Impact of Mixed-Phase Cloud Parameterization on Warm Conveyor Belts and Upper-Tropospheric Dynamics

Marie Mazoyer aCNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

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Didier Ricard aCNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

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Gwendal Rivière bLMD/IPSL, École Normale Supérieure, PSL Research University, École Polytechnique, Sorbonne Universités, CNRS, Paris, France

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Julien Delanoë cLATMOS-IPSL, CNRS/INSU, University of Versailles, Guyancourt, France

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Sébastien Riette aCNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

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Clotilde Augros aCNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

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Mary Borderies aCNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

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Benoit Vié aCNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

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Abstract

This study investigates mixed-phase cloud (MPC) processes along the warm conveyor belts (WCBs) of two extratropical cyclones observed during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX). The aim is to investigate the effect of two radically distinct parameterizations for MPCs on the WCB and the ridge building downstream: the first one (REF) drastically limits the formation of liquid clouds, while the second one (T40) forces the liquid clouds to exist. REF exhibits a stronger heating below 6-km height and a more important cooling above 6-km height than T40. The stronger heating at lower levels is due to more important water vapor depositional processes while the larger cooling at upper levels is due to differences in radiative cooling. The consequence is a more efficient potential vorticity destruction in the WCB outflow region and a more rapid ridge building in REF than T40. A comparison with airborne remote sensing measurements is performed. REF does not form any MPCs whereas T40 does, in particular in regions detected by the radar–lidar platform like below the dry intrusion. Comparison of both ice water content and reflectivity shows there may be too much pristine ice and not enough snow in REF and not enough cold hydrometeors in general in T40. The lower ice-to-snow ratio in T40 likely explains its better distribution of hydrometeors with respect to height compared to REF. These results underline the influence of MPC processes on the upper-tropospheric circulation and the need for more MPC observations in midlatitudes.

Significance Statement

The diabatic processes occurring in the warm conveyor belt (WCB) of extratropical cyclones impact the jet stream structure at midlatitudes. This study highlights some sensitivity of upper-level dynamics to mixed-phase-cloud-related processes. Comparisons of two different microphysical schemes for mixed-phase clouds shows that the ratio of liquid to solid clouds along the WCB ascents impacts the latent heat release and the radiation. Data from the NAWDEX campaign helps to determine room for improvement for both schemes and point out the need of a better understanding of these processes for an improved prediction of upper-level dynamics.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Marie Mazoyer, marie.mazoyer@yahoo.fr

Abstract

This study investigates mixed-phase cloud (MPC) processes along the warm conveyor belts (WCBs) of two extratropical cyclones observed during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX). The aim is to investigate the effect of two radically distinct parameterizations for MPCs on the WCB and the ridge building downstream: the first one (REF) drastically limits the formation of liquid clouds, while the second one (T40) forces the liquid clouds to exist. REF exhibits a stronger heating below 6-km height and a more important cooling above 6-km height than T40. The stronger heating at lower levels is due to more important water vapor depositional processes while the larger cooling at upper levels is due to differences in radiative cooling. The consequence is a more efficient potential vorticity destruction in the WCB outflow region and a more rapid ridge building in REF than T40. A comparison with airborne remote sensing measurements is performed. REF does not form any MPCs whereas T40 does, in particular in regions detected by the radar–lidar platform like below the dry intrusion. Comparison of both ice water content and reflectivity shows there may be too much pristine ice and not enough snow in REF and not enough cold hydrometeors in general in T40. The lower ice-to-snow ratio in T40 likely explains its better distribution of hydrometeors with respect to height compared to REF. These results underline the influence of MPC processes on the upper-tropospheric circulation and the need for more MPC observations in midlatitudes.

Significance Statement

The diabatic processes occurring in the warm conveyor belt (WCB) of extratropical cyclones impact the jet stream structure at midlatitudes. This study highlights some sensitivity of upper-level dynamics to mixed-phase-cloud-related processes. Comparisons of two different microphysical schemes for mixed-phase clouds shows that the ratio of liquid to solid clouds along the WCB ascents impacts the latent heat release and the radiation. Data from the NAWDEX campaign helps to determine room for improvement for both schemes and point out the need of a better understanding of these processes for an improved prediction of upper-level dynamics.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Marie Mazoyer, marie.mazoyer@yahoo.fr

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  • Alexander, S., G. McFarquhar, R. Marchand, A. Protat, É. Vignon, G. Mace, and A. Klekociuk, 2021: Mixed-phase clouds and precipitation in Southern Ocean cyclones and cloud systems observed poleward of 64°S by ship-based cloud radar and lidar. J. Geophys. Res. Atmos., 126, e2020JD033626, https://doi.org/10.1029/2020JD033626.

    • Search Google Scholar
    • Export Citation
  • Augros, C., V. Caumont, O. Ducrocq, N. Gaussiat, and P. P. Tabary, 2016: Comparisons between S, C, and X band polarimetric radar observations and convective-scale simulations of HyMeX first special observing period. Quart. J. Roy. Meteor. Soc., 142, 347362, https://doi.org/10.1002/qj.2572.

    • Search Google Scholar
    • Export Citation
  • Bengtsson, L., and Coauthors, 2017: The HARMONIE–AROME model configuration in the ALADIN–HIRLAM NWP system. Mon. Wea. Rev., 145, 19191935, https://doi.org/10.1175/MWR-D-16-0417.1.

    • Search Google Scholar
    • Export Citation
  • Bergeron, T., 1935: On the physics of clouds and precipitation. Proces Verbaux de l’Association de Météorologie, International Union of Geodesy and Geophysics, Imprimerie Paul Dupont, 156–178.

  • Berman, J. D., and R. D. Torn, 2019: The impact of initial condition and warm conveyor belt forecast uncertainty on variability in the downstream waveguide in an ECWMF case study. Mon. Wea. Rev., 147, 40714089, https://doi.org/10.1175/MWR-D-18-0333.1.

    • Search Google Scholar
    • Export Citation
  • Bernstein, B., and Coauthors, 2021: The In-Cloud Icing and Large-Drop Experiment science and operations plan. Tech. Rep. DOT/FAA/TC-21/29, Department of Transportation, Federal Aviation Administration, 174 pp.

  • Blanchard, N., F. Pantillon, J.-P. Chaboureau, and J. Delanoë, 2020: Organization of convective ascents in a warm conveyor belt. Wea. Climate Dyn., 1, 617634, https://doi.org/10.5194/wcd-1-617-2020.

    • Search Google Scholar
    • Export Citation
  • Blanchard, N., F. Pantillon, J.-P. Chaboureau, and J. Delanoë, 2021: Mid-level convection in a warm conveyor belt accelerates the jet stream. Wea. Climate Dyn., 2, 3753, https://doi.org/10.5194/wcd-2-37-2021.

    • Search Google Scholar
    • Export Citation
  • Boettcher, M., and Coauthors, 2021: Lagrangian matches between observations from aircraft, lidar and radar in a warm conveyor belt crossing orography. Atmos. Chem. Phys., 21, 54775498, https://doi.org/10.5194/acp-21-5477-2021.

    • Search Google Scholar
    • Export Citation
  • Borderies, M., and Coauthors, 2018: Simulation of W-band radar reflectivity for model validation and data assimilation. Quart. J. Roy. Meteor. Soc., 144, 391403, https://doi.org/10.1002/qj.3210.

    • Search Google Scholar
    • Export Citation
  • Boudala, F. S., G. A. Isaac, S. G. Cober, and Q. Fu, 2004: Liquid fraction in stratiform mixed-phase clouds from in situ observations. Quart. J. Roy. Meteor. Soc., 130, 29192931, https://doi.org/10.1256/qj.03.153.

    • Search Google Scholar
    • Export Citation
  • Browning, K. A., 1986: Conceptual models of precipitation systems. Wea. Forecasting, 1, 2341, https://doi.org/10.1175/1520-0434(1986)001<0023:CMOPS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Caniaux, G., J. Redelsperger, and J. P. Lafore, 1994: A numerical study of the stratiform region of a fast-moving squall line. Part I: General description and water and heat budgets. J. Atmos. Sci., 51, 20462074, https://doi.org/10.1175/1520-0469(1994)051<2046:ANSOTS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Cazenave, Q., M. Ceccaldi, J. Delanoë, J. Pelon, S. Groß, and A. Heymsfield, 2019: Evolution of DARDAR-CLOUD ice cloud retrievals: New parameters and impacts on the retrieved microphysical properties. Atmos. Meas. Tech., 12, 28192835, https://doi.org/10.5194/amt-12-2819-2019.

    • Search Google Scholar
    • Export Citation
  • Chagnon, J., S. Gray, and J. Methven, 2013: Diabatic processes modifying potential vorticity in a North Atlantic cyclone. Quart. J. Roy. Meteor. Soc., 139, 12701282, https://doi.org/10.1002/qj.2037.

    • Search Google Scholar
    • Export Citation
  • Cober, S. G., G. A. Isaac, and J. W. Strapp, 2001: Characterizations of aircraft icing environments that include supercooled large drops. J. Appl. Meteor., 40, 19842002, https://doi.org/10.1175/1520-0450(2001)040<1984:COAIET>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Delanoë, J., and R. J. Hogan, 2008: A variational scheme for retrieving ice cloud properties from combined radar, lidar, and infrared radiometer. J. Geophys. Res., 113, D07204, https://doi.org/10.1029/2007JD009000.

    • Search Google Scholar
    • Export Citation
  • Delanoë, J., and R. J. Hogan, 2010: Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds. J. Geophys. Res., 115, D00H29, https://doi.org/10.1029/2009JD012346.

    • Search Google Scholar
    • Export Citation
  • Delanoë, J., A. Protat, O. Jourdan, J. Pelon, M. Papazzoni, R. Dupuy, J.-F. Gayet, and C. Jouan, 2013: Comparison of airborne in situ, airborne radar–lidar, and spaceborne radar–lidar retrievals of polar ice cloud properties sampled during the POLARCAT campaign. J. Atmos. Oceanic Technol., 30, 5773, https://doi.org/10.1175/JTECH-D-11-00200.1.

    • Search Google Scholar
    • Export Citation
  • DeMott, P. J., and D. C. Rogers, 1990: Freezing nucleation rates of dilute solution droplets measured between −30°C and −40°C in laboratory simulations of natural clouds. J. Atmos. Sci., 47, 10561064, https://doi.org/10.1175/1520-0469(1990)047<1056:FNRODS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Dirren, S., M. Didone, and H. Davies, 2003: Diagnosis of “forecast-analysis” differences of a weather prediction system. Geophys. Res. Lett., 30, 2060, https://doi.org/10.1029/2003GL017986.

    • Search Google Scholar
    • Export Citation
  • Engdahl, B. J. K., G. Thompson, and L. Bengtsson, 2020: Improving the representation of supercooled liquid water in the HARMONIE-AROME weather forecast model. Tellus, 72A, 118, https://doi.org/10.1080/16000870.2019.1697603.

    • Search Google Scholar
    • Export Citation
  • Findeisen, W., 1938: Kolloid-meteorologische vorgänge bei neiderschlags-bildung. Meteor. Z., 55, 121133.

  • Flack, D., G. Rivière, I. Musat, R. Roehrig, S. Bony, J. Delanoë, Q. Cazenave, and J. Pelon, 2021: Representation by two climate models of the dynamical and diabatic processes involved in the development of an explosively-deepening cyclone during NAWDEX. Wea. Climate Dyn., 2, 233253, https://doi.org/10.5194/wcd-2-233-2021.

    • Search Google Scholar
    • Export Citation
  • Gehring, J., A. Oertel, É. Vignon, N. Jullien, N. Besic, and A. Berne, 2020: Microphysics and dynamics of snowfall associated with a warm conveyor belt over Korea. Atmos. Chem. Phys., 20, 73737392, https://doi.org/10.5194/acp-20-7373-2020.

    • Search Google Scholar
    • Export Citation
  • Gheusi, F., and J. Stein, 2002: Lagrangian description of airflows using Eulerian passive tracers. Quart. J. Roy. Meteor. Soc., 128, 337360, https://doi.org/10.1256/00359000260498914.

    • Search Google Scholar
    • Export Citation
  • Grams, C. M., and Coauthors, 2011: The key role of diabatic processes in modifying the upper-tropospheric wave guide: A North Atlantic case-study. Quart. J. Roy. Meteor. Soc., 137, 21742193, https://doi.org/10.1002/qj.891.

    • Search Google Scholar
    • Export Citation
  • Gray, S. L., C. Dunning, J. Methven, G. Masato, and J. M. Chagnon, 2014: Systematic model forecast error in Rossby wave structure. Geophys. Res. Lett., 41, 29792987, https://doi.org/10.1002/2014GL059282.

    • Search Google Scholar
    • Export Citation
  • Harrold, T., 1973: Mechanisms influencing the distribution of precipitation within baroclinic disturbances. Quart. J. Roy. Meteor. Soc., 99, 232251, https://doi.org/10.1002/qj.49709942003.

    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., P. Francis, H. Flentje, A. Illingworth, M. Quante, and J. Pelon, 2003: Characteristics of mixed-phase clouds. I: Lidar, radar and aircraft observations from CLARE’98. Quart. J. Roy. Meteor. Soc., 129, 20892116, https://doi.org/10.1256/rj.01.208.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., M. McIntyre, and A. W. Robertson, 1985: On the use and significance of isentropic potential vorticity maps. Quart. J. Roy. Meteor. Soc., 111, 877946, https://doi.org/10.1002/qj.49711147002.

    • Search Google Scholar
    • Export Citation
  • Hu, Y., S. Rodier, K. Xu, W. Sun, J. Huang, B. Lin, P. Zhai, and D. Josset, 2010: Occurrence, liquid water content, and fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements. J. Geophys. Res., 115, D00H34, https://doi.org/10.1029/2009JD012384.

    • Search Google Scholar
    • Export Citation
  • Illingworth, A., and Coauthors, 2007: Cloudnet: Continuous evaluation of cloud profiles in seven operational models using ground-based observations. Bull. Amer. Meteor. Soc., 88, 883898, https://doi.org/10.1175/BAMS-88-6-883.

    • Search Google Scholar
    • Export Citation
  • Joos, H., 2019: Warm conveyor belts and their role for cloud radiative forcing in the extratropical storm tracks. J. Climate, 32, 53255343, https://doi.org/10.1175/JCLI-D-18-0802.1.

    • Search Google Scholar
    • Export Citation
  • Joos, H., and H. Wernli, 2012: Influence of microphysical processes on the potential vorticity development in a warm conveyor belt: A case-study with the limited-area model COSMO. Quart. J. Roy. Meteor. Soc., 138, 407418, https://doi.org/10.1002/qj.934.

    • Search Google Scholar
    • Export Citation
  • Joos, H., and R. M. Forbes, 2016: Impact of different IFS microphysics on a warm conveyor belt and the downstream flow evolution. Quart. J. Roy. Meteor. Soc., 142, 27272739, https://doi.org/10.1002/qj.2863.

    • Search Google Scholar
    • Export Citation
  • Korolev, A. V., and I. P. Mazin, 2003: Supersaturation of water vapor in clouds. J. Atmos. Sci., 60, 29572974, https://doi.org/10.1175/1520-0469(2003)060<2957:SOWVIC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Korolev, A. V., J. Strapp, G. Isaac, and A. Nevzorov, 1998: The Nevzorov airborne hot-wire LWC–TWC probe: Principle of operation and performance characteristics. J. Atmos. Oceanic Technol., 15, 14951510, https://doi.org/10.1175/1520-0426(1998)015<1495:TNAHWL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Korolev, A. V., and Coauthors, 2017: Mixed-phase clouds: Progress and challenges. Ice Formation and Evolution in Clouds and Precipitation: Measurement and Modeling Challenges, Meteor. Monogr., No. 58, Amer. Meteor. Soc., https://doi.org/10.1175/AMSMONOGRAPHS-D-17-0001.1.

  • Kumar, S., A. Hazra, and B. Goswami, 2014: Role of interaction between dynamics, thermodynamics and cloud microphysics on summer monsoon precipitating clouds over the Myanmar Coast and the Western Ghats. Climate Dyn., 43, 911924, https://doi.org/10.1007/s00382-013-1909-3.

    • Search Google Scholar
    • Export Citation
  • Lac, C., and Coauthors, 2018: Overview of the Meso-NH model version 5.4 and its applications. Geosci. Model Dev., 11, 19291969, https://doi.org/10.5194/gmd-11-1929-2018.

    • Search Google Scholar
    • Export Citation
  • Liu, C., K. Ikeda, G. Thompson, R. Rasmussen, and J. Dudhia, 2011: High-resolution simulations of wintertime precipitation in the Colorado headwaters region: Sensitivity to physics parameterizations. Mon. Wea. Rev., 139, 35333553, https://doi.org/10.1175/MWR-D-11-00009.1.

    • Search Google Scholar
    • Export Citation
  • Lord, S. J., H. E. Willoughby, and J. M. Piotrowicz, 1984: Role of a parameterized ice-phase microphysics in an axisymmetric, nonhydrostatic tropical cyclone model. J. Atmos. Sci., 41, 28362848, https://doi.org/10.1175/1520-0469(1984)041<2836:ROAPIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Maddison, J., S. Gray, O. Martinez-Alvarado, and K. Williams, 2019: Upstream cyclone influence on the predictability of block onsets over the Euro-Atlantic region. Mon. Wea. Rev., 147, 12771296, https://doi.org/10.1175/MWR-D-18-0226.1.

    • Search Google Scholar
    • Export Citation
  • Madonna, E., H. Wernli, H. Joos, and O. Martius, 2014: Warm conveyor belts in the ERA-Interim dataset (1979–2010). Part I: Climatology and potential vorticity evolution. J. Climate, 27, 326, https://doi.org/10.1175/JCLI-D-12-00720.1.

    • Search Google Scholar
    • Export Citation
  • Martínez-Alvarado, O., E. Madonna, S. L. Gray, and H. Joos, 2016: A route to systematic error in forecasts of Rossby waves. Quart. J. Roy. Meteor. Soc., 142, 196210, https://doi.org/10.1002/qj.2645.

    • Search Google Scholar
    • Export Citation
  • Mazoyer, M., and Coauthors, 2021: Microphysics impacts on the warm conveyor belt and ridge building of the NAWDEX IOP6 cyclone. Mon. Wea. Rev., 149, 39613980, https://doi.org/10.1175/MWR-D-21-0061.1.

    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M., and Coauthors, 2011: Indirect and semi-direct aerosol campaign: The impact of arctic aerosols on clouds. Bull. Amer. Meteor. Soc., 92, 183201, https://doi.org/10.1175/2010BAMS2935.1.

    • Search Google Scholar
    • Export Citation
  • Mishchenko, M. I., L. D. Travis, and D. W. Mackowski, 1996: T-matrix computations of light scattering by nonspherical particles: A review. J. Quant. Spectrosc. Radiat. Transfer, 55, 535575, https://doi.org/10.1016/0022-4073(96)00002-7.

    • Search Google Scholar
    • Export Citation
  • Morrison, H., M. Shupe, and J. Curry, 2003: Modeling clouds observed at SHEBA using a bulk microphysics parameterization implemented into a single-column model. J. Geophys. Res., 108, 4255, https://doi.org/10.1029/2002JD002229.

    • Search Google Scholar
    • Export Citation
  • Mülmenstädt, J., O. Sourdeval, J. Delanoë, and J. Quaas, 2015: Frequency of occurrence of rain from liquid-, mixed-, and ice-phase clouds derived from A-train satellite retrievals. Geophys. Res. Lett., 42, 65026509, https://doi.org/10.1002/2015GL064604.

    • Search Google Scholar
    • Export Citation
  • Oertel, A., M. Boettcher, H. Joos, M. Sprenger, H. Konow, M. Hagen, and H. Wernli, 2019: Convective activity in an extratropical cyclone and its warm conveyor belt—A case-study combining observations and a convection-permitting model simulation. Quart. J. Roy. Meteor. Soc., 145, 14061426, https://doi.org/10.1002/qj.3500.

    • Search Google Scholar
    • Export Citation
  • Pinty, J., and P. Jabouille, 1998: A mixed-phase cloud parameterization for use in mesoscale non-hydrostatic model: Simulations of a squall line and of orographic precipitations. Conf. on Cloud Physics, Everett, WA, Amer. Meteor. Soc., 217–220.

  • Pomroy, H. R., and A. J. Thorpe, 2000: The evolution and dynamical role of reduced upper-tropospheric potential vorticity in intensive observing period one of FASTEX. Mon. Wea. Rev., 128, 18171834, https://doi.org/10.1175/1520-0493(2000)128<1817:TEADRO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rasp, S., T. Selz, and G. C. Craig, 2016: Convective and slantwise trajectory ascent in convection-permitting simulations of midlatitude cyclones. Mon. Wea. Rev., 144, 39613976, https://doi.org/10.1175/MWR-D-16-0112.1.

    • Search Google Scholar
    • Export Citation
  • Rivière, G., M. Wimmer, P. Arbogast, J.-M. Piriou, J. Delanoë, C. Labadie, Q. Cazenave, and J. Pelon, 2021: The impact of deep convection representation in a global atmospheric model on the warm conveyor belt and jet stream during NAWDEX IOP6. Wea. Climate Dyn., 2, 10111031, https://doi.org/10.5194/wcd-2-1011-2021.

    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., and W. L. Woodley, 2000: Deep convective clouds with sustained supercooled liquid water down to −37.5°C. Nature, 405, 440442, https://doi.org/10.1038/35013030.

    • Search Google Scholar
    • Export Citation
  • Sánchez, C., J. Methven, S. Gray, and M. Cullen, 2020: Linking rapid forecast error growth to diabatic processes. Quart. J. Roy. Meteor. Soc., 146, 35483569, https://doi.org/10.1002/qj.3861.

    • Search Google Scholar
    • Export Citation
  • Schäfer, S. A. K., and A. Voigt, 2018: Radiation weakens idealized midlatitude cyclones. Geophys. Res. Lett., 45, 28332841, https://doi.org/10.1002/2017GL076726.

    • Search Google Scholar
    • Export Citation
  • Schäfler, A., and Coauthors, 2018: The North Atlantic Waveguide and Downstream Impact Experiment. Bull. Amer. Meteor. Soc., 99, 16071637, https://doi.org/10.1175/BAMS-D-17-0003.1.

    • Search Google Scholar
    • Export Citation
  • Seifert, A., and K. Beheng, 2006: A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 2: Maritime vs. continental deep convective storms. Meteor. Atmos. Phys., 92, 6782, https://doi.org/10.1007/s00703-005-0113-3.

    • Search Google Scholar
    • Export Citation
  • Shupe, M. D., and Coauthors, 2008: A focus on mixed-phase clouds: The status of ground-based observational methods. Bull. Amer. Meteor. Soc., 89, 15491562, https://doi.org/10.1175/2008BAMS2378.1.

    • Search Google Scholar
    • Export Citation
  • Smith, P. J., 2000: The importance of the horizontal distribution of heating during extratropical cyclone development. Mon. Wea. Rev., 128, 36923694, https://doi.org/10.1175/1520-0493(2000)128<3692:TIOTHD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Steinfeld, D., M. Boettcher, R. Forbes, and S. Pfahl, 2020: The sensitivity of atmospheric blocking to upstream latent heating—Numerical experiments. Wea. Climate Dyn., 1, 405426, https://doi.org/10.5194/wcd-1-405-2020.

    • Search Google Scholar
    • Export Citation
  • Sun, Z., and K. P. Shine, 1994: Studies of the radiative properties of ice and mixed-phase clouds. Quart. J. Roy. Meteor. Soc., 120, 111137, https://doi.org/10.1002/qj.49712051508.

    • Search Google Scholar
    • Export Citation
  • Tao, W.-K., J. Simpson, and M. McCumber, 1989: An ice-water saturation adjustment. Mon. Wea. Rev., 117, 231235, https://doi.org/10.1175/1520-0493(1989)117<0231:AIWSA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Tremblay, A., P. A. Vaillancourt, S. G. Cober, A. Glazer, and G. A. Isaac, 2003: Improvements of a mixed-phase cloud scheme using aircraft observations. Mon. Wea. Rev., 131, 672686, https://doi.org/10.1175/1520-0493(2003)131<0672:IOAMPC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Vié, B., J.-P. Pinty, S. Berthet, and M. Leriche, 2016: LIMA (v1. 0): A quasi two-moment microphysical scheme driven by a multimodal population of cloud condensation and ice freezing nuclei. Geosci. Model Dev., 9, 567586, https://doi.org/10.5194/gmd-9-567-2016.

    • Search Google Scholar
    • Export Citation
  • Wegener, A., 1926: Thermodynamik der atmosphäre. Anwendung der Thermodynamik, Springer, 156–189.

  • Wurtz, J., D. Bouniol, B. Vié, and C. Lac, 2021: Evaluation of the AROME model’s ability to represent ice crystal icing using in situ observations from the HAIC 2015 field campaign. Quart. J. Roy. Meteor. Soc., 147, 27962817, https://doi.org/10.1002/qj.4100.

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  • Yau, M. K., and R. R. Rogers, 1996: A Short Course in Cloud Physics. Elsevier Science, 304 pp.

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