1. Effects of 3D radiation on cloud evolution
Steven Dobbie
Univ of Leeds

2. Motivation Climate - radiative properties and cloud feedbacks
Weather - heat and moisture distributions and fluxes
Aerosols - distributions and processing
Heterogeneous chemistry
Satellite retrievals

3. Motivation Cirrus cloud structure (1, 2-3, 5, 20 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

4. Clouds in GCMs
Prognostic water schemes

5. More motivation
GCSS WG2 (Starr et al 2000)

6. Research Question What effect does 3D radiation
have on the evolution of clouds?

7. Research Tools
LEM (cloud model)
MC (3D radiation model)

8. IWC Time Evolution
Rad
No-Rad

9. Scales of inhomogeneity
Rad
No-Rad

10. Spectral Dependence

11. Lifetime

12. PPA radiative transfer

13. ICA or IPA

14. Monte Carlo radiation

15. Radiative smoothing DZ

16. Inhomogeneity scale

17. Layer simulations MC
IPA

18. Layer simulations
Rmc=0.219
Rppa=0.225

19. Layer simulations
Wavg
IWC

20. Finite layers MC
IPA

21. Finite simulations
Rmc=0.423
Rppa=0.396

22. Finite simulations
Wavg
IWC

23. Discussion

24. Deep Convection
Gerard Devine (Leeds)

25. Radiative Properties - Reflection
+2.7 %

26. Radiative Properties - Absorption
-1.45 %

27. Summary and Conclusions
Radiation drives inhomogeneity in cirrus
Inhomogeneous stratiform layers: 2-3%
Finite cirrus layers: 6-7%
Competing effects
Deep convection: 2-3% (domain 250km)

28. Future work Deep convection case (Toga-Coare) Observations
Chilbolton, FIREII, Emerald1, Crystal Face
Ensemble of runs
Quantify microphysical effects
Shear

29. Thanks: Peter Jonas, John Marsham, NERC
Contact:

31. Future work
[G. Heymsfield]

33. Stability Numbers

36. Layer simulations

37. Finite simulations

38. Instability (No Rad.)

39. Inhomogeneous layer

40. Effect of depth
Keep?

41. Finite cirrus layer

42. 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

43. Effect of shear on vertical correlation of IWC

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

45. Instability (Rad. Influenced)

46. Observed and LEM profiles

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

48. Chilbolton Case Study

49. Radiative Heating Profiles

50. 16 July C-F Anvil Mission P. Lawson D. Baumgardner A. Heymsfield

51. 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.

52. Observed and LEM profiles
Reading, Dec 8

53. Microphysics

54. 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

55. 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

56. Effect of shear on vertical correlation of IWC

57. 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)