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
Related authors
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
Short summary
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.
Zane Dedekind, Alexei Korolev, and Jason Aaron Milbrandt
EGUsphere, https://doi.org/10.5194/egusphere-2025-3007, https://doi.org/10.5194/egusphere-2025-3007, 2025
Short summary
Short summary
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.
Zhipeng Qu, Alexei Korolev, Jason A. Milbrandt, Ivan Heckman, Mélissa Cholette, Cuong Nguyen, and Mengistu Wolde
EGUsphere, https://doi.org/10.5194/egusphere-2025-649, https://doi.org/10.5194/egusphere-2025-649, 2025
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Konstantin Baibakov, Samuel LeBlanc, Keyvan Ranjbar, Norman T. O'Neill, Mengistu Wolde, Jens Redemann, Kristina Pistone, Shao-Meng Li, John Liggio, Katherine Hayden, Tak W. Chan, Michael J. Wheeler, Leonid Nichman, Connor Flynn, and Roy Johnson
Atmos. Chem. Phys., 21, 10671–10687, https://doi.org/10.5194/acp-21-10671-2021, https://doi.org/10.5194/acp-21-10671-2021, 2021
Short summary
Short summary
We find that the airborne measurements of the vertical extinction due to aerosols (aerosol optical depth, AOD) obtained in the Athabasca Oil Sands Region (AOSR) can significantly exceed ground-based values. This can have an effect on estimating the AOSR radiative impact and is relevant to satellite validation based on ground-based measurements. We also show that the AOD can marginally increase as the plumes are being transported away from the source and the new particles are being formed.
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, https://doi.org/10.5194/amt-14-4893-2021, 2021
Short summary
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.
Katherine Hayden, Shao-Meng Li, Paul Makar, John Liggio, Samar G. Moussa, Ayodeji Akingunola, Robert McLaren, Ralf M. Staebler, Andrea Darlington, Jason O'Brien, Junhua Zhang, Mengistu Wolde, and Leiming Zhang
Atmos. Chem. Phys., 21, 8377–8392, https://doi.org/10.5194/acp-21-8377-2021, https://doi.org/10.5194/acp-21-8377-2021, 2021
Short summary
Short summary
We developed a method using aircraft measurements to determine lifetimes with respect to dry deposition for oxidized sulfur and nitrogen compounds over the boreal forest in Alberta, Canada. Atmospheric lifetimes were significantly shorter than derived from chemical transport models with differences related to modelled dry deposition velocities. The shorter lifetimes suggest models need to reassess dry deposition treatment and predictions of sulfur and nitrogen in the atmosphere and ecosystems.
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
Short summary
Short summary
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.
Alexei Korolev and Thomas Leisner
Atmos. Chem. Phys., 20, 11767–11797, https://doi.org/10.5194/acp-20-11767-2020, https://doi.org/10.5194/acp-20-11767-2020, 2020
Short summary
Short summary
Secondary ice production (SIP) plays a key role in the formation of ice particles in tropospheric clouds. This work presents a critical review of the laboratory studies related to secondary ice production. It aims to identify gaps in our knowledge of SIP as well as to stimulate further laboratory studies focused on obtaining a quantitative description of efficiencies for each SIP mechanism.
Cited articles
Bernstein, B., DiVito, S., Riley, J. T., Landolt, S., Haggerty, J., Thompson, G., Adriaansen, D., Serke, D., Kessinger, C., Tessendorf, S., Wolde, M., Korolev, A., Brown, A., Nichman, L., Sims,D., and Dumont, C.:
The In-Cloud Icing and Large-Drop Experiment (ICICLE) Science and Operations Plans, Federal Aviation Administration, William J. Hughes Technical Center, Aviation Research Division, DOT/FAA/TC-21/29, Atlantic City International Airport, NJ, Federal Aviation Administration, https://www.tc.faa.gov/its/worldpac/techrpt/tc21-29.pdf (last access: 7 May 2022), 2021.
Bohren, C. F. and Huffman, D. R.:
Absorption and Scattering of Light by Small Particles, John Wiley and Sons, New York, ISBN 10 047105772X, 530 pp., 1983.
Davison, C., Ratvasky, T., and Lilie, L.:
Naturally aspirating isokinetic total water content probe: Wind tunnel test results and design modifications, in: SAE 2011 International Conference on Aircraft and Engine Icing and Ground Deicing, Chicago, Illinois, 13–17 June 2011, https://doi.org/10.4271/2011-38-0036, 2011.
Field, P. R., Heymsfield, A. J., and Bansemer, A.:
Shattering and Particle Inter-arrival Times Measured by Optical Array Probes in Ice Clouds, J. Atmos. Ocean. Tech., 23, 1357–1370, 2006.
Heymsfield, A. J. and Parrish, J. L.:
Techniques employed in the processing of particle size spectra and state parameter data obtained with the T-28 aircraft platform (No. NCAR/TN-137+IA), University Corporation for Atmospheric Research, https://doi.org/10.5065/D6639MPN, 1979.
Heymsfield, A. J., Matrosov S. Y., and Wood, N.:
Toward improving ice water content and snow-rate retrievals from radars. Part I: X and W bands, emphasizing CloudSat, J. Appl. Meteorol. Clim., 55, 2063–2090, https://doi.org/10.1175/JAMC-D-15-0290.1, 2016.
Hogan, R. J., Illingworth, A. J., and Sauvageot, H.:
Measuring crystal size in cirrus using 35- and 94-GHz radars, J. Atmos. Ocean. Tech., 17, 27–37, 2000.
Kneifel, S., Kulie, M. S., and Bennartz, R: A triple-frequency approach to retrieve microphysical snowfall parameters, J. Geophys. Res., 116, D11203, https://doi.org/10.1029/2010JD015430, 2011.
Knollenberg, R. G.:
Techniques for probing cloud microstructure, in: Clouds their Formation, Optical Properties, and Effects, edited by: Hobbs, P. V and Deepak, A., Elsevier, Amsterdam, ISBN 978-0-12-350720-4, 15–91, 1981.
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, 2014.
Korolev, A. and Field, P. R.:
Assessment of the performance of the inter-arrival time algorithm to identify ice shattering artifacts in cloud particle probe measurements, Atmos. Meas. Tech., 8, 761–777, https://doi.org/10.5194/amt-8-761-2015, 2015.
Korolev, A. and Heckman, I.:
NRC Convair 580 Composite Liquid and Ice Size Distribution Data. Version 1.0, UCAR/NCAR – Earth Observing Laboratory [data set], https://doi.org/10.26023/7BZP-NGPY-WG0B, 2020a.
Korolev, A. and Heckman, I.:
NRC Convair 580 Bulk Parameters. Version 0.4, UCAR/NCAR – Earth Observing Laboratory [data set], https://doi.org/10.26023/R6A2-G92Q-CF0S, 2020b.
Korolev, A. and Heckman, I.: NRC Convair 580 2DS Particle Images. Version 1.0, UCAR/NCAR – Earth Observing Laboratory [data set], https://doi.org/10.26023/DREN-VTHA-0N0E, 2020c.
Korolev, A. and Sussman, B.:
A technique for habit classification of cloud particles, J. Atmos. Ocean. Tech., 17, 1047–1059, 2000.
Korolev, A., Shashkov, A., and Barker, H.:
Calibrations and performance of the airborne Cloud Extinction Probe. J. Atmos. Ocean. Tech., 31, 326–345, 2014.
Lance, S., Brock, C. A., Rogers, D., and Gordon, J. A.:
Water droplet calibration of the Cloud Droplet Probe (CDP) and in-flight performance in liquid, ice and mixed-phase clouds during ARCPAC, Atmos. Meas. Tech., 3, 1683–1706, https://doi.org/10.5194/amt-3-1683-2010, 2010.
Lawson, R. P., Baker, B. A., Schmitt, C. G., and Jensen, T. L.:
An overview of microphysical properties of Arctic clouds observed in May and July 1998 during FIRE ACE, J. Geophys. Res.-Atmos., 106, 14989–15014, https://doi.org/10.1029/2000JD900789, 2001.
Lawson, R. P., O'Connor, D. C., Zmarzly, P., Weaver, K., Baker, B., Mo, Q., and Jonsson, H.: The 2D-S (Stereo) Probe: Design and preliminary tests of a new airborne, high speed, high-resolution particle imaging probe, J. Atmos. Ocean. Tech., 23, 1462–1477, https://doi.org/10.1175/JTECH1927.1, 2006.
Lawson, R. P., Gurganus, C., Woods, S., and Bruintjes, R.:
Aircraft observations of cumulus microphysics ranging from the tropics to midlatitudes: Implications for a “new” secondary ice process, J. Atmos. Sci., 74, 2899–2920, https://doi.org/10.1175/JAS-D-17-0033.1, 2017.
Leinonen, J., Lebsock, M. D., Tanelli, S., Sy, O. O., Dolan, B., Chase, R. J., Finlon, J. A., von Lerber, A., and Moisseev, D.:
Retrieval of snowflake microphysical properties from multifrequency radar observations, Atmos. Meas. Tech., 11, 5471–5488, https://doi.org/10.5194/amt-11-5471-2018, 2018.
Liao, L., R. Meneghini, T. Iguchi, and A. Detwiler: Use of dual-wavelength radar for snow parameter estimates, J. Atmos. Ocean. Tech., 22, 1494–1506, https://doi.org/10.1175/JTECH1808.1, 2005.
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.
Matrosov, S. Y.:
Possibilities of cirrus particle sizing from dual-frequency radar measurements, J. Geophys. Res., 98, 20675–20683, https://doi.org/10.1029/93JD02335, 1993.
Matrosov, S. Y.:
Variability of microphysical parameters in high altitude ice clouds: Results of the remote sensing method, J. Appl. Meteorol., 36, 617–626, https://doi.org/10.1175/1520-0450-36.6.633, 1997.
Matrosov, S. Y.:
Potential for attenuation-based estimations of rainfall rate from CloudSat, Geophys. Res. Lett., 34, L05817, https://doi.org/10.1029/2006GL029161, 2007.
Matrosov, S. Y.:
CloudSat studies of stratiform precipitation systems observed in the vicinity of the Southern Great Plains atmospheric radiation measurement site, J. Appl. Meteorol. Clim., 49, 1756–1765, https://doi.org/10.1175/2010JAMC2444.1, 2010.
Matrosov, S. Y. and Heymsfield, A. J.:
Empirical relations between size parameters of ice hydrometeor populations and radar reflectivity, J. Appl. Meteorol. Clim., 56, 2479–2488, https://doi.org/10.1175/JAMC-D-17-0076.1, 2017.
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. Ocean. Tech., 29, 989–1008, https://doi.org/10.1175/JTECH-D-11-00131.1, 2012.
Matrosov, S. Y., Kennedy, P. C., and Cifelli, R.:
Experimentally based estimates of relations between X-band radar signal attenuation characteristics and differential phase in rain, J. Atmos. Ocean. Tech., 31, 2442–2450, https://doi.org/10.1175/JTECH-D-13-00231.1, 2014.
Matrosov, S. Y., Maahn, M., and de Boer, G.:
Observational and modelling study of ice hydrometeor radar dual-wavelength ratios. J. Appl. Meteorol. Clim., 58, 2015–2017, https://doi.org/10.1175/JAMC-D-19-0018.1, 2019.
Mazin, I. P., Korolev, A. V., Heymsfield, A., Isaac, G., and Cober, S. G.:
Thermodynamics of icing cylinder for measurements of liquid water content in supercooled clouds. J. Atmos. Ocean. Tech., 18, 543–558, 2001.
McFarquhar, G. M. and Heymsfield, A. J.:
The definition and significance of an effective radius for ice clouds, J. Atmos. Sci., 55, 2039–2052, 1998.
Mitchell, D. L.:
The use of mass- and area-dimensional power laws for determining precipitating particle terminal velocities, J. Atmos. Sci., 53, 1710–1723, 1996.
Mitchell, D. L., Lawson, R. P., and Baker, B.:
Understanding effective diameter and its application to terrestrial radiation in ice clouds, Atmos. Chem. Phys., 11, 3417–3429, https://doi.org/10.5194/acp-11-3417-2011, 2011.
Mroz, K., Battaglia, A., Nguyen, C., Heymsfield, A., Protat, A., and Wolde, M.:
Triple-frequency radar retrieval of microphysical properties of snow, Atmos. Meas. Tech., 14, 7243–7254, https://doi.org/10.5194/amt-14-7243-2021, 2021.
Nguyen, C. and Wolde, M.:
NRC Convair 580 Airborne X-Band Radar Data and Imagery. Version 1.0, UCAR/NCAR – Earth Observing Laboratory [data set], https://doi.org/10.26023/KAGA-JH3J-0Y06, 2020a.
Nguyen, C. and Wolde, M.:
NRC Convair 580 Airborne W-Band (NAW) Radar Data and Imagery. Version 1.0, UCAR/NCAR – Earth Observing Laboratory [data set], https://doi.org/10.26023/PBVG-0S4X-3D05, 2020b.
Nguyen, C. M., Wolde, M., Battaglia, A., Nichman, L., Bliankinshtein, N., Haimov, S., Bala, K., and Schuettemeyer, D.:
Coincident in situ and triple-frequency radar airborne observations in the Arctic, Atmos. Meas. Tech., 15, 775–795, https://doi.org/10.5194/amt-15-775-2022, 2022.
Ryzhkov, A. Bukovcic, P., Murphy, A., Zhang, P., and McFarquhar, G.:
Ice microphysical retrievals using polarimetric radar data, 10th European conference on radar in meteorology and hydrology, 1–6 July, Wageningen, Netherlands, pp. 494–504, https://edepot.wur.nl/454537 (last access: 25 May 2022), 2018.
Sassen, K., Matrosov, S., and Campbell, J.:
CloudSat spaceborne 94 GHz radar bright band in the melting layer: An attenuation-driven upside-down lidar analog, Geophys. Res. Lett., 34, L16818, https://doi.org/10.1029/2007GL030291, 2007.
Schumann, U., Mayer, B., Gierens, K., Unterstrasser, S., Jessberger, P., Petzold, A., Voight, C., and Gayet, J. F.:
Effective radius of ice particles in cirrus and contrails, J. Atmos. Sci., 68, 300–321, https://doi.org/10.1175/2010JAS3562.1, 2011.
Shupe, M. D., Matrosov, S. Y., and Uttal, T.:
Arctic mixed-phase cloud properties derived from surface-based sensors at SHEBA, J. Atmos. Sci., 63, 697–711, https://doi.org/10.1175/JAS3659.1, 2006.
Tan, I. and Storelvmo, T.:
Evidence of strong contributions from mixed-phase clouds to arctic climate change, Geophys. Res. Lett., 46, 2894–2902, https://doi.org/10.1029/2018GL081871, 2019.
Tridon, F., Battaglia, A., Chase, R. J., Turk, F. J., Leinonen, J., Kneifel, S., Mroz, K., Finlon, J., Bansemer, A., Tanelli, S., Heymsfield, A. J., and Nesbitt, S. W.: The microphysics of stratiform precipitation during OLYMPEX: Compatibility between triple-frequency radar and airborne in situ observations, J. Geophys. Res., 124, 8764–8792, https://doi.org/10.1029/2018JD029858, 2019.
Tyynelä, J. and Chandrasekar, V.:
Characterizing falling snow using multifrequency dual-polarization measurements, J. Geophys. Res.-Atmos., 119, 8268–8283, https://doi.org/10.1002/2013JD021369, 2014.
Wolde, M. and Pazmany, A.:
NRC dual-frequency airborne radar for atmospheric research, Proceedings of the 32 AMS conference on radar meteorology, P1R.9, Albuquerque, NM, 2005.
Wolde, M., Nguyen, C., Bastian, M., Korolev, A., and Heckman, I.:
Characterization of the pilot X-band radar responses to the HIWC environment during the Cayenne HAIC-HIWC 2015 Campaign, American Institute of Aeronautics and Astronautics, https://doi.org/10.2514/6.2016-4201, 2016.
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...