Brief review of my previous work in Beijing

1. Brief review of my previous work in Beijing Xiaofeng Wang Directed by : GuoguangZheng HuiwenXue

2. Two parts • A study of shallow cumulus cloud droplet dispersion by large-eddy simulations Wang, X., H. Xue, W. Fang, and G. Zheng, ActaMeteorologicaSinica, 2011(25), 166-175. • Analysis of microphysical properties of stratiform clouds in North China Xiaofeng Wang, Thesis for master degree, 2011 Actually, I think my previous work is just some simple academic practice.

3. Part I: A study of shallow cumulus cloud droplet dispersion by large-eddy simulations • Introduction • Model description and case setup • Aerosol effects on droplet dispersion • Effects of homogeneous mixing • Parameterization of cloud optical depth • Summary

4. Introduction • Aerosol indirect effects complicate the assessment of aerosol and cloud effects on climate, making it full of uncertainties. • In GCMs, reasonable parameterizations of clouds and other small-scale processes are important. Effective radius (re) is usually used to parameterize cloud optical depth (). where H: physical thickness of cloud；ρw :water density；LWC: liquid water content；CDNC:cloud droplet number concentration，β is related to cloud spectrum.

5. ε is relative dispersionof cloud droplet spectrum，defined as the ratio of standard deviation (σr) to mean radius (rm) of cloud spectrum. • β increases with ε. • If only monodisperse spectra are considered (ε=0, β=1), re is underestimated, and thus , albedo and cooling effect on climate is overestimated. • Now, in present GCMs, polydisperse spectra are considered (ε0).

6. How can aerosol concentration affect relative dispersion? • Positive correlation: (Liu and Daum, 2002; Liu et al., 2006; Lu et al., 2008; Pawlowska et al., 2006; Peng et al., 2007; Xue and Feingold, 2004; Yum and Hudson, 2005) • Negative correlation: (Lu and Seinfeld, 2006; Lu et al., 2007; Martins and Dias, 2009; Miles et al., 2000; Pawlowska et al., 2006; Wang et al., 2009) • No obvious dependence: (Deng et al., 2009; Lu and Seinfeld, 2006; Lu et al., 2008; Miles et al., 2000; Warner, 1969; Zhao et al., 2006) • This paper focuses on the aerosol and homogeneous mixing effects on relative dispersion.

7. Brief model description • Large-eddy simulation: the same as the LES model used here. • Sounding profiles: BOMEX • 4 cases: • aerosol concentration : 25, 100, 2000 /mg; • 25 /mg, but artificially turn off gravitational sedimentation and droplet collision- coalescence. • Parcel model • Used to calculate the vertical profile of the adiabatic liquid water content (LWCa). • Initial conditions: from the BOMEX profile. • Chemical component: ammonium sulfate, with a lognormal spectrum • Aerosol concentration: 50 /mg.

8. Aerosol Effects Mean radias, standard deviation and relative dispersion decrease with increasing aerosol loading. This is similar to another LES results but for Sc. (Lu et al., 2007) Collision-Coalescence takes effect.

9. Effects of mixing • Homogeneous mixing: turbulent mixing is faster than evaporation, so all droplets are exposed to the same undersaturated air. • Measure of mixing: adiabatic ratio or factor (AF/AR), defined as LWC/LWCa. • For cumulus clouds, AF is small, and thus mixing is very strong. This is consistent with other cumulus obervations (Lu et al., 2008; Arabas et al., 2009).

10. Aerosol has insignificant effects on relative dispersion in larger AF regions. The results are similar to the LES results for Sc. (Lu and Seinfeld, 2006) In large AF regions, effective radius is large, standard deviation is small, and relative dispersion is small.

11. Parameterization of optical depth for low clouds kEis extinction coeffecient， QEis extinction effeciency ( 2, for low clouds)。 More aerosols induce large cloud optical depth. The difference between detailed calculation and parameterization is slight.

12. Summary • Aerosols, collision-coalescence, and homogeneous mixing influence the relative dispersion of cloud droplet spectrum. • Parameterization of optical depth for low clouds is plausible.

13. Part II: Analysis of microphysical properties of stratiform clouds in North China • Introduction • Data • Results • Summary

14. Introduction • Stratiform clouds are the main precipitating clouds in North China. • A well understanding of the microphysical properties of stratiform clouds will help to improve the operation of weather modification. • Stratiform clouds are important in climate and global energy budget.

15. Data • Aircraft in-situ measurements from China Meteorological Administration.

16. Result: Weather on Apr.18, 2011 700hpa 500hpa Short wave trough Warm center Surffient water vapor Sruface Low pressure center

17. 2009-04-18 • Fight tracks: • Shijiazhuang Cheyenne IIIA: • upper layer of clouds • Datong Yun-12: • middle layer of clouds • Zhangjiakou Yun-12: • lower layer of clouds

18. Time series Small particles Large particles SJZ DT ZJK SJZ DT ZJK • When CDNC is large，effective radius is large，indicating aerosol effects is less significant than meteorological effects. • Upper layer: more large particles, contributing more to LWC. • Lower layer: more small particles。

19. Vertical profiles Shijiazhuang Datong Zhangjiakou Particle radius is lower than 25μm. • Aerosol concentration and CCN concentration decrease with height • CDNC and LWC decrease with height, and in the lower layer of clouds they vary very much. • Effective radius keeps constant.

20. Weather on May 1, 2009 500hpa 700hpa trough Warm center Surface Lower center

21. 2009-05-01 • Fight tracks: • Shijiazhuang Cheyenne IIIA: • upper layer of clouds • Datong Yun-12: • middle layer of clouds • Zhangjiakou Yun-12: • lower layer of clouds

22. Time series Small particles Large particles SJZ DT ZJK SJZ DT ZJK • When CDNC is large, effective radius is large, indicating aerosol effects is less significant than meteorological effects. • Upper layer: more large particles, contributing more to LWC. • Lower layer:more small particles。

23. Vertical Profiles SJZ DT ZJK Radius is lower than 50μm • Aerosol concentration and CCN concentration decrease with height. In the case of Zhangjiakou, aerosol concentration keeps constant with height. • CDNC decrease with height, LWC is larger in the middle layer and in the lower layer of clouds they vary very much. • Effective radius increases with height.

24. Aerosol effects on microphysics SJZ DT ZJK 4-18 Radius is lower than 25μm Vertical profiles of properties of cloud spectrum Standard deviation keeps constant; Mean radius： 04-18, vary little with height; 05-01, increase。 Relative dispersion： 04-18, decrease with height; 05-01, increase with height. 5-1

25. As aerosol concentration increases, CCN and CDNC increase.

26. As aerosol concentration increases，standard deviation, mean radius, and relative dispersion decreases. The range of their variations also narrows. These results are very consistent with others observed in North China. (Zhao et al., 2006; Deng et al, 2009)

27. Summary • The microphysical properties of stratiform clouds in North China ： • 1) Aerosol and CCN concentration decrease with height. • 2) CDNC decreases with height. • In the lower layer, CDNC varies very much. • 3) LWC may decrease with height, or have maximum in the middle layer. • 4) Effective radius increases with height or keeps constant. • Aerosol effects on cloud spectrum： • 1) standard deviation keeps constant； • On Apr. 18，mean radius varies a little with height, and relative dispersion decreases. • On May 1, mean radius and relative dispersion increases with height. • 2) As aerosol concentration increases, CCN and CDNC increase, • standard deviation, mean radius, relative dispersion and their variation decreases.