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Topic #3: Mixed-phase clouds and glaciation

Topic #3: Mixed-phase clouds and glaciation. Co-leaders Ulrike Lohmann (modeling) Ken Sassen (remote sensing) Paul Field (in-situ). Participants

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Topic #3: Mixed-phase clouds and glaciation

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  1. Topic #3: Mixed-phase clouds and glaciation Co-leaders Ulrike Lohmann (modeling) Ken Sassen (remote sensing) Paul Field (in-situ) Participants In-situ: Field, McFarquhar, Krämer, Wex, Lawson, Johnson, Schwarzenböck, Crosier, Meyer, DeMott, Jourdan, Jackson, Henneberger, Niedermeier, Hamilton, Minikin Remote sensing: Wendisch, Bühl, Straka Modeling: Flossmann, Straka, Franklin

  2. General Description of Topic Theme and Objectives of the Topic Working Group • 1) What do we currently understand about mixed phase cloud - how do they form, what controls their glaciation rates, what are the important microphysical/dynamic processes, importance of ice nucleation modes, etc. • 2) What do we still not understand and why? • 3) What is the importance of mixed phase clouds on weather and climate? • 4) How can we improve our understanding?

  3. Mixed-phase: What do we know? • It occurs commonly, decreasing in frequency with decreasing temperature Moss+Johnson 1994

  4. Mixed-phase occurs in multiple regimes Arctic Layer clouds – Morrison et al. 2012 Shear regions in frontal cloud – Hogan et al. 200X Image of shear driven slw in frontal Mesoscale Alpine Programme UoWash

  5. Mixed-phase: the last three years • ~40 papers with mixed-phase in title, ~200 with MPC mentioned in abstract • In-situ observation (e.g. Lawson, ICE-T, Henneberger et al., 2013) • Cloudsat/Calipso data set analyses (e.g. Delanoe+Hogan 2010) • Mixed-phase stratus simulations (e.g. model intercomparisons: Morrison et al. 2011, Muhlbauer et al 2010) • Further exploration of Squires equation: • IN impacts e.g. Ervens et al. 2012 • CCN impacts e.g. Lance et al. • Effects of turbulence e.g. Field et al. 2013.

  6. Mixed-phase: in-situ observations • examples from: • Paul Lawson (SPEC), • Robert Jackson (aircraft observations) • Jan Henneberger et al., 2013: Digital in-line holography • Jessica Meyer & Martina Krämer      (aircraft observations)

  7. Glaciation indirect effect (Lohmann 2002) Riming indirect effect (Borys et al. 2004) Thermodyna-micindirect effect (Rangno & Hobbs 2001)

  8. M-PACEOctober 2004 Pristine Conditions Open ocean Few cloud droplets Ice multiplication Precipitation Measurements by ~10 instruments aerosol properties cloud microphysics atmospheric state. Polluted Conditions Sea Ice Many cloud droplets Ice nucleation Little precipitation Measurements by ~40 instruments aerosol properties cloud microphysics radiative energy atmospheric state. ISDACApril 2008

  9. ISDAC M-PACE Normalized Frequency

  10. ISDAC M-PACE Normalized Frequency LWC < for ISDAC than M-PACE, consistent with more open water during M-PACE

  11. ISDAC M-PACE Normalized Frequency

  12. ISDAC M-PACE Normalized Frequency Nliq > for ISDAC than M-PACE, consistent with presence of more aerosols/CCN

  13. ISDAC M-PACE Normalized Frequency

  14. ISDAC M-PACE Normalized Frequency rel < for ISDAC than M-PACE,

  15. ISDAC M-PACE Normalized Frequency Nice < for ISDAC than M-PACE, consistent with thermoynamic indirect effect

  16. Convair 580 Measurements in Arctic Single-Layer Mixed-Phase Cloud 27 April 2008

  17. Convair 580 Measurements in Arctic Single-Layer Mixed-Phase Cloud 27 April 2008

  18. SPEC Learjet Repeated Hawkeye/3V-CPI Measurements in ICE-T 19 July 2011 Tropical Cu All Particles > 100 mmare Ice Rapid Transition Zone as Millimeter Drops Rapidly Freeze First Ice are < 100 mm Particles in Field of Millimeter Drops

  19. SPEC Tethered Balloon CPI Measurements of Mixed-Phase Cloud at -32C on 26 January 2009 at South Pole Station (Lawson et al. 2010)

  20. Mixed-phase observations at Jungfraujoch as compared to elsewhere Figures from Henneberger (2013)

  21. Mixed-phase clouds: Remote Sensing (Ken Sassen, Johannes Bühl) • Overview: Remote sensing of MCP properties has progressed significantly with growing multiple remote sensor field sites, algorithm development, and CALIPSO/CloudSat global satellite studies. • Sensors: Polarization lidar for cloud particle phase and aerosols; Millimeter-wave Doppler Radar for ice particle detection; Dual-channel Microwave Radiometer for liquid water path measurement.

  22. Leipzig Punta Arenas • Recent studies of mixed-phase layered cloud occurrence by TROPOS at Leipzig and Punta Arenas • Comparison between northern (polluted) and southern (less polluted) atmosphere show considerable differences in cloud freezing temperatures. • Connection with locally available ice nuclei? • Higher ice detection sensitivity of Radar does NOT alone explain the difference between Punta Arenas and Leipzig References: Seifert et al. 2010, JGR Zhang et. al 2010, GRL Kanitz et. al 2011, GRL Bühl et. al 2013, GRL (submitted)

  23. Quantification of heterogeneous ice formation with help of remote sensing and in-situ measurements of Hogan et. al, 2006 • A lot of cloud cases at temperatures > -15°C show very low ice content and low ice to liquid mass ratio • What ice content is necessary to significantly influence cloud microphysics? Example Case Study Lidar = cloud top detector : Radar = ice detector : (graphs from Bühl et. al, 2013, submitted)

  24. Applications… • Radar and Lidar Algorithms: • FIGURE 6 from Wang et al., 2004: Studying altocumulus with ice virga using ground-based active and passive remote sensors. J. Appl. Meteor., 43, 449-460. (I can’t grab this figure from home!)

  25. Lidar depolarization of transported Saharan dust (top, <6 km) indicating brief glaciation of Ac at ~-9C cloud temperature.

  26. Applications… • Radar cloud glaciation- model studies (Sassen and Khvorostyanov, 2007:Microphysical and radiative properties of mixed phase altocumulus: A model evaluation of glaciation effects. Atmos. Res.,84, 390-398.) Figure below shows that cloud droplet Z are too low to be detectable by most radars, but the ice development during glaciation is clear.

  27. Applications…

  28. Global distribution of supercooled Altocumulus from CloudSat/CALIPSO (2-y average): Sassen and Wang, 2012

  29. Mixed-phase: modeling • Aerosol effects on orographic MPCs and precipitation (Zubler et al. 2011) • Persistence of Arctic MPCs (Morrison et al. 2011, 2012; Klein et al., 2009; deBoer et al., 2011; Lance et al., 2011; Fan et al., 2011; Ovchinnikov et al., 2011) • Influence of ice habit on glaciation and evolution (Sulia & Harrington, 2011; Avramov and Harrington, 2010) • Impact of aerosols on MPCs and the radiation balance (Lohmann and Hoose, 2009; Hoose et al., 2010; Salzmann et al., 2010; Storelvmo et al. 2010) • Importance of the Bergeron-Findeisen process for MPCs (Lohmann and Hoose, 2009; Storelvmo et al., 2008; Fan et al., 2011)

  30. Zubler et al., JAS, 2011

  31. Occurrence of IWC/TWC Lohmann et al.,ACP, 2007; Obs. from Korolev et al., 2003

  32. Introduction of the Korolev (2007) Bergeron-Findeisen process in ECHAM Lohmann and Hoose, 2009

  33. Introduction of the Korolev (2007) Bergeron-Findeisen process in ECHAM Lohmann and Hoose, 2009

  34. Lohmann and Hoose, 2009

  35. Indirect aerosol effect in global climate models with and without mixed-phase clouds

  36. Mixed-phase: What we do know? • Active physical processes are: • Competition between ice and liquid for vapour (e.g. Korolev, 2007). Special case - WBF process when w~0 Squires supersaturation evolution equation • Need to know Nd(r), Ni(D), m-D, Cap, ventilation, Si, w, T, P • Riming • Need to know Nd(r), Ni(D), v-D, collection kernel • (Lowenthal et al At. Env 2011 use oxygen isotope analysis to identify ice mass grown by riming or deposition)

  37. Mixed-phase: What we do know? • Exploring the Squires equation • Simple vertical motion • Periodic motion • Turbulent motion

  38. Mixed-phase: what we know less about? • Secondary ice production • Hallett-Mossop - are there any new lab experiments? • Other multiplication effects These processes short-circuit the primary nucleation mechanisms – only very few IN required – how few is sufficient?

  39. Mixed-phase: what do we know less about? • Mixed-phase as a function of scale: • What is the frequency of occurrence of supercooled/mixed/ice regions of length, L ? • Large scale models may assume too much overlap between ice and liquid. Larson et al. 2011 parameterize the correlations between different hydrometeor species based on LES (From Korolev 2007 JAS)

  40. Remaining Unknowns and Uncertainties • Capacitance/ventilation of ice particles – vapour sink term • Primary ice nucleation: • Arctic stratus • Cu glaciation at -10ºC • Longevity of MPCs: • Importance of vertical velocity vs. aerosols • Climate impact of MPCs: dominance of the glaciation or de-activation indirect effect

  41. Gaps to be tackled • Quantifying the horizontal as well as vertical distribution of mixed-phase/liquid/ice regions. • Can we make more use of LES? • Identify and quantify the secondary production processes in the field and the lab • Improved representation of (PSD * Cap * ventilation): proportional to sink of vapour

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