Articles | Volume 21, issue 17
https://doi.org/10.5194/acp-21-13593-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-21-13593-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Sep 2021
Research article |
| 13 Sep 2021
| 13 Sep 2021
Supercooled liquid water and secondary ice production in Kelvin–Helmholtz instability as revealed by radar Doppler spectra observations
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, Finland
Alexei Korolev
Environment and Climate Change Canada, Toronto, Canada
Dmitri Moisseev
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, Finland
Finnish Meteorological Institute, Helsinki, Finland
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Chuanhong Zhao, Yijun Zhang, Dong Zheng, Haoran Li, Sai Du, Xueyan Peng, Xiantong Liu, Pengguo Zhao, Jiafeng Zheng, and Juan Shi
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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.
Haoran Li, Dmitri Moisseev, Yali Luo, Liping Liu, Zheng Ruan, Liman Cui, and Xinghua Bao
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Short summary
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Jenna Ritvanen, Ewan O'Connor, Dmitri Moisseev, Raisa Lehtinen, Jani Tyynelä, and Ludovic Thobois
Atmos. Meas. Tech., 15, 6507–6519, https://doi.org/10.5194/amt-15-6507-2022, https://doi.org/10.5194/amt-15-6507-2022, 2022
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Doppler lidars and weather radars provide accurate wind measurements, with Doppler lidar usually performing better in dry weather conditions and weather radar performing better when there is precipitation. Operating both instruments together should therefore improve the overall performance. We investigate how well a co-located Doppler lidar and X-band radar perform with respect to various weather conditions, including changes in horizontal visibility, cloud altitude, and precipitation.
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.
Han Ding, Haoran Li, and Liping Liu
Atmos. Meas. Tech., 15, 6181–6200, https://doi.org/10.5194/amt-15-6181-2022, https://doi.org/10.5194/amt-15-6181-2022, 2022
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In this study, a framework for processing the Doppler spectra observations of a multi-mode pulse compression Ka–Ku cloud radar system is presented. We first proposed an approach to identify and remove the clutter signals in the Doppler spectrum. Then, we developed a new algorithm to remove the range sidelobe at the modes implementing the pulse compression technique. The radar observations from different modes were then merged using the shift-then-average method.
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.
Silvia M. Calderón, Juha Tonttila, Angela Buchholz, Jorma Joutsensaari, Mika Komppula, Ari Leskinen, Liqing Hao, Dmitri Moisseev, Iida Pullinen, Petri Tiitta, Jian Xu, Annele Virtanen, Harri Kokkola, and Sami Romakkaniemi
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The spatial and temporal restrictions of observations and oversimplified aerosol representation in large eddy simulations (LES) limit our understanding of aerosol–stratocumulus interactions. In this closure study of in situ and remote sensing observations and outputs from UCLALES–SALSA, we have assessed the role of convective overturning and aerosol effects in two cloud events observed at the Puijo SMEAR IV station, Finland, a diurnal-high aerosol case and a nocturnal-low aerosol case.
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.
Victoria Anne Sinclair, Jenna Ritvanen, Gabin Urbancic, Irene Erner, Yurii Batrak, Dmitri Moisseev, and Mona Kurppa
Atmos. Meas. Tech., 15, 3075–3103, https://doi.org/10.5194/amt-15-3075-2022, https://doi.org/10.5194/amt-15-3075-2022, 2022
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We investigate the boundary-layer (BL) height and surface stability in southern Finland using radiosondes, a microwave radiometer and ERA5 reanalysis. Accurately quantifying the BL height is challenging, and the diagnosed BL height can depend strongly on the method used. Microwave radiometers provide reliable estimates of the BL height but only in unstable conditions. ERA5 captures the BL height well except under very stable conditions, which occur most commonly at night during the warm season.
Zoé Brasseur, Dimitri Castarède, Erik S. Thomson, Michael P. Adams, Saskia Drossaart van Dusseldorp, Paavo Heikkilä, Kimmo Korhonen, Janne Lampilahti, Mikhail Paramonov, Julia Schneider, Franziska Vogel, Yusheng Wu, Jonathan P. D. Abbatt, Nina S. Atanasova, Dennis H. Bamford, Barbara Bertozzi, Matthew Boyer, David Brus, Martin I. Daily, Romy Fösig, Ellen Gute, Alexander D. Harrison, Paula Hietala, Kristina Höhler, Zamin A. Kanji, Jorma Keskinen, Larissa Lacher, Markus Lampimäki, Janne Levula, Antti Manninen, Jens Nadolny, Maija Peltola, Grace C. E. Porter, Pyry Poutanen, Ulrike Proske, Tobias Schorr, Nsikanabasi Silas Umo, János Stenszky, Annele Virtanen, Dmitri Moisseev, Markku Kulmala, Benjamin J. Murray, Tuukka Petäjä, Ottmar Möhler, and Jonathan Duplissy
Atmos. Chem. Phys., 22, 5117–5145, https://doi.org/10.5194/acp-22-5117-2022, https://doi.org/10.5194/acp-22-5117-2022, 2022
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The present measurement report introduces the ice nucleation campaign organized in Hyytiälä, Finland, in 2018 (HyICE-2018). We provide an overview of the campaign settings, and we describe the measurement infrastructure and operating procedures used. In addition, we use results from ice nucleation instrument inter-comparison to show that the suite of these instruments deployed during the campaign reports consistent results.
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.
Teresa Vogl, Maximilian Maahn, Stefan Kneifel, Willi Schimmel, Dmitri Moisseev, and Heike Kalesse-Los
Atmos. Meas. Tech., 15, 365–381, https://doi.org/10.5194/amt-15-365-2022, https://doi.org/10.5194/amt-15-365-2022, 2022
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We are using machine learning techniques, a type of artificial intelligence, to detect graupel formation in clouds. The measurements used as input to the machine learning framework were performed by cloud radars. Cloud radars are instruments located at the ground, emitting radiation with wavelenghts of a few millimeters vertically into the cloud and measuring the back-scattered signal. Our novel technique can be applied to different radar systems and different weather conditions.
Anna Franck, Dmitri Moisseev, Ville Vakkari, Matti Leskinen, Janne Lampilahti, Veli-Matti Kerminen, and Ewan O'Connor
Atmos. Meas. Tech., 14, 7341–7353, https://doi.org/10.5194/amt-14-7341-2021, https://doi.org/10.5194/amt-14-7341-2021, 2021
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We proposed a method to derive a convective boundary layer height, using insects in radar observations, and we investigated the consistency of these retrievals among different radar frequencies (5, 35 and 94 GHz). This method can be applied to radars at other measurement stations and serve as additional way to estimate the boundary layer height during summer. The entrainment zone was also observed by the 5 GHz radar above the boundary layer in the form of a Bragg scatter layer.
Haoran Li, Ottmar Möhler, Tuukka Petäjä, and Dmitri Moisseev
Atmos. Chem. Phys., 21, 14671–14686, https://doi.org/10.5194/acp-21-14671-2021, https://doi.org/10.5194/acp-21-14671-2021, 2021
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In natural clouds, ice-nucleating particles are expected to be rare above –10 °C. In the current paper, we found that the formation of ice columns is frequent in stratiform clouds and is associated with increased precipitation intensity and liquid water path. In single-layer shallow clouds, the production of ice columns was attributed to secondary ice production, despite the rime-splintering process not being expected to take place in such clouds.
Cited articles
Baker, M.: Cloud microphysics and climate, Science, 276, 1072–1078, 1997. a
Baker, M. B. and Peter, T.: Small-scale cloud processes and climate, Nature,
451, 299–300, 2008. a
Chin, H.-N. S., Rodriguez, D. J., Cederwall, R. T., Chuang, C. C., Grossman,
A. S., Yio, J. J., Fu, Q., and Miller, M. A.: A microphysical retrieval
scheme for continental low-level stratiform clouds: Impacts of the
subadiabatic character on microphysical properties and radiation budgets,
Mon. Weather Rev., 128, 2511–2527, 2000. a
Conrick, R., Mass, C. F., and Zhong, Q.: Simulated Kelvin–Helmholtz waves over
terrain and their microphysical implications, J. Atmos.
Sci., 75, 2787–2800, 2018. a
Falconi, M. T., von Lerber, A., Ori, D., Marzano, F. S., and Moisseev, D.: Snowfall retrieval at X, Ka and W bands: consistency of backscattering and microphysical properties using BAECC ground-based measurements, Atmos. Meas. Tech., 11, 3059–3079, https://doi.org/10.5194/amt-11-3059-2018, 2018. a
Field, P., Lawson, R. P., Brown, P. R. A., Lloyd, G., Westbrook, C.,Moisseev, D., Miltenberger, A., Nenes, A., Blyth, A., Choularton, T., Connolly, P., Buehl, J., Crosier, J., Cui, Z., Dearden, C.,DeMott, P., Flossmann, A., Heymsfield, A., Huang, Y., Kalesse,H., Kanji, Z. A., Korolev, A., Kirchgaessner, A., Lasher-Trapp, S., Leisner, T., McFarquhar, G., Phillips, V., Stith, J., and Sullivan, S.: Secondary
ice production: Current state of the science and recommendations for the
future, Meteorol. Monogr., 58, 7–1, 2017. a, b, c, d, e
Gehring, J., Oertel, A., Vignon, É., Jullien, N., Besic, N., and Berne, A.: Microphysics and dynamics of snowfall associated with a warm conveyor belt over Korea, Atmos. Chem. Phys., 20, 7373–7392, https://doi.org/10.5194/acp-20-7373-2020, 2020. a
Grasmick, C. and Geerts, B.: Detailed dual-Doppler structure of
Kelvin-Helmholtz waves from an airborne profiling radar over complex terrain.
Part I: Dynamic structure, J. Atmos. Sci., 77,
1761–1782, https://doi.org/10.1175/JAS-D-19-0108.1, 2020. a
Haoran, L.: Supercooled liquid water and secondary ice production in Kelvin–Helmholtz instability, ZENODO [data set], https://doi.org/10.5281/zenodo.4019602, 2020. a
Hari, P. and Kulmala, M.: Station for Measuring Ecosystem-Atmosphere
Relations (SMEAR II), Bor. Environ. Res., 10, 315–322, 2005. a
Helmus, J. J. and Collis, S. M.: The Python ARM Radar Toolkit (Py-ART), a
library for working with weather radar data in the Python programming
language, Journal of Open Research Software, 4, 2016. a
Hill, A., Field, P., Furtado, K., Korolev, A., and Shipway, B.: Mixed-phase
clouds in a turbulent environment. Part 1: Large-eddy simulation experiments,
Q. J. Roy. Meteor. Soc., 140, 855–869, 2014. a
Hogan, R. J., Behera, M. D., O'Connor, E. J., and Illingworth, A. J.: Estimate
of the global distribution of stratiform supercooled liquid water clouds
using the LITE lidar, Geophys. Res. Lett., 31, https://doi.org/10.1029/2003GL018977, 2004. a
Hogan, R. J., Mittermaier, M. P., and Illingworth, A. J.: The retrieval of ice
water content from radar reflectivity factor and temperature and its use in
evaluating a mesoscale model, J. Appl. Meteorol. Clim.,
45, 301–317, 2006. a
Houze Jr, R. A. and Medina, S.: Turbulence as a mechanism for orographic
precipitation enhancement, J. Atmos. Sci., 62,
3599–3623, 2005. a
Intrieri, J., Shupe, M., Uttal, T., and McCarty, B.: An annual cycle of Arctic
cloud characteristics observed by radar and lidar at SHEBA, J. Geophys. Res.-Oceans, 107, C108030, https://doi.org/10.1029/2000JC000423, 2002. a
Kalesse, H., Szyrmer, W., Kneifel, S., Kollias, P., and Luke, E.: Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling, Atmos. Chem. Phys., 16, 2997–3012, https://doi.org/10.5194/acp-16-2997-2016, 2016. a, b, c
Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo,
D. J., and Krämer, M.: Overview of ice nucleating particles,
Meteorol. Monogr., 58, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0006.1, 2017. a
Kato, S., Mace, G. G., Clothiaux, E. E., Liljegren, J. C., and Austin, R. T.:
Doppler cloud radar derived drop size distributions in liquid water stratus
clouds, J. Atmos. Sci., 58, 2895–2911, 2001. a
Klein, S. A., McCoy, R., Morrison, H., Ackerman, A., Avramov,A., de Boer, G., Chen, M., Cole, J., DelGenio, A. D., Falk, M.,Foster, M., Fridlind, A., Golaz, J.-C., Hashino, T., Harrington,J., Hoose, C., Khairoutdinov, M., Larson, V., Liu, X., Luo, Y.,McFarquhar, G., Menon, S., Neggers, R., Park, S., von Salzen,K., Schmidt, J. M., Sednev, I., Shipway, B., Shupe, M., Spangenberg, D., Sud, Y., Turner, D., Veron, D., Walker, G., Wang,Z., Wolf, A., Xie, S., Xu, K.-M., Yang, G., and Zhang, G.:
Intercomparison of model simulations of mixed-phase clouds observed during
the ARM Mixed-Phase Arctic Cloud Experiment, I: Single-layer cloud, Q. J. Roy. Meteor. Soc., 135, 979–1002, 2009. a, b, c
Kneifel, S., von Lerber, A., Tiira, J., Moisseev, D., Kollias, P., and
Leinonen, J.: Observed relations between snowfall microphysics and
triple-frequency radar measurements, J. Geophys. Res.-Atmos., 120, 6034–6055, 2015. a
Kogan, Z. N., Mechem, D. B., and Kogan, Y. L.: Assessment of variability in
continental low stratiform clouds based on observations of radar
reflectivity, J. Geophys. Res.-Atmos., 110, https://doi.org/10.1029/2005JD006158, 2005. a
Kollias, P., Albrecht, B. A., Lhermitte, R., and Savtchenko, A.: Radar
observations of updrafts, downdrafts, and turbulence in fair-weather cumuli,
J. Atmos. Sci., 58, 1750–1766, 2001. a
Kollias, P., Rémillard, J., Luke, E., and Szyrmer, W.: Cloud radar Doppler
spectra in drizzling stratiform clouds: 1. Forward modeling and remote
sensing applications, J. Geophys. Res.-Atmos., 116, https://doi.org/10.1029/2010JD015237,
2011. a
Korolev, A. and Field, P. R.: The effect of dynamics on mixed-phase clouds:
Theoretical considerations, J. Atmos. Sci., 65, 66–86,
2008. a
Korolev, A., McFarquhar, G., Field, P. R., Franklin, C., Lawson,P., Wang, Z., Williams, E., Abel, S. J., Axisa, D., Borrmann,S., Crosier, J., Fugal, J., Krämer, M., Lohmann, U., Schlenczek,O., Schnaiter, M., and Wendisch, M.: Mixed-Phase Clouds: Progress and Challenges, Meteorol. Monogr., 58, 1–50, https://doi.org/10.1175/amsmonographs-d-17-0001.1, 2017. a
Korolev, A., Heckman, I., Wolde, M., Ackerman, A. S., Fridlind, A. M., Ladino, L. A., Lawson, R. P., Milbrandt, J., and Williams, E.: A new look at the environmental conditions favorable to secondary ice production, Atmos. Chem. Phys., 20, 1391–1429, https://doi.org/10.5194/acp-20-1391-2020, 2020. a, b, c, d
Korolev, A. V. and Mazin, I. P.: Supersaturation of water vapor in clouds,
J. Atmos. Sci., 60, 2957–2974, 2003. a
Küchler, N., Kneifel, S., Löhnert, U., Kollias, P., Czekala, H., and
Rose, T.: A W-Band radar–radiometer system for accurate and continuous
monitoring of clouds and precipitation, J. Atmos. Ocean. Tech., 34, 2375–2392, 2017. a
Lamb, D. and Verlinde, J.: Physics and chemistry of clouds, Cambridge
University Press, https://doi.org/10.1017/CBO9780511976377, 2011. a, b, c, d
Lasher-Trapp, S., Leon, D. C., DeMott, P. J., Villanueva-Birriel, C. M.,
Johnson, A. V., Moser, D. H., Tully, C. S., and Wu, W.: A multisensor
investigation of rime splintering in tropical maritime cumuli, J. Atmos. Sci., 73, 2547–2564, 2016. a
Lauber, A., Henneberger, J., Mignani, C., Ramelli, F., Pasquier, J. T., Wieder, J., Hervo, M., and Lohmann, U.: Continuous secondary-ice production initiated by updrafts through the melting layer in mountainous regions, Atmos. Chem. Phys., 21, 3855–3870, https://doi.org/10.5194/acp-21-3855-2021, 2021. a
Leinonen, J., Moisseev, D., Chandrasekar, V., and Koskinen, J.: Mapping radar
reflectivity values of snowfall between frequency bands, IEEE T. Geosci. Remote, 49, 3047–3058, 2011. a
Li, H. and Moisseev, D.: Two layers of melting ice particles within a single
radar bright band: Interpretation and implications, Geophys. Res. Lett., 47, e2020GL087499, https://doi.org/10.1029/2020GL087499, 2020. a, b
Li, H., Tiira, J., von Lerber, A., and Moisseev, D.: Towards the connection between snow microphysics and melting layer: insights from multifrequency and dual-polarization radar observations during BAECC, Atmos. Chem. Phys., 20, 9547–9562, https://doi.org/10.5194/acp-20-9547-2020, 2020. a
Li, H., Möhler, O., Petäjä, T., and Moisseev, D.: Multiyear statistics of columnar ice production in stratiform clouds over Hyytiälä, Finland, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2021-332, in review, 2021. a, b
Liebe, H. J.: An updated model for millimeter wave propagation in moist air,
Radio Science, 20, 1069–1089, 1985. a
Lohmann, U., Henneberger, J., Henneberg, O., Fugal, J., Bühl, J., and
Kanji, Z. A.: Persistence of orographic mixed-phase clouds, Geophys. Res. Lett., 43, 10–512, 2016. a
Luce, H., Nishi, N., Caccia, J.-L., Fukao, S., Yamamoto, M. K., Mega, T.,
Hashiguchi, H., Tajiri, T., and Nakazato, M.: Kelvin-Helmholtz billows
generated at a cirrus cloud base within a tropopause fold/upper-level frontal
system, Geophys. Res. Lett., 39, https://doi.org/10.1029/2011GL050120, 2012. a, b
Luke, E. P., Kollias, P., and Shupe, M. D.: Detection of supercooled liquid in
mixed-phase clouds using radar Doppler spectra, J. Geophys. Res.-Atmos., 115, https://doi.org/10.1029/2009JD012884, 2010. a, b
Luke, E. P., Yang, F., Kollias, P., Vogelmann, A. M., and Maahn, M.: New
insights into ice multiplication using remote-sensing observations of
slightly supercooled mixed-phase clouds in the Arctic, P. Natl. Acad. Sci. USA, 118, https://doi.org/10.1073/pnas.2021387118, 2021. a, b, c, d
Matrosov, S. Y.: Theoretical study of radar polarization parameters obtained
from cirrus clouds, J. Atmos. Sci., 48, 1062–1070,
1991. a
Matrosov, S. Y., Reinking, R. F., Kropfli, R. A., and Bartram, B. W.:
Estimation of ice hydrometeor types and shapes from radar polarization
measurements, J. Atmos. Ocean. Tech., 13, 85–96,
1996. a
McCoy, D. T., Tan, I., Hartmann, D. L., Zelinka, M. D., and Storelvmo, T.: On
the relationships among cloud cover, mixed-phase partitioning, and planetary
albedo in GCMs, J. Adv. Model. Earth Sy., 8, 650–668,
2016. a
Medina, S. and Houze Jr, R. A.: Kelvin–Helmholtz waves in extratropical
cyclones passing over mountain ranges, Q. J. Roy. Meteor. Soc., 142, 1311–1319, 2016. a
Morrison, H. and Pinto, J.: Intercomparison of bulk cloud microphysics schemes
in mesoscale simulations of springtime Arctic mixed-phase stratiform clouds,
Mon. Weather Rev., 134, 1880–1900, 2006. a
Morrison, H., De Boer, G., Feingold, G., Harrington, J., Shupe, M. D., and
Sulia, K.: Resilience of persistent Arctic mixed-phase clouds, Nat. Geosci., 5, 11, https://doi.org/10.1038/NGEO1332, 2012. a, b, c
Morrison, H., van Lier-Walqui, M., Fridlind, A. M., Grabowski, W. W.,
Harrington, J. Y., Hoose, C., Korolev, A., Kumjian, M. R., Milbrandt, J. A.,
Pawlowska, H., et al.: Confronting the challenge of modeling cloud and
precipitation microphysics, J. Adv. Model. Earth Sys.,
12, e2019MS001689, https://doi.org/10.1029/2019MS001689, 2020. a, b
Mossop, S.: Secondary ice particle production during rime growth: The effect of
drop size distribution and rimer velocity, Q. J. Roy. Meteor. Soc., 111, 1113–1124, 1985. a
Mossop, S. and Hallett, J.: Ice crystal concentration in cumulus clouds:
Influence of the drop spectrum, Science, 186, 632–634, 1974. a
Mülmenstädt, J., Sourdeval, O., Delanoë, J., and Quaas, J.:
Frequency of occurrence of rain from liquid-, mixed-, and ice-phase clouds
derived from A-Train satellite retrievals, Geophys. Res. Lett., 42,
6502–6509, 2015. a
Nguyen, C. M., Moisseev, D. N., and Chandrasekar, V.: A parametric time domain
method for spectral moment estimation and clutter mitigation for weather
radars, J. Atmos. Ocean. Tech., 25, 83–92, 2008. a
Petäjä, T., O’Connor, E. J., Moisseev, D., Sinclair, V. A., Manninen, A. J., Väänänen, R., von Lerber, A., Thornton, J. A., Nicoll, K., Petersen, W., Chandrasekar, V., Smith, J. N., Winkler, P. M., Krüger, O., Hakola, H., Timonen, H., Brus, D., Laurila, T., Asmi, E., Riekkola, M.-L., Mona, L., Massoli, P., Engelmann, R., Komppula, M., Wang, J., Kuang, C., Bäck, J., Virtanen, A., Levula, J., Ritsche, M., and Hickmon, N.: BAECC: A field campaign to elucidate the impact of
biogenic aerosols on clouds and climate, B. Am. Meteorol. Soc., 97, 1909–1928, 2016. a
Pinto, J. O.: Autumnal mixed-phase cloudy boundary layers in the Arctic,
J. Atmos. Sci., 55, 2016–2038, 1998. a
Rambukkange, M. P., Verlinde, J., Eloranta, E. W., Flynn, C. J., and
Clothiaux, E. E.: Using Doppler Spectra to Separate Hydrometeor Populations
and Analyze Ice Precipitation in Multilayered Mixed-Phase Clouds, IEEE T. Geosci. Remote, 8, 108–112,
https://doi.org/10.1109/LGRS.2010.2052781, 2011. a
Rauber, R. M., Geerts, B., Xue, L., French, J., Friedrich, K., Rasmussen,
R. M., Tessendorf, S. A., Blestrud, D. R., Kunkel, M. L., and Parkinson, S.:
Wintertime Orographic Cloud Seeding – A Review, J. Appl. Meteorol. Clim., 58, 2117–2140, 2019. a
Schneider, J., Höhler, K., Heikkilä, P., Keskinen, J., Bertozzi, B., Bogert, P., Schorr, T., Umo, N. S., Vogel, F., Brasseur, Z., Wu, Y., Hakala, S., Duplissy, J., Moisseev, D., Kulmala, M., Adams, M. P., Murray, B. J., Korhonen, K., Hao, L., Thomson, E. S., Castarède, D., Leisner, T., Petäjä, T., and Möhler, O.: The seasonal cycle of ice-nucleating particles linked to the abundance of biogenic aerosol in boreal forests, Atmos. Chem. Phys., 21, 3899–3918, https://doi.org/10.5194/acp-21-3899-2021, 2021. a
Shaw, R. A., Cantrell, W., Chen, S., Chuang, P., Donahue, N., Feingold, G.,
Kollias, P., Korolev, A., Kreidenweis, S., Krueger, S., et al.:
Cloud–Aerosol–Turbulence Interactions: Science Priorities and Concepts for
a Large-Scale Laboratory Facility, B. Am. Meteorol. Soc., 101, 1026–1035, 2020. a
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, 2006. a
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, 10–954, 2016. a
Solomon, A., Shupe, M. D., Persson, P. O. G., and Morrison, H.: Moisture and dynamical interactions maintaining decoupled Arctic mixed-phase stratocumulus in the presence of a humidity inversion, Atmos. Chem. Phys., 11, 10127–10148, https://doi.org/10.5194/acp-11-10127-2011, 2011. a
Sun, Z. and Shine, K. P.: Studies of the radiative properties of ice and
mixed-phase clouds, Q. J. Roy. Meteor. Soc.,
120, 111–137, 1994. a
Tan, I., Storelvmo, T., and Zelinka, M. D.: Observational constraints on
mixed-phase clouds imply higher climate sensitivity, Science, 352, 224–227,
2016. a
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. a, b
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.
Kelvin–Helmholtz (K–H) clouds embedded in a stratiform precipitation event were uncovered via...
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