1. Effects of 3D radiation on cloud evolution
(Photo courtesy of
Steven Dobbie, University of Leeds
Leeds, April 6

2. Research Activities Dr Sat Ghosh - Diffusivity of H2O (FIRE II)
- Mid-lat SH cirrus: Emerald I case – microphysics
- Radiative forcing of multi-component aerosol
Dr John Marsham
- Mid-lat NH cirrus: Chilbolton case – effects of shear
- Initialisation, validation, resolution, 3D runs, fall velocities

3. Research Activities Adrian Hill
- Semi-direct/indirect effects: effect of soot on clouds.
Clare Allen
- Tropical cirrus: evolution of anvil with emphasis on
sensitivity to outflow region and ice nuclei.
Gourihar Kulkarni (GK)
- Nucleation chamber/microphysics.

4. Research Activities My activities
- Growth and optical properties of seasalt aerosols (direct eff)
- Treatment of overlap and inhomogeneity for radiation
- 3D radiative effects on cloud evolution

5. Clouds in GCMs Diagnostic Prognostic ice/liquid water content
‘Statistical’ Prognostic schemes (eg Tompkins 2002).
Plane parallel homogeneous (PPH) clouds introduce bias (Cahalan 1994, Barker et al 1998 and Larson et al 2001)

6. Motivation Climate is very sensitive to cirrus
Cirrus are poorly understood (GCSS WG2)
Inhomogeneity and radiative properties

7. Motivation Observed cloud structure (1, 2-3, 5 km)
Smith and Jonas, ‘96, ‘97
Quante et al., ‘96
Demoz et al., ‘96
Gultepe and Starr, ‘95
Starr et al., ‘92
Starr and Cox, ‘85
GCM sub-grid inhomogeneity treatment

8. The Large Eddy Model The LEM: 2D mode (100 km domain)
100 m horizontal resolution, 125 m vertical resolution
3 phase microphysics with dual moment ice/snow
Rigid top and bottom
Periodic lateral boundary conditions
Fu-Liou radiation model

9. Initial Profiles
UK LES CRM

10. IWC Time Evolution

11. Cellular Development

12. Length-scales of inhomogeneity

13. Inhomogeneity and Cloud Depth

14. Spectral Dependence

15. Radiative Heating Profiles

16. Cloud Lifetime

17. Radiation and Latent Stability Numbers

18. Instability (Rad. Influenced)

19. Instability (No Rad.)

20. Previous studies
Wide range of results between cirrus models even for simple idealised case studies (Starr et al 2000).
There are few comparisons of CRM results with observations for ice clouds. In existing comparisons modelled inhomogeneity can be much less than observed (eg Benedetti and Stephens 2001)

21. Observed and LEM profiles

22. Ice Water Contents (IWCs)
Radar
LEM
Approx km

23. Effects of shear on sub-grid variability
9.25 km
8.25 km
Orange is with shear, Black is without (all are over 50 km in the horizontal and 375 m in the vertical).
Ice water content
Total Water Content

24. Effect of shear on vertical correlation of IWC

25. Motivation
Question: By neglecting 3D radiative transfer, are we missing an important influence on cloud evolution or can it be neglected?

26. PPA and ICA/IPA Radiaton

27. Monte Carlo Radiation

28. Radiative smoothing scale

30. Inhomogeneous cirrus layersMC
IPA

31. Inhomogeneous cirrus layers
Rmc=0.219
R4s=0.225
Rnr=0.196

32. Inhomogeneous cirrus layers

33. Finite cirrus layer MC
IPA

34. Finite cirrus layer Rmc=0.423 R4s=0.396 Rnr=0.372

35. Finite cirrus layer

36. Summary/Conclusions Radiative effects are important for cirrus
Inhomogeneous stratiform layers: 2-3%
Finite, inhomogeneous cirrus clouds: 6-7%

37. Further Work
Realistic clouds (Chilbolton,FIREII, Emerald1, Crystal Face)
with various geometries
Longer duration simulations
Quantify effects on cloud microphysics
Effect for PDFs?
Understand 3D radiation in presence of other effects, like shear
Other cloud types

38. [G. Heymsfield]
Tropical Anvils

41. Inhomogeneous layer

42. Finite cirrus layer

43. 16 July C-F Anvil Mission P. Lawson D. Baumgardner A. Heymsfield

44. Observations:. Supersaturation Frequently Observed in the Upper
Observations: Supersaturation Frequently Observed in the Upper Troposphere
[J. Smith, A. Anderson, P. Bui]
We observe supersaturation both in clear air and in the presence of cirrus.

45. Observed and LEM profiles
Reading, Dec 8

46. Microphysics

47. Effects of shear on sub-grid variability
9.25 km
8.25 km
Orange is with shear, Black is without (all are over 50 km in the horizontal and 375 m in the vertical).
Ice water content
Total Water Content

48. Effects of shear on sub-grid variability
6.5 km
4.7 km
Orange is with shear, Black is without (all are over 50 km in the horizontal and 375 m in the vertical).
Ice water content
Total Water Content

49. Effect of shear on vertical correlation of IWC

50. Conclusions Further Work
Distributions of modelled IWCs and total water contents are well described by beta functions.
Shear tends to decrease the variance in IWC and total water contents.
The decorrelation of IWC with height is initially linear (as suggested in Hogan and Illingworth 2002). At larger vertical separations correlations tend to be zero for zero shear and are more complex for inhomogenous clouds with large wind-shears.
Further Work
Improve the initialisation of the LEM.
Study a better observed case (with aircraft observations).
(Acknowledgements: Robin Hogan, Reading University)