Articles | Volume 17, issue 23
https://doi.org/10.5194/amt-17-6965-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-6965-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dual-frequency (Ka-band and G-band) radar estimates of liquid water content profiles in shallow clouds
Juan M. Socuellamos
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Raquel Rodriguez Monje
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Matthew D. Lebsock
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Ken B. Cooper
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Pavlos Kollias
Division of Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA
Department of Environmental and Climate Sciences, Brookhaven National Laboratory, Upton, NY, USA
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Current knowledge of the link between clouds and climate is limited by lack of observations of the drop size distribution (DSD) within clouds, especially for the smallest drops. We demonstrate a method of retrieving DSDs down to small drop sizes using observations of drizzling marine layer clouds captured by the CloudCube millimeter-wave Doppler radar. We compare the shape of the observed spectra to theoretical expectations of radar echoes to solve for DSDs at each time and elevation.
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The study present a method to estimate how much the radar signal is weakened as it passes through rain or clouds, designed to implement in the new EarthCARE satellite cloud profiling radar data. The approach builds on the method used in the CloudSat mission, with key improvements that make it robust under non-ideal instrument conditions in the early mission phase. This leads to more reliable retrieval of clouds and rainfall during initial satellite operations.
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Atmos. Meas. Tech., 18, 2295–2310, https://doi.org/10.5194/amt-18-2295-2025, https://doi.org/10.5194/amt-18-2295-2025, 2025
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EGUsphere, https://doi.org/10.5194/egusphere-2025-1914, https://doi.org/10.5194/egusphere-2025-1914, 2025
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Convection drives atmospheric circulation but is difficult to observe and model. EarthCARE's radar provides the first space-based vertical wind data, capturing updrafts and downdrafts. Combined with satellite imagery from other sensors, it offers a broader view of convective storms. While resolution limits detail, cloud-top cooling helps track storm development. This combined approach improves understanding and modeling of convection.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-322, https://doi.org/10.5194/egusphere-2025-322, 2025
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EGUsphere, https://doi.org/10.5194/egusphere-2025-618, https://doi.org/10.5194/egusphere-2025-618, 2025
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EGUsphere, https://doi.org/10.5194/egusphere-2025-714, https://doi.org/10.5194/egusphere-2025-714, 2025
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This study explores how clouds respond to pollution throughout the day using high-resolution simulations. Polluted clouds show stronger daily changes: thicker clouds at night and in the morning but faster thinning in the afternoon. Pollution reduces rainfall but enhances drying, deepening the cloud layer. While the pollution initially brightens clouds, the daily cycle of cloudiness slightly reduces this brightening effect.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-671, https://doi.org/10.5194/egusphere-2025-671, 2025
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Doppler spectral data inform on how particles of varying vertical velocities contribute to total backscattered power observed. Through examining three case studies, consistent features in radar moment data were found to be characteristic of multi-modal spectra. We quantified how spectrum width and mean Doppler velocity can be used to determine whether or not a layer is multi-modal. The identification criteria and methods are described in Part 1 and assessed in Part 2.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-416, https://doi.org/10.5194/egusphere-2025-416, 2025
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The WIVERN conically scanning Doppler W-band radar, has the potential, for the first time, to map the mesoscale and synoptic variability of cloud dynamics, and precipitation microphysics. This study shows that the oblique angle of incidence will be advantageous compared to standard nadir-looking radars due to substantial clutter suppression over ocean surface. This feature will enable the detection and quantification of light and moderate precipitation, with improved proximity to the surface.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
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.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
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This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
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Robin J. Hogan, Anthony J. Illingworth, Pavlos Kollias, Hajime Okamoto, and Ulla Wandinger
Atmos. Meas. Tech., 17, 3081–3083, https://doi.org/10.5194/amt-17-3081-2024, https://doi.org/10.5194/amt-17-3081-2024, 2024
Kristofer S. Tuftedal, Bernat Puigdomènech Treserras, Mariko Oue, and Pavlos Kollias
Atmos. Chem. Phys., 24, 5637–5657, https://doi.org/10.5194/acp-24-5637-2024, https://doi.org/10.5194/acp-24-5637-2024, 2024
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This study analyzed coastal convective cells from June through September 2018–2021. The cells were classified and their lifecycles were analyzed to better understand their characteristics. Features such as convective-core growth, for example, are shown. The study found differences in the initiation location of shallow convection and in the aerosol loading in deep convective environments. This work provides a foundation for future analyses of convection or other tracked events elsewhere.
Zeen Zhu, Fan Yang, Pavlos Kollias, Raymond A. Shaw, Alex B. Kostinski, Steve Krueger, Katia Lamer, Nithin Allwayin, and Mariko Oue
Atmos. Meas. Tech., 17, 1133–1143, https://doi.org/10.5194/amt-17-1133-2024, https://doi.org/10.5194/amt-17-1133-2024, 2024
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In this article, we demonstrate the feasibility of applying advanced radar technology to detect liquid droplets generated in the cloud chamber. Specifically, we show that using radar with centimeter-scale resolution, single drizzle drops with a diameter larger than 40 µm can be detected. This study demonstrates the applicability of remote sensing instruments in laboratory experiments and suggests new applications of ultrahigh-resolution radar for atmospheric sensing.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Luis F. Millán, Matthew D. Lebsock, Ken B. Cooper, Jose V. Siles, Robert Dengler, Raquel Rodriguez Monje, Amin Nehrir, Rory A. Barton-Grimley, James E. Collins, Claire E. Robinson, Kenneth L. Thornhill, and Holger Vömel
Atmos. Meas. Tech., 17, 539–559, https://doi.org/10.5194/amt-17-539-2024, https://doi.org/10.5194/amt-17-539-2024, 2024
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In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign.
Matthew D. Lebsock and Mikael Witte
Atmos. Chem. Phys., 23, 14293–14305, https://doi.org/10.5194/acp-23-14293-2023, https://doi.org/10.5194/acp-23-14293-2023, 2023
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This paper evaluates measurements of cloud drop size distributions made from airplanes. We find that as the number of cloud drops increases the distribution of the cloud drop sizes narrows. The data are used to develop a simple equation that relates the drop number to the width of the drop sizes. We then use this equation to demonstrate that existing approaches to observe the drop number from satellites contain errors that can be corrected by including the new relationship.
David P. Donovan, Pavlos Kollias, Almudena Velázquez Blázquez, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5327–5356, https://doi.org/10.5194/amt-16-5327-2023, https://doi.org/10.5194/amt-16-5327-2023, 2023
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The Earth Cloud, Aerosol and Radiation Explorer mission (EarthCARE) is a multi-instrument cloud–aerosol–radiation-oriented satellite for climate and weather applications. For this satellite mission to be successful, the development and implementation of new techniques for turning the measured raw signals into useful data is required. This paper describes how atmospheric model data were used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
Imke Schirmacher, Pavlos Kollias, Katia Lamer, Mario Mech, Lukas Pfitzenmaier, Manfred Wendisch, and Susanne Crewell
Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, https://doi.org/10.5194/amt-16-4081-2023, 2023
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CloudSat’s relatively coarse spatial resolution, low sensitivity, and blind zone limit its assessment of Arctic low-level clouds, which affect the surface energy balance. We compare cloud fractions from CloudSat and finely resolved airborne radar observations to determine CloudSat’s limitations. Cloudsat overestimates cloud fractions above its blind zone, especially during cold-air outbreaks over open water, and misses a cloud fraction of 32 % and half of the precipitation inside its blind zone.
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.
Richard M. Schulte, Matthew D. Lebsock, and John M. Haynes
Atmos. Meas. Tech., 16, 3531–3546, https://doi.org/10.5194/amt-16-3531-2023, https://doi.org/10.5194/amt-16-3531-2023, 2023
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In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.
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.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Pavlos Kollias, Bernat Puidgomènech Treserras, Alessandro Battaglia, Paloma C. Borque, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 1901–1914, https://doi.org/10.5194/amt-16-1901-2023, https://doi.org/10.5194/amt-16-1901-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission developed by the European Space Agency (ESA) and Japan Aerospace Exploration Agency (JAXA) features the first spaceborne 94 GHz Doppler cloud-profiling radar (CPR) with Doppler capability. Here, we describe the post-processing algorithms that apply quality control and corrections to CPR measurements and derive key geophysical variables such as hydrometeor locations and best estimates of particle sedimentation fall velocities.
Zackary Mages, Pavlos Kollias, Zeen Zhu, and Edward P. Luke
Atmos. Chem. Phys., 23, 3561–3574, https://doi.org/10.5194/acp-23-3561-2023, https://doi.org/10.5194/acp-23-3561-2023, 2023
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Cold-air outbreaks (when cold air is advected over warm water and creates low-level convection) are a dominant cloud regime in the Arctic, and we capitalized on ground-based observations, which did not previously exist, from the COMBLE field campaign to study them. We characterized the extent and strength of the convection and turbulence and found evidence of secondary ice production. This information is useful for model intercomparison studies that will represent cold-air outbreak processes.
Mariko Oue, Stephen M. Saleeby, Peter J. Marinescu, Pavlos Kollias, and Susan C. van den Heever
Atmos. Meas. Tech., 15, 4931–4950, https://doi.org/10.5194/amt-15-4931-2022, https://doi.org/10.5194/amt-15-4931-2022, 2022
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This study provides an optimization of radar observation strategies to better capture convective cell evolution in clean and polluted environments as well as a technique for the optimization. The suggested optimized radar observation strategy is to better capture updrafts at middle and upper altitudes and precipitation particle evolution of isolated deep convective clouds. This study sheds light on the challenge of designing remote sensing observation strategies in pre-field campaign periods.
Kevin M. Smalley, Matthew D. Lebsock, Ryan Eastman, Mark Smalley, and Mikael K. Witte
Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, https://doi.org/10.5194/acp-22-8197-2022, 2022
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We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.
Zeen Zhu, Pavlos Kollias, Edward Luke, and Fan Yang
Atmos. Chem. Phys., 22, 7405–7416, https://doi.org/10.5194/acp-22-7405-2022, https://doi.org/10.5194/acp-22-7405-2022, 2022
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Drizzle (small rain droplets) is an important component of warm clouds; however, its existence is poorly understood. In this study, we capitalized on a machine-learning algorithm to develop a drizzle detection method. We applied this algorithm to investigate drizzle occurrence and found out that drizzle is far more ubiquitous than previously thought. This study demonstrates the ubiquitous nature of drizzle in clouds and will improve understanding of the associated microphysical process.
Alessandro Battaglia, Paolo Martire, Eric Caubet, Laurent Phalippou, Fabrizio Stesina, Pavlos Kollias, and Anthony Illingworth
Atmos. Meas. Tech., 15, 3011–3030, https://doi.org/10.5194/amt-15-3011-2022, https://doi.org/10.5194/amt-15-3011-2022, 2022
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We present an instrument simulator for a new sensor, WIVERN (WInd VElocity Radar Nephoscope), a conically scanning radar payload with Doppler capabilities, recently down-selected as one of the four candidates for the European Space Agency Earth Explorer 11 program. The mission aims at measuring horizontal winds in cloudy areas. The simulator is instrumental in the definition and consolidation of the mission requirements and the evaluation of mission performances.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
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Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Richard J. Roy, Matthew Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 14, 6443–6468, https://doi.org/10.5194/amt-14-6443-2021, https://doi.org/10.5194/amt-14-6443-2021, 2021
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This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 21, 14039–14058, https://doi.org/10.5194/acp-21-14039-2021, https://doi.org/10.5194/acp-21-14039-2021, 2021
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This numerical study provides insights into the sensitivity of shallow-cumulus dilution to geostrophic vertical wind profile. The cumulus dilution is strongly sensitive to vertical wind shear in the cloud layer, with shallow cumuli being more diluted in sheared environments. On the other hand, wind shear in the subcloud layer leads to less diluted cumuli. The sensitivities are explained by jointly considering the impacts of vertical velocity and the properties of the entrained air.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
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Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
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Multi-wavelength radar measurements provide capabilities to identify ice particle types and growth processes in clouds beyond the capabilities of single-frequency radar measurements. This study introduces Doppler velocity and polarimetric radar observables into the multi-wavelength radar reflectivity measurement to improve identification analysis. The analysis clearly discerns snowflake aggregation and riming processes and even early stages of riming.
Katia Lamer, Mariko Oue, Alessandro Battaglia, Richard J. Roy, Ken B. Cooper, Ranvir Dhillon, and Pavlos Kollias
Atmos. Meas. Tech., 14, 3615–3629, https://doi.org/10.5194/amt-14-3615-2021, https://doi.org/10.5194/amt-14-3615-2021, 2021
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Observations collected during the 25 February 2020 deployment of the VIPR at the Stony Brook Radar Observatory clearly demonstrate the potential of G-band radars for cloud and precipitation research. The field experiment, which coordinated an X-, Ka-, W- and G-band radar, revealed that the differential reflectivity from Ka–G band pair provides larger signals than the traditional Ka–W pairing underpinning an increased sensitivity to smaller amounts of liquid and ice water mass and sizes.
David R. Thompson, Brian H. Kahn, Philip G. Brodrick, Matthew D. Lebsock, Mark Richardson, and Robert O. Green
Atmos. Meas. Tech., 14, 2827–2840, https://doi.org/10.5194/amt-14-2827-2021, https://doi.org/10.5194/amt-14-2827-2021, 2021
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Concentrations of water vapor in the atmosphere vary dramatically over space and time. Mapping this variability can provide insights into atmospheric processes that help us understand atmospheric processes in the Earth system. Here we use a new measurement strategy based on imaging spectroscopy to map atmospheric water vapor concentrations at very small spatial scales. Experiments demonstrate the accuracy of this technique and some initial results from an airborne remote sensing experiment.
Marek Jacob, Pavlos Kollias, Felix Ament, Vera Schemann, and Susanne Crewell
Geosci. Model Dev., 13, 5757–5777, https://doi.org/10.5194/gmd-13-5757-2020, https://doi.org/10.5194/gmd-13-5757-2020, 2020
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We compare clouds in different cloud-resolving atmosphere simulations with airborne remote sensing observations. The focus is on warm shallow clouds in the Atlantic trade wind region. Those clouds are climatologically important but challenging for climate models. We use forward operators to apply instrument-specific thresholds for cloud detection to model outputs. In this comparison, the higher-resolution model better reproduces the layered cloud structure.
Sonja Drueke, Daniel J. Kirshbaum, and Pavlos Kollias
Atmos. Chem. Phys., 20, 13217–13239, https://doi.org/10.5194/acp-20-13217-2020, https://doi.org/10.5194/acp-20-13217-2020, 2020
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This numerical study provides insights into selected environmental sensitivities of shallow-cumulus dilution. Among the parameters under consideration, the dilution of the cloud cores is strongly sensitive to continentality and cloud-layer relative humidity and weakly sensitive to subcloud- and cloud-layer depths. The impacts of all four parameters are interpreted using a similarity theory of shallow cumulus and buoyancy-sorting arguments.
Luis Millán, Richard Roy, and Matthew Lebsock
Atmos. Meas. Tech., 13, 5193–5205, https://doi.org/10.5194/amt-13-5193-2020, https://doi.org/10.5194/amt-13-5193-2020, 2020
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This paper describes the feasibility of using a differential absorption radar technique for the remote sensing of total column water vapor from a spaceborne platform.
Mark Richardson, Matthew D. Lebsock, James McDuffie, and Graeme L. Stephens
Atmos. Meas. Tech., 13, 4947–4961, https://doi.org/10.5194/amt-13-4947-2020, https://doi.org/10.5194/amt-13-4947-2020, 2020
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We previously combined CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data and reflected-sunlight measurements from OCO-2 (Orbiting Carbon Observatory 2) for information about low clouds over oceans. The satellites are no longer formation-flying, so this work is a step towards getting new information about these clouds using only OCO-2. We can rapidly and accurately identify liquid oceanic clouds and obtain their height better than a widely used passive sensor.
Alessandro Battaglia, Pavlos Kollias, Ranvir Dhillon, Katia Lamer, Marat Khairoutdinov, and Daniel Watters
Atmos. Meas. Tech., 13, 4865–4883, https://doi.org/10.5194/amt-13-4865-2020, https://doi.org/10.5194/amt-13-4865-2020, 2020
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Warm rain accounts for slightly more than 30 % of the total rain amount and 70 % of the total rain area in the tropical belt and usually appears in kilometer-size cells. Spaceborne radars adopting millimeter wavelengths are excellent tools for detecting such precipitation types and for separating between the cloud and rain components. Our work highlights the benefits of operating multifrequency radars and discusses the impact of antenna footprints in quantitative estimates of liquid water paths.
Mario Mech, Maximilian Maahn, Stefan Kneifel, Davide Ori, Emiliano Orlandi, Pavlos Kollias, Vera Schemann, and Susanne Crewell
Geosci. Model Dev., 13, 4229–4251, https://doi.org/10.5194/gmd-13-4229-2020, https://doi.org/10.5194/gmd-13-4229-2020, 2020
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The Passive and Active Microwave TRAnsfer tool (PAMTRA) is a public domain software package written in Python and Fortran for the simulation of microwave remote sensing observations. PAMTRA models the interaction of radiation with gases, clouds, precipitation, and the surface using either in situ observations or model output as input parameters. The wide range of applications is demonstrated for passive (radiometer) and active (radar) instruments on ground, airborne, and satellite platforms.
Cited articles
Albrecht, B. A., Fairall, C. W., Thomson, D. W., and White, A. B.: Surface-based Remote Sensing of the Observed and the Adiabatic Liquid Water Content of Stratocumulus Clouds, Geophys. Res. Lett., 17, 89–92, https://doi.org/10.1029/GL017i001p00089, 1990.
Atlas, D.: The Estimation of Cloud Parameters by Radar, Atmos. Sci., 11, 309–317, https://doi.org/10.1175/1520-0469(1954)011<309:TEOCPB>2.0.CO;2, 1954.
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.
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, 2020.
Bony, S. and Dufresne, J.: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett., 32, L20806, https://doi.org/10.1029/2005GL023851, 2005.
Brient, F., Schneider, T., Tan, Z., Bony, S., Qu, X., and Hall, A.: Shallowness of tropical low clouds as a predictor of climate models' response to warming, Clim. Dynam., 47, 433–449, https://doi.org/10.1007/s00382-015-2846-0, 2016.
Cadeddu, M., Gibler, G., Koontz, A., and Tuftedal, M.: Microwave Radiometer, 3 Channel (MWR3C), Atmospheric Radiation Measurement (ARM) User Facility [data set], https://doi.org/10.5439/1025248, 2024.
Cadeddu, M. P.: Microwave Radiometer – 3-Channel (MWR3C) Instrument Handbook, U. S. Department of Energy, Atmospheric Radiation Measurement user facility, Richland, Washington, DOE/SC-ARM-TR-300, https://www.arm.gov/publications/tech_reports/handbooks/doe-sc-arm-tr-300.pdf (last access: 13 September 2024), 2024.
Cadeddu, M. P., Ghate, V. P., and Mech, M.: Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds, Atmos. Meas. Tech., 13, 1485–1499, https://doi.org/10.5194/amt-13-1485-2020, 2020.
Chandrakar, K. K., Cantrell, W., Chang, K., Ciochetto, D., Niedermeier, D., Ovchinnikov, M., Shaw, R. A., and Yang, F.: Aerosol indirect effect from turbulence-induced broadening of cloud–droplet size distributions, P. Natl. Acad. Sci. USA, 113, 14243–14248, https://doi.org/10.1073/pnas.1612686113, 2016.
Cooper, K. B., Roy, R. J, Dengler, R., Rodriguez Monje, R., Alonso-Delpino, M., Siles, J. V., Yurduseven, O., Parashare, C., Millan, L., and Lebsock, M.: G-Band Radar for Humidity and Cloud Remote Sensing, IEEE T. Geosci. Remote, 59, 1106–1117, https://doi.org/10.1109/TGRS.2020.2995325, 2021.
Courtier, B. M., Battaglia, A., Huggard, P. G., Westbrook, C., Mroz, K., Dhillon, R. S., Walden, C. J., Howells, G., Wang, H., Ellison, B. N., Reeves, R., Robertson, D. A., and Wylde, R. J.: First Observations of G-band Radar Doppler Spectra, Geophys. Res. Lett., 49, e2021GL096475, https://doi.org/10.1029/2021GL096475, 2022.
Doviak, R. and Zrnic, D.: Doppler radar and weather observations academic, Academic Press, San Diego, CA, ISBN 978-0-12-221422-6, 1993.
Ebell, K., Lohnert, U., Crewell, S., and Turner, D. D.: On characterizing the error in a remotely sensed liquid water content profile, Atmos. Res., 98, 57–68, https://doi.org/10.1016/j.atmosres.2010.06.002, 2010.
Eccles, P. J. and Mueller, E. A.: X-band attenuation and liquid water content estimation by a dual-wavelength radar, J. Appl. Meteorol. Clim., 10, 1252–1259, https://doi.org/10.1175/1520-0450(1971)010<1252:XBAALW>2.0.CO;2, 1971.
Ellis, S. M. and Vivekanandan, J.: Liquid water content estimates using simultaneous S and Ka band radar measurements, Radio Sci., 46, RS2021, https://doi.org/10.1029/2010RS004361, 2011.
Fast, J. D., Berg, L. K., Alexander, L., Bell, D., D'Ambro, E., Hubbe, J., Kuang, C., Liu, J., Long, C., Matthews, A., Mei, F., Newsom, R., Pekour., Pinterich, T., Schmid, B., Schobesberger, S., Shilling, J., Smith, J. N., Springston, S., Suski, K., Thornton, J. A., Tomlinson, J., Wang, J., Xiao, H., and Zelenyuk, A.: Overview of the HI-SCALE Field Campaign: A New Perspective on Shallow Convective Clouds, B. Am. Meteorol. Soc., 100, 821–840, https://doi.org/10.1175/BAMS-D-18-0030.1, 2019.
Feng, Y.-C., Lindenmaier, I., Johnson, K., Matthews, A., Wendler, T., Melo de Castro, V., Deng, M., and Rocque, M.: Ka ARM Zenith Radar (KAZRCFRGE), Atmospheric Radiation Measurement (ARM) User Facility [data set], https://doi.org/10.5439/1498936, 2024.
Fox, N. I. and Illingworth A. J.: The retrieval of stratocumulus cloud properties by ground-based cloud radar, J. Appl. Meteorol. Clim., 36, 485–492, https://doi.org/10.1175/1520-0450(1997)036<485:TROSCP>2.0.CO;2, 1997.
Frisch, A., Feingold, G., Fairall, C., Uttal, T., and Snider, J.: On cloud radar and microwave radiometer measurements of stratus cloud liquid water profiles, J. Geophys. Res., 103, 195–197, https://doi.org/10.1029/98JD01827, 1998.
Grosvenor, D. P., Sourdeval, O., Zuidema, P., Ackerman, A., Alexandrov, M. D., Bennartz, R., Boers, R., Cairns, B., Chiu, J. C., Christensen, M., Deneke, H., Diamond, M., Feingold, G., Fridlind, A., Hünerbein, A., Knist, C., Kollias, P., Marshak, A., McCoy, D., Merk, D., Painemal, D., Rausch, J., Rosenfeld, D., Russchenberg, H., Seifert, P., Sinclair, K., Stier, P., van Diedenhoven, B., Wendisch, M., Werner, F., Wood, R., Zhang, Z., and Quaas, J.: Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives, Rev. Geophys., 56, 409–453, https://doi.org/10.1029/2017rg000593, 2018.
Hitschfeld, W. and Bordan, J.: Errors inherent in the radar measurement of rainfall at attenuating wavelengths, J. Atmos. Sci., 11, 58–67, https://doi.org/10.1175/1520-0469(1954)011<0058:EIITRM>2.0.CO;2, 1954.
Hogan, R. J., Gaussiat, N., and Illingworth, A. J.: Stratocumulus liquid water content from dual-wavelength radar, J. Atmos. Ocean. Tech., 22, 1207–1218, https://doi.org/10.1175/JTECH1768.1, 2005.
Illingworth, A., Hogan, R., O'connor, E., Bouniol, D., Brooks, M., Delanoe, J., Donovan, D. P., Eastment, J. D., Gaussiat, N., Goddard, W. F., Haeffelin, M., Klein, H., Krasnov, O. A., Pelon, J., Piriou, J., Protat, A., Russcheberg, H. W. J., Seifert, A., Tompkins, A. M., van Zadelhoff, G. J., Vinit, F., Willen, U., Wilson, D. R., and Wrench, C. L.: Cloudnet: Continuous evaluation of cloud profiles in seven operational models using ground-based observations, B. Am. Meteorol. Soc., 88, 883–898, https://doi.org/10.1175/BAMS-88-6-883, 2007.
ITU (International Communication Union): ITU-R P.840-9 Recommendation: Attenuation due to clouds and fog, ITUPublications, https://www.itu.int/dms_pubrec/itu-r/rec/p/R-REC-P.840-9-202308-I!!PDF-E.pdf (last access: 30 September 2024), 2023.
Jensen, M., Giangrande, S., Fairless, T., and Zhou, A.: Gridded Sonde VAP Product (GRIDDEDSONDE), Atmospheric Radiation Measurement (ARM) User Facility [data set], https://doi.org/10.5439/1350631, 2024.
Kollias, P., Clothiaux, E. E., Ackerman, T. P., Albrecht, B. A., Widener, K. B., Moran, K. P., Luke, E. P., Johnson, K. L., Bharadwaj, N., and Mead, J. B.: Development and applications of ARM millimeter-wavelength cloud radars, Meteor. Mon., 57, 17.11–17.19, 2016.
Küchler, N., Kneifel, S., Kollias, P., & Löhnert, U.: Revisiting liquid water content retrievals in warm stratified clouds: The modified Frisch, Geophys. Res. Lett., 45, 9323–9330, https://doi.org/10.1029/2018GL079845, 2018.
Lamer, K., Oue, M., Battaglia, A., Roy, R. J., Cooper, K. B., Dhillon, R., and Kollias, P.: Multifrequency radar observations of clouds and precipitation including the G-band, Atmos. Meas. Tech., 14, 3615–3629, https://doi.org/10.5194/amt-14-3615-2021, 2021.
Lebsock, M. D. and Witte, M.: Quantifying the dependence of drop spectrum width on cloud drop number concentration for cloud remote sensing, Atmos. Chem. Phys., 23, 14293–14305, https://doi.org/10.5194/acp-23-14293-2023, 2023.
Lhermitte, R.: Attenuation and scattering of millimeter wavelength radiation by clouds and precipitation, J. Atmos. Ocean. Tech., 7, 464–479, https://doi.org/10.1175/1520-0426(1990)007<464:AASOMW>2.0.CO;2, 1990.
Löhnert, U., Crewell, S., Simmer, C., and Macke, A.: Profiling cloud liquid water by combining active and passive microwave measurements with cloud model statistics, J. Atmos. Ocean. Tech., 18, 1354–1366, https://doi.org/10.1175/1520-0426(2001)018<1354:PCLWBC>2.0.CO;2, 2001.
Matrosov, S. Y., Uttal, T., and Hazen, D. A.: Evaluation of Radar Reflectivity-Based Estimates of Water Content in Stratiform Marine Clouds, J. Appl. Meteorol. Clim., 43, 405–419, https://doi.org/10.1175/1520-0450(2004)043<1405:EORREO>2.0.CO;2, 2004.
Medeiros, B., Shaw, J., Kay, J. E., and Davis, I.: Assessing clouds using satellite observations through three generations of global atmosphere models, Earth Space Sci., 10, e2023EA002918, https://doi.org/10.1029/2023EA002918, 2023.
Miles, N. L., Verlinde, J., and Clothiaux, E. E.: Cloud droplet size distributions in low-level stratiform clouds, J. Atmos. Sci., 57, 295–311, https://doi.org/10.1175/1520-0469(2000)057<0295:CDSDIL>2.0.CO;2, 2000.
Miller, M. A., Jensen, M. P., and Clothiaux, E. E.: Diurnal Cloud and Thermodynamic Variations in the Stratocumulus Transition Regime: A Case Study Using In Situ and Remote Sensors, J. Atmos. Sci., 55, 2294–2310, https://doi.org/10.1175/1520-0469(1998)055<2294:DCATVI>2.0.CO;2, 1998.
Morris, V. R.: Ceilometer Instrument Handbook, U. S. Department of Energy, Atmospheric Radiation Measurement user facility, Richland, Washington, DOE/SC-ARM-TR-020, https://www.arm.gov/publications/tech_reports/handbooks/ceil_handbook.pdf (last access: 13 September 2024), 2016.
Randall, D.: Beyond deadlock, Geophys. Res. Lett., 40, 5970–5976, https://doi.org/10.1002/2013GL057998, 2013.
Rauber, R. M., Stevens, B., Ochs, H. T., Knight, C., Albrecht, B. A., Blyth, A. M., et al.: Rain in Shallow Cumulus Over the Ocean: The RICO Campaign, B. Am. Meteorol. Soc., 88, 1912–1928, https://doi.org/10.1175/BAMS-88-12-1912, 2007.
Rosenkranz, P. W.: Water vapor microwave continuum absorption: A comparison of measurements and models, Radio Sci., 33, 919–928, https://doi.org/10.1029/98RS01182, 1998.
Russell, L. M., Lubin, D, Silber, I., Eloranta, E., Muelmenstaedt, J., Burrows, S., Aiken, A., Wang, D., Petters, M., Miller, M., Ackerman, A., Fridlind, A., Witte, M., Lebsock, M., Painemal, D., Chang, R., Liggio, J., and Wheeler, M.: Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) Science Plan, U. S. Department of Energy, Office of Science, https://www.arm.gov/publications/programdocs/doe-sc-arm-21-009.pdf (last access: 29 February 2024), 2021.
Sassen, K., Mace G. G., Wang, Z., Poellot, M. R., Sekelsky, S. M., and McIntosh, R. E.: Continental Stratus Clouds: A Case Study Using Coordinated Remote Sensing and Aircraft measurements, J. Atmos. Sci., 56, 2345–2358, https://doi.org/10.1175/1520-0469(1999)056<2345:CSCACS>2.0.CO;2,1999.
Sauvegeout, H., and Omar, J.: Radar reflectivity of cumulus clouds, J. Atmos. Ocean. Techn., 4, 264–272, https://doi.org/10.1175/1520-0426(1987)004<0264:RROCC>2.0.CO;2, 1987.
Schneider, T., Leung, L. R., and Wills, R. C. J.: Opinion: Optimizing climate models with process knowledge, resolution, and artificial intelligence, Atmos. Chem. Phys., 24, 7041–7062, https://doi.org/10.5194/acp-24-7041-2024, 2024.
Socuellamos, J. M., Rodriguez Monje, R., Cooper, K. B., Lebsock, M. D., Nagaraja, P. M. S., Siles, J. V., Beauchamp, R. M., and Tanelli, S.: A G-band Doppler Radar for Atmospheric Profiling, IEEE T. Geosci. Remote, 62, 1–8, https://doi.org/10.1109/TGRS.2024.3398616, 2024a.
Socuellamos, J. M., Rodriguez Monje, R., Lebsock, M. D., Cooper, K. B., Beauchamp, R. M., and Umeyama, A.: Multifrequency radar observations of marine clouds during the EPCAPE campaign, Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, 2024b.
Socuellamos, J. M., Rodriguez Monje, R., Lebsock, M., Cooper, K., Beauchamp, R., and Umeyama, A.: Ka, W and G-band radar observations of clouds and light precipitation during the EPCAPE campaign in March and April 2023, Zenodo [data set], https://doi.org/10.5281/zenodo.11043877, 2024c.
Squires, P.: The Microstructure and Colloidal Stability of Warm Clouds: Part I-The Relation between Structure and Stability, Tellus, 10, 256–261, https://doi.org/10.3402/tellusa.v10i2.9229, 1958.
Williams, J. K., and Vivekanandan, J.: Sources of error in dual-wavelength radar remote sensing of cloud liquid water content, J. Atmos. Ocean. Tech., 24, 1317–1336, https://doi.org/10.1175/jtech2042.1, 2007.
Wood, R.: Stratocumulus Clouds, Rev. Arti. Mon. Weather Rev., 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012.
Zelinka, M. D., Zhou, C., and Klein, S. A.: Insights from a refined decomposition of cloud feedbacks, Geophys. Res. Lett., 43, 9259–9269, https://doi.org/10.1002/2016GL069917, 2016.
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. C., Klein, S. A., and Taylor, K. E.: Causes of Higher Climate Sensitivity in CMIP6 Models, Geophys. Res. Lett., 47, 1–12, https://doi.org/10.1029/2019GL085782, 2020.
Zhang, D., Ermold, B., and Morris, V.: Ceilometer (CEIL), Atmospheric Radiation Measurement (ARM) User Facility [data set], https://doi.org/10.5439/1181954, 2024.
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, 184–197, https://doi.org/10.1029/2019JD031188, 2019.
Short summary
This article presents a novel technique to estimate liquid water content (LWC) profiles in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows retrieving the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
This article presents a novel technique to estimate liquid water content (LWC) profiles in...