Aerosol-cloud research at IMAU Geert-Jan Roelofs BBC workshop KNMI, 18-19 October 2004

1. Aerosol-cloud research at IMAU Geert-Jan Roelofs BBC workshop KNMI, 18-19 October 2004

2. Topics • precipitation formation • cloud processing of aerosol

3. IMAU cloud parcel model • air parcel with aerosol and water vapor • Köhler microphysics • pseudo-adiabatic ascent -> cloud drop activation • collision/coalescence -> drizzle formation • multi-phase chemistry • aerosol/cloud water: 400 bins • precipitation water: 75 bins

5. precip cloud water total LWC Research question: How do aerosol properties influence the drizzle formation efficiency? • Sensitivity study: • different aerosol populations • (Jaenicke, 1988) • - 50% soluble • - base case concentration Na • - vary between Na/3 and Na*3 • - vary updraft speed between 5 and 200 cm/s

6. IMAU cloud parcel model rural aerosol, Na updraft speed 50 cm/s Na/2 Na Na*2

7. Na/2 Na Na*2 LWC>50 r>50

10. -0% -40 mm -5% -80 mm +4% -6 mm +0.5% -25 mm N -> N*2

11. Other sensitivity studies: - solubility - organic aerosol - gaseous HNO3 - internal/external mixing (see: Roelofs and Jongen, JGR, accepted, 2004)

12. PHOENICS Particles of Human Origin Extinguish Natural solar Irradiance in the Climate System (EVK2-CT-2001-0098) • goals: • - assess direct climate effects of aerosol • - evaluate impact of European emissions • tools: • - climate model ECHAM • aerosol module M7 • task IMAU: • parameterization for cloud processing

13. M7 4 soluble and 3 insoluble aerosol modes Characterized by N, Dr, s (Wilson et al., 2001)

15. Cloud chemical processing of aerosol after before

16. Cloud processing parameterization • Basic requirements: • prediction of cloud drop number concentration • calculate in-cloud sulfate formation • account for internal/external chemical mixtures • account for drop size and chemical variabilities

17. Scheme for cloud processing parameterization ECHAM cloud parameterization: LWC updraft speed precip formation M7: Na ras (for 7 aerosol types) parameterization: Nc -> rc DSO4 precip reducesNc return to M7: Na’ ra’ s (for 7 aerosol types)

18. 1.2 3 0.8 2 0.4 1 g/kg 0 % 30 300 20 200 10 100 0 mm 0 cm-3 LWC Smax rc Nc

19. Further research planned at IMAU • the effect of in-cloud spatial variability on precipitation formation and chemistry, e.g., through 1D or 3D cloud modelling with size-resolved mphysics. • study of (in-)organic chemistry with KPP • parameterization of cloud processing

20. Observations necessary for cloud processing validation • - atmospheric dynamics • below the cloud: aerosol size distribution, chemical composition, solubility • in-cloud: drop size distribution at several altitudes, (size-resolved) aqueous phase chemical composition and pH • during cloud lifetime: evolution of precipitation intensity, precipitation chemical composition and pH • after cloud evaporation: aerosol size distribution, chemical composition, solubility

22. Parameterization from Hänel (1987) Key characteristics: - simplified mixture of Köhler and parcel theory with empirical correction - relatively cheap:~ 80 lines of code, few iterations - errors in Smaxand Nc generally below 35% - largest errors for mostly insoluble small aerosol and for low updraft speed (few cm/s) (G. Hänel, Beitr. Phys. Atmosph., 60, 321-339, 1987)

23. increasing updraft velocity solubility background cont., internal mixture sol/unsol

24. Cloud processing / aq phase sulfate prod. • distribution of produced sulfate over cloud droplets depends on their size distribution and chemical composition • parameterization lumps cloud drop bins and chemical matter into two bins: • diluted undiluted • water /cdnc 75% 25% • aerosol mass 20% 80% • eff. O3 oxid + - • eff. H2O2 oxid + +

27. collector droplets R 10 cm/s 50 cm/s 200 cm/s collected droplets r Coalescence is relatively inefficient for r/R <~0.2 and r/R >~0.8, and maximizes inbetween

28. Cloud processing of aerosol

30. Na/2 Na Na*2

31. N -> N*2 r>50 (mm) -5 mm -25 mm LWC>50 (%) +4.5% -0.5%