Europe, Mon. Weather Rev., 147, 3901–3916,
https://doi.org/10.1175/MWR-D-19-0204.1, 2019. a
Ryzhkov, A., Zhang, P., Reeves, H., Kumjian, M., Tschallener, T., Trömel,
S., and Simmer, C.: Quasi-vertical profiles – a new way to look at
polrimetric radar data, J. Atmos. Ocean. Tech., 33, 551–562,
https://doi.org/10.1175/JTECH-D-15-0020.1, 2016. a, b
Ryzhkov, A. V. and Zrnic, D. S.: Radar polarimetry for weather observations, Springer, Cham, ISBN 978-3-030-05093-1, https://doi.org/10.1007/978-3-030-05093-1, 2019. a, b, c
Savitzky, A. and Golay, M. J. E.: Smoothing and differentiation of data by
simplified least squares procedures, Anal. Chem., 36, 1627–1639,
https://doi.org/10.1021/ac60214a047, 1964. a
Shupe, M. D., Kollias, P., Matrosov, S. Y., and Schneider, T. L.: Deriving mixed-phase cloud properties from Doppler radar spectra, J. Atmos. Ocean. Tech., 21, 660–670, https://doi.org/10.1175/1520-0426(2004)021<0660:DMCPFD>2.0.CO;2, 2004. a
Siggia, A. D. and Passarelli, R. E.: Gaussian model adaptive processing (GMAP) for improved ground clutter cancellation and moment calculation, in: Proc. 3rd European Conf. on Radar Meteorology (ERAD), Visby, Sweden, 6–10 September 2004, 67–73, https://www.copernicus.org/erad/2004/online/ERAD04_P_67.pdf (last access: 15 December 2022), 2004. a
Singh, D. K., Donovan, S., Pardyjak, E. R., and Garrett, T. J.: A differential emissivity imaging technique for measuring hydrometeor mass and type, Atmos. Meas. Tech., 14, 6973–6990, https://doi.org/10.5194/amt-14-6973-2021, 2021. a
Steinert, J., Tracksdorf, P., and Heizenreder, D.: Hymec: surface precipitation type estimation at the German Weather Service, Weather Forecast., 36, 1611–1627, https://doi.org/10.1175/WAF-D-20-0232.1, 2021. a, b
Thompson, E. J., Rutledge, S. A., Dolan, B., Chandrasekar, V., and Cheong,
B. L.: A dual-polarization radar hydrometeor classification algorithm for
winter precipitation, J. Atmos. Ocean. Tech., 31, 1457–1481,
https://doi.org/10.1175/JTECH-D-13-00119.1, 2014. a
Trömel, S., Ryzhkov, A. V., Zhang, P., and Simmer, C.: Investigations of
backscatter differential phase in the melting layer, J. Appl. Meteorol.
Clim., 53, 2344–2359, https://doi.org/10.1175/JAMC-D-14-0050.1, 2014. a
Trömel, S., Simmer, C., Blahak, U., Blanke, A., Doktorowski, S., Ewald, F., Frech, M., Gergely, M., Hagen, M., Janjic, T., Kalesse-Los, H., Kneifel, S., Knote, C., Mendrok, J., Moser, M., Köcher, G., Mühlbauer, K., Myagkov, A., Pejcic, V., Seifert, P., Shrestha, P., Teisseire, A., von Terzi, L., Tetoni, E., Vogl, T., Voigt, C., Zeng, Y., Zinner, T., and Quaas, J.: Overview: Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes, Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, 2021. a, b, c, d
Virtanen, P., Gommers, R., Oliphant, T. E., et al.: SciPy 1.0: fundamental algorithms for scientific computing in Python, Nat. Methods, 17, 261–272, https://doi.org/10.1038/s41592-019-0686-2, 2020. a, b
Vivekanandan, J., Zhang, G., and Brandes, E.: Polarimetric radar estimators
based on a constrained gamma drop size distribution model, J. Appl.
Meteorol., 43, 217–230, 2004. a
Vogel, J. M. and Fabry, F.: Contrasting polarimetric observations of stratiform riming and nonriming events, J. Appl. Meteorol. Clim., 57, 457–476, https://doi.org/10.1175/JAMC-D-16-0370.1, 2018. a
Vogl, T., Maahn, M., Kneifel, S., Schimmel, W., Moisseev, D., and Kalesse-Los, H.: Using artificial neural networks to predict riming from Doppler cloud radar observations, Atmos. Meas. Tech., 15, 365–381, https://doi.org/10.5194/amt-15-365-2022, 2022. a
Voigt, C., Lelieveld, J., Schlager, H., Schneider, J., Sauer, D., Meerkötter, R., Pöhlker, M., Bugliaro, L., Curtius, J., Erbertseder, T., Hahn, V., Jöckel, P., Li, Q., Marsing, A., Mertens, M., Pöhlker, C., Pöschl, U., Pozzer, A., Tomsche, L., and Schumann, U.: Aerosol and Cloud Changes during the Corona Lockdown in 2020 – First highlights from the BLUESKY campaign, EGU General Assembly 2021, online, 19–30 April 2021, EGU21-13134, https://doi.org/10.5194/egusphere-egu21-13134, 2021.
a
Yu, T.-Y., Xiao, X., and Wang, Y.: Statistical quality of spectral polarimetric variables for weather radar, J. Atmos. Ocean. Tech., 29, 1221–1235, https://doi.org/10.1175/JTECH-D-11-00090.1, 2012. a
Yuter, S. E., Kingsmill, D. E., Nance, L. B., and Löffler-Mang, M.:
Observations of precipitation size and fall speed characteristics within
coexisting rain and wet snow, J. Appl. Meteorol. Clim., 45, 1450–1464,
2006. a
Zängl, G., Reinert, D., Ripodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M:
description of the non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc.,
141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a, b
Zhang, C., Mapes, B. E., and Soden, B. J.: Bimodality in tropical water vapour, Q. J. Roy. Meteor. Soc., 129, 2847–2866, https://doi.org/10.1256/qj.02.166, 2003. a, b
Zipser, E. J., Cecil, D. J., Liu, C., Nesbitt, S. W., and Yorty, D. P.: Where are the most intense thunderstorms on Earth?, B. Am. Meteorol. Soc., 87,
1057–1072, https://doi.org/10.1175/BAMS-87-8-1057, 2006. a
Short summary
This study presents the new vertically pointing birdbath scan of the German C-band radar network, which provides high-resolution profiles of precipitating clouds above all DWD weather radars since the spring of 2021. Our AI-based postprocessing method for filtering and analyzing the recorded radar data offers a unique quantitative view into a wide range of precipitation events from snowfall over stratiform rain to intense frontal showers and will be used to complement DWD's operational services.
This study presents the new vertically pointing birdbath scan of the German C-band radar...
