Articles | Volume 13, issue 9
https://doi.org/10.5194/amt-13-5065-2020
© Author(s) 2020. 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-13-5065-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Sep 2020
Research article |
| 28 Sep 2020
| 28 Sep 2020
Estimating total attenuation using Rayleigh targets at cloud top: applications in multilayer and mixed-phase clouds observed by ground-based multifrequency radars
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Alessandro Battaglia
Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Turin, Italy
Department of Physics and Astronomy, University of Leicester, Leicester, UK
Stefan Kneifel
Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
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Shannon L. Mason, Robin J. Hogan, Christopher D. Westbrook, Stefan Kneifel, Dmitri Moisseev, and Leonie von Terzi
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José Dias Neto, Stefan Kneifel, Davide Ori, Silke Trömel, Jan Handwerker, Birger Bohn, Normen Hermes, Kai Mühlbauer, Martin Lenefer, and Clemens Simmer
Earth Syst. Sci. Data, 11, 845–863, https://doi.org/10.5194/essd-11-845-2019, https://doi.org/10.5194/essd-11-845-2019, 2019
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This study describes a 2-month dataset of ground-based, vertically pointing triple-frequency cloud radar observations recorded during the winter season 2015/2016 in Jülich, Germany. Intensive quality control has been applied to the unique long-term dataset, which allows the multifrequency signatures of ice and snow particles to be statistically analyzed for the first time. The analysis includes, for example, aggregation and its dependence on cloud temperature, riming, and onset of melting.
Mengistu Wolde, Alessandro Battaglia, Cuong Nguyen, Andrew L. Pazmany, and Anthony Illingworth
Atmos. Meas. Tech., 12, 253–269, https://doi.org/10.5194/amt-12-253-2019, https://doi.org/10.5194/amt-12-253-2019, 2019
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This paper presents an implementation of polarization diversity pulse-pair processing (PDPP) on the National Research Council of Canada airborne W-band radar (NAW) system. A description of the NAW PDPP pulsing schemes and an analysis of comprehensive airborne data collected in diverse weather conditions in Canada is presented. The analysis shows a successful airborne measurement of Doppler velocity exceeding 100 m s−1 using PDPP approach, the first such measurement from a moving platform.
Claudia Acquistapace, Stefan Kneifel, Ulrich Löhnert, Pavlos Kollias, Maximilian Maahn, and Matthias Bauer-Pfundstein
Atmos. Meas. Tech., 10, 1783–1802, https://doi.org/10.5194/amt-10-1783-2017, https://doi.org/10.5194/amt-10-1783-2017, 2017
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The goal of the paper is to understand what the optimal cloud radar settings for drizzle detection are. The number of cloud radars in the world has increased in the last 10 years and it is important to develop strategies to derive optimal settings which can be applied to all radar systems. The study is part of broader research focused on better understanding the microphysical process of drizzle growth using ground-based observations.
Francesco De Angelis, Domenico Cimini, James Hocking, Pauline Martinet, and Stefan Kneifel
Geosci. Model Dev., 9, 2721–2739, https://doi.org/10.5194/gmd-9-2721-2016, https://doi.org/10.5194/gmd-9-2721-2016, 2016
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Ground-based microwave radiometers (MWRs) offer to bridge the observational gap in the atmospheric boundary layer. Currently MWRs are operational at many sites worldwide. However, their potential is largely under-exploited, partly due to the lack of a fast radiative transfer model (RTM) suited for data assimilation into numerical weather prediction models. Here we propose and test an RTM, building on satellite heritage and adapting for ground-based MWRs, which addresses this shortage.
Heike Kalesse, Wanda Szyrmer, Stefan Kneifel, Pavlos Kollias, and Edward Luke
Atmos. Chem. Phys., 16, 2997–3012, https://doi.org/10.5194/acp-16-2997-2016, https://doi.org/10.5194/acp-16-2997-2016, 2016
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Mixed-phase clouds are ubiquitous. Process-level understanding is needed to address the complexity of mixed-phase clouds and to improve their representation in models. This study illustrates steps to identify the impact of a microphysical process (riming) on cloud Doppler radar observations. It suggests that in situ observations of key ice properties are needed to complement radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations in models.
I. V. Gorodetskaya, S. Kneifel, M. Maahn, K. Van Tricht, W. Thiery, J. H. Schween, A. Mangold, S. Crewell, and N. P. M. Van Lipzig
The Cryosphere, 9, 285–304, https://doi.org/10.5194/tc-9-285-2015, https://doi.org/10.5194/tc-9-285-2015, 2015
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Our paper presents a new cloud-precipitation-meteorological observatory established in the escarpment zone of Dronning Maud Land, East Antarctica. The site is characterised by bimodal cloud occurrence (clear sky or overcast) with liquid-containing clouds occurring 20% of the cloudy periods. Local surface mass balance strongly depends on rare intense snowfall events. A substantial part of the accumulated snow is removed by surface and drifting snow sublimation and wind-driven snow erosion.
A. Battaglia, C. D. Westbrook, S. Kneifel, P. Kollias, N. Humpage, U. Löhnert, J. Tyynelä, and G. W. Petty
Atmos. Meas. Tech., 7, 1527–1546, https://doi.org/10.5194/amt-7-1527-2014, https://doi.org/10.5194/amt-7-1527-2014, 2014
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
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In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
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The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
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We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
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The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
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The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Gerald Mace
EGUsphere, https://doi.org/10.5194/egusphere-2023-2606, https://doi.org/10.5194/egusphere-2023-2606, 2023
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The number of cloud droplets, Nd, in a cloud is important for understanding aerosol-cloud interaction. In this study we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometer. We show that the deriving Nd is very uncertain although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
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The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
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Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
EGUsphere, https://doi.org/10.5194/egusphere-2023-2804, https://doi.org/10.5194/egusphere-2023-2804, 2023
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Multilayer (ML) clouds affect the radiation budget differently than single-layer (SL) clouds and need to be identified in satellite images. A neural network was trained to identify ML clouds by matching imagery with lidar/radar data. This method correctly identifies ~87 % SL and ML clouds with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
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A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
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Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
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The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
EGUsphere, https://doi.org/10.5194/egusphere-2023-2260, https://doi.org/10.5194/egusphere-2023-2260, 2023
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This work aims to define a new approach to retrieve from spectral infrared measurements the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds. The capability of retrieving from satellites these shapes of the ice crystals in clouds will allow to extend the current available climatologies to be used as physical constrains in the global circulation models. This could could allow to improve their accuracy and prediction performance.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
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Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
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We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
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This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
Christian Matar, Céline Cornet, Frédéric Parol, Laurent C.-Labonnote, Frédérique Auriol, and Marc Nicolas
Atmos. Meas. Tech., 16, 3221–3243, https://doi.org/10.5194/amt-16-3221-2023, https://doi.org/10.5194/amt-16-3221-2023, 2023
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The optimal estimation formalism is applied to OSIRIS airborne high-resolution multi-angular measurements to retrieve COT and Reff. The corresponding uncertainties related to measurement errors, which are up to 6 and 12 %, the non-retrieved parameters, which are less than 0.5 %, and the cloud model assumptions show that the heterogeneous vertical profiles and the 3D radiative transfer effects lead to average uncertainties of 5 and 4 % for COT and 13 and 9 % for Reff.
Yuichiro Hagihara, Yuichi Ohno, Hiroaki Horie, Woosub Roh, Masaki Satoh, and Takuji Kubota
Atmos. Meas. Tech., 16, 3211–3219, https://doi.org/10.5194/amt-16-3211-2023, https://doi.org/10.5194/amt-16-3211-2023, 2023
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The CPR on the EarthCARE satellite is the first satellite-borne Doppler radar. We evaluated the effectiveness of horizontal integration and the unfolding method for the reduction of the Doppler error (the standard deviation of the random error) in the CPR_ECO product. The error was higher in the tropics than in the other latitudes due to frequent rain echo occurrence and limitation of its unfolding correction. If we use low-mode operation (high PRF), the errors become small enough.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-109, https://doi.org/10.5194/amt-2023-109, 2023
Revised manuscript accepted for AMT
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We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals is always decreasing with the increasing distance from the cloud far edge. The decreasing is the direct consequence of the fact that the forward peak of particles phase functions is much larger than the receiver field of view.
Kamil Mroz, Bernat Puidgomènech Treserras, Alessandro Battaglia, Pavlos Kollias, Aleksandra Tatarevic, and Frederic Tridon
Atmos. Meas. Tech., 16, 2865–2888, https://doi.org/10.5194/amt-16-2865-2023, https://doi.org/10.5194/amt-16-2865-2023, 2023
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We present the theoretical basis of the algorithm that estimates the amount of water and size of particles in clouds and precipitation. The algorithm uses data collected by the Cloud Profiling Radar that was developed for the upcoming Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite mission. After the satellite launch, the vertical distribution of cloud and precipitation properties will be delivered as the C-CLD product.
Anja Hünerbein, Sebastian Bley, Stefan Horn, Hartwig Deneke, and Andi Walther
Atmos. Meas. Tech., 16, 2821–2836, https://doi.org/10.5194/amt-16-2821-2023, https://doi.org/10.5194/amt-16-2821-2023, 2023
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The Multi-Spectral Imager (MSI) on board the EarthCARE satellite will provide the information needed for describing the cloud and aerosol properties in the cross-track direction, complementing the measurements from the Cloud Profiling Radar, Atmospheric Lidar and Broad-Band Radiometer. The accurate discrimination between clear and cloudy pixels is an essential first step. Therefore, the cloud mask algorithm provides a cloud flag, cloud phase and cloud type product for the MSI observations.
Zhipeng Qu, Howard W. Barker, Jason N. S. Cole, and Mark W. Shephard
Atmos. Meas. Tech., 16, 2319–2331, https://doi.org/10.5194/amt-16-2319-2023, https://doi.org/10.5194/amt-16-2319-2023, 2023
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This paper describes EarthCARE’s L2 product ACM-3D. It includes the scene construction algorithm (SCA) used to produce the indexes for reconstructing 3D atmospheric scene based on satellite nadir retrievals. It also provides the information about the buffer zone sizes of 3D assessment domains and the ranking scores for selecting the best 3D assessment domains. These output variables are needed to run 3D radiative transfer models for the radiative closure assessment of EarthCARE’s L2 retrievals.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Sebastian Schmidt, and Steffen Mauceri
Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
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This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
Armin Blanke, Andrew J. Heymsfield, Manuel Moser, and Silke Trömel
Atmos. Meas. Tech., 16, 2089–2106, https://doi.org/10.5194/amt-16-2089-2023, https://doi.org/10.5194/amt-16-2089-2023, 2023
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We present an evaluation of current retrieval techniques in the ice phase applied to polarimetric radar measurements with collocated in situ observations of aircraft conducted over the Olympic Mountains, Washington State, during winter 2015. Radar estimates of ice properties agreed most with aircraft observations in regions with pronounced radar signatures, but uncertainties were identified that indicate issues of some retrievals, particularly in warmer temperature regimes.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 1803–1847, https://doi.org/10.5194/amt-16-1803-2023, https://doi.org/10.5194/amt-16-1803-2023, 2023
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We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Leilei Kou, Zhengjian Lin, Haiyang Gao, Shujun Liao, and Piman Ding
Atmos. Meas. Tech., 16, 1723–1744, https://doi.org/10.5194/amt-16-1723-2023, https://doi.org/10.5194/amt-16-1723-2023, 2023
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Forward modeling of spaceborne millimeter-wave radar composed of eight submodules is presented. We quantify the uncertainties in radar reflectivity that may be caused by the physical model parameters via a sensitivity analysis. The simulations with improved and conventional settings are compared with CloudSat data, and the simulation results are evaluated and analyzed. The results are instructive to the optimization of forward modeling and microphysical parameter retrieval.
Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn
Atmos. Meas. Tech., 16, 1683–1704, https://doi.org/10.5194/amt-16-1683-2023, https://doi.org/10.5194/amt-16-1683-2023, 2023
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The Virga-Sniffer, a new modular open-source Python package tool to characterize full precipitation evaporation (so-called virga) from ceilometer cloud base height and vertically pointing cloud radar reflectivity time–height fields, is described. Results of its first application to RV Meteor observations during the EUREC4A field experiment in January–February 2020 are shown. About half of all detected clouds with bases below the trade inversion height were found to produce virga.
Yulan Hong, Stephen W. Nesbitt, Robert J. Trapp, and Larry Di Girolamo
Atmos. Meas. Tech., 16, 1391–1406, https://doi.org/10.5194/amt-16-1391-2023, https://doi.org/10.5194/amt-16-1391-2023, 2023
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Deep convective updrafts form overshooting tops (OTs) when they extend into the upper troposphere and lower stratosphere. An OT often indicates hazardous weather conditions. The global distribution of OTs is useful for understanding global severe weather conditions. The Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and Terra satellites provides 2 decades of records on the Earth–atmosphere system with stable orbits, which are used in this study to derive 20-year OT climatology.
Pragya Vishwakarma, Julien Delanoë, Susana Jorquera, Pauline Martinet, Frederic Burnet, Alistair Bell, and Jean-Charles Dupont
Atmos. Meas. Tech., 16, 1211–1237, https://doi.org/10.5194/amt-16-1211-2023, https://doi.org/10.5194/amt-16-1211-2023, 2023
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Cloud observations are necessary to characterize the cloud properties at local and global scales. The observations must be translated to cloud geophysical parameters. This paper presents the estimation of liquid water content (LWC) using radar and microwave radiometer (MWR) measurements. Liquid water path from MWR scales LWC and retrieves the scaling factor (ln a). The retrievals are compared with in situ observations. A climatology of ln a is built to estimate LWC using only radar information.
Bhupendra A. Raut, Paytsar Muradyan, Rajesh Sankaran, Robert C. Jackson, Seongha Park, Sean A. Shahkarami, Dario Dematties, Yongho Kim, Joseph Swantek, Neal Conrad, Wolfgang Gerlach, Sergey Shemyakin, Pete Beckman, Nicola J. Ferrier, and Scott M. Collis
Atmos. Meas. Tech., 16, 1195–1209, https://doi.org/10.5194/amt-16-1195-2023, https://doi.org/10.5194/amt-16-1195-2023, 2023
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We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.
William K. Jones, Matthew W. Christensen, and Philip Stier
Atmos. Meas. Tech., 16, 1043–1059, https://doi.org/10.5194/amt-16-1043-2023, https://doi.org/10.5194/amt-16-1043-2023, 2023
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Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
Andrew M. Sayer, Luca Lelli, Brian Cairns, Bastiaan van Diedenhoven, Amir Ibrahim, Kirk D. Knobelspiesse, Sergey Korkin, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 969–996, https://doi.org/10.5194/amt-16-969-2023, https://doi.org/10.5194/amt-16-969-2023, 2023
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This paper presents a method to estimate the height of the top of clouds above Earth's surface using satellite measurements. It is based on light absorption by oxygen in Earth's atmosphere, which darkens the signal that a satellite will see at certain wavelengths of light. Clouds "shield" the satellite from some of this darkening, dependent on cloud height (and other factors), because clouds scatter light at these wavelengths. The method will be applied to the future NASA PACE mission.
Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
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In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Minrui Wang, Takashi Y. Nakajima, Woosub Roh, Masaki Satoh, Kentaroh Suzuki, Takuji Kubota, and Mayumi Yoshida
Atmos. Meas. Tech., 16, 603–623, https://doi.org/10.5194/amt-16-603-2023, https://doi.org/10.5194/amt-16-603-2023, 2023
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SMILE (a spectral misalignment in which a shift in the center wavelength appears as a distortion in the spectral image) was detected during our recent work. To evaluate how it affects the cloud retrieval products, we did a simulation of EarthCARE-MSI forward radiation, evaluating the error in simulated scenes from a global cloud system-resolving model and a satellite simulator. Our results indicated that the error from SMILE was generally small and negligible for oceanic scenes.
Ming Li, Husi Letu, Hiroshi Ishimoto, Shulei Li, Lei Liu, Takashi Y. Nakajima, Dabin Ji, Huazhe Shang, and Chong Shi
Atmos. Meas. Tech., 16, 331–353, https://doi.org/10.5194/amt-16-331-2023, https://doi.org/10.5194/amt-16-331-2023, 2023
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Influenced by the representativeness of ice crystal scattering models, the existing terahertz ice cloud remote sensing inversion algorithms still have significant uncertainties. We developed an ice cloud remote sensing retrieval algorithm of the ice water path and particle size from aircraft-based terahertz radiation measurements based on the Voronoi model. Validation revealed that the Voronoi model performs better than the sphere and hexagonal column models.
Yoonjin Lee, Christian D. Kummerow, and Milija Zupanski
Atmos. Meas. Tech., 15, 7119–7136, https://doi.org/10.5194/amt-15-7119-2022, https://doi.org/10.5194/amt-15-7119-2022, 2022
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Vertical profiles of latent heating are derived from GOES-16 to be used in convective initialization. They are compared with other latent heating products derived from NEXRAD and GPM satellites, and the results show that their values are very similar to the radar-derived products. Finally, using latent heating derived from GOES-16 for convective initialization shows improvements in precipitation forecasts, which are comparable to the results using latent heating derived from NEXRAD.
Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 15, 6653–6668, https://doi.org/10.5194/amt-15-6653-2022, https://doi.org/10.5194/amt-15-6653-2022, 2022
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With more than 15 years of measurements, the IASI radiance dataset is becoming a reference climate data record. Its exploitation for satellite applications requires an accurate and unbiased detection of cloud scenes. Here, we present a new cloud detection algorithm for IASI that is both sensitive and consistent over time. It is based on the use of a neural network, relying on IASI radiance information only and taking as a reference the last version of the operational IASI L2 cloud product.
Wenyu Wang, Zhenzhan Wang, Qiurui He, and Lanjie Zhang
Atmos. Meas. Tech., 15, 6489–6506, https://doi.org/10.5194/amt-15-6489-2022, https://doi.org/10.5194/amt-15-6489-2022, 2022
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This paper uses a neural network approach to retrieve the ice water path from FY-3B/MWHS polarimetric measurements, focusing on its unique 150 GHz quasi-polarized channels. The Level 2 product of CloudSat is used as the reference value for the neural network. The results show that the polarization information is helpful for the retrieval in scenes with thicker cloud ice, and the 150 GHz channels give a significant improvement compared to using only 183 GHz channels.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
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The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Han Ding, Haoran Li, and Liping Liu
Atmos. Meas. Tech., 15, 6181–6200, https://doi.org/10.5194/amt-15-6181-2022, https://doi.org/10.5194/amt-15-6181-2022, 2022
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In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.
Andrew T. Prata, Roy G. Grainger, Isabelle A. Taylor, Adam C. Povey, Simon R. Proud, and Caroline A. Poulsen
Atmos. Meas. Tech., 15, 5985–6010, https://doi.org/10.5194/amt-15-5985-2022, https://doi.org/10.5194/amt-15-5985-2022, 2022
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Satellite observations are often used to track ash clouds and estimate their height, particle sizes and mass; however, satellite-based techniques are always associated with some uncertainty. We describe advances in a satellite-based technique that is used to estimate ash cloud properties for the June 2019 Raikoke (Russia) eruption. Our results are significant because ash warning centres increasingly require uncertainty information to correctly interpret,
aggregate and utilise the data.
Adrià Amell, Patrick Eriksson, and Simon Pfreundschuh
Atmos. Meas. Tech., 15, 5701–5717, https://doi.org/10.5194/amt-15-5701-2022, https://doi.org/10.5194/amt-15-5701-2022, 2022
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Geostationary satellites continuously image a given location on Earth, a feature that satellites designed to characterize atmospheric ice lack. However, the relationship between geostationary images and atmospheric ice is complex. Machine learning is used here to leverage such images to characterize atmospheric ice throughout the day in a probabilistic manner. Using structural information from the image improves the characterization, and this approach compares favourably to traditional methods.
Cited articles
Barrett, A. I., Westbrook, C. D., Nicol, J. C., and Stein, T. H. M.: Rapid ice aggregation process revealed through triple-wavelength Doppler spectrum radar analysis, Atmos. Chem. Phys., 19, 5753–5769, https://doi.org/10.5194/acp-19-5753-2019, 2019. a
Battaglia, A., Kummerow, C., Shin, D.-B., and Williams, C.: Toward
characterizing the effect of radar bright bands on microwave brightness
temperatures, J. Atmos. Ocean. Technol., 20, 856–871,
https://doi.org/10.1175/1520-0426(2003)020<0856:CMBTBR>2.0.CO;2, 2003. a
Battaglia, A., Westbrook, C. D., Kneifel, S., Kollias, P., Humpage, N., Löhnert, U., Tyynelä, J., and Petty, G. W.: G band atmospheric radars: new frontiers in cloud physics, Atmos. Meas. Tech., 7, 1527–1546, https://doi.org/10.5194/amt-7-1527-2014, 2014. a, b, c
Battaglia, A., Mroz, K., Lang, T., Tridon, F., Tanelli, S., Tian, L., and
Heymsfield, G. M.: Using a multiwavelength suite of microwave instruments to
investigate the microphysical structure of deep convective cores, J. Geophys. Res.-Atmos., 121,
9356–9381, https://doi.org/10.1002/2016JD025269, 2016. a, b, c
Battaglia, A., Kollias, P., Dhillon, R., Roy, R., Tanelli, S., Lamer, K.,
Grecu, M., Lebsock, M., Watters, D., Mroz, K., Heymsfield, G., Li, L., and
Furukawa, K.: Spaceborne Cloud and Precipitation Radars: Status, Challenges,
and Ways Forward, Rev. Geophys., 58, e2019RG000686,
https://doi.org/10.1029/2019RG000686, 2020a. a, b, c, d, e, f, g
Cadeddu, M. and Ghate, V.: Microwave Radiometer, 3 Channel (MWR3C),
2014-02-21 to 2014-03-22, ARM Mobile Facility (TMP) University of Helsinki Research
Station (SMEAR II), Hyytiala, Finland; AMF2 (M1), Atmospheric Radiation
Measurement (ARM) user facility, https://doi.org/10.5439/1025248, 2014a. a, b
Cadeddu, M. and Ghate, V.: Microwave Radiometer (MWRLOS), 2014-02-21 to 2014-03-22, ARM Mobile Facility (TMP) U. of Helsinki Research Station (SMEAR II), Hyytiala, Finland; AMF2 (M1), Atmospheric Radiation Measurement (ARM) user facility, https://doi.org/10.5439/1046211,
2014b. a, b
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
Cooper, K. B., Rodriguez Monje, R., Millán, L., Lebsock, M.,
Tanelli, S., Siles, J. V., Lee, C., and Brown, A.: Atmospheric
Humidity Sounding Using Differential Absorption Radar Near 183 GHz, IEEE
Geosci. Remote Sens. Lett., 15, 163–167,
https://doi.org/10.1109/LGRS.2017.2776078, 2018. a
Delrieu, G., Caoudal, S., and Creutin, J. D.: Feasibility of Using Mountain
Return for the Correction of Ground-Based X-Band Weather Radar Data, J.
Atmos. Ocean. Technol., 14, 368–385,
https://doi.org/10.1175/1520-0426(1997)014<0368:FOUMRF>2.0.CO;2, 1997. a
Dias Neto, J., Kneifel, S., Ori, D., Trömel, S., Handwerker, J., Bohn, B., Hermes, N., Mühlbauer, K., Lenefer, M., and Simmer, C.: The TRIple-frequency and Polarimetric radar Experiment for improving process observations of winter precipitation, Earth Syst. Sci. Data, 11, 845–863, https://doi.org/10.5194/essd-11-845-2019, 2019. a, b, c, d, e, f
Duncan, D. I. and Eriksson, P.: An update on global atmospheric ice estimates from satellite observations and reanalyses, Atmos. Chem. Phys., 18, 11205–11219, https://doi.org/10.5194/acp-18-11205-2018, 2018. a, b
Ellison, W. J.: Permittivity of Pure Water, at Standard Atmospheric Pressure,
over the Frequency Range 0–25THz and the Temperature Range 0–100 ∘C, J. Phys. Chem. Ref. Data, 36, 1–18,
https://doi.org/10.1063/1.2360986, 2007. a, b, c, d
Firda, J. M., Sekelsky, S. M., and McIntosh, R. E.: Application of
Dual-Frequency Millimeter-Wave Doppler Spectra for the Retrieval of Drop Size
Distributions and Vertical Air Motion in Rain, J. Atmos.
Ocean. Technol., 16, 216–236,
https://doi.org/10.1175/1520-0426(1999)016<0216:AODFMW>2.0.CO;2, 1999. a
Grecu, M., Tian, L., Heymsfield, G. M., Tokay, A., Olson, W. S., Heymsfield,
A. J., and Bansemer, A.: Nonparametric Methodology to Estimate Precipitating
Ice from Multiple-Frequency Radar Reflectivity Observations, J.
Appl. Meteorol. Climatol., 57, 2605–2622,
https://doi.org/10.1175/JAMC-D-18-0036.1, 2018. a
Haynes, J. M., L'Ecuyer, T. S., Stephens, G. L., Miller, S. D., Mitrescu, C.,
Wood, N. B., and Tanelli, S.: Rainfall retrieval over the ocean with
spaceborne W-band radar, J. Geophys. Res.-Atmos., 114, D00A22, https://doi.org/10.1029/2008JD009973, 2009. a, b
Hitschfeld, W. and Bordan, J.: Errors Inherent in the Radar Measurement of
Rainfall at Attenuating Wavelengths, J. Meteorology, 11, 58–67,
https://doi.org/10.1175/1520-0469(1954)011<0058:EIITRM>2.0.CO;2, 1954. a
Hogan, R. J. and Illingworth, A. J.: The Potential of Spaceborne
Dual-Wavelength Radar to Make Global Measurements of Cirrus Clouds, J. Atmos. Ocean. Technol., 16, 518–531,
https://doi.org/10.1175/1520-0426(1999)016<0518:TPOSDW>2.0.CO;2, 1999. a
Hogan, R. J., Illingworth, A. J., and Sauvageot, H.: Measuring Crystal Size in Cirrus Using 35- and 94-GHz Radars, J. Atmos. Ocean.
Technol., 17, 27–37,
https://doi.org/10.1175/1520-0426(2000)017<0027:MCSICU>2.0.CO;2, 2000. a
Hogan, R. J., Mittermaier, M. P., and Illingworth, A. J.: The retrieval of ice
water content from radar reflectivity factor and temperature and its use in
the evaluation of a mesoscale model, J. Appl. Meteorol., 45, 301–317,
https://doi.org/10.1175/JAM2340.1, 2006. a
Houze, R. A.: Cloud Dynamics, International Geophysics Series, Academic
Press, 2014. a
Huang, D., Johnson, K., Liu, Y., and Wiscombe, W.: High resolution retrieval of
liquid water vertical distributions using collocated Ka-band and W-band cloud
radars, Geophys. Res. Lett., 36, L24807, https://doi.org/10.1029/2009GL041364, 2009. a, b
Iguchi, T. and Matsui, T.: Remote Sensing of Clouds and Precipitation, chap.
Advances in Clouds and Precipitation Modeling Supported by Remote Sensing
Measurements, Springer Remote Sensing/Photogrammetry, Springer, Cham, 2018. a
Iguchi, T. and Meneghini, R.: Intercomparison of Single-Frequency Methods for
Retrieving a Vertical Rain Profile from Airborne or Spaceborne Radar Data,
J. Atmos. Ocean. Technol., 11, 1507–1516,
https://doi.org/10.1175/1520-0426(1994)011<1507:IOSFMF>2.0.CO;2, 1994. a
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of Working
Group I to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA, https://doi.org/10.1017/CBO9781107415324, 2013. a
Isom, B., Lindenmaier, I., and Matthews, A.: Marine W-Band (95 GHz) ARM Cloud Radar (MWACR), 2014-02-21 to 2014-03-22, ARM Mobile Facility (TMP) University of Helsinki Research Station (SMEAR II), Hyytiala, Finland; AMF2 (M1), Atmospheric Radiation Measurement (ARM) user facility, https://doi.org/10.5439/1150242, 2014a. a, b
Isom, B., Lindenmaier, I., Nelson, D., and Matthews, A.: Ka ARM Zenith
Radar (KAZR), 2014-02-21 to 2014-03-22, ARM Mobile Facility (TMP), Univrsity of
Helsinki Research Station (SMEAR II), Hyytiala, Finland; AMF2 (M1),
Atmospheric Radiation Measurement (ARM) user facility, https://doi.org/10.5439/1095601, 2014b. a, b
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, c
Kneifel, S., Löhnert, U., Battaglia, A., Crewell, S., and Siebler, D.: Snow
scattering signals in ground-based passive microwave radiometer measurements,
J. Geophys. Res., 115, D16214, https://doi.org/10.1029/2010JD013856, 2010. 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., 120, 6034–6055,
https://doi.org/10.1002/2015JD023156, 2015. a, b
Kneifel, S., Kollias, P., Battaglia, A., Leinonen, J., Maahn, M., Kalesse, H.,
and Tridon, F.: First observations of triple-frequency radar Doppler spectra
in snowfall: Interpretation and applications, Geophys. Res. Lett., 43,
2225–2233, https://doi.org/10.1002/2015GL067618, 2016. a
Kneifel, S., Leinonen, J., Tyynelä, J., Ori, D., and Battaglia, A.: Scattering of Hydrometeors, in: Satellite Precipitation Measurement, Advances in Global Change Research, edited by: Levizzani, V., Kidd, C., Kirschbaum, D., Kummerow, C., Nakamura, K., and Turk, F., Vol 67. Springer, Cham., https://doi.org/10.1007/978-3-030-24568-9_15, 2020. a, b
Kollias, P., Clothiaux, E. E., Miller, M. A., Albrecht, B. A., Stephens, G. L.,
and Ackerman, T. P.: Millimeter-Wavelength Radars: New Frontier in
Atmospheric Cloud and Precipitation Research, B. Am. Meteorol. Soc.,
88, 1608–1624, https://doi.org/10.1175/BAMS-88-10-1608, 2007. a
Kollias, P., Bharadwaj, N., Clothiaux, E. E., Lamer, K., Oue, M., Hardin, J.,
Isom, B., Lindenmaier, I., Matthews, A., Luke, E. P., Giangrande, S. E.,
Johnson, K., Collis, S., Comstock, J., and Mather, J. H.: The ARM Radar
Network: At the Leading Edge of Cloud and Precipitation Observations,
B. Am. Meteorol. Soc., 101, E588–E607,
https://doi.org/10.1175/BAMS-D-18-0288.1, 2020. a
Küchler, N., Kneifel, S., Löhnert, U., Kollias, P., Czekala, H., and Rose,
T.: A W-Band Radar-Radiometer System for Accurate and Continuous
Monitoring of Clouds and Precipitation, J. Atmos. Ocean. Technol., 34,
2375–2392, https://doi.org/10.1175/JTECH-D-17-0019.1, 2017. a
Kulie, M. S., Hiley, M. J., Bennartz, R., Kneifel, S., and Tanelli, S.:
Triple-Frequency Radar Reflectivity Signatures of Snow: Observations and
Comparisons with Theoretical Ice Particle Scattering Models, J. Appl. Meteor. Climatol., 53, 1080–1098,
https://doi.org/10.1175/JAMC-D-13-066.1, 2014. 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. Meteor. Climatol.,
53, 1636–1658, https://doi.org/10.1175/JAMC-D-13-0312.1, 2014. a, b
L'Ecuyer, T. S. and Stephens, G. L.: An Estimation-Based Precipitation
Retrieval Algorithm for Attenuating Radars, J. Appl. Meteorol., 41,
272–285, https://doi.org/10.1175/1520-0450(2002)041<0272:AEBPRA>2.0.CO;2, 2002. a, b
L’Ecuyer, T. S., Beaudoing, H. K., Rodell, M., Olson, W., Lin, B., Kato, S.,
Clayson, C. A., Wood, E., Sheffield, J., Adler, R., Huffman, G., Bosilovich,
M., Gu, G., Robertson, F., Houser, P. R., Chambers, D., Famiglietti, J. S.,
Fetzer, E., Liu, W. T., Gao, X., Schlosser, C. A., Clark, E., Lettenmaier,
D. P., and Hilburn, K.: The Observed State of the Energy Budget in the Early
Twenty-First Century, J. Climate, 28, 8319–8346, https://doi.org/10.1175/JCLI-D-14-00556.1, 2015. a
Leinonen, J., Lebsock, M. D., Tanelli, S., Sy, O. O., Dolan, B., Chase, R. J., Finlon, J. A., von Lerber, A., and Moisseev, D.: Retrieval of snowflake microphysical properties from multifrequency radar observations, Atmos. Meas. Tech., 11, 5471–5488, https://doi.org/10.5194/amt-11-5471-2018, 2018. a, b
Lhermitte, R.: Attenuation and Scattering of Millimeter Wavelength Radiation
by Clouds and Precipitation, J. Atmos. Ocean. Technol., 7, 464–479,
https://doi.org/10.1175/1520-0426(1990)007<0464:AASOMW>2.0.CO;2, 1990. a, b
Li, H. and Moisseev, D.: Melting Layer Attenuation at Ka- and W-Bands as
Derived From Multifrequency Radar Doppler Spectra Observations, J.
Geophys. Res.-Atmos., 124, 9520–9533,
https://doi.org/10.1029/2019JD030316, 2019. a, b, c, d
Liao, L. and Meneghini, R.: A Study on the Feasibility of Dual-Wavelength
Radar for Identification of Hydrometeor Phases, 50, 449–456,
https://doi.org/10.1175/2010JAMC2499.1, 2011. a
Liao, L. and Meneghini, R.: Physical Evaluation of GPM DPR Single- and
Dual-Wavelength Algorithms, J. Atmos. Ocean. Technol., 36, 883–902,
https://doi.org/10.1175/JTECH-D-18-0210.1, 2019. a, b
Löhnert, U. and Crewell, S.: Accuracy of cloud liquid water path from
ground-based microwave radiometry 1. Dependency on cloud model statistics,
Radio Sci., 38, 8041, https://doi.org/10.1029/2002RS002654, 2003. a
Löhnert, U., Schween, J. H., Acquistapace, C., Ebell, K., Maahn, M.,
Barrera-Verdejo, M., Hirsikko, A., Bohn, B., Knaps, A., O'Connor, E., Simmer,
C., Wahner, A., and Crewell, S.: JOYCE: Jülich Observatory for Cloud
Evolution, B. Am. Meteorol. Soc., 96, 1157–1174,
https://doi.org/10.1175/BAMS-D-14-00105.1, 2015. a, b
Lubin, D., Zhang, D., Silber, I., Scott, R. C., Kalogeras, P., Battaglia, A.,
Bromwich, D. H., Cadeddu, M., Eloranta, E., Fridlind, A., Frossard, A.,
Hines, K. M., Kneifel, S., Leaitch, W. R., Lin, W., Nicolas, J., Powers, H.,
Quinn, P. K., Rowe, P., Russell, L. M., Sharma, S., Verlinde, J., and
Vogelmann, A. M.: AWARE: The Atmospheric Radiation Measurement (ARM) West
Antarctic Radiation Experiment, B. Am. Meteorol.
Soc., B. Am. Meteorol. Soc., 101, E1069–E1091, https://doi.org/10.1175/BAMS-D-18-0278.1, 2020. 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.-Atmos., 115, D19201, https://doi.org/10.1029/2009JD012884, 2010. a
Marzoug, M. and Amayenc, P.: A Class of Single- and Dual-Frequency Algorithms
for Rain-Rate Profiling from a Spaceborne Radar. Pad I: Principle and Tests
from Numerical Simulations, J. Atmos. Ocean. Technol., 11, 1480–1506,
https://doi.org/10.1175/1520-0426(1994)011<1480:ACOSAD>2.0.CO;2, 1994. a
Mason, S. L., Chiu, J. C., Hogan, R. J., and Tian, L.: Improved rain rate and drop size retrievals from airborne Doppler radar, Atmos. Chem. Phys., 17, 11567–11589, https://doi.org/10.5194/acp-17-11567-2017, 2017. a
Mason, S. L., Hogan, R. J., Westbrook, C. D., Kneifel, S., Moisseev, D., and von Terzi, L.: The importance of particle size distribution and internal structure for triple-frequency radar retrievals of the morphology of snow, Atmos. Meas. Tech., 12, 4993–5018, https://doi.org/10.5194/amt-12-4993-2019, 2019. a
Matrosov, S.: Attenuation-Based Estimates of Rainfall Rates Aloft with
Vertically Pointing Ka-Band Radars, J. Atmos. Ocean. Technol., 22, 43–54,
https://doi.org/10.1175/JTECH-1677.1, 2005. a, b
Matrosov, S.: Assessment of Radar Signal Attenuation Caused by the Melting
Hydrometeor Layer, IEEE Trans. Geosci. Remote Sens., 46, 1039–1047, https://doi.org/10.1109/TGRS.2008.915757, 2008. a
Matrosov, S., May, P., and Shupe, M.: Rainfall Profiling Using Atmospheric
Radiation Measurement Program Vertically Pointing 8-mm Wavelength Radars, J.
Atmos. Ocean. Technol., 23, 1478–1491, https://doi.org/10.1175/JTECH1957.1, 2006. a, b
Matrosov, S. Y.: Modeling Backscatter Properties of Snowfall at Millimeter
Wavelengths, J. Atmos. Sci., 64, 1727–1736,
https://doi.org/10.1175/JAS3904.1, 2007. a
Matrosov, S. Y.: Feasibility of using radar differential Doppler velocity and
dual-frequency ratio for sizing particles in thick ice clouds, J.
Geophys. Res.-Atmos., 116, D17202, https://doi.org/10.1029/2011JD015857, 2011. a
Matrosov, S. Y.: Characteristic Raindrop Size Retrievals from Measurements of
Differences in Vertical Doppler Velocities at Ka- and W-Band Radar
Frequencies, J. Atmos. Ocean. Technol., 34, 65–71,
https://doi.org/10.1175/JTECH-D-16-0181.1, 2017. a
Matrosov, S. Y. and Turner, D. D.: Retrieving Mean Temperature of Atmospheric
Liquid Water Layers Using Microwave Radiometer Measurements, J. Atmos.
Ocean. Technol., 35, 1091–1102, https://doi.org/10.1175/JTECH-D-17-0179.1, 2018. a
Matrosov, S. Y., Maahn, M., and de Boer, G.: Observational and Modeling Study
of Ice Hydrometeor Radar Dual-Wavelength Ratios, J. Appl. Meteor. Climatol., 58, 2005–2017,
https://doi.org/10.1175/JAMC-D-19-0018.1, 2019. a
Meneghini, R., Iguchi, T., Kozu, T., Liao, L., Okamoto, K., Jones, J. A., and
Kwiatkowski, J.: Use of the Surface Reference Technique for Path Attenuation
Estimates from the TRMM Precipitation Radar, J. Appl. Meteorol., 39,
2053–2070, https://doi.org/10.1175/1520-0450(2001)040<2053:UOTSRT>2.0.CO;2, 2000. a
Meneghini, R., Kim, H., Liao, L., Jones, J. A., and Kwiatkowski, J. M.: An
Initial Assessment of the Surface Reference Technique Applied to Data from
the Dual-Frequency Precipitation Radar (DPR) on the GPM Satellite, J. Atmos.
Ocean. Technol., 32, 2281–2296, https://doi.org/10.1175/JTECH-D-15-0044.1, 2015. a
Mróz, K., Battaglia, A., Kneifel, S., D'Adderio, L. P., and Dias Neto, J.:
Triple-Frequency Doppler Retrieval of Characteristic Raindrop Size, Earth
Space Sci., 7, e2019EA000789, https://doi.org/10.1029/2019EA000789, 2020. a
Nemarich, J., Wellman, R. J., and Lacombe, J.: Backscatter and
attenuation by falling snow and rain at 96, 140, and 225 GHz, IEEE Trans. Geosci. Remote Sens., 26, 319–329,
https://doi.org/10.1109/36.3034, 1988. a, b
Petäjä, T., O’Connor, E. J., Moisseev, D., Sinclair, V. A., Manninen,
A. J., Väänänen, R., von Lerber, A., Thornton, J. A., Nicoll, K.,
Petersen, W., Chandrasekar, V., Smith, J. N., Winkler, P. M., Krüger, O.,
Hakola, H., Timonen, H., Brus, D., Laurila, T., Asmi, E., Riekkola, M.-L.,
Mona, L., Massoli, P., Engelmann, R., Komppula, M., Wang, J., Kuang, C.,
Bäck, J., Virtanen, A., Levula, J., Ritsche, M., and Hickmon, N.: BAECC: A
Field Campaign to Elucidate the Impact of Biogenic Aerosols on Clouds and
Climate, B. Am. Meteorol. Soc., 97, 1909–1928,
https://doi.org/10.1175/BAMS-D-14-00199.1, 2016. a
Protat, A., Delanoë, J., Bouniol, D., Heymsfield, A. J.,
Bansemer, A., and Brown, P.: Evaluation of Ice Water Content Retrievals
from Cloud Radar Reflectivity and Temperature Using a Large Airborne In Situ
Microphysical Database, J. Appl. Meteorol. Climatol., 46,
557–572, https://doi.org/10.1175/JAM2488.1, 2007. a, b
Protat, A., Rauniyar, S., Delanoë, J., Fontaine, E., and Schwarzenboeck, A.:
W-Band (95 GHz) Radar Attenuation in Tropical Stratiform Ice Anvils, J.
Atmos. Ocean. Technol., 36, 1463–1476, https://doi.org/10.1175/JTECH-D-18-0154.1,
2019. a, b
Rose, T., Crewell, S., Löhnert, U., and Simmer, C.: A network
suitable microwave radiometer for operational monitoring of the cloudy
atmosphere, Atmos. Res., 75, 183–200,
https://doi.org/10.1016/j.atmosres.2004.12.005, 2005. a
Rosenkranz, P. W.: A Model for the Complex Dielectric Constant of
Supercooled Liquid Water at Microwave Frequencies, IEEE Trans.
Geosci. Remote Sens., 53, 1387–1393,
https://doi.org/10.1109/TGRS.2014.2339015, 2015. a, b, c
Roy, R. J., Lebsock, M., Millán, L., Dengler, R., Rodriguez Monje, R., Siles, J. V., and Cooper, K. B.: Boundary-layer water vapor profiling using differential absorption radar, Atmos. Meas. Tech., 11, 6511–6523, https://doi.org/10.5194/amt-11-6511-2018, 2018. a
Serrar, S., Delrieu, G., Creutin, J.-D., and Uijlenhoet, R.: Mountain
reference technique: Use of mountain returns to calibrate weather radars
operating at attenuating wavelengths, J. Geophys. Res.-Atmos., 105, 2281–2290,
https://doi.org/10.1029/1999JD901025, 2000. 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. Technol., 21, 660–670,
https://doi.org/10.1175/1520-0426(2004)021<0660:DMCPFD>2.0.CO;2, 2004. a
Shupe, M. D., Daniel, J. S., de Boer, G., Eloranta, E. W., Kollias, P., Long,
C. N., Luke, E. P., Turner, D. D., and Verlinde, J.: A Focus On Mixed-Phase
Clouds, B. Am. Meteorol. Soc., 89, 1549–1562,
https://doi.org/10.1175/2008BAMS2378.1, 2008. a
Simmer, C., Thiele-Eich, I., Masbou, M., Amelung, W., Bogena, H., Crewell, S.,
Diekkrüger, B., Ewert, F., Hendricks Franssen, H.-J., Huisman, J. A., Kemna,
A., Klitzsch, N., Kollet, S., Langensiepen, M., Löhnert, U., Rahman, A. S.
M. M., Rascher, U., Schneider, K., Schween, J., Shao, Y., Shrestha, P.,
Stiebler, M., Sulis, M., Vanderborght, J., Vereecken, H., van der Kruk, J.,
Waldhoff, G., and Zerenner, T.: Monitoring and Modeling the Terrestrial
System from Pores to Catchments: The Transregional Collaborative Research
Center on Patterns in the Soil–Vegetation–Atmosphere System, B.
Am. Meteorol. Soc., 96, 1765–1787,
https://doi.org/10.1175/BAMS-D-13-00134.1, 2015. a
Stephens, G. L., Li, J., Wild, M., Clayson, C., Loeb, N., Kato, S., L'Ecuyer,
T., Stackhouse, P., Lebsock, M., and Andrews, T.: An update on Earth's
energy balance in light of the latest global observations, Nat.
Geosci., 5, 691–696, https://doi.org/10.1038/ngeo1580, 2012. a
Tridon, F. and Battaglia, A.: Dual-frequency radar Doppler spectral retrieval
of rain drop size distributions and entangled dynamics variables, J. Geophys. Res.-Atmos., 120,
5585–5601, https://doi.org/10.1002/2014JD023023, 2015. a, b
Tridon, F., Battaglia, A., and Kollias, P.: Disentangling Mie and attenuation
effects in rain using a Ka-W dual-wavelength Doppler spectral ratio
technique, Geophys. Res. Lett., 40, 5548–5552, https://doi.org/10.1002/2013GL057454,
2013a. a, b
Tridon, F., Battaglia, A., Kollias, P., Luke, E., and Williams, C. R.: Signal
Postprocessing and Reflectivity Calibration of the Atmospheric Radiation
Measurement Program 915-MHz Wind Profilers, J. Atmos. Ocean. Technol., 30,
1038–1054, https://doi.org/10.1175/JTECH-D-12-00146.1, 2013b. a
Tridon, F., Battaglia, A., Luke, E., and Kollias, P.: Rain retrieval from
dual-frequency radar Doppler spectra: validation and potential for a
midlatitude precipitating case-study, Q. J. Roy. Meteorol. Soc., 143,
1364–1380, https://doi.org/10.1002/qj.3010, 2017a. a, b, c, d
Tridon, F., Battaglia, A., and Watters, D.: Evaporation in action sensed by
multiwavelength Doppler radars, J. Geophys. Res.-Atmos., 122, 9379–9390, https://doi.org/10.1002/2016JD025998,
2017b. a
Tridon, F., Battaglia, A., Chase, R. J., Turk, F. J., Leinonen, J., Kneifel,
S., Mroz, K., Finlon, J., Bansemer, A., Tanelli, S., Heymsfield, A. J., and
Nesbitt, S. W.: The Microphysics of Stratiform Precipitation During OLYMPEX:
Compatibility Between Triple-Frequency Radar and Airborne In Situ
Observations, J. Geophys. Res.-Atmos., 124, 8764–8792, https://doi.org/10.1029/2018JD029858,
2019a. a
Tridon, F., Planche, C., Mroz, K., Banson, S., Battaglia, A., Van Baelen, J.,
and Wobrock, W.: On the Realism of the Rain Microphysics Representation of a
Squall Line in the WRF Model. Part I: Evaluation with Multifrequency Cloud
Radar Doppler Spectra Observations, Mon. Weather Rev., 147, 2787–2810,
https://doi.org/10.1175/MWR-D-18-0018.1, 2019b.
a
von Lerber, A., Moisseev, D., Bliven, L. F., Petersen, W., Harri, A.-M., and
Chandrasekar, V.: Microphysical Properties of Snow and Their Link to Ze–S
Relations during BAECC 2014, J. Appl. Meteorol. Climatol.,
56, 1561–1582, https://doi.org/10.1175/JAMC-D-16-0379.1, 2017. a, b, c
Wallace, H. B.: Millimeter-wave propagation measurements at the Ballistic
Research Laboratory, IEEE Trans. Geosci. Remote Sens., 26, 253–258, https://doi.org/10.1109/36.3028, 1988. a
Wild, M., Folini, D., Schär, C., Loeb, N., Dutton, E. G., and
König-Langlo, G.: The global energy balance from a surface perspective,
Clim. Dynam., 40, 3107–3134, https://doi.org/10.1007/s00382-012-1569-8, 2013. a
Williams, C. R., Beauchamp, R. M., and Chandrasekar, V.: Vertical Air
Motions and Raindrop Size Distributions Estimated Using Mean Doppler Velocity
Difference From 3- and 35-GHz Vertically Pointing Radars, IEEE Trans. Geosci. Remote Sens., 54, 6048–6060,
https://doi.org/10.1109/TGRS.2016.2580526, 2016. a
Zelinka, M. D., Randall, D. A., Webb, M. J., and Klein, S. A.: Clearing clouds
of uncertainty, Nat. Clim. Change, 7, 674–678,
https://doi.org/10.1038/nclimate3402, 2017. a
Zhu, Z., Lamer, K., Kollias, P., and Clothiaux, E. E.: The Vertical Structure
of Liquid Water Content in Shallow Clouds as Retrieved From Dual-Wavelength
Radar Observations, J. Geophys. Res.-Atmos., 124, 14184–14197, https://doi.org/10.1029/2019JD031188, 2019. a, b
Short summary
The droplets and ice crystals composing clouds and precipitation interact with microwaves and can therefore be observed by radars, but they can also attenuate the signal they emit. By combining the observations made by two ground-based radars, this study describes an original approach for estimating such attenuation. As a result, the latter can be not only corrected in the radar observations but also exploited for providing an accurate characterization of droplet and ice crystal properties.
The droplets and ice crystals composing clouds and precipitation interact with microwaves and...
