Articles | Volume 15, issue 21
https://doi.org/10.5194/amt-15-6373-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-6373-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sizing ice hydrometeor populations using the dual-wavelength radar ratio
Sergey Y. Matrosov
CORRESPONDING AUTHOR
Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA
National Atmospheric and Oceanic Administration, Physical Sciences Laboratory, Boulder, CO 80305, USA
Alexei Korolev
Environment and Climate Change Canada, Toronto, ON, M3H5T4, Canada
Mengistu Wolde
Flight Research Laboratory, National Research Council Canada, Ottawa, K1A0R6, Canada
Cuong Nguyen
Flight Research Laboratory, National Research Council Canada, Ottawa, K1A0R6, Canada
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Mélissa Cholette, Caroline Jouan, Hugh Morrison, Jason A. Milbrandt, Zhipeng Qu, Zane Dedekind, Alexei Korolev, and Zen Mariani
EGUsphere, https://doi.org/10.5194/egusphere-2026-4229, https://doi.org/10.5194/egusphere-2026-4229, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study implements prognostic aerosols in the P3 bulk microphysics scheme. Using aerosol awareness, the convection-permitting simulations of layered Arctic mixed-phase clouds are improved with more persistent supercooled liquid water and better agreement with EarthCARE and in situ observations. The new framework enhances the microphysics realism of aerosol–cloud interactions, which are critical for radiative balance and weather prediction in polar regions and elsewhere.
Patrick C. Taylor, Armin Sorooshian, Rei Ueyama, Sebastian Schmidt, Ihab Abboud, Quincy Allison, Kevin Barry, Sebastian Becker, Holly A. Bender, Joseph R. Bennett, James B. Blair, Niklas Bohn, Linette Boisvert, Matthew D. Brown, Roelof Bruintjes, Anthony Bucholtz, Megan Buzanowicz, Brian Cairns, Filippo Calì Quaglia, Eduard Chemyakin, Bo Chen, Gao Chen, Hong Chen, Yu-Wen Chen, Zezhen Cheng, Swarup China, Dan Chirica, Yonghoon Choi, Peter Colarco, Brian Collister, Ewan Crosbie, Maurice J. Cross, Janet Daniels, Paul DeMott, Joshua P. DiGangi, Alcide Giorgio di Sarra, Glenn S. Diskin, Erica K. Dolinar, Eva-Lou Edwards, Samuel Ephraim, Nikolaos Evangeliou, Romanos Foskinis, Francesca Gallo, Lan Gao, José Luis Gómez-Amo, Daisy Gonzalez, Christine Groot Zwaaftink, Pawan Gupta, Ivan Heckman, Michael Hendrickson, Miguel Ricardo A. Hilario, Ken Hirata, Michelle Hofton, Andrew L. Holen, Ulas Im, Alia L. Khan, Ralph Kahn, Alexei V. Korolev, Sonia Kreidenweis, Thomas Krumpen, Nathan Kurtz, Leslie Lait, Bradley Lamkin, Jack Landy, Nurun Nahar Lata, Paul Lawson, Samuel LeBlanc, Sean Leavor, Jing Li, Thorsten Markus, Hal Maring, Andreas H. Massling, Camille Mavis, Flynn McGinnity, Kerry Meyer, Gabriel Mojica, Richard H. Moore, Parker Morris, Giovanni Muscari, Vikas Nataraja, Amin R. Nehrir, Athanasios Nenes, Edward P. Nowottnick, Matteo Ottaviani, Chelsea Parker, Ryan Patnaude, Michael Perez, Russell J. Perkins, Colten Peterson, Alek Petty, Stevie Phothisane, Chris Polashenski, Kerri A. Pratt, Kayla M. Preisler, John Prytherch, David Rabine, Jens Redemann, Ju-Mee Ryoo, Joseph S. Schlosser, Vanessa Selimovic, Michael A. Shook, Morgan Silverman, Henrik Skov, Alexander Smirnov, Cassidy Soloff, Amy Solomon, Snorre Stamnes, Azusa Takeishi, David R. Thompson, K. Lee Thornhill, Rachel Tilling, Michael Tjernström, Monica Tosco, Pedro C. Valdelomar, David Van Gilst, Jian Wang, Zhien Wang, Andrzej Wasilewski, Manfred Wendisch, Brent Wilder, Edward L. Winstead, Albert Wu, Peng Xian, Lauren M. Zamora, Jiaoshi Zhang, Lei Zhang, Lu Zhang, Luke Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-241, https://doi.org/10.5194/essd-2026-241, 2026
Preprint under review for ESSD
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This article summarizes the data sets collected during the Arctic Radiation Cloud aerosol Sea ice Interaction eXperiment (ARCSIX), NASA's most comprehensive Arctic field campaign to date. The overarching goal was to quantify the contributions of surface, clouds, aerosol particles, and precipitation to summer sea ice melt. This paper describes the ARCSIX implementation including the flight strategy, instruments, complementary data sets, access, and usage details.
Zane Dedekind, Alexei Korolev, and Jason A. Milbrandt
Atmos. Chem. Phys., 26, 4489–4508, https://doi.org/10.5194/acp-26-4489-2026, https://doi.org/10.5194/acp-26-4489-2026, 2026
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We studied how airplane contrails form and persist under cold, moist conditions. Using computer simulations and real observations, we found that weather predicting models often underestimate moisture levels, limiting accurate trail prediction. Adjusting how ice grows in clouds allowed us to better simulate these contrails. Improving moisture representation in models can help predict the climate effects of these clouds.
Alexei V. Korolev and R. Paul Lawson
Atmos. Chem. Phys., 26, 2331–2352, https://doi.org/10.5194/acp-26-2331-2026, https://doi.org/10.5194/acp-26-2331-2026, 2026
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The International Panel on Climate Change has concluded that aerosols and clouds are significant contributors to the rate of warming in the Arctic, which is now shown to be more than twice that of the global average. Climate model predictions suggest that the Arctic Ocean will become ice-free sometime between 2030 and 2050. The research presented here increases our knowledge of how aerosols, clouds and surface properties contribute to warming and the melting of sea ice in the Arctic.
Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Mélissa Cholette, Cuong Nguyen, and Mengistu Wolde
Atmos. Chem. Phys., 25, 17845–17868, https://doi.org/10.5194/acp-25-17845-2025, https://doi.org/10.5194/acp-25-17845-2025, 2025
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This study examines the impact of incorporating secondary ice production (SIP) parameterizations into high-resolution numerical weather prediction simulations for mid-latitude continental winter conditions. Aircraft in situ and remote sensing observations are used to evaluate the simulations. Results show that including SIP improves the representation of cloud and freezing rain properties, with its impact varying based on cloud regime, such as convective or stratiform.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 18, 471–485, https://doi.org/10.5194/amt-18-471-2025, https://doi.org/10.5194/amt-18-471-2025, 2025
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This study evaluates and compares a new microwave hyperspectrometer with an infrared hyperspectrometer for clear-sky temperature and water vapor retrievals. The analysis reveals that the information content of the infrared hyperspectrometer exceeds that of the microwave hyperspectrometer and provides higher vertical resolution in ground-based zenith measurements. Leveraging the ground–airborne synergy between the two instruments yielded optimal sounding results.
Alexei Korolev, Zhipeng Qu, Jason Milbrandt, Ivan Heckman, Mélissa Cholette, Mengistu Wolde, Cuong Nguyen, Greg M. McFarquhar, Paul Lawson, and Ann M. Fridlind
Atmos. Chem. Phys., 24, 11849–11881, https://doi.org/10.5194/acp-24-11849-2024, https://doi.org/10.5194/acp-24-11849-2024, 2024
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The phenomenon of high ice water content (HIWC) occurs in mesoscale convective systems (MCSs) when a large number of small ice particles with typical sizes of a few hundred micrometers is found at high altitudes. It was found that secondary ice production in the vicinity of the melting layer plays a key role in the formation and maintenance of HIWC. This study presents a conceptual model of the formation of HIWC in tropical MCSs based on in situ observations and numerical simulation.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 17, 2219–2233, https://doi.org/10.5194/amt-17-2219-2024, https://doi.org/10.5194/amt-17-2219-2024, 2024
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We conducted a radiance closure experiment using a unique combination of two hyperspectral radiometers, one operating in the microwave and the other in the infrared. By comparing the measurements of the two hyperspectrometers to synthetic radiance simulated from collocated atmospheric profiles, we affirmed the proper performance of the two instruments and quantified their radiometric uncertainty for atmospheric sounding applications.
Alexei Korolev, Paul J. DeMott, Ivan Heckman, Mengistu Wolde, Earle Williams, David J. Smalley, and Michael F. Donovan
Atmos. Chem. Phys., 22, 13103–13113, https://doi.org/10.5194/acp-22-13103-2022, https://doi.org/10.5194/acp-22-13103-2022, 2022
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The present study provides the first explicit in situ observation of secondary ice production at temperatures as low as −27 °C, which is well outside the range of the Hallett–Mossop process (−3 to −8 °C). This observation expands our knowledge of the temperature range of initiation of secondary ice in clouds. The obtained results are intended to stimulate laboratory and theoretical studies to develop physically based parameterizations for weather prediction and climate models.
Katherine L. Hayden, Shao-Meng Li, John Liggio, Michael J. Wheeler, Jeremy J. B. Wentzell, Amy Leithead, Peter Brickell, Richard L. Mittermeier, Zachary Oldham, Cristian M. Mihele, Ralf M. Staebler, Samar G. Moussa, Andrea Darlington, Mengistu Wolde, Daniel Thompson, Jack Chen, Debora Griffin, Ellen Eckert, Jenna C. Ditto, Megan He, and Drew R. Gentner
Atmos. Chem. Phys., 22, 12493–12523, https://doi.org/10.5194/acp-22-12493-2022, https://doi.org/10.5194/acp-22-12493-2022, 2022
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In this study, airborne measurements provided the most detailed characterization, to date, of boreal forest wildfire emissions. Measurements showed a large diversity of air pollutants expanding the volatility range typically reported. A large portion of organic species was unidentified, likely comprised of complex organic compounds. Aircraft-derived emissions improve wildfire chemical speciation and can support reliable model predictions of pollution from boreal forest wildfires.
Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Yongjie Huang, Greg M. McFarquhar, Hugh Morrison, Mengistu Wolde, and Cuong Nguyen
Atmos. Chem. Phys., 22, 12287–12310, https://doi.org/10.5194/acp-22-12287-2022, https://doi.org/10.5194/acp-22-12287-2022, 2022
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Secondary ice production (SIP) is an important physical phenomenon that results in an increase in the cloud ice particle concentration and can have a significant impact on the evolution of clouds. Here, idealized simulations of a tropical convective system were conducted. Agreement between the simulations and observations highlights the impacts of SIP on the maintenance of tropical convection in nature and the importance of including the modelling of SIP in numerical weather prediction models.
Yongjie Huang, Wei Wu, Greg M. McFarquhar, Ming Xue, Hugh Morrison, Jason Milbrandt, Alexei V. Korolev, Yachao Hu, Zhipeng Qu, Mengistu Wolde, Cuong Nguyen, Alfons Schwarzenboeck, and Ivan Heckman
Atmos. Chem. Phys., 22, 2365–2384, https://doi.org/10.5194/acp-22-2365-2022, https://doi.org/10.5194/acp-22-2365-2022, 2022
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Numerous small ice crystals in tropical convective storms are difficult to detect and could be potentially hazardous for commercial aircraft. Previous numerical simulations failed to reproduce this phenomenon and hypothesized that key microphysical processes are still lacking in current models to realistically simulate the phenomenon. This study uses numerical experiments to confirm the dominant role of secondary ice production in the formation of these large numbers of small ice crystals.
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.
Haoran Li, Alexei Korolev, and Dmitri Moisseev
Atmos. Chem. Phys., 21, 13593–13608, https://doi.org/10.5194/acp-21-13593-2021, https://doi.org/10.5194/acp-21-13593-2021, 2021
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Kelvin–Helmholtz (K–H) clouds embedded in a stratiform precipitation event were uncovered via radar Doppler spectral analysis. Given the unprecedented detail of the observations, we show that multiple populations of secondary ice columns were generated in the pockets where larger cloud droplets are formed and not at some constant level within the cloud. Our results highlight that the K–H instability is favorable for liquid droplet growth and secondary ice formation.
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Short summary
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.
A remote sensing method to retrieve sizes of particles in ice clouds and precipitation from...