Articles | Volume 14, issue 7
https://doi.org/10.5194/amt-14-4893-2021
© Author(s) 2021. 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-14-4893-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Analysis of the microphysical properties of snowfall using scanning polarimetric and vertically pointing multi-frequency Doppler radars
School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA
Pavlos Kollias
School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA
Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, USA
Sergey Y. Matrosov
Cooperative Institute for Research in Environmental Sciences, University
of Colorado Boulder and NOAA Physical Sciences Laboratory, Boulder, CO, USA
Alessandro Battaglia
Department of Environment, Land and Infrastructure Engineering, Politecnico di Torino, Turin, Italy
Department of Physics and Astronomy, University of Leicester, Leicester, UK
Alexander V. Ryzhkov
NSSL, University of Oklahoma, Norman, OK, USA
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Zeen Zhu, Fan Yang, Pavlos Kollias, Raymond Shaw, Alex Kostinski, Steve Krueger, Katia Lamer, Nithin Allwayin, and Mariko Oue
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-218, https://doi.org/10.5194/amt-2023-218, 2023
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In this article, we demonstrated the feasibility of applying advanced radar technology to detect liquid droplets generated in the cloud chamber. Specifically, we show that using radar with cm scale resolution, single drizzle drops with a diameter larger than 40 micrometers can be detected. This study proves the applicability of remote sensing instruments in laboratory experiments and suggests new applications of ultra-high-resolution radar for atmospheric sensing.
Kristofer S. Tuftedal, Bernat Puigdomènech Treserras, Mariko Oue, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2023-821, https://doi.org/10.5194/egusphere-2023-821, 2023
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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 and environments. The study found differences in initiation location of shallow convection, in mid-level moisture between shallow and deep 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.
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.
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.
Mariko Oue, Aleksandra Tatarevic, Pavlos Kollias, Dié Wang, Kwangmin Yu, and Andrew M. Vogelmann
Geosci. Model Dev., 13, 1975–1998, https://doi.org/10.5194/gmd-13-1975-2020, https://doi.org/10.5194/gmd-13-1975-2020, 2020
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We developed the Cloud-resolving model Radar SIMulator (CR-SIM) capable of apples-to-apples comparisons between the multiwavelength, zenith-pointing, and scanning radar and multi-remote-sensing (radar and lidar) observations and the high-resolution atmospheric model output. Applications of CR-SIM as a virtual observatory operator aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements.
Mariko Oue, Pavlos Kollias, Alan Shapiro, Aleksandra Tatarevic, and Toshihisa Matsui
Atmos. Meas. Tech., 12, 1999–2018, https://doi.org/10.5194/amt-12-1999-2019, https://doi.org/10.5194/amt-12-1999-2019, 2019
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This study investigated impacts of the selected radar volume coverage pattern, the sampling time period, the number of radars used, and the added value of advection correction on the retrieval of vertical air motion from a multi-Doppler-radar technique. The results suggest that the use of rapid-scan radars can substantially improve the quality of wind retrievals and that the retrieved wind field needs to be carefully used considering the limitations of the radar observing system.
Kirk W. North, Mariko Oue, Pavlos Kollias, Scott E. Giangrande, Scott M. Collis, and Corey K. Potvin
Atmos. Meas. Tech., 10, 2785–2806, https://doi.org/10.5194/amt-10-2785-2017, https://doi.org/10.5194/amt-10-2785-2017, 2017
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Vertical air motion retrievals from 3DVAR multiple distributed scanning Doppler radars are compared against collocated profiling radars and retrieved from an upward iteration integration iterative technique to characterize their veracity. The retrieved vertical air motions are generally within 1–2 m s−1 of agreement with profiling radars and better solution than the upward integration technique, and therefore can be used as a means to improve parameterizations in numerical models moving forward.
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.
Zeen Zhu, Fan Yang, Pavlos Kollias, Raymond Shaw, Alex Kostinski, Steve Krueger, Katia Lamer, Nithin Allwayin, and Mariko Oue
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-218, https://doi.org/10.5194/amt-2023-218, 2023
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In this article, we demonstrated the feasibility of applying advanced radar technology to detect liquid droplets generated in the cloud chamber. Specifically, we show that using radar with cm scale resolution, single drizzle drops with a diameter larger than 40 micrometers can be detected. This study proves the applicability of remote sensing instruments in laboratory experiments and suggests new applications of ultra-high-resolution radar for atmospheric sensing.
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.
Shannon L. Mason, 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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1682, https://doi.org/10.5194/egusphere-2023-1682, 2023
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When the EarthCARE mission enters its operational phase a large number of retrieval data products will be available, many of 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 ESA production model, with the intention of providing a compact guide to users.
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.
Kristofer S. Tuftedal, Bernat Puigdomènech Treserras, Mariko Oue, and Pavlos Kollias
EGUsphere, https://doi.org/10.5194/egusphere-2023-821, https://doi.org/10.5194/egusphere-2023-821, 2023
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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 and environments. The study found differences in initiation location of shallow convection, in mid-level moisture between shallow and deep 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.
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.
Sergey Y. Matrosov, Alexei Korolev, Mengistu Wolde, and Cuong Nguyen
Atmos. Meas. Tech., 15, 6373–6386, https://doi.org/10.5194/amt-15-6373-2022, https://doi.org/10.5194/amt-15-6373-2022, 2022
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A remote sensing method to retrieve sizes of particles in ice clouds and precipitation from radar measurements at two wavelengths is described. This method is based on relating the particle size information to the ratio of radar signals at these two wavelengths. It is demonstrated that this ratio is informative about different characteristic particle sizes. Knowing atmospheric ice particle sizes is important for many applications such as precipitation estimation and climate modeling.
Sachin Patade, Deepak Waman, Akash Deshmukh, Ashok Kumar Gupta, Arti Jadav, Vaughan T. J. Phillips, Aaron Bansemer, Jacob Carlin, and Alexander Ryzhkov
Atmos. Chem. Phys., 22, 12055–12075, https://doi.org/10.5194/acp-22-12055-2022, https://doi.org/10.5194/acp-22-12055-2022, 2022
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This modeling study focuses on the role of multiple groups of primary biological aerosol particles as ice nuclei on cloud properties and precipitation. This was done by implementing a more realistic scheme for biological ice nucleating particles in the aerosol–cloud model. Results show that biological ice nucleating particles have a limited role in altering the ice phase and precipitation in deep convective clouds.
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.
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.
Cuong M. Nguyen, Mengistu Wolde, Alessandro Battaglia, Leonid Nichman, Natalia Bliankinshtein, Samuel Haimov, Kenny Bala, and Dirk Schuettemeyer
Atmos. Meas. Tech., 15, 775–795, https://doi.org/10.5194/amt-15-775-2022, https://doi.org/10.5194/amt-15-775-2022, 2022
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An analysis of airborne triple-frequency radar and almost perfectly co-located coincident in situ data from an Arctic storm confirms the main findings of modeling work with radar dual-frequency ratios (DFRs) at different zones of the DFR plane associated with different ice habits. High-resolution CPI images provide accurate identification of rimed particles within the DFR plane. The relationships between the triple-frequency signals and cloud microphysical properties are also presented.
Kamil Mroz, Alessandro Battaglia, Cuong Nguyen, Andrew Heymsfield, Alain Protat, and Mengistu Wolde
Atmos. Meas. Tech., 14, 7243–7254, https://doi.org/10.5194/amt-14-7243-2021, https://doi.org/10.5194/amt-14-7243-2021, 2021
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A method for estimating microphysical properties of ice clouds based on radar measurements is presented. The algorithm exploits the information provided by differences in the radar response at different frequency bands in relation to changes in the snow morphology. The inversion scheme is based on a statistical relation between the radar simulations and the properties of snow calculated from in-cloud sampling.
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.
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.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Xuguang Wang, Hugh Morrison, Alexander Ryzhkov, Yachao Hu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, Jason Milbrandt, Alexei V. Korolev, and Ivan Heckman
Atmos. Chem. Phys., 21, 6919–6944, https://doi.org/10.5194/acp-21-6919-2021, https://doi.org/10.5194/acp-21-6919-2021, 2021
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Numerous small ice crystals in the tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. This study evaluated the numerical models against the airborne observations and investigated the potential cloud processes that could lead to the production of these large numbers of small ice crystals. It is found that key microphysical processes are still lacking or misrepresented in current numerical models to realistically simulate the phenomenon.
Kamil Mróz, Alessandro Battaglia, Stefan Kneifel, Leonie von Terzi, Markus Karrer, and Davide Ori
Atmos. Meas. Tech., 14, 511–529, https://doi.org/10.5194/amt-14-511-2021, https://doi.org/10.5194/amt-14-511-2021, 2021
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The article examines the relationship between the characteristics of rain and the properties of the ice cloud from which the rain originated. Our results confirm the widely accepted assumption that the mass flux through the melting zone is well preserved with an exception of extreme aggregation and riming conditions. Moreover, it is shown that the mean (mass-weighted) size of particles above and below the melting zone is strongly linked, with the former being on average larger.
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.
Frédéric Tridon, Alessandro Battaglia, and Stefan Kneifel
Atmos. Meas. Tech., 13, 5065–5085, https://doi.org/10.5194/amt-13-5065-2020, https://doi.org/10.5194/amt-13-5065-2020, 2020
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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.
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.
Katia Lamer, Pavlos Kollias, Alessandro Battaglia, and Simon Preval
Atmos. Meas. Tech., 13, 2363–2379, https://doi.org/10.5194/amt-13-2363-2020, https://doi.org/10.5194/amt-13-2363-2020, 2020
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According to ground-based radar observations, 50 % of liquid low-level clouds over the Atlantic extend below 1.2 km and are thinner than 400 m, thus limiting their detection from space. Using an emulator, we estimate that a 250 m resolution radar would capture cloud base better than the CloudSat radar which misses about 52 %. The more sensitive EarthCARE radar is expected to capture cloud cover but stretch cloud. This calls for the operation of interlaced pulse modes for future space missions.
Mariko Oue, Aleksandra Tatarevic, Pavlos Kollias, Dié Wang, Kwangmin Yu, and Andrew M. Vogelmann
Geosci. Model Dev., 13, 1975–1998, https://doi.org/10.5194/gmd-13-1975-2020, https://doi.org/10.5194/gmd-13-1975-2020, 2020
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We developed the Cloud-resolving model Radar SIMulator (CR-SIM) capable of apples-to-apples comparisons between the multiwavelength, zenith-pointing, and scanning radar and multi-remote-sensing (radar and lidar) observations and the high-resolution atmospheric model output. Applications of CR-SIM as a virtual observatory operator aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements.
Fan Yang, Robert McGraw, Edward P. Luke, Damao Zhang, Pavlos Kollias, and Andrew M. Vogelmann
Atmos. Meas. Tech., 12, 5817–5828, https://doi.org/10.5194/amt-12-5817-2019, https://doi.org/10.5194/amt-12-5817-2019, 2019
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In-cloud supersaturation is crucial for droplet activation, growth, and drizzle initiation but is poorly known and hardly measured. Here we provide a novel method to estimate supersaturation fluctuation in stratocumulus clouds using remote-sensing measurements, and results show that our estimated supersaturation agrees reasonably well with in situ measurements. Our method provides a unique way to estimate supersaturation in stratocumulus clouds from long-term ground-based observations.
Mario Mech, Leif-Leonard Kliesch, Andreas Anhäuser, Thomas Rose, Pavlos Kollias, and Susanne Crewell
Atmos. Meas. Tech., 12, 5019–5037, https://doi.org/10.5194/amt-12-5019-2019, https://doi.org/10.5194/amt-12-5019-2019, 2019
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An improved understanding of Arctic mixed-phase clouds and their contribution to Arctic warming can be achieved by observations from airborne platforms with remote sensing instruments. Such an instrument is MiRAC combining active and passive techniques to gain information on the distribution of clouds, the occurrence of precipitation, and the amount of liquid and ice within the cloud. Operated during a campaign in Arctic summer, it could observe lower clouds often not seen by spaceborne radars.
Pavlos Kollias, Bernat Puigdomènech Treserras, and Alain Protat
Atmos. Meas. Tech., 12, 4949–4964, https://doi.org/10.5194/amt-12-4949-2019, https://doi.org/10.5194/amt-12-4949-2019, 2019
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Profiling millimeter-wavelength radars are the cornerstone instrument of surface-based observatories. Calibrating these radars is important for establishing a long record of observations suitable for model evaluation and improvement. Here, the CloudSat CPR is used to assess the calibration of a record over 10 years long of ARM cloud radar observations (a total of 44 years). The results indicate that correction coefficients are needed to improve record reliability and usability.
Katia Lamer, Bernat Puigdomènech Treserras, Zeen Zhu, Bradley Isom, Nitin Bharadwaj, and Pavlos Kollias
Atmos. Meas. Tech., 12, 4931–4947, https://doi.org/10.5194/amt-12-4931-2019, https://doi.org/10.5194/amt-12-4931-2019, 2019
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This article describes the three newly deployed second-generation radar of the Atmospheric Radiation Measurement program. Techniques to retrieve precipitation rate from their measurements are presented: noise and clutter filtering, gas and liquid attenuation correction, and radar reflectivity calibration. Rain rate for a 40 km radius domain around Graciosa estimated from all three radar differ, which highlights the need to consider sensor capabilities when interpreting radar measurements.
Alessandro Battaglia and Pavlos Kollias
Atmos. Meas. Tech., 12, 3335–3349, https://doi.org/10.5194/amt-12-3335-2019, https://doi.org/10.5194/amt-12-3335-2019, 2019
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This work investigates the potential of an innovative differential absorption radar for retrieving relative humidity inside ice clouds. The radar exploits the strong spectral dependence of the water vapour absorption for frequencies close to the 183 GHz water vapour band.
Results show that observations from a system with 4–6 frequencies can provide
novel information for understanding the formation and growth of ice crystals.
Ann M. Fridlind, Marcus van Lier-Walqui, Scott Collis, Scott E. Giangrande, Robert C. Jackson, Xiaowen Li, Toshihisa Matsui, Richard Orville, Mark H. Picel, Daniel Rosenfeld, Alexander Ryzhkov, Richard Weitz, and Pengfei Zhang
Atmos. Meas. Tech., 12, 2979–3000, https://doi.org/10.5194/amt-12-2979-2019, https://doi.org/10.5194/amt-12-2979-2019, 2019
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Weather radars are offering improved capabilities to investigate storm physics, which remain poorly understood. We investigate enhanced use of such data near Houston, Texas, where pollution sources often provide a convenient contrast between polluted and clean air. We conclude that Houston is a favorable location to conduct a future field campaign during June through September because isolated storms are common and tend to last an hour, allowing frequent observations of a full life cycle.
Mariko Oue, Pavlos Kollias, Alan Shapiro, Aleksandra Tatarevic, and Toshihisa Matsui
Atmos. Meas. Tech., 12, 1999–2018, https://doi.org/10.5194/amt-12-1999-2019, https://doi.org/10.5194/amt-12-1999-2019, 2019
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This study investigated impacts of the selected radar volume coverage pattern, the sampling time period, the number of radars used, and the added value of advection correction on the retrieval of vertical air motion from a multi-Doppler-radar technique. The results suggest that the use of rapid-scan radars can substantially improve the quality of wind retrievals and that the retrieved wind field needs to be carefully used considering the limitations of the radar observing system.
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.
Guangjie Zheng, Yang Wang, Allison C. Aiken, Francesca Gallo, Michael P. Jensen, Pavlos Kollias, Chongai Kuang, Edward Luke, Stephen Springston, Janek Uin, Robert Wood, and Jian Wang
Atmos. Chem. Phys., 18, 17615–17635, https://doi.org/10.5194/acp-18-17615-2018, https://doi.org/10.5194/acp-18-17615-2018, 2018
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Here, we elucidate the key processes that drive marine boundary layer (MBL) aerosol size distribution in the eastern North Atlantic (ENA) using long-term measurements. The governing equations of particle concentration are established for different modes. Particles entrained from the free troposphere represent the major source of MBL cloud condensation nuclei (CCN), contributing both directly to CCN population and indirectly by supplying Aitken-mode particles that grow to CCN in the MBL.
Katia Lamer, Ann M. Fridlind, Andrew S. Ackerman, Pavlos Kollias, Eugene E. Clothiaux, and Maxwell Kelley
Geosci. Model Dev., 11, 4195–4214, https://doi.org/10.5194/gmd-11-4195-2018, https://doi.org/10.5194/gmd-11-4195-2018, 2018
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Weather and climate predictions of cloud, rain, and snow occurrence remain uncertain, in part because guidance from observation is incomplete. We present a tool that transforms predictions into observations from ground-based remote sensors. Liquid water and ice occurrence errors associated with the transformation are below 8 %, with ~ 3 % uncertainty. This (GO)2-SIM forward-simulator tool enables better evaluation of cloud, rain, and snow occurrence predictions using available observations.
Fan Yang, Pavlos Kollias, Raymond A. Shaw, and Andrew M. Vogelmann
Atmos. Chem. Phys., 18, 7313–7328, https://doi.org/10.5194/acp-18-7313-2018, https://doi.org/10.5194/acp-18-7313-2018, 2018
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Cloud droplet size distribution (CDSD), which is related to cloud albedo and lifetime, is usually observed broader than predicted from adiabatic parcel calculations. Results in this study show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation. Our results suggest that it is important to consider both curvature and solute effects before and after cloud droplet activation in a 3-D cloud model.
Damao Zhang, Zhien Wang, Pavlos Kollias, Andrew M. Vogelmann, Kang Yang, and Tao Luo
Atmos. Chem. Phys., 18, 4317–4327, https://doi.org/10.5194/acp-18-4317-2018, https://doi.org/10.5194/acp-18-4317-2018, 2018
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Ice production in atmospheric clouds is important for global water cycle and radiation budget. Active satellite remote sensing measurements are analyzed to quantitatively study primary ice particle production in stratiform mixed-phase clouds on a global scale. We quantify the geographic and seasonal variations of ice production and their correlations with aerosol, especially mineral dust activities. The results can be used to evaluate mixed-phased clouds simulations by global climate models.
Xiaoli Zhou, Andrew S. Ackerman, Ann M. Fridlind, Robert Wood, and Pavlos Kollias
Atmos. Chem. Phys., 17, 12725–12742, https://doi.org/10.5194/acp-17-12725-2017, https://doi.org/10.5194/acp-17-12725-2017, 2017
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Shallow maritime clouds make a well-known transition from stratocumulus to trade cumulus with flow from the subtropics equatorward. Three-day large-eddy simulations that investigate the potential influence of overlying African biomass burning plumes during that transition indicate that cloud-related impacts are likely substantially cooling to negligible at the top of the atmosphere, with magnitude sensitive to background and perturbation aerosol and cloud properties.
Kirk W. North, Mariko Oue, Pavlos Kollias, Scott E. Giangrande, Scott M. Collis, and Corey K. Potvin
Atmos. Meas. Tech., 10, 2785–2806, https://doi.org/10.5194/amt-10-2785-2017, https://doi.org/10.5194/amt-10-2785-2017, 2017
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Vertical air motion retrievals from 3DVAR multiple distributed scanning Doppler radars are compared against collocated profiling radars and retrieved from an upward iteration integration iterative technique to characterize their veracity. The retrieved vertical air motions are generally within 1–2 m s−1 of agreement with profiling radars and better solution than the upward integration technique, and therefore can be used as a means to improve parameterizations in numerical models moving forward.
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.
A. Chandra, C. Zhang, P. Kollias, S. Matrosov, and W. Szyrmer
Atmos. Meas. Tech., 8, 3685–3699, https://doi.org/10.5194/amt-8-3685-2015, https://doi.org/10.5194/amt-8-3685-2015, 2015
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An automated algorithm is developed for routinely retrieving rain rates from the profiling Ka-Band zenith radars. The algorithm is implemented in two steps: higher rain rates are retrieved by using the amount of attenuation in rain layers, while low rain rates are retrieved from the reflectivity-rain rate (Ze-R) relation. Observations collected by rain gauge, disdrometer and scanning precipitation radars during the DYNAMO field campaign at Gan Island are used to validate the proposed approach.
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Version 8 IMK–IAA MIPAS temperatures from 12–15 µm spectra: Middle and Upper Atmosphere modes
GNSS radio occultation excess-phase processing for climate applications including uncertainty estimation
Impact analysis of processing strategies for long-term GPS zenith tropospheric delay (ZTD)
Irradiance and cloud optical properties from solar photovoltaic systems
Single field-of-view sounder atmospheric product retrieval algorithm: establishing radiometric consistency for hyper-spectral sounder retrievals
Higher-order calibration on WindRAD (Wind Radar) scatterometer winds
On the polarimetric backscatter by a still or quasi-still wind turbine
OH airglow observations with two identical spectrometers: benefits of increased data homogeneity in the identification of variations induced by the 11-year solar cycle, the QBO, and other factors
Broadband radiative quantities for the EarthCARE mission: the ACM-COM and ACM-RT products
Difference spectrum fitting of the ion-neutral collision frequency from dual-frequency EISCAT measurements
Long-term multi-source precipitation estimation with high resolution (RainGRS Clim)
Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations
Using optimal estimation to retrieve winds from velocity-azimuth display (VAD) scans by a Doppler lidar
Angular sampling of a monochromatic, wide-field-of-view camera to augment next-generation Earth radiation budget satellite observations
Radar and Environment-based Hail Damage Estimates using Machine Learning
Performance evaluation of three bio-optical models in aerosol and ocean color joint retrievals
Efficient collocation of global navigation satellite system radio occultation soundings with passive nadir microwave soundings
Analysis of 2D airglow imager data with respect to dynamics using machine learning
Estimation of extreme precipitation events in Estonia and Italy using dual-polarization weather radar quantitative precipitation estimations
Observation of horizontal temperature variations by a spatial heterodyne interferometer using single-sided interferograms
Joint 1DVar Retrievals of Tropospheric Temperature and Water Vapor from GNSS-RO and Microwave Radiometer Observations
Detection and localization of F-layer ionospheric irregularities with the back-propagation method along the radio occultation ray path
Observations of anomalous propagation over waters near Sweden
Suppression of precipitation bias on wind velocity from continuous-wave Doppler lidars
Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at Réunion island and the Observatoire de Haute-Provence
Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach
High-resolution 3D winds derived from a modified WISSDOM synthesis scheme using multiple Doppler lidars and observations
Atmospheric boundary layer height from ground-based remote sensing: a review of capabilities and limitations
Assessing and mitigating the radar–radar interference in the German C-band weather radar network
Spectral replacement using machine learning methods for continuous mapping of the Geostationary Environment Monitoring Spectrometer (GEMS)
Doppler spectra from DWD's operational C-band radar birdbath scan: sampling strategy, spectral postprocessing, and multimodal analysis for the retrieval of precipitation processes
High-fidelity retrieval from instantaneous line-of-sight returns of nacelle-mounted lidar including supervised machine learning
Horizontal small-scale variability of water vapor in the atmosphere: implications for intercomparison of data from different measuring systems
Satellite observations of gravity wave momentum flux in the mesosphere and lower thermosphere (MLT): feasibility and requirements
An improved near-real-time precipitation retrieval for Brazil
Radio frequency interference detection and mitigation in the DWD C-band weather radar network
Quality control and error assessment of the Aeolus L2B wind results from the Joint Aeolus Tropical Atlantic Campaign
Long-distance propagation of 162 MHz shipping information links associated with sporadic E
Estimation of refractivity uncertainties and vertical error correlations in collocated radio occultations, radiosondes, and model forecasts
DeepPrecip: a deep neural network for precipitation retrievals
Machine learning-based prediction of Alpine foehn events using GNSS troposphere products: first results for Altdorf, Switzerland
Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm
Adaptive thermal image velocimetry of spatial wind movement on landscapes using near-target infrared cameras
Image muting of mixed precipitation to improve identification of regions of heavy snow in radar data
Extending water vapor measurement capability of photon-limited differential absorption lidars through simultaneous denoising and inversion
GPROF-NN: a neural-network-based implementation of the Goddard Profiling Algorithm
Sensitivity analysis of DSD retrievals from polarimetric radar in stratiform rain based on the μ–Λ relationship
On the use of high-frequency surface wave oceanographic research radars as bistatic single-frequency oblique ionospheric sounders
A statistically optimal analysis of systematic differences between Aeolus horizontal line-of-sight winds and NOAA's Global Forecast System
Hierarchical deconvolution for incoherent scatter radar data
Maya García-Comas, Bernd Funke, Manuel López-Puertas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Belén Martínez-Mondéjar, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 5357–5386, https://doi.org/10.5194/amt-16-5357-2023, https://doi.org/10.5194/amt-16-5357-2023, 2023
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We have released version 8 of MIPAS IMK–IAA temperatures and pointing information retrieved from MIPAS Middle and Upper Atmosphere mode version 8.03 calibrated spectra, covering 20–115 km altitude. We considered non-local thermodynamic equilibrium emission explicitly for each limb scan, essential to retrieve accurate temperatures above the mid-mesosphere. Comparisons of this temperature dataset with SABER measurements show excellent agreement, improving those of previous MIPAS versions.
Josef Innerkofler, Gottfried Kirchengast, Marc Schwärz, Christian Marquardt, and Yago Andres
Atmos. Meas. Tech., 16, 5217–5247, https://doi.org/10.5194/amt-16-5217-2023, https://doi.org/10.5194/amt-16-5217-2023, 2023
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Atmosphere remote sensing using GNSS radio occultation provides a highly valuable basis for atmospheric and climate science. For the highest-quality demands, the Wegener Center set up a rigorous system for processing low-level measurement data. This excess-phase processing setup includes integrated quality control and uncertainty estimation. It was successfully evaluated and inter-compared, ensuring the capability of producing reliable long-term data records for climate applications.
Jingna Bai, Yidong Lou, Weixing Zhang, Yaozong Zhou, Zhenyi Zhang, Chuang Shi, and Jingnan Liu
Atmos. Meas. Tech., 16, 5249–5259, https://doi.org/10.5194/amt-16-5249-2023, https://doi.org/10.5194/amt-16-5249-2023, 2023
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Homogenized atmospheric water vapor data are an important prerequisite for climate analysis. Compared to other techniques, GPS has an inherent homogeneity advantage but requires reprocessing and homogenization to eliminate impacts of applied strategy and observation environmental changes. The low-elevation cut-off angles are suggested for the best estimates of zenith tropospheric delay (ZTD) reprocessing time series when compared to homogenized radiosonde data or ERA5 reference time series.
James Barry, Stefanie Meilinger, Klaus Pfeilsticker, Anna Herman-Czezuch, Nicola Kimiaie, Christopher Schirrmeister, Rone Yousif, Tina Buchmann, Johannes Grabenstein, Hartwig Deneke, Jonas Witthuhn, Claudia Emde, Felix Gödde, Bernhard Mayer, Leonhard Scheck, Marion Schroedter-Homscheidt, Philipp Hofbauer, and Matthias Struck
Atmos. Meas. Tech., 16, 4975–5007, https://doi.org/10.5194/amt-16-4975-2023, https://doi.org/10.5194/amt-16-4975-2023, 2023
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Measured power data from solar photovoltaic (PV) systems contain information about the state of the atmosphere. In this work, power data from PV systems in the Allgäu region in Germany were used to determine the solar irradiance at each location, using state-of-the-art simulation and modelling. The results were validated using concurrent measurements of the incoming solar radiation in each case. If applied on a wider scale, this algorithm could help improve weather and climate models.
Wan Wu, Xu Liu, Liqiao Lei, Xiaozhen Xiong, Qiguang Yang, Qing Yue, Daniel K. Zhou, and Allen M. Larar
Atmos. Meas. Tech., 16, 4807–4832, https://doi.org/10.5194/amt-16-4807-2023, https://doi.org/10.5194/amt-16-4807-2023, 2023
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We present a new operational physical retrieval algorithm that is used to retrieve atmospheric properties for each single field-of-view measurement of hyper-spectral IR sounders. The physical scheme includes a cloud-scattering calculation in its forward-simulation part. The data product generated using this algorithm has an advantage over traditional IR sounder data production algorithms in terms of improved spatial resolution and minimized error due to cloud contamination.
Zhen Li, Ad Stoffelen, Anton Verhoef, Zhixiong Wang, Jian Shang, and Honggang Yin
Atmos. Meas. Tech., 16, 4769–4783, https://doi.org/10.5194/amt-16-4769-2023, https://doi.org/10.5194/amt-16-4769-2023, 2023
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WindRAD (Wind Radar) is the first dual-frequency rotating fan-beam scatterometer in orbit. We observe non-linearity in the backscatter distribution. Therefore, higher-order calibration (HOC) is proposed, which removes the non-linearities per incidence angle. The combination of HOC and NOCant is discussed. It can remove not only the non-linearity but also the anomalous harmonic azimuth dependencies caused by the antenna rotation; hence the optimal winds can be achieved with this combination.
Marco Gabella, Martin Lainer, Daniel Wolfensberger, and Jacopo Grazioli
Atmos. Meas. Tech., 16, 4409–4422, https://doi.org/10.5194/amt-16-4409-2023, https://doi.org/10.5194/amt-16-4409-2023, 2023
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A still wind turbine observed with a fixed-pointing radar antenna has shown distinctive polarimetric signatures: the correlation coefficient between the two orthogonal polarization states was persistently equal to 1. The differential reflectivity and the radar reflectivity factors were also stable in time. Over 2 min (2000 Hz, 128 pulses were used; consequently, the sampling time was 64 ms), the standard deviation of the differential backscattering phase shift was only a few degrees.
Carsten Schmidt, Lisa Küchelbacher, Sabine Wüst, and Michael Bittner
Atmos. Meas. Tech., 16, 4331–4356, https://doi.org/10.5194/amt-16-4331-2023, https://doi.org/10.5194/amt-16-4331-2023, 2023
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Two identical instruments in a parallel setup were used to observe the mesospheric OH airglow for more than 10 years (2009–2020) at 47.42°N, 10.98°E. This allows unique analyses of data quality aspects and their impact on the obtained results. During solar cycle 24 the influence of the sun was strong (∼6 K per 100 sfu). A quasi-2-year oscillation (QBO) of ±1 K is observed mainly during the maximum of the solar cycle. Unlike the stratospheric QBO the variation has a period of or below 24 months.
Jason N. S. Cole, Howard W. Barker, Zhipeng Qu, Najda Villefranque, and Mark W. Shephard
Atmos. Meas. Tech., 16, 4271–4288, https://doi.org/10.5194/amt-16-4271-2023, https://doi.org/10.5194/amt-16-4271-2023, 2023
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Measurements from the EarthCARE satellite mission will be used to retrieve profiles of cloud and aerosol properties. These retrievals are combined with auxiliary information about surface properties and atmospheric state, e.g., temperature and water vapor. This information allows computation of 1D and 3D solar and thermal radiative transfer for small domains, which are compared with coincident radiometer observations to continually assess EarthCARE retrievals.
Florian Günzkofer, Gunter Stober, Dimitry Pokhotelov, Yasunobu Miyoshi, and Claudia Borries
EGUsphere, https://doi.org/10.5194/egusphere-2023-1495, https://doi.org/10.5194/egusphere-2023-1495, 2023
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Electric currents in the ionosphere can impact both satellite and ground-based infrastructure. These currents depend strongly on the collisions of ions and neutral particles. Measuring ion-neutral collisions is often only possible via certain assumptions. Direct measurement of ion-neutral collision frequencies is possible with multifrequency Incoherent Scatter Radar measurements. This paper presents one analysis method of such measurements and discusses its advantages and disadvantages.
Anna Jurczyk, Katarzyna Ośródka, Jan Szturc, Magdalena Pasierb, and Agnieszka Kurcz
Atmos. Meas. Tech., 16, 4067–4079, https://doi.org/10.5194/amt-16-4067-2023, https://doi.org/10.5194/amt-16-4067-2023, 2023
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A data-processing algorithm, RainGRS Clim, has been developed to work on precipitation accumulations such as daily or monthly totals. The algorithm makes the most of additional opportunities: access to high-quality data that are not operationally available and greater efficiency of the algorithms for data quality control and merging for longer accumulations. Monthly accumulations estimated by RainGRS Clim were found to be significantly more reliable than accumulations generated operationally.
Sophie Rosenburg, Charlotte Lange, Evelyn Jäkel, Michael Schäfer, André Ehrlich, and Manfred Wendisch
Atmos. Meas. Tech., 16, 3915–3930, https://doi.org/10.5194/amt-16-3915-2023, https://doi.org/10.5194/amt-16-3915-2023, 2023
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Snow layer melting and melt pond formation on Arctic sea ice are important seasonal processes affecting the surface reflection and energy budget. Sea ice reflectivity was surveyed by airborne imaging spectrometers in May–June 2017. Adapted retrieval approaches were applied to find snow layer liquid water fraction, snow grain effective radius, and melt pond depth. The retrievals show the potential and limitations of spectral airborne imaging to map melting snow layer and melt pond properties.
Sunil Baidar, Timothy J. Wagner, David D. Turner, and W. Alan Brewer
Atmos. Meas. Tech., 16, 3715–3726, https://doi.org/10.5194/amt-16-3715-2023, https://doi.org/10.5194/amt-16-3715-2023, 2023
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This paper provides a new method to retrieve wind profiles from coherent Doppler lidar (CDL) measurements. It takes advantage of layer-to-layer correlation in wind profiles to provide continuous profiles of up to 3 km by filling in the gaps where the CDL signal is too small to retrieve reliable results by itself. Comparison with the current method and collocated radiosonde wind measurements showed excellent agreement with no degradation in results where the current method gives valid results.
Jake J. Gristey, K. Sebastian Schmidt, Hong Chen, Daniel R. Feldman, Bruce C. Kindel, Joshua Mauss, Mathew van den Heever, Maria Z. Hakuba, and Peter Pilewskie
Atmos. Meas. Tech., 16, 3609–3630, https://doi.org/10.5194/amt-16-3609-2023, https://doi.org/10.5194/amt-16-3609-2023, 2023
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The concept of a satellite-based camera is demonstrated for sampling the angular distribution of outgoing radiance from Earth needed to generate data products for new radiation budget spectral channels.
Luis Ackermann, Joshua Soderholm, Alain Protat, Rhys Whitley, Lisa Ye, and Nina Ridder
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-161, https://doi.org/10.5194/amt-2023-161, 2023
Revised manuscript accepted for AMT
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The manuscript addresses the crucial topic of hail damage quantification using radar observations. We propose a new radar-derived hail product that utilises a large dataset of insurance hail damage claims and radar observations. A deep neural network was employed, trained with local meteorological variables and the radar observations, to better quantify hail damage. Key meteorological variables were identified to have the most predictive capability in this regards.
Neranga K. Hannadige, Peng-Wang Zhai, Meng Gao, Yongxiang Hu, P. Jeremy Werdell, Kirk Knobelspiesse, and Brian Cairns
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-142, https://doi.org/10.5194/amt-2023-142, 2023
Revised manuscript accepted for AMT
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We evaluated the impact of three ocean optical models with different numbers of free parameters on the performance of an aerosol and ocean color remote sensing algorithm using the multi-angle polarimeter (MAP) measurements. It was demonstrated that the 3 and 7-parameter bio-optical models can be used to accurately represent both open and coastal waters, whereas the 1-parameter model does have smaller retrieval uncertainty over open waters.
Alex Meredith, Stephen Leroy, Lucy Halperin, and Kerri Cahoy
Atmos. Meas. Tech., 16, 3345–3361, https://doi.org/10.5194/amt-16-3345-2023, https://doi.org/10.5194/amt-16-3345-2023, 2023
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We developed a new efficient algorithm leveraging orbital dynamics to collocate radio occultation soundings with microwave radiance soundings. This new algorithm is 99 % accurate and is much faster than traditional collocation-finding approaches. Speeding up collocation finding is useful for calibrating and validating microwave radiometers and for data assimilation into numerical weather prediction models. Our algorithm can also be used to predict collocation yield for new satellite missions.
René Sedlak, Andreas Welscher, Patrick Hannawald, Sabine Wüst, Rainer Lienhart, and Michael Bittner
Atmos. Meas. Tech., 16, 3141–3153, https://doi.org/10.5194/amt-16-3141-2023, https://doi.org/10.5194/amt-16-3141-2023, 2023
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We show that machine learning can help in classifying images of the OH* airglow, a thin layer in the middle atmosphere (ca. 86 km height) emitting infrared radiation, in an efficient way. By doing this,
dynamicepisodes of strong movement in the OH* airglow caused predominantly by waves can be extracted automatically from large data sets. Within these dynamic episodes, turbulent wave breaking can also be found. We use these observations of turbulence to derive the energy released by waves.
Roberto Cremonini, Tanel Voormansik, Piia Post, and Dmitri Moisseev
Atmos. Meas. Tech., 16, 2943–2956, https://doi.org/10.5194/amt-16-2943-2023, https://doi.org/10.5194/amt-16-2943-2023, 2023
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Extreme rainfall for a specific location is commonly evaluated when designing stormwater management systems. This study investigates the use of quantitative precipitation estimations (QPEs) based on polarimetric weather radar data, without rain gauge corrections, to estimate 1 h rainfall total maxima in Italy and Estonia. We show that dual-polarization weather radar provides reliable QPEs and effective estimations of return periods for extreme rainfall in climatologically homogeneous regions.
Konstantin Franz Fotios Ntokas, Jörn Ungermann, Martin Kaufmann, Tom Neubert, and Martin Riese
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-74, https://doi.org/10.5194/amt-2023-74, 2023
Revised manuscript accepted for AMT
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A nano-satellite was developed to obtain 1-D vertical temperature profiles in the mesosphere and lower thermosphere, which can be used to derive wave parameters needed for atmospheric models. A new processing method is shown, which allows to extract two 1-D temperature profiles. The location of the two profiles is analyzed, as it is needed for deriving wave parameters. We show that this method is feasible, which however will increase the requirements of an accurate calibration and processing.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
EGUsphere, https://doi.org/10.5194/egusphere-2023-85, https://doi.org/10.5194/egusphere-2023-85, 2023
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In this article we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO/MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO/MWR retrieval.
Vinícius Ludwig-Barbosa, Joel Rasch, Thomas Sievert, Anders Carlström, Mats I. Pettersson, Viet Thuy Vu, and Jacob Christensen
Atmos. Meas. Tech., 16, 1849–1864, https://doi.org/10.5194/amt-16-1849-2023, https://doi.org/10.5194/amt-16-1849-2023, 2023
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In this paper, the back-propagation method's capabilities and limitations regarding the location of irregularity regions in the ionosphere, e.g. equatorial plasma bubbles, are evaluated. The assessment was performed with simulations in which different scenarios were assumed. The results showed that the location estimate is possible if the amplitude of the ionospheric disturbance is stronger than the instrument noise level. Further, multiple patches can be located if regions are well separated.
Lars Norin
Atmos. Meas. Tech., 16, 1789–1801, https://doi.org/10.5194/amt-16-1789-2023, https://doi.org/10.5194/amt-16-1789-2023, 2023
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The atmosphere can cause radar beams to bend more or less towards the ground. When the atmosphere differs from standard atmospheric conditions, the propagation is considered anomalous. Radars affected by anomalous propagation can observe ground clutter far beyond the radar horizon. Here, 4.5 years' worth of data from five operational Swedish weather radars are presented. Analyses of the data reveal a strong seasonal cycle and weaker diurnal cycle in ground clutter from across nearby waters.
Liqin Jin, Jakob Mann, Nikolas Angelou, and Mikael Sjöholm
EGUsphere, https://doi.org/10.5194/egusphere-2023-464, https://doi.org/10.5194/egusphere-2023-464, 2023
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By sampling the spectra of a Doppler lidar faster than the raindrop's beam transit time, the rain signal can be filtered away and the bias on the wind velocity estimation can be reduced. In the method we propose, 3 kHz spectra are normalized with their peak values before retrieving the radial wind velocity. In three hours period, we have observed a significant reduction of the bias of the lidar data relative to the sonic. The tendency is that the more it rains, the more the bias is reduced.
Mathieu Ratynski, Sergey Khaykin, Alain Hauchecorne, Robin Wing, Jean-Pierre Cammas, Yann Hello, and Philippe Keckhut
Atmos. Meas. Tech., 16, 997–1016, https://doi.org/10.5194/amt-16-997-2023, https://doi.org/10.5194/amt-16-997-2023, 2023
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Aeolus is the first spaceborne wind lidar providing global wind measurements since 2018. This study offers a comprehensive analysis of Aeolus instrument performance, using ground-based wind lidars and meteorological radiosondes, at tropical and mid-latitudes sites. The analysis allows assessing the long-term evolution of the satellite's performance for more than 3 years. The results will help further elaborate the understanding of the error sources and the behavior of the Doppler wind lidar.
Anne-Claire Billault-Roux, Gionata Ghiggi, Louis Jaffeux, Audrey Martini, Nicolas Viltard, and Alexis Berne
Atmos. Meas. Tech., 16, 911–940, https://doi.org/10.5194/amt-16-911-2023, https://doi.org/10.5194/amt-16-911-2023, 2023
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Better understanding and modeling snowfall properties and processes is relevant to many fields, ranging from weather forecasting to aircraft safety. Meteorological radars can be used to gain insights into the microphysics of snowfall. In this work, we propose a new method to retrieve snowfall properties from measurements of radars with different frequencies. It relies on an original deep-learning framework, which incorporates knowledge of the underlying physics, i.e., electromagnetic scattering.
Chia-Lun Tsai, Kwonil Kim, Yu-Chieng Liou, and GyuWon Lee
Atmos. Meas. Tech., 16, 845–869, https://doi.org/10.5194/amt-16-845-2023, https://doi.org/10.5194/amt-16-845-2023, 2023
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Since the winds in clear-air conditions usually play an important role in the initiation of various weather systems and phenomena, the modified Wind Synthesis System using Doppler Measurements (WISSDOM) synthesis scheme was developed to derive high-quality and high-spatial-resolution 3D winds under clear-air conditions. The performance and accuracy of derived 3D winds from this modified scheme were evaluated with an extreme strong wind event over complex terrain in Pyeongchang, South Korea.
Simone Kotthaus, Juan Antonio Bravo-Aranda, Martine Collaud Coen, Juan Luis Guerrero-Rascado, Maria João Costa, Domenico Cimini, Ewan J. O'Connor, Maxime Hervo, Lucas Alados-Arboledas, María Jiménez-Portaz, Lucia Mona, Dominique Ruffieux, Anthony Illingworth, and Martial Haeffelin
Atmos. Meas. Tech., 16, 433–479, https://doi.org/10.5194/amt-16-433-2023, https://doi.org/10.5194/amt-16-433-2023, 2023
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Profile observations of the atmospheric boundary layer now allow for layer heights and characteristics to be derived at high temporal and vertical resolution. With novel high-density ground-based remote-sensing measurement networks emerging, horizontal information content is also increasing. This review summarises the capabilities and limitations of various sensors and retrieval algorithms which need to be considered during the harmonisation of data products for high-impact applications.
Michael Frech, Cornelius Hald, Maximilian Schaper, Bertram Lange, and Benjamin Rohrdantz
Atmos. Meas. Tech., 16, 295–309, https://doi.org/10.5194/amt-16-295-2023, https://doi.org/10.5194/amt-16-295-2023, 2023
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Weather radar data are the backbone of a lot of meteorological products. In order to obtain a better low-level coverage with radar data, additional systems have to be included. The frequency range in which radars are allowed to operate is limited. A potential radar-to-radar interference has to be avoided. The paper derives guidelines on how additional radars can be included into a C-band weather radar network and how interferences can be avoided.
Yeeun Lee, Myoung-Hwan Ahn, Mina Kang, and Mijin Eo
Atmos. Meas. Tech., 16, 153–168, https://doi.org/10.5194/amt-16-153-2023, https://doi.org/10.5194/amt-16-153-2023, 2023
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This study aims to verify that a partly defective hyperspectral measurement can be successfully reproduced with concise machine learning models coupled with principal component analysis. Evaluation of the approach is performed with radiances and retrieval results of ozone and cloud properties. Considering that GEMS is the first geostationary UV–VIS hyperspectral spectrometer, we expect our findings can be introduced further to similar geostationary environmental instruments to be launched soon.
Mathias Gergely, Maximilian Schaper, Matthias Toussaint, and Michael Frech
Atmos. Meas. Tech., 15, 7315–7335, https://doi.org/10.5194/amt-15-7315-2022, https://doi.org/10.5194/amt-15-7315-2022, 2022
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This study presents the new vertically pointing birdbath scan of the German C-band radar network, which provides high-resolution profiles of precipitating clouds above all DWD weather radars since the spring of 2021. Our AI-based postprocessing method for filtering and analyzing the recorded radar data offers a unique quantitative view into a wide range of precipitation events from snowfall over stratiform rain to intense frontal showers and will be used to complement DWD's operational services.
Kenneth A. Brown and Thomas G. Herges
Atmos. Meas. Tech., 15, 7211–7234, https://doi.org/10.5194/amt-15-7211-2022, https://doi.org/10.5194/amt-15-7211-2022, 2022
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The character of the airflow around and within wind farms has a significant impact on the energy output and longevity of the wind turbines in the farm. For both research and control purposes, accurate measurements of the wind speed are required, and these are often accomplished with remote sensing devices. This article pertains to a field experiment of a lidar mounted to a wind turbine and demonstrates three data post-processing techniques with efficacy at extracting useful airflow information.
Xavier Calbet, Cintia Carbajal Henken, Sergio DeSouza-Machado, Bomin Sun, and Tony Reale
Atmos. Meas. Tech., 15, 7105–7118, https://doi.org/10.5194/amt-15-7105-2022, https://doi.org/10.5194/amt-15-7105-2022, 2022
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Water vapor concentration in the atmosphere at small scales (< 6 km) is considered. The measurements show Gaussian random field behavior following Kolmogorov's theory of turbulence two-thirds law. These properties can be useful when estimating the water vapor variability within a given observed satellite scene or when different water vapor measurements have to be merged consistently.
Qiuyu Chen, Konstantin Ntokas, Björn Linder, Lukas Krasauskas, Manfred Ern, Peter Preusse, Jörn Ungermann, Erich Becker, Martin Kaufmann, and Martin Riese
Atmos. Meas. Tech., 15, 7071–7103, https://doi.org/10.5194/amt-15-7071-2022, https://doi.org/10.5194/amt-15-7071-2022, 2022
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Observations of phase speed and direction spectra as well as zonal mean net gravity wave momentum flux are required to understand how gravity waves reach the mesosphere–lower thermosphere and how they there interact with background flow. To this end we propose flying two CubeSats, each deploying a spatial heterodyne spectrometer for limb observation of the airglow. End-to-end simulations demonstrate that individual gravity waves are retrieved faithfully for the expected instrument performance.
Simon Pfreundschuh, Ingrid Ingemarsson, Patrick Eriksson, Daniel A. Vila, and Alan J. P. Calheiros
Atmos. Meas. Tech., 15, 6907–6933, https://doi.org/10.5194/amt-15-6907-2022, https://doi.org/10.5194/amt-15-6907-2022, 2022
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We used methods from the field of artificial intelligence to train an algorithm to estimate rain from satellite observations. In contrast to other methods, our algorithm not only estimates rain, but also the uncertainty of the estimate. Using independent measurements from rain gauges, we show that our method performs better than currently available methods and that the provided uncertainty estimates are reliable. Our method makes satellite-based measurements of rain more accurate and reliable.
Maximilian Schaper, Michael Frech, David Michaelis, Cornelius Hald, and Benjamin Rohrdantz
Atmos. Meas. Tech., 15, 6625–6642, https://doi.org/10.5194/amt-15-6625-2022, https://doi.org/10.5194/amt-15-6625-2022, 2022
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C-band weather radar data are commonly compromised by radio frequency interference (RFI) from external sources. It is not possible to separate a superimposed interference signal from the radar data. Therefore, the best course of action is to shut down RFI sources as quickly as possible. An automated RFI detection algorithm has been developed. Since its implementation, persistent RFI sources are eliminated much more quickly, while the number of short-lived RFI sources keeps steadily increasing.
Oliver Lux, Benjamin Witschas, Alexander Geiß, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Stephan Rahm, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 6467–6488, https://doi.org/10.5194/amt-15-6467-2022, https://doi.org/10.5194/amt-15-6467-2022, 2022
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We discuss the influence of different quality control schemes on the results of Aeolus wind product validation and present statistical tools for ensuring consistency and comparability among diverse validation studies with regard to the specific error characteristics of the Rayleigh-clear and Mie-cloudy winds. The developed methods are applied for the validation of Aeolus winds against an ECMWF model background and airborne wind lidar data from the Joint Aeolus Tropical Atlantic Campaign.
Alex T. Chartier, Thomas R. Hanley, and Daniel J. Emmons
Atmos. Meas. Tech., 15, 6387–6393, https://doi.org/10.5194/amt-15-6387-2022, https://doi.org/10.5194/amt-15-6387-2022, 2022
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This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.
Johannes K. Nielsen, Hans Gleisner, Stig Syndergaard, and Kent B. Lauritsen
Atmos. Meas. Tech., 15, 6243–6256, https://doi.org/10.5194/amt-15-6243-2022, https://doi.org/10.5194/amt-15-6243-2022, 2022
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This paper provides a new way to estimate uncertainties and error correlations. The method is a generalization of a known method called the
three-cornered hat: Instead of calculating uncertainties from assumed knowledge about the observation method, uncertainties and error correlations are estimated statistically from tree independent observation series, measuring the same variable. The results are useful for future estimation of atmospheric-specific humidity from the bending of radio waves.
Fraser King, George Duffy, Lisa Milani, Christopher G. Fletcher, Claire Pettersen, and Kerstin Ebell
Atmos. Meas. Tech., 15, 6035–6050, https://doi.org/10.5194/amt-15-6035-2022, https://doi.org/10.5194/amt-15-6035-2022, 2022
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Under warmer global temperatures, precipitation patterns are expected to shift substantially, with critical impact on the global water-energy budget. In this work, we develop a deep learning model for predicting snow and rain accumulation based on surface radar observations of the lower atmosphere. Our model demonstrates improved skill over traditional methods and provides new insights into the regions of the atmosphere that provide the most significant contributions to high model accuracy.
Matthias Aichinger-Rosenberger, Elmar Brockmann, Laura Crocetti, Benedikt Soja, and Gregor Moeller
Atmos. Meas. Tech., 15, 5821–5839, https://doi.org/10.5194/amt-15-5821-2022, https://doi.org/10.5194/amt-15-5821-2022, 2022
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This study develops an innovative approach for the detection and prediction of foehn winds. The approach uses products generated from GNSS (Global Navigation Satellite Systems) in combination with machine learning-based classification algorithms to detect and predict foehn winds at Altdorf, Switzerland. Results are encouraging and comparable to similar studies using meteorological data, which might qualify the method as an additional tool for short-term foehn forecasting in the future.
Gunter Stober, Alan Liu, Alexander Kozlovsky, Zishun Qiao, Ales Kuchar, Christoph Jacobi, Chris Meek, Diego Janches, Guiping Liu, Masaki Tsutsumi, Njål Gulbrandsen, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, and Nicholas Mitchell
Atmos. Meas. Tech., 15, 5769–5792, https://doi.org/10.5194/amt-15-5769-2022, https://doi.org/10.5194/amt-15-5769-2022, 2022
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Precise and accurate measurements of vertical winds at the mesosphere and lower thermosphere are rare. Although meteor radars have been used for decades to observe horizontal winds, their ability to derive reliable vertical wind measurements was always questioned. In this article, we provide mathematical concepts to retrieve mathematically and physically consistent solutions, which are compared to the state-of-the-art non-hydrostatic model UA-ICON.
Benjamin Schumacher, Marwan Katurji, Jiawei Zhang, Peyman Zawar-Reza, Benjamin Adams, and Matthias Zeeman
Atmos. Meas. Tech., 15, 5681–5700, https://doi.org/10.5194/amt-15-5681-2022, https://doi.org/10.5194/amt-15-5681-2022, 2022
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This investigation presents adaptive thermal image velocimetry (A-TIV), a newly developed algorithm to spatially measure near-surface atmospheric velocities using an infrared camera mounted on uncrewed aerial vehicles. A validation and accuracy assessment of the retrieved velocity fields shows the successful application of the algorithm over short-cut grass and turf surfaces in dry conditions. This provides new opportunities for atmospheric scientists to study surface–atmosphere interactions.
Laura M. Tomkins, Sandra E. Yuter, Matthew A. Miller, and Luke R. Allen
Atmos. Meas. Tech., 15, 5515–5525, https://doi.org/10.5194/amt-15-5515-2022, https://doi.org/10.5194/amt-15-5515-2022, 2022
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Locally higher radar reflectivity values in winter storms can mean more snowfall or a transition from snow to mixtures of snow, partially melted snow, and/or rain. We use the correlation coefficient to de-emphasize regions of mixed precipitation. Visual muting is valuable for analyzing and monitoring evolving weather conditions during winter storm events.
Willem J. Marais and Matthew Hayman
Atmos. Meas. Tech., 15, 5159–5180, https://doi.org/10.5194/amt-15-5159-2022, https://doi.org/10.5194/amt-15-5159-2022, 2022
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For atmospheric science and weather prediction, it is important to make water vapor measurements in real time. A low-cost lidar instrument has been developed by Montana State University and the National Center for Atmospheric Research. We developed an advanced signal-processing method to extend the scientific capability of the lidar instrument. With the new method we show that the maximum altitude at which the MPD can make water vapor measurements can be extended up to 8 km.
Simon Pfreundschuh, Paula J. Brown, Christian D. Kummerow, Patrick Eriksson, and Teodor Norrestad
Atmos. Meas. Tech., 15, 5033–5060, https://doi.org/10.5194/amt-15-5033-2022, https://doi.org/10.5194/amt-15-5033-2022, 2022
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The Global Precipitation Measurement mission is an international satellite mission providing regular global rain measurements. We present two newly developed machine-learning-based implementations of one of the algorithms responsible for turning the satellite observations into rain measurements. We show that replacing the current algorithm with a neural network improves the accuracy of the measurements. A neural network that also makes use of spatial information unlocks further improvements.
Christos Gatidis, Marc Schleiss, and Christine Unal
Atmos. Meas. Tech., 15, 4951–4969, https://doi.org/10.5194/amt-15-4951-2022, https://doi.org/10.5194/amt-15-4951-2022, 2022
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Knowledge of the raindrop size distribution (DSD) is crucial for understanding rainfall microphysics and quantifying uncertainty in quantitative precipitation estimates. In this study a general overview of the DSD retrieval approach from a polarimetric radar is discussed, highlighting sensitivity to potential sources of errors, either directly linked to the radar measurements or indirectly through the critical modeling assumptions behind the method such as the shape–size (μ–Λ) relationship.
Stephen R. Kaeppler, Ethan S. Miller, Daniel Cole, and Teresa Updyke
Atmos. Meas. Tech., 15, 4531–4545, https://doi.org/10.5194/amt-15-4531-2022, https://doi.org/10.5194/amt-15-4531-2022, 2022
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This investigation demonstrates how useful ionospheric parameters can be extracted from existing high-frequency radars that are used for oceanographic research. The methodology presented can be used by scientists and radio amateurs to understand ionospheric dynamics.
Hui Liu, Kevin Garrett, Kayo Ide, Ross N. Hoffman, and Katherine E. Lukens
Atmos. Meas. Tech., 15, 3925–3940, https://doi.org/10.5194/amt-15-3925-2022, https://doi.org/10.5194/amt-15-3925-2022, 2022
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A total least squares (TLS) regression is used to optimally estimate linear speed-dependent biases between Aeolus Level-2B winds and short-term (6 h) forecasts of NOAA’s FV3GFS. The winds for 1–7 September 2019 are examined. Clear speed-dependent biases for both Mie and Rayleigh winds are found, particularly in the tropics and Southern Hemisphere. Use of the TLS correction improves the forecast of the 26–28 November 2019 winter storm over the USA.
Snizhana Ross, Arttu Arjas, Ilkka I. Virtanen, Mikko J. Sillanpää, Lassi Roininen, and Andreas Hauptmann
Atmos. Meas. Tech., 15, 3843–3857, https://doi.org/10.5194/amt-15-3843-2022, https://doi.org/10.5194/amt-15-3843-2022, 2022
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Radar measurements of thermal fluctuations in the Earth's ionosphere produce weak signals, and tuning to specific altitudes results in suboptimal resolution for other regions, making an accurate analysis of these changes difficult. A novel approach to improve the resolution and remove measurement noise is considered. The method can capture variable characteristics, making it ideal for the study of a large range of data. Synthetically generated examples and two measured datasets were considered.
Cited articles
Andrić, J., Kumjian, M. R., Zrnić, D., Straka, J. M., and Melnikov,
V.: Polarimetric signatures above the melting layer in winter storms: An
observational and modeling study, J. Appl. Meteorol. Climatol., 52, 682–700,
https://doi.org/10.1175/JAMC-D-12-028.1, 2013.
Battaglia, A., Rustemeier, E., Tokay, A., Blahak, U., and Simmer, C.:
PARSIVEL Snow Observations: A Critical Assessment, J. Atmos. Ocean. Tech.,
27, 333–344, https://doi.org/10.1175/2009JTECHA1332.1, 2010.
Battaglia, A., Mroz, K., 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.
Battaglia, A., Kollias, P., Dhillon, R., Roy, R., Tanelli, S., Lebsock, M.,
Grecu, M., Lamer, K., Watters, D., Mroz, K., Heymsfield, G., Li, L., and
Furukawa, K.: Space-borne cloud and precipitation radars: status, challenges
and ways forward, Rev. Geophys., 58, e2019RG000686,
https://doi.org/10.1029/2019RG000686, 2020.
Bechini, R., Baldini, L., and Chandrasekar, V.: Polarimetric radar
observations in the ice region of precipitating clouds at C-band and X-band
radar frequencies, Appl. Meteorol. Clim., 52, 1147–1169,
https://doi.org/10.1175/JAMC-D-12-055.1, 2013.
Böhm, H.: A general equation for the terminal fall speed of solid
hydrometeors, J. Atmos. Sci., 46, 2419–2427,
https://doi.org/10.1175/1520-0469(1989)046<2419:AGEFTT>2.0.CO;2, 1989.
Colle, B. A., Stark, D., and Yuter, S. E.: Surface microphysical observations
within East coast winter storms on Long Island, Mon. Weather Rev., 142,
3126–3146, 2014.
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.
Garrett, T. J. and Yuter, S. E.: Observed influence of riming, temperature,
and turbulence on the fallspeed of solid precipitation, Geophys. Res. Lett.,
41, 6515–6522, https://doi.org/10.1002/2014GL061016, 2014.
Garrett, T. J., Fallgatter, C., Shkurko, K., and Howlett, D.: Fall speed measurement and high-resolution multi-angle photography of hydrometeors in free fall, Atmos. Meas. Tech., 5, 2625–2633, https://doi.org/10.5194/amt-5-2625-2012, 2012.
Giangrande, S., Toto, T., Bansemer, A., Kumjian, M., Mishra, S., and
Ryzhkov, A.: Insights into riming and aggregation processes as revealed by
aircraft, radar, and disdrometer observations for a 27 April 2011 widespread
precipitation event, J. Geophys. Res.-Atmos, 121, 5846–5863, https://doi.org/10.1002/2015JD024537, 2016.
Griffin, E. M., Schuur, T. J., and Ryzhkov, A. V.: A Polarimetric Analysis
of Ice Microphysical Processes in Snow, Using Quasi-Vertical Profiles, J.
Appl. Meteorol. Clim., 57, 31–50, https://doi.org/10.1175/JAMC-D-17-0033.1,
2018.
Griffin, E. M., Schuur, T. J., and Ryzhkov, A. V.: A polarimetric radar analysis of
ice microphysical properties in melting layers of winter storms using S-band
quasi-vertical profiles, J. Appl. Meteorol. Clim., 59, 751–767,
https://doi.org/10.1175/JAMC-D-19-0128.1, 2020.
Heymsfield, A. J. and Westbrook, C. D.: Advances in the estimation of ice
particle fall speeds using laboratory and field measurements, J. Atmos.
Sci., 67, 2469–2482, https://doi.org/10.1175/2010JAS3379.1, 2010.
Hogan, R. J. and Westbrook, C. D.: Equation for the microwave backscatter
cross section of aggregate snowflakes using the self-similar Rayleigh–Gans
approximation, J. Atmos. Sci., 71, 3292–3301, 2014.
Hogan, R. J., Gaussiat, N., and Illingworth, A. J.: Stratocumulus liquid
water content from dual-wavelength radar, J. Atmos. Ocean. Tech., 22,
1207–1218, 2005.
Hogan, R. J., Honeyager, R., Tyynelä, J., and Kneifel, S.: Calculating the
millimetre-wave scattering phase function of snowflakes using the
self-similar Rayleigh–Gans approximation, Q. J. Roy.
Meteor. Soc., 143, 834–844, 2017.
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.
Hubbert, J. C. and Bringi, V. N.: An iterative filtering technique for the
analysis of copolar differential phase and dual-Frequency Radar
Measurements, J. Atmos. Ocean. Tech., 12, 643–648, https://doi.org/10.1175/1520-0426(1995)012<0643:AIFTFT>2.0.CO;2, 1995.
Illingworth, A. J., Barker, H. W., Beljaars, A., Ceccaldi, M., Chepfer, H., Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., Donovan, D. P., Fukuda, S., Hirakata, M., Hogan, R. J., Huenerbein, A., Kollias, P., Kubota, T., Nakajima, T., Nakajima, T. Y., Nishizawa, T., Ohno,Y., Okamoto, H., Oki, R., Sato, K., Satoh, M., Shephard, M. W., Velázquez-Blázquez, A., Wandinger, U., Wehr, T., and van Zadelhoff, G.-J.:
The EarthCARE satellite: The next step forward in global measurements of
clouds, aerosols, precipitation, and radiation, B. Am. Meteorol. Soc.,
96, 1311–1332, 2015.
Jiang, Z., Oue, M., Verlinde, J., Clothiaux, E., Aydin, K., Botta, G., and
Lu, Y.: What can we conclude about the real aspect ratios of ice particle
aggregates from two-dimensional images?, J. Appl. Meteorol. Clim., 56, 725–734,
2017.
Kajikawa, M.: Observation of the falling motion of early snowflakes. Part
II: On the variation of falling velocity, J. Meteorol. Soc. Jpn., 67,
731–738, 1989.
Kalesse, H., Kollias, P., and Szyrmer, W.: On using the relationship between
Doppler velocity and radar reflectivity to identify microphysical processes
in midlatitudinal ice clouds, J. Geophys. Res.-Atmos., 118, 12168–12179, https://doi.org/10.1002/2013JD020386, 2013.
Kennedy, P. C. and Rutledge, S. A.: S-band dual-polarization radar
observations of winter storms, J. Appl. Meteorol. Clim., 50, 844–858,
https://doi.org/10.1175/2010JAMC2558.1, 2011.
Kneifel, S. and Moisseev, D.: Long-term statistics of riming in
nonconvective clouds derived from ground-based Doppler cloud radar
observations, J. Atmos. Sci., 77, 3495–3508,
https://doi.org/10.1175/JAS-D-20-0007.1, 2020.
Kneifel, S., Lerber, A., Tiira, J., Moisseev, D., Kollias, P., and Leinonen,
J.: Observed relations between snowfall microphysics and triple-frequency
radar measurements, J. Geophys. Res.-Atmos., 120, 6034–6055,
https://doi.org/10.1002/2015JD023156, 2015.
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.
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, 2007.
Kollias, P., Bharadwaj, N., Widener, K., Jo, I., and Johnson, K.: Scanning
ARM cloud radars. Part I: Operational sampling strategies, J. Atmos. Ocean.
Tech., 31, 569–582, https://doi.org/10.1175/JTECH-D-13-00044.1, 2014.
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., Mead, J. B.,
Miller, M. A., Verlinde, J., Marchand, R. T., and Mace, G. G.: Development
and Applications of ARM Millimeter-Wavelength Cloud Radars, Meteor.
Mon., 57, 17.1–17.19,
https://doi.org/10.1175/AMSMONOGRAPHS-D-15-0037.1, 2016.
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, 2020a.
Kollias, P., Luke, E., Oue, M., and Lamer, K.: Agile adaptive radar sampling
of fast evolving atmospheric phenomena guided by satellite imagery and
surface cameras, Geophys. Res. Lett., 47, e2020GL088440, https://doi.org/10.1029/2020GL088440, 2020b.
Korolev, A. V. and Isaac, G.: Roundness and aspect ratio of particles in ice
clouds, J. Atmos. Sci., 60, 1795–1808,
https://doi.org/10.1175/1520-0469(2003)060<1795:RAAROP>2.0.CO;2,
2003.
Kumjian, M. R., Rutledge, S. A., Rasmussen, R. M., Kennedy, P. C., and
Dixon, M.: High-resolution polarimetric radar observations of snow
generating cells, J. Appl. Meteorol. Clim., 53, 1636–1658, https://doi.org/10.1175/JAMC-D-13-0312.1, 2014.
Kumjian, M. R., Mishra, S., Giangrande, S. E., Toto, T., Ryzhkov, A. V., and
Bansemer, A.: Polarimetric radar and aircraft observations of saggy bright
bands during MC3E, J. Geophys. Res., 121, 3584–3607, https://doi.org/10.1002/2015JD024446, 2016.
Kumjian, M. R., Tobin, D. M., Oue, M., and Kollias, P.: Microphysical
Insights into Ice Pellet Formation Revealed by Fully Polarimetric Ka-band
Doppler Radar, J. Appl. Meteorol. Clim., https://doi.org/10.1175/JAMC-D-20-0054.1, 2020.
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.
Leinonen, J. and Moisseev, D.: What do triple-frequency radar signatures
reveal about aggregate snowflakes?, J. Geophys. Res.-Atmos., 120, 229–239,
https://doi.org/10.1002/2014JD022072, 2015.
Leinonen, J. and Szyrmer, W.: Radar signatures of snowflake riming: a
modeling study, Earth and Space Science, 2, 346–358,
https://doi.org/10.1002/2015EA000102, 2015.
Leinonen, J., Moisseev, D., and Nousiainen, T.: Linking snowflake
microstructure to multi-frequency radar observations, J. Geophys. Res.-Atmos., 118, 3259–3270, https://doi.org/10.1002/jgrd.50163, 2013.
Lewis, E. R., Wiscombe, W. J., Albrecht, B. A., Bland, G. L., Flagg, C. N., Klein, S. A., Kollias, P., Mace, G., Reynolds, R. M., Schwartz, S. E., Siebesma, A. P., Teixeira, J., Wood, R., and Zhang, M.: MAGIC: Marine ARM GPCI Investigation of
Clouds, DOE/SC-ARM-12-020, U.S. Department of Energy, 12 pp., available at: https://www.arm.gov/publications/programdocs/doe-sc-arm-12-020.pdf, last access: 6 July 2021, 2012.
Li, H., Moisseev, D., and von Lerber, A.: How does riming affect
dual-polarization observations and snowflake shape?, J. Geophys. Res., 123, 6070–6081, 2018.
Liebe, H. J., Hufford, G., and Cotton, M.: Propagation modeling of moist air
and suspended water/ice particles at frequencies below 1000 GHz, presented
at an AGARD Meeting on “Atmospheric Propagation Effects through Natural and
Man-Made Obscurants for Visible to MM-Wave Radiation”, Mallorca, Spain, 17–20 May 1993 1993.
Locatelli, J. D. and Hobbs, P. V.: Fall speeds and masses of solid
precipitation particles, Geophys. Res.-Atmos., 79, 2185–2197, 1974.
Löffler-Mang, M. and Blahak, U.: Estimation of the Equivalent Radar
Reflectivity Factor from Measured Snow Size Spectra, J. Appl. Meteor., 40,
843–849, https://doi.org/10.1175/1520-0450(2001)040<0843:EOTERR>2.0.CO;2, 2001.
Luke, E., 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.
Mason, S. L., Chiu, C. J., Hogan, R. J., Moisseev, D., and Kneifel, S.:
Retrievals of riming and snow density from vertically pointing Doppler
radars, J. Geophys. Res.-Atmos., 123, 13807–13834,
https://doi.org/10.1029/2018JD028603, 2018.
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.
Mather, J. H. and Voyles, J. W.: The Arm Climate Research Facility: A
review of structure and capabilities. B. Am. Meteorol. Soc., 94,
377–392, https://doi.org/10.1175/BAMS-D-11-00218.1, 2013.
Matrosov, S. Y.: Theoretical study of radar polarization parameters obtained
from cirrus clouds, J. Atmos. Sci., 48, 1062–1070,
https://doi.org/10.1175/1520-0469(1991)048<1062:TSORPP>2.0.CO;2, 1991.
Matrosov, S. Y.: A dual-wavelength radar method to measure snowfall rate, J.
Appl. Meteorol., 37, 11, 1510–1521, https://doi.org/10.1175/1520-0450(1998)037<1510:ADWRMT>2.0.CO;2, 1998.
Matrosov, S. Y.: Polarimetric radar variables in snowfall at Ka- and W-band
frequency bands: A comparative analysis, J. Atmos. Oceanic Technol., 38,
91–101, https://doi.org/10.1175/JTECH-D-20-0138.1, 2021.
Matrosov, S. Y., Mace, G. G., Marchand, R., Shupe, M. D., Hallar, A. G. and
McCubbin, I. B.: Observations of ice crystal habits with a scanning
polarimetric W-band radar at slant linear depolarization ratio mode, J.
Atmos. Oceanic Technol., 29, 989–1008.
https://doi.org/10.1175/JTECH-D-11-00131.1, 2012.
Matrosov, S. Y., Schmitt, C. G., Maahn, M., and de Boer, G.: Atmospheric ice
particle shape estimates from polarimetric radar measurements and in situ
observations, J. Atmos. Oceanic Technol., 34, 2569–2587, https://doi.org/10.1175/JTECH-D-17-0111.1, 2017.
Matrosov, S. Y., Maahn, M., and de Boer, G.: Observational and modeling study
of ice hydrometeor radar dual-wavelength ratios, J. Appl. Meteorol. Clim.,
58, 2005–2017, https://doi.org/10.1175/JAMC-D-19-0018.1, 2019.
Matrosov, S. Y., Ryzhkov, A. V., Maahn, M., and de Boer, G.: Hydrometeor shape
variability in snowfall as retrieved from polarimetric radar measurements,
J. Appl. Meteorol. Clim., 59, 1503–1517,
https://doi.org/10.1175/JAMC-D-20-0052.1, 2020.
Mead, J. B., PopStefanija, I., Kollias, P., Albrecht, B., and Bluth, R.: Compact airborne solid-state 95 GHz FMCW
radar system, 31st Int. Conf. on Radar Meteorology, Seattle, WA, 6–12 August 2003, available at: https://ams.confex.com/ams/pdfpapers/63494.pdf (last access: 6 July 2021), 2003.
Mitchell, D. L.: Use of mass- and area-dimensional power laws for
determining precipitation particle terminal velocities, J. Atmos. Sci., 53,
1710–1723, https://doi.org/10.1175/1520-0469(1996)053<1710:UOMAAD>2.0.CO;2, 1996.
Mitchell, D. L. and Heymsfield, A. J.: Refinements in the treatment of ice
particle terminal velocities, highlighting aggregates, J. Atmos. Sci., 62,
1637–1644, https://doi.org/10.1175/JAS3413.1, 2005.
Moisseev, D. N., Lautaportti, S., Tyynela, J., and Lim, S.:
Dual-polarization radar signatures in snowstorms: Role of snowflake
aggregation, J. Geophys. Res.-Atmos., 120, 12644–12655,
https://doi.org/10.1002/2015JD023884, 2015.
Moisseev, D., von Lerber, A., and Tiira, J.: Quantifying the effect of
riming on snowfall using ground-based observations, J. Geophys. Res.-Atmos., 122, 4019–4037, 2017
Myagkov, A., Seifert, P., Wandinger, U., Bühl, J., and Engelmann, R.: Relationship between temperature and apparent shape of pristine ice crystals derived from polarimetric cloud radar observations during the ACCEPT campaign, Atmos. Meas. Tech., 9, 3739–3754, https://doi.org/10.5194/amt-9-3739-2016, 2016.
Orr, B. W. and Kropfli, R.: A method for estimating particle fall
velocities from vertically pointing Doppler radar, J. Atmos. Oceanic
Technol., 16, 29–37, https://doi.org/10.1175/1520-0426(1999)016<0029:AMFEPF>2.0.CO;2, 1999.
Oue, M.: Stony Brook Radar Observatory radar data for February 20, 2019 (2021), SoMAS Research Data, 11, available at: https://commons.library.stonybrook.edu/somasdata/11 (last access: 6 July 2021), Stony Brook University [data set], 2021
Oue, M., Kumjian, M. R., Lu, Y., Verlinde, J., Aydin, K., and Clothiaux, E.
E.: Linear depolarization ratios of columnar ice crystals in a deep
precipitating system over the Arctic observed by zenith-pointing Ka-band
Doppler radar, J. Appl. Meteorol. Clim., 54, 1060–1068, https://doi.org/10.1175/JAMC-D-15-0012.1, 2015.
Oue, M., Galletti, M., Verlinde, J., Ryzhkov, A., and Lu, Y.: Use of X-Band
differential reflectivity measurements to study shallow Arctic mixed-phase
clouds, J. Appl. Meteorol. Clim., 55, 403–424, https://doi.org/10.1175/JAMC-D-15-0168.1, 2016.
Oue, M., Kollias, P., Ryzhkov, A., and Luke, E.: Toward exploring the
synergy between cloud radar polarimetry and Doppler spectral analysis in
deep cold precipitating systems in the Arctic, J. Geophys. Res, 123,
2797–2815, https://doi.org/10.1002/2017JD027717, 2018.
Peters, G., Fischer, B., and Andersson, T.: Rain observations with a vertically
looking Micro Rain Radar (MRR), Boreal Environ. Res., 7, 353–362, 2002.
Protat, A. and Williams, C. R.: The accuracy of radar estimates of ice
terminal fall speed from vertically pointing Doppler radar measurements, J.
Appl. Meteorol. Clim., 50, 2120–2138, https://doi.org/10.1175/JAMC-D-10-05031.1, 2011.
Pruppacher, H. R. and Klett, J. D.: Microphysics of clouds and
precipitation, Springer, Dordrecht, 975 pp., https://doi.org/10.1007/978-0-306-48100-0, 2010.
Reinking, R. F., Matrosov, S. Y. Kropfli, R. A., and Bartram, B. W.: Evaluation
of a 45-degree slant quasi-linear radar polarization state for
distinguishing drizzle droplets, pristine ice crystals, and less regular ice
particles, J. Atmos. Oceanic Technol., 19, 296–321, https://doi.org/10.1175/1520-0426-19.3.296, 2002.
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.
Ryzhkov, A. V., Zrnić, D. S., and Gordon, B. A.: Polarimetric method for
ice water content determination, J. Appl. Meteorol., 37, 125–134, https://doi.org/10.1175/1520-0450(1998)037<0125:PMFIWC>2.0.CO;2, 1998.
Ryzhkov, A. V., Zhang, P., Reeves, H. D., Kumjian, M. R., Tschallener, T.,
Trömel, S., and Simmer, C.: Quasi-vertical profiles – A new way to look
at polarimetric radar data, J. Atmos. Ocean. Tech., 33, 551–562, https://doi.org/10.1175/JTECH-D-15-0020.1, 2016.
Schneebeli, M., Dawes, N., Lehning, M., and Berne, A.:
High-resolution vertical profiles of X-band polarimetric radar observables
during snowfall in the Swiss Alps, J. Appl. Meteorol. Clim., 52, 378–394, https://doi.org/10.1175/JAMC-D-12-015.1, 2013.
Schrom, R. S. and Kumjian, M. R.: Connecting microphysical processes in
Colorado Winter storms with vertical profiles of radar observations, J.
Appl. Meteorol. Clim., 55, 1771–1787, https://doi.org/10.1175/JAMC-D-15-0338.1, 2016.
Schrom, R. S., Kumjian, M. R., and Lu, Y.: Polarimetric radar signatures of
dendritic growth zones within Colorado winter storms, J. Appl. Meteorol.
Clim., 54, 2365–2388, https://doi.org/10.1175/JAMC-D-15-0004.1, 2015.
Sinclair, V. A., Moisseev, D., and von Lerber, A.: How dual-polarization
radar observations can be used to verify model representation of secondary
ice, J. Geophys. Res.-Atmos., 121, 10954–10970, https://doi.org/10.1002/2016JD025381,
2016.
Stokes, G. M. and Schwartz, S. E.: The Atmospheric Radiation Measurement
(ARM) Program: Programmatic Background and Design of the Cloud and Radiation
Test, B. Am. Meteorol. Soc., 75, 1201–1222,
https://doi.org/10.1175/1520-0477(1994)075<1201:TARMPP>2.0.CO;2, 1994.
Szyrmer, W. and Zawadzki, I.: Snow Studies. Part II: Average relationship
between mass of snowflakes and their terminal fall velocity, J. Atmos. Sci.,
67, 3319–3335, https://doi.org/10.1175/2010JAS3390.1, 2010.
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, 2013.
Tridon, F., Battaglia, A., Chase, R. J., Turk, F. J., Leinonen, J., Kneifel,
S., Mroz, K., Finlon, J., Bansemer, A., and Tanelli, S.: The microphysics of
stratiform precipitation during OLYMPEX: Compatibility between
triple-frequency radar and airborne in situ observations, J. Geophys. Res.-Atmos., 124, 8764–8792, 2019.
Tridon, F., Battaglia, A., and Kneifel, S.: Estimating total attenuation using Rayleigh targets at cloud top: applications in multilayer and mixed-phase clouds observed by ground-based multifrequency radars, Atmos. Meas. Tech., 13, 5065–5085, https://doi.org/10.5194/amt-13-5065-2020, 2020.
Troemel, S., Ryzhkov, A., Hickman, B., Muhlbauer, K., and Simmer, C.:
Polarimetric radar variables in the layers of melting and dendritic growth
at X band – implications for a nowcasting strategy in stratiform rain, J.
Appl. Meteorol. Clim., 58, 2497–2522, 2019.
Tyynelä, J., Leinonen, J., Moisseev, D., and Nousiainen, T.: Radar
backscattering from snowflakes: Comparison of fractal, aggregate and
soft-spheroid models, J. Atmos. Oceanic Technol., 28, 1365–1372,
https://doi.org/10.1175/JTECH-D-11-00004.1, 2011.
Vivekanandan, J., Bringi, V., Hagen, M., and Meischner, P.: Polarimetric
radar studies of atmospheric ice particles, IEEE T. Geosci. Remote, 32, 1–10, https://doi.org/10.1109/36.285183, 1994.
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.
Williams, E., Smalley, D., Donovan, M., Hallowell, R., Hood, K., Bennett,
B., Evaristo, R., Stepanek, A., Bals-Elsholz, T., Cobb, J., Ritzman, J.,
Korolev, A., and Wolde, M.: Measurements of differential reflectivity in
snowstorms and warm season stratiform systems, J. Appl. Meteorol. Clim., 54,
573–595, https://doi.org/10.1175/JAMC-D-14-0020.1, 2015.
Zawadzki, I., Fabry, F., and Szyrmer, W.: Observations of supercooled water
and secondary ice generation by a vertically pointing X-band Doppler radar,
Atmos. Res., 59–60, 343–359, https://doi.org/10.1016/S0169-8095(01)00124-7, 2001.
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, 2019.
Short summary
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.
Multi-wavelength radar measurements provide capabilities to identify ice particle types and...