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Yali Luo State Key Lab of Severe Weather (LaSW) Chinese Academy of Meteorological Sciences

Multi-Layer Arctic Mixed-Phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity Experiments. Yali Luo State Key Lab of Severe Weather (LaSW) Chinese Academy of Meteorological Sciences

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Yali Luo State Key Lab of Severe Weather (LaSW) Chinese Academy of Meteorological Sciences

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  1. Multi-Layer Arctic Mixed-Phase Clouds Simulated by a Cloud-Resolving Model:Comparison with ARM Observations and Sensitivity Experiments Yali Luo State Key Lab of Severe Weather (LaSW) Chinese Academy of Meteorological Sciences Co-authors: Kuan-Man Xu (LaRC), Hugh Morrison (NCAR), Greg McFarquhar (U Illinois), Zhien Wang (U Wyoming), Gong Zhang (U Illinois) Polar Cloud Working Group Breakout Session II, 4th Pan-GCSS Meeting June 4th 2008; Toulouse, France

  2. Outline • Introduction • Large-scale background and observations • Model and simulations • Comparing Baseline results with observations • Results from sensitivity experiments

  3. Introduction • The UCLA/CAMS CRM is used to simulate the multiple-layer mixed-phase stratiform (MPS) clouds that occurred during a 3.5-day sub-period of the M-PACE (14Z 5 Oct - 02Z 9 Oct) • The large-scale forcing data used is the same as that for the ARM inter-comparison of model simulations • Baseline results are compared to the M-PACE observations • Sensitivity experiments are conducted to explore the possible mechanisms for the formation and evolution of the multiple-layer MPS clouds

  4. Outline • Introduction • Large-scale background and observations • Model and simulations • Comparing Baseline results with observations • Results from sensitivity experiments • Conclusions

  5. High pressure over the pack ice to the northeast of the Alaska coast 201 km 360 km Toolik Lake Large-scale background Barrow Midlevel low pressure system drifted along the northern Alaska coast North Slope of Alaska (NSA)

  6. Observations of Cloud properties • Occurrences and locations of mixed-phase cloud layers • Liquid water path • Bulk cloud microphysical properties

  7. Other observations used • Aerosol properties (for microphysics calculation) • Surface precipitation rate, temperature, moisture (for model evaluation; produced by the ARM analysis)

  8. Outline • Introduction • Large-scale background and observations • Model and simulations • Comparing Baseline results with observations • Results from sensitivity experiments • Conclusions

  9. UCLA/CAMS CRM(University of California at Los Angeles/Chinese Academy of Meteorological Sciences) • Anelastic dynamic framework • Third-order turbulence closure • d-four-stream radiative transfer scheme • Two-moment microphysics parameterization Krueger, S. K., 1988: Numerical simulation of tropical cumulus clouds and their interaction with the subcloud layer. J. Atmos. Sci., 45, 2221-2250. Luo, Y., etc., 2008: Arctic mixed-phase clouds simulated by a cloud-resolving model: Comparison with ARM observations and sensitivity to microphysics parameterizations. J.Atmos. Sci., 65, 1285-1303.

  10. Large-scale forcing data • Large-scale advection of temperature and moisture • Surface fluxes of latent and sensible heat • Skin temperature • Surface broadband albedo Klein, S., A. Fridlind, R. McCoy, G. McFarquhar, S. Menon, H. Morrison, S. Xie, J. J. Yio, and M. Zhang (2006), Arm Cloud Parameterization and Modeling Working Group – GCSS Polar Cloud Working Group model intercomparison. Procedures for ARM CPMWG Case 5/GCSS Polar Cloud WG SCM/CRM/LES Intercomparison Case f2004: ARM Mixed-phase Arctic Cloud Experiment (M-PACE): October 5-22, 2004. Xie, S., S. A. Klein, M. Zhang, J. J. Yio, R. T. Cederwall, and R. McCoy (2006), Developing large-scale forcing data for single-column and cloud-resolving models from the Mixed-Phase Arctic Cloud Experiment, J. Geophys. Res., 111, D19104, doi:10.1029/2005JD006950.

  11. List of simulations • Baseline: standard baseline simulation • noLSforcing: neglecting large-scale advective forcing • noSfcFlx: neglecting surface fluxes of latent and sensible heat • noLWrad: neglecting longwave radiative cooling/heating • noIce: neglecting ice-phase microphysical processes • IN50th：decreasing IFN concentration from 0.16/L to 0.003/L • IN50：increasing IFN concentration from 0.16/L to 8/L

  12. Outline • Introduction • Large-scale background and observations • Model and simulations • Comparing Baseline results with observations • Results from sensitivity experiments • Conclusions

  13. Baseline Results: Time-height distribution of horizontal-averaged LWC (shades) and IWC (lines) Time (hrs from 14Z October 5, 2004)

  14. Baseline Results: Occurrences of multiple-layer MPS clouds

  15. Cloud Base Height Cloud Top Height Cloud Physical Thickness Baseline Results: Histograms ofcloud-base height, cloud-top height and cloud physical thickness of the 1st MPS cloud layer CRM Baseline Observations Lower!

  16. Baseline Results: Histograms ofcloud-base height, cloud-top height and cloud physical thickness of the 2nd MPS cloud layer Observations CRM Baseline Cloud Base Height Cloud Top Height Too homogeneous in the horizontal! Cloud Physical Thickness Thicker!

  17. Aircraft Obs. CRM Baseline Baseline Results: Vertical profiles of in-cloud LWC Subperiod A Subperiod B Subperiod C

  18. Baseline Results: Vertical profiles of in-cloud nc Aircraft Obs. CRM Baseline Subperiod A ? CCN activation parameterization Subperiod B ? Subperiod C

  19. Baseline Results: Vertical profiles of in-cloud IWC Aircraft Obs. CRM Baseline Subperiod A Reproduced the larger IWCs below 1.5 km; Subperiod B but a few times smaller than observations. Subperiod C

  20. Baseline Results: Vertical profiles of in-cloud ni Aircraft Obs. CRM Baseline Subperiod A Differ by one order of magnitude! Subperiod B Subperiod C

  21. Baseline Results: Surface precipitation Dashed line: CRM Baseline Solid line: Observations 2 underestimated delayed 1 3

  22. Summary of baseline results • The Baseline simulation reproduces the dominance of single- and double-layer MPS clouds revealed by the MMCR-MPL observations and qualitatively captures the major characteristics in the vertical distributions of LWC, nc, ISWC and nis and their interperiod differences suggested by the aircraft observations. • However, • The simulated first MPS cloud layer is too low and nc within the lower layer decreases with height, in contrast to the relatively constant nc revealed by the observations. These could be due to uncertainties associated with the parameterizations (e.g., turbulence, droplet activation, radiation), and the forcing data. • The simulated second cloud layer is too thick with too large LWC, causing too strong LW cooling and negative biases in temperature. • Both simulated cloud layers contain too few ice crystal numbers and too small ice crystal masses, indicating missing of ice enhancement mechanisms in the microphysics scheme and resulting in the underestimate of surface precipitation rates.

  23. Outline • Introduction • Large-scale background and observations • Model and simulations • Comparing Baseline results with observations • Results from sensitivity experiments

  24. Time-height distribution of LWC and ISWC :Baseline vs. noLSadv Baseline noLSadv T advection qv advection noSfcFlx cooling moistening

  25. Time-height distribution of LWC and ISWC :Baseline vs. noSfcFlx noSfcFlx Baseline LH: 185 W m-2 SH: 35 W m-2

  26. Time-height distribution of LWC and ISWC:Baseline vs. noLWrad Baseline noLWrad LW radiative cooling/heating in Baseline

  27. IN50th Time-height distribution of LWC and ISWC:Baseline vs. noIce and IN50th Baseline noIce The temporally averaged LWP is increased by a factor of 3 in noIce compared to the Baseline, suggesting depletion of liquid droplets by ice crystals in Baseline.

  28. Time-height distribution of LWC and ISWC:Baseline vs. IN50 Baseline IN50 No MPS clouds are formed in IN50 experiment (while magnitude of the vertically integrated ice and snow mass increases by a factor of 6).

  29. Summary of sensitivity experiments LW radiative cooling Bergeron process LW radiative warming LS advection Bergeron process Surface fluxes of latent and sensible heat

  30. End. Thanks for your attention!

  31. Summary of sensitivity experiments LW radiative cooling Bergeron process LW radiative warming LS advection Bergeron process Surface fluxes of latent and sensible heat

  32. Time-height distribution of LWC and ISWC :Baseline vs. noMicLat noMicLat Baseline a larger magnitude of LWC in the interior of the MPS cloud layers Heating/cooling due to phase change in Baseline

  33. Observations of Aerosol properties Aerosol composition: ammonium bisurfate (NH4HSO4) with an insoluble fraction of 30% observed and fitted dry aerosol size distribution

  34. Observations of Ice nulcei (IN) number concentration • Active IN acting in deposition, condensation-freezing, and immersion-freezing modes: a mean of 0.16 L-1 • Contact-freezing IN: a function of temperature (Meyers et al., 1992)

  35. Field measurements: Profiles of the sample numbers for liquid water content (solid lines) and ice water content (dashed lines), respectively, in each height bin of 400 m during the three missions that the UND Citation took on October 5 (a), October 6 (b), and October 8 (c), 2004.

  36. CRM Baseline Baseline-Analysis water vapor mixing ratio temperature Baseline Results: Temperature and moisture

  37. Baseline Results: Time series of LWP MWR retrieval (81 g m-2) Baseline (79 g m-2)

  38. Results from sensitivity tests: eddy kinetic energy

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