Articles | Volume 23, issue 4
https://doi.org/10.5194/acp-23-2345-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-2345-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Feb 2023
Research article |
| 20 Feb 2023
| 20 Feb 2023
Heavy snowfall event over the Swiss Alps: did wind shear impact secondary ice production?
Department of Earth, Ocean, and Atmospheric Sciences, University of British Columbia, Earth Sciences Building, 2207 Main Mall, Vancouver, BC, V6T 1Z4, Canada
Environmental Remote Sensing Laboratory (LTE), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Philip H. Austin
Department of Earth, Ocean, and Atmospheric Sciences, University of British Columbia, Earth Sciences Building, 2207 Main Mall, Vancouver, BC, V6T 1Z4, Canada
Ulrike Lohmann
Institute of Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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Colin Tully, David Neubauer, Diego Villanueva, and Ulrike Lohmann
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This study details the first attempt with a GCM to simulate a fully prognostic aerosol species specifically for cirrus climate intervention. The new approach is in line with the real-world delivery mechanism via aircraft. However, to achieve an appreciable signal from seeding, smaller particles were needed, and their mass emissions needed to be scaled by at least a factor of 100. These biases contributed to either overseeding or small and insignificant effects in response to seeding cirrus.
Colin Tully, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 16, 2957–2973, https://doi.org/10.5194/gmd-16-2957-2023, https://doi.org/10.5194/gmd-16-2957-2023, 2023
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Julie Thérèse Pasquier, Jan Henneberger, Fabiola Ramelli, Annika Lauber, Robert Oscar David, Jörg Wieder, Tim Carlsen, Rosa Gierens, Marion Maturilli, and Ulrike Lohmann
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Florin N. Isenrich, Nadia Shardt, Michael Rösch, Julia Nette, Stavros Stavrakis, Claudia Marcolli, Zamin A. Kanji, Andrew J. deMello, and Ulrike Lohmann
Atmos. Meas. Tech., 15, 5367–5381, https://doi.org/10.5194/amt-15-5367-2022, https://doi.org/10.5194/amt-15-5367-2022, 2022
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Colin Tully, David Neubauer, Nadja Omanovic, and Ulrike Lohmann
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Jörg Wieder, Nikola Ihn, Claudia Mignani, Moritz Haarig, Johannes Bühl, Patric Seifert, Ronny Engelmann, Fabiola Ramelli, Zamin A. Kanji, Ulrike Lohmann, and Jan Henneberger
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Ulrike Proske, Sylvaine Ferrachat, David Neubauer, Martin Staab, and Ulrike Lohmann
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Jörg Wieder, Claudia Mignani, Mario Schär, Lucie Roth, Michael Sprenger, Jan Henneberger, Ulrike Lohmann, Cyril Brunner, and Zamin A. Kanji
Atmos. Chem. Phys., 22, 3111–3130, https://doi.org/10.5194/acp-22-3111-2022, https://doi.org/10.5194/acp-22-3111-2022, 2022
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Jussi Leinonen, Jacopo Grazioli, and Alexis Berne
Atmos. Meas. Tech., 14, 6851–6866, https://doi.org/10.5194/amt-14-6851-2021, https://doi.org/10.5194/amt-14-6851-2021, 2021
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Measuring the shape, size and mass of a large number of snowflakes is a challenging task; it is hard to achieve in an automatic and instrumented manner. We present a method to retrieve these properties of individual snowflakes using as input a triplet of images/pictures automatically collected by a multi-angle snowflake camera (MASC) instrument. Our method, based on machine learning, is trained on artificially generated snowflakes and evaluated on 3D-printed snowflake replicas.
Zane Dedekind, Annika Lauber, Sylvaine Ferrachat, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 15115–15134, https://doi.org/10.5194/acp-21-15115-2021, https://doi.org/10.5194/acp-21-15115-2021, 2021
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Paolo Pelucchi, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 14, 5413–5434, https://doi.org/10.5194/gmd-14-5413-2021, https://doi.org/10.5194/gmd-14-5413-2021, 2021
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Stratocumulus are thin clouds whose cloud cover is underestimated in climate models partly due to overly low vertical resolution. We develop a scheme that locally refines the vertical grid based on a physical constraint for the cloud top. Global simulations show that the scheme, implemented only in the radiation routine, can increase stratocumulus cloud cover. However, this effect is poorly propagated to the simulated cloud cover. The scheme's limitations and possible ways forward are discussed.
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Atmos. Chem. Phys., 21, 10993–11012, https://doi.org/10.5194/acp-21-10993-2021, https://doi.org/10.5194/acp-21-10993-2021, 2021
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Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol–cloud droplet link in alpine mixed-phase clouds. Predicted droplet number, Nd, agrees with observations and never exceeds a characteristic “limiting droplet number”, Ndlim, which depends solely on σw. Nd becomes velocity limited when it is within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol–cloud interactions.
Martin Lainer, Jordi Figueras i Ventura, Zaira Schauwecker, Marco Gabella, Montserrat F.-Bolaños, Reto Pauli, and Jacopo Grazioli
Atmos. Meas. Tech., 14, 3541–3560, https://doi.org/10.5194/amt-14-3541-2021, https://doi.org/10.5194/amt-14-3541-2021, 2021
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We show results from two unique measurement campaigns aimed at better understanding effects of large wind turbines on radar returns by deploying a mobile X-band weather radar system in the proximity of a small wind park. Measurements were taken in 24/7 operation with dedicated scan strategies to retrieve the variability and most extreme values of reflectivity and radar cross-section of the wind turbines. The findings are useful for wind turbine interference mitigation measures in radar systems.
Fabiola Ramelli, Jan Henneberger, Robert O. David, Johannes Bühl, Martin Radenz, Patric Seifert, Jörg Wieder, Annika Lauber, Julie T. Pasquier, Ronny Engelmann, Claudia Mignani, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 6681–6706, https://doi.org/10.5194/acp-21-6681-2021, https://doi.org/10.5194/acp-21-6681-2021, 2021
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Orographic mixed-phase clouds are an important source of precipitation, but the ice formation processes within them remain uncertain. Here we investigate the origin of ice crystals in a mixed-phase cloud in the Swiss Alps using aerosol and cloud data from in situ and remote sensing observations. We found that ice formation primarily occurs in cloud top generating cells. Our results indicate that secondary ice processes are active in the feeder region, which can enhance orographic precipitation.
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Atmos. Chem. Phys., 21, 5151–5172, https://doi.org/10.5194/acp-21-5151-2021, https://doi.org/10.5194/acp-21-5151-2021, 2021
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Ulrike Proske, Verena Bessenbacher, Zane Dedekind, Ulrike Lohmann, and David Neubauer
Atmos. Chem. Phys., 21, 5195–5216, https://doi.org/10.5194/acp-21-5195-2021, https://doi.org/10.5194/acp-21-5195-2021, 2021
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Ice crystals falling out of one cloud can initiate freezing in a second cloud below. We estimate the occurrence frequency of this natural cloud seeding over Switzerland from satellite data and sublimation calculations. We find that such situations with an ice cloud above another cloud are frequent and that the falling crystals survive the fall between two clouds in a significant number of cases, suggesting that natural cloud seeding is an important phenomenon over Switzerland.
Annika Lauber, Jan Henneberger, Claudia Mignani, Fabiola Ramelli, Julie T. Pasquier, Jörg Wieder, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 3855–3870, https://doi.org/10.5194/acp-21-3855-2021, https://doi.org/10.5194/acp-21-3855-2021, 2021
Short summary
Short summary
An accurate prediction of the ice crystal number concentration (ICNC) is important to determine the radiation budget, lifetime, and precipitation formation of clouds. Even though secondary-ice processes can increase the ICNC by several orders of magnitude, they are poorly constrained and lack a well-founded quantification. During measurements on a mountain slope, a high ICNC of small ice crystals was observed just below 0 °C, attributed to a secondary-ice process and parametrized in this study.
Cited articles
Andrić, J., Kumjian, M. R., Zrnić, D. S., Straka, J. M., and Melnikov, V. M.:
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. a, b
Bader, M. J., Clough, S. A., and Cox, G. P.: Aircraft and dual polarization
radar observations of hydrometeors in light stratiform precipitation,
Q. J. Roy. Meteor. Soc., 113, 491–515,
https://doi.org/10.1002/qj.49711347605, 1987. a
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and
Reinhardt, T.: Operational Convective-Scale Numerical Weather
Prediction with the COSMO Model: Description and Sensitivities,
Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1,
2011. a, b
Baumgartner, A. and Reichel, E.: The World Water Balance: Mean Annual
Global, Continental and Maritime Precipitation, Evaporation and
Run-off, Elsevier Scientific Publishing Company, 179 pp., ISBN 978-0-444-99858-3, 1975. a
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, J. Appl.
Meteorol. Climatol., 52, 1147–1169, https://doi.org/10.1175/JAMC-D-12-055.1, 2013. a, b, c
Blyth, A. M. and Latham, J.: A multi-thermal model of cumulus glaciation via
the hallett-Mossop process, Q. J. Roy. Meteor. Soc., 123, 1185–1198, https://doi.org/10.1002/qj.49712354104, 1997. a
Cotton, R. J. and Field, P. R.: Ice nucleation characteristics of an isolated
wave cloud, Q. J. Roy. Meteor. Soc., 128,
2417–2437, https://doi.org/10.1256/qj.01.150, 2002. a
Dawe, J. T. and Austin, P. H.: Direct entrainment and detrainment rate distributions of individual shallow cumulus clouds in an LES, Atmos. Chem. Phys., 13, 7795–7811, https://doi.org/10.5194/acp-13-7795-2013, 2013. a, b
Dedekind, Z.: The Impact of the Ice Phase on Orographic Mixed-phase
Clouds and Surface Precipitation in the Swiss Alps, Doctoral
Thesis, ETH Zurich, https://doi.org/10.3929/ethz-b-000511939, 2021. a, b, c, d
Dedekind, Z., Grazioli, J., Austin, P. H., and Lohmann, U.: Dataset for Heavy snowfall event over the Swiss Alps: Did wind shear impact secondary ice production? (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.6609251, 2022a. a
Dedekind, Z., Grazioli, J., Austin, P. H., and Lohmann, U.: Software for Heavy snowfall event over the Swiss Alps: Did wind shear impact secondary ice production? (Version 1), Zenodo [code], https://doi.org/10.5281/zenodo.6612296, 2022b. a
Eirund, G. K., Possner, A., and Lohmann, U.: Response of Arctic mixed-phase clouds to aerosol perturbations under different surface forcings, Atmos. Chem. Phys., 19, 9847–9864, https://doi.org/10.5194/acp-19-9847-2019, 2019. a
Eirund, G. K., Drossaart van Dusseldorp, S., Brem, B. T., Dedekind, Z., Karrer,
Y., Stoll, M., and Lohmann, U.: Aerosol–cloud–precipitation interactions
during a Saharan dust event – A summertime case-study from the Alps,
Q. J. Roy. Meteor. Soc., https://doi.org/10.1002/qj.4240,
2021. a, b
Field, P. R., 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,
Meteorological Monographs, 58, 7.1–7.20,
https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0014.1, 2016. a
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, b
Georgakaki, P., Sotiropoulou, G., Vignon, É., Billault-Roux, A.-C., Berne, A., and Nenes, A.: Secondary ice production processes in wintertime alpine mixed-phase clouds, Atmos. Chem. Phys., 22, 1965–1988, https://doi.org/10.5194/acp-22-1965-2022, 2022. a, b
Glassmeier, F. and Lohmann, U.: Precipitation Susceptibility and Aerosol
Buffering of Warm- and Mixed-Phase Orographic Clouds in
Idealized Simulations, J. Atmos. Sci., 75,
1173–1194, https://doi.org/10.1175/JAS-D-17-0254.1, 2018. a
Grazioli, J., Schneebeli, M., and Berne, A.: Accuracy of Phase-Based
Algorithms for the Estimation of the Specific Differential Phase
Shift Using Simulated Polarimetric Weather Radar Data, IEEE
Geosci. Remote Sens. Lett., 11, 763–767,
https://doi.org/10.1109/LGRS.2013.2278620, 2014a. a
Grazioli, J., Tuia, D., Monhart, S., Schneebeli, M., Raupach, T., and Berne, A.: Hydrometeor classification from two-dimensional video disdrometer data, Atmos. Meas. Tech., 7, 2869–2882, https://doi.org/10.5194/amt-7-2869-2014, 2014b. a
Grazioli, J., Lloyd, G., Panziera, L., Hoyle, C. R., Connolly, P. J., Henneberger, J., and Berne, A.: Polarimetric radar and in situ observations of riming and snowfall microphysics during CLACE 2014, Atmos. Chem. Phys., 15, 13787–13802, https://doi.org/10.5194/acp-15-13787-2015, 2015a. a, b, c, d, e, f, g
Grazioli, J., Tuia, D., and Berne, A.: Hydrometeor classification from polarimetric radar measurements: a clustering approach, Atmos. Meas. Tech., 8, 149–170, https://doi.org/10.5194/amt-8-149-2015, 2015b. a
Grazioli, J., Genthon, C., Boudevillain, B., Duran-Alarcon, C., Del Guasta, M., Madeleine, J.-B., and Berne, A.: Measurements of precipitation in Dumont d'Urville, Adélie Land, East Antarctica, The Cryosphere, 11, 1797–1811, https://doi.org/10.5194/tc-11-1797-2017, 2017. a
Hacine-Gharbi, A., Deriche, M., Ravier, P., Harba, R., and Mohamadi, T.: A new
histogram-based estimation technique of entropy and mutual information using
mean squared error minimization, Comput. Electr. Eng., 39,
918–933, https://doi.org/10.1016/j.compeleceng.2013.02.010, 2013. a
Hallett, J. and Mossop, S. C.: Production of secondary ice particles during the
riming process, Nature, 249, 26–28, https://doi.org/10.1038/249026a0, 1974. a, b
Henneberg, O.: Orographic Mixed-phase Clouds in the Swiss Alps –
Occurrence, Persistence and Sensitivity, Doctoral Thesis, ETH Zurich,
https://doi.org/10.3929/ethz-b-000223156, 2017. a
Henneberg, O., Henneberger, J., and Lohmann, U.: Formation and Development of
Orographic Mixed-Phase Clouds, J. Atmos. Sci.,
74, 3703–3724, https://doi.org/10.1175/JAS-D-16-0348.1, 2017. a, b, c
Heymsfield, A. J., Bansemer, A., Poellot, M. R., and Wood, N.: Observations of
Ice Microphysics through the Melting Layer, J. Atmos. Sci., 72, 2902–2928, https://doi.org/10.1175/JAS-D-14-0363.1, 2015. a
Heymsfield, A. J., Schmitt, C., Chen, C.-C.-J., Bansemer, A., Gettelman, A.,
Field, P. R., and Liu, C.: Contributions of the Liquid and Ice Phases
to Global Surface Precipitation: Observations and Global Climate
Modeling, J. Atmos. Sci., 77, 2629–2648,
https://doi.org/10.1175/JAS-D-19-0352.1, 2020. a
Hoarau, T., Pinty, J.-P., and Barthe, C.: A representation of the collisional ice break-up process in the two-moment microphysics LIMA v1.0 scheme of Meso-NH, Geosci. Model Dev., 11, 4269–4289, https://doi.org/10.5194/gmd-11-4269-2018, 2018. a
Hogan, R. J., Field, P. R., Illingworth, A. J., Cotton, R. J., and Choularton,
T. W.: Properties of embedded convection in warm-frontal mixed-phase cloud
from aircraft and polarimetric radar, Q. J. Roy. Meteor. Soc., 128, 451–476, https://doi.org/10.1256/003590002321042054,
2002. a
Kärcher, B., Hendricks, J., and Lohmann, U.: Physically based parameterization
of cirrus cloud formation for use in global atmospheric models, J.
Geophys. Res.-Atmos., 111, 1–11, https://doi.org/10.1029/2005JD006219,
2006. a
Keil, C., Baur, F., Bachmann, K., Rasp, S., Schneider, L., and Barthlott, C.:
Relative contribution of soil moisture, boundary-layer and microphysical
perturbations on convective predictability in different weather regimes,
Q. J. Roy. Meteor. Soc., 145, 3102–3115,
https://doi.org/10.1002/qj.3607, 2019. a
Kumjian, M. R. and Lombardo, K. A.: Insights into the Evolving
Microphysical and Kinematic Structure of Northeastern U.S.
Winter Storms from Dual-Polarization Doppler Radar, Mon. Weather Rev., 145, 1033–1061, https://doi.org/10.1175/MWR-D-15-0451.1, 2017. a, b
Kumjian, M. R. and Ryzhkov, A. V.: The Impact of Size Sorting on the
Polarimetric Radar Variables, J. Atmos. Sci., 69,
2042–2060, https://doi.org/10.1175/JAS-D-11-0125.1, 2012. a
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. Climatol.,
53, 1636–1658, https://doi.org/10.1175/JAMC-D-13-0312.1, 2014. a, b
Lohmann, U., Henneberger, J., Henneberg, O., Fugal, J. P., Bühl, J., and
Kanji, Z. A.: Persistence of orographic mixed-phase clouds, Geophys. Res. Lett., 43, 10512–10519, https://doi.org/10.1002/2016GL071036, 2016. 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, e2021387118, https://doi.org/10.1073/pnas.2021387118, 2021. a
Medina, S., Smull, B. F., Houze, R. A., and Steiner, M.: Cross-Barrier Flow
during Orographic Precipitation Events: Results from MAP and
IMPROVE, J. Atmos. Sci., 62, 3580–3598,
https://doi.org/10.1175/JAS3554.1, 2005. a, b, c
Milbrandt, J. A. and McTaggart-Cowan, R.: Sedimentation-Induced Errors in
Bulk Microphysics Schemes, J. Atmos. Sci., 67,
3931–3948, https://doi.org/10.1175/2010JAS3541.1, 2010. a
Milbrandt, J. A. and Morrison, H.: Parameterization of Cloud Microphysics
Based on the Prediction of Bulk Ice Particle Properties. Part
III: Introduction of Multiple Free Categories, J. Atmos. Sci., 73, 975–995, https://doi.org/10.1175/JAS-D-15-0204.1, 2016. 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, https://doi.org/10.1002/2015GL064604, 2015. a
Murphy, A. M., Ryzhkov, A., and Zhang, P.: Columnar Vertical Profile
(CVP) Methodology for Validating Polarimetric Radar Retrievals in
Ice Using In Situ Aircraft Measurements, J. Atmos. Ocean. Tech., 37, 1623–1642, https://doi.org/10.1175/JTECH-D-20-0011.1,
2020. a, b, c
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.
Climatol., 54, 1060–1068, https://doi.org/10.1175/JAMC-D-15-0012.1, 2015. a
Oue, M., Kollias, P., Matrosov, S. Y., Battaglia, A., and Ryzhkov, A. V.: Analysis of the microphysical properties of snowfall using scanning polarimetric and vertically pointing multi-frequency Doppler radars, Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021, 2021. a
Ovtchinnikov, M. and Kogan, Y. L.: An Investigation of Ice Production
Mechanisms in Small Cumuliform Clouds Using a 3D Model with
Explicit Microphysics. Part I: Model Description, J.
Atmos. Sci., 57, 2989–3003,
https://doi.org/10.1175/1520-0469(2000)057<2989:AIOIPM>2.0.CO;2, 2000. a
Phillips, V. T. J., Blyth, A. M., Brown, P. R. A., Choularton, T. W., and
Latham, J.: The glaciation of a cumulus cloud over New Mexico, Q. J. Roy. Meteor. Soc., 127, 1513–1534,
https://doi.org/10.1002/qj.49712757503, 2006. a
Phillips, V. T. J., DeMott, P. J., and Andronache, C.: An Empirical
Parameterization of Heterogeneous Ice Nucleation for Multiple
Chemical Species of Aerosol, J. Atmos. Sci., 65,
2757–2783, https://doi.org/10.1175/2007JAS2546.1, 2008. a
Phillips, V. T. J., Yano, J.-I., Formenton, M., Ilotoviz, E., Kanawade, V.,
Kudzotsa, I., Sun, J., Bansemer, A., Detwiler, A. G., Khain, A., and
Tessendorf, S. A.: Ice Multiplication by Breakup in Ice–Ice
Collisions. Part II: Numerical Simulations, J. Atmos. Sci., 74, 2789–2811, https://doi.org/10.1175/JAS-D-16-0223.1, 2017. a, b, c
Pinsky, M., Khain, A., and Shapiro, M.: Collision Efficiency of Drops in a
Wide Range of Reynolds Numbers: Effects of Pressure on Spectrum
Evolution, J. Atmos. Sci., 58, 742–764,
https://doi.org/10.1175/1520-0469(2001)058<0742:CEODIA>2.0.CO;2, 2001. a
Possner, A., Ekman, A. M. L., and Lohmann, U.: Cloud response and feedback
processes in stratiform mixed-phase clouds perturbed by ship exhaust,
Geophys. Res. Lett., 44, 1964–1972, https://doi.org/10.1002/2016GL071358,
2017. a
Ryzhkov, A. V. and Zrnic, D. S.: Radar Polarimetry for Weather
Observations, Springer Atmospheric Sciences, Springer International
Publishing, Cham, https://doi.org/10.1007/978-3-030-05093-1, 2019. a
Ryzhkov, A. V., Giangrande, S. E., Melnikov, V. M., and Schuur, T. J.:
Calibration Issues of Dual-Polarization Radar Measurements, J. Atmos. Ocean. Tech., 22, 1138–1155,
https://doi.org/10.1175/JTECH1772.1, 2005. a
Schär, C., Leuenberger, D., Fuhrer, O., Lüthi, D., and Girard, C.: A New
Terrain-Following Vertical Coordinate Formulation for Atmospheric
Prediction Models, Mon. Weather Rev., 130, 2459–2480,
https://doi.org/10.1175/1520-0493(2002)130<2459:ANTFVC>2.0.CO;2, 2002. a
Seifert, A. and Beheng, K. D.: A double-moment parameterization for simulating
autoconversion, accretion and selfcollection, Atmos. Res., 59-60,
265–281, https://doi.org/10.1016/S0169-8095(01)00126-0, 2001. a
Seifert, A., Khain, A., Pokrovsky, A., and Beheng, K. D.: A comparison of
spectral bin and two-moment bulk mixed-phase cloud microphysics, Atmos. Res., 80, 46–66, https://doi.org/10.1016/j.atmosres.2005.06.009, 2006. a, b
Selz, T. and Craig, G. C.: Upscale Error Growth in a High-Resolution
Simulation of a Summertime Weather Event over Europe, Mon. Weather Rev., 143, 813–827, https://doi.org/10.1175/MWR-D-14-00140.1, 2015. 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, 10,954–10,970,
https://doi.org/10.1002/2016JD025381, 2016. a, b
Sotiropoulou, G., Sullivan, S., Savre, J., Lloyd, G., Lachlan-Cope, T., Ekman, A. M. L., and Nenes, A.: The impact of secondary ice production on Arctic stratocumulus, Atmos. Chem. Phys., 20, 1301–1316, https://doi.org/10.5194/acp-20-1301-2020, 2020. a, b, c
Sotiropoulou, G., Vignon, É., Young, G., Morrison, H., O'Shea, S. J., Lachlan-Cope, T., Berne, A., and Nenes, A.: Secondary ice production in summer clouds over the Antarctic coast: an underappreciated process in atmospheric models, Atmos. Chem. Phys., 21, 755–771, https://doi.org/10.5194/acp-21-755-2021, 2021. a, b, c
Stull, R.: Practical Meteorology: An Algebra-based Survey of
Atmospheric Science, AVP International, University of British Columbia,
google-Books-ID: xP2sDAEACAAJ, 2016. a
Vardiman, L.: The Generation of Secondary Ice Particles in Clouds by
Crystal–Crystal Collision, J. Atmos. Sci., 35,
2168–2180, https://doi.org/10.1175/1520-0469(1978)035<2168:TGOSIP>2.0.CO;2, 1978. a
von Terzi, L., Dias Neto, J., Ori, D., Myagkov, A., and Kneifel, S.: Ice microphysical processes in the dendritic growth layer: a statistical analysis combining multi-frequency and polarimetric Doppler cloud radar observations, Atmos. Chem. Phys., 22, 11795–11821, https://doi.org/10.5194/acp-22-11795-2022, 2022. a, b, c
Wisner, C., Orville, H. D., and Myers, C.: A Numerical Model of a
Hail-Bearing Cloud, J. Atmos. Sci., 29,
1160–1181, https://doi.org/10.1175/1520-0469(1972)029<1160:ANMOAH>2.0.CO;2, 1972.
a
Yano, J.-I. and Phillips, V. T. J.: Ice–Ice Collisions: An Ice
Multiplication Process in Atmospheric Clouds, J. Atmos. Sci., 68, 322–333, https://doi.org/10.1175/2010JAS3607.1, 2011. a, b
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. a
Zhao, X., Liu, X., Phillips, V. T. J., and Patade, S.: Impacts of secondary ice production on Arctic mixed-phase clouds based on ARM observations and CAM6 single-column model simulations, Atmos. Chem. Phys., 21, 5685–5703, https://doi.org/10.5194/acp-21-5685-2021, 2021. a, b
Short summary
Simulations allowing ice particles to collide with one another producing more ice particles represented surface observations of ice particles accurately. An increase in ice particles formed through collisions was related to sharp changes in the wind direction and speed with height. Changes in wind speed and direction can therefore cause more enhanced collisions between ice particles and alter how fast and how much precipitation forms. Simulations were conducted with the atmospheric model COSMO.
Simulations allowing ice particles to collide with one another producing more ice particles...
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