Cloud Processing: Past Work and Issues to Address

1. Cloud Processing: Past Work and Issues to Address Mary BarthNational Center for Atmospheric ResearchMesoscale and Microscale MeteorologyandAtmospheric Chemistry Divisions

3. high photolysis rates ice chemistry transport phase cloud chemistry cloud microphysics and chemical species low photolysis rates size How clouds affect chemical species NO production from lightning washout and rainout

4. transport How clouds affect chemical species

5. 0 50 100 150 200 12 10 8 6 4 2 Transport Cloud Scale: Given good input data, cloud-scale models simulate transport of passive tracers well. For example: Data from STERAO-Deep Convection 1996 (Dye et al., 2000)

6. Transport Cloud Scale: Skamarock et al. (2000) simulated with a 3-d cloud model the tracer transport well

7. Transport Cloud Scale: Chatfield and Crutzen (1984) Dickerson et al. (1987) Scala et al. (1990, 1993) Pickering et al. (1992a,b) Thompson et al. (1994) Wang and Chang (1993a-d) Wang and Crutzen (1995) Hauf et al. (1995) And many others

8. Transport Large Scale: A much bigger challenge, particularly for subgrid convection Mass flux schemes Emmanuel (1991), Feichter and Crutzen (1990), Hack (1994), Tiedtke (1989), Zhang and McFarlane (1995), and others Mass flux + convective-scale w + mesoscale effects Donner et al. (2001) “superparameterization” 2-d cloud resolving model used as convective transport parameterization Grabowski (2001) Khairoutdinov and Randall (2001)

9. Mass flux + convective-scale w + mesoscale effects Donner et al. (2001)

10. “superparameterization” Khairoutdinov and Randall (2001) CCSM/ CRM CCSM Obs.

11. How can we improve convective transport of chemical constituents in large-scale models? • CRMs need to generalize their results • Can we use several CRMs with chemistry in concert to analyze convective transport for all different types of convection? Could the results be brought together to produce general characteristics of tracer transport? • Should superparameterizations include simple cloud chemistry? • Effort to verify model results with observations

12. How clouds affect chemical species washout and rainout

13. Wet Deposition Resolved Clouds: Precipitation rate = r Vr qr where r = air density Vr = fall speed of rain qr = mixing ratio of rain Wet deposition rate = r Vr Cr where Cr = mixing ratio of species in rain If Cr is not predicted in the model,usually Henry’s law is used: Cr = KH R T LWC Cg where KH = Henry’s law coefficient (mol/L-atm) R (L-atm/mol-K), T (K), LWC (cm3 H2O/cm3 air), Cg = gas-phase mixing ratio

14. 1000 r=25 mm H2O2 100 r=10 mm T=30°C 20°C 10°C 1e5 3.5e5 T=10°C HNO3 Is the Henry’s law assumption valid? 2000 25 mm NH3 20 mm H2O2 1000 15 mm 500 10 mm 5 mm 1e4 1e6 1e8 1e10 1e12 This assumption depends on the time step and Henry’s law coefficient

15. Wet Deposition Large-scale Models • Giorgio and Chameides (1986) • Wetdep = - l Cgas where l = Q F TcBL • Flux Method 1 (Barth et al., 2000; Roelofs and Lelieveld, 1995) Wabove  More physically correct, but still is not great Win = qr_prod KH* Cgas Wbelow = Wabove + Win W_below_cloud = (Pr – E) KH* Cgas qr_prod = conversion from CW to rain, Pr = precip. Rate, E= evaporation rate

16. Wet Deposition Subgrid-scale Clouds • Flux Method 2 (work in progress, Hess et al.) Wabove Win = (qr_prod – E) KH* Cgas Wbelow = Wabove + Win  This is even more physically correct, but still needs work: qr_prod = conversion from CW to rain, E= evaporation rate

17. Height (km) MOZART, Giorgi and Chameides (1986) wet deposition MOZART, Flux Method 2 wet deposition Observations

18. Wet Deposition: Needs • Wet deposition depends on both the precipitation rate and the concentration of the species in the precipitation. Do we get the precipitation rate right? If not, what are we missing? • Small cumulus: giant aerosols that form large cloud drops that initiate formation of rain • Deep convection: ice processes • Verification of what parameterizations work or not • Comparisons of nitrate wet deposition model vs. observations (Holland et al.) • Comparisons of wet deposition from global-scale models with cloud-scale models

19. ice chemistry cloud chemistry How clouds affect chemical species

20. Aqueous Chemistry Separation of Species SO2 S(IV) SO4= H2O2 H2O2 HO2 + O2- Cloud Chemistry • Aqueous-phase Chemical Reactions • Modification of Gas-phase Chemistry because Reactants are Separated • Examples:

22. Simulated Sulfate Budget Source: Roelofs et al., 2001; Rasch et al., 2000 E. North America Europe SE Asia Global Percentage of Total Production or Destruction Rate E. N. America Europe SE Asia Global

23. SO2 = 2 ppbv H2O2 = 1 ppbv O3 = 50 ppbv Rates of S(IV) aqueous reactions HSO3- + H2O2 Rate of Reaction (M s-1) SO3= + O3 HSO3- + O3 pH

24. Aqueous Sulfur Chemistry Needs • Representing S(IV)  S(VI) conversion seems to be pretty well in hand. • Minor – Major Improvements: • Importance of representing size and therefore pH of drops better (more on this later) • Importance of getting the LWC correct • Conversion via other reactions e.g. transition metal ion chemistry

25. Does Cloud Chemistry Affect O3 Concentrations? Lelieveld and Crutzen (1991) “Clouds thus directly reduce the concentrations of O3, CH2O, NOx and HOx” Liang and Jacob (1997) “It is found that the maximum perturbation to O3 from cloud chemistry in the tropics and midlatitudes summer is less than 3%”

26. Does Cloud Chemistry Affect O3 Concentrations? Walcek, Yuan, and Stockwell (1997) “… in-cloud reactions strongly influence local O3 production in polluted areas, but longer-term impacts of clouds on O3 formation would be much smaller due to compensating chemical processes in regions remote from NOx emissions.” Barth, Hess, and Madronich (2002) find that O3 is depleted via cloud chemistry by a small amount at low pH and by a more significant amount at high pH. Further, the effect of cloud on photolysis rates can contribute to O3 depletion.

27. Percent Change in Ozone for a Cloud-topped Marine Boundary Layer (z<2 km) near Hawaii (regional chemistry transport model results) Percent Change in Ozone with the Effect of Clouds on Photolysis vs. without the Effect on Photolysis

28. Spatially Averaged, Diurnally Averaged O3 Production and Loss Rates Units are pptv/day

29. Does Cloud Chemistry Affect O3 Concentrations? Cloud Chemistry (aqueous chemistry + separation of reactants) may not have a big effect on O3 concentrations by itself, but the sum of the cloud effects (cloud chem., radiation, scavenging, etc.) may perturb O3 “substantially”. What are the key parameters for calculating cloud chemistry? Liquid Water Content The size of the drops (more on this later)

30. Is the question, “Does cloud chemistry alter O3 concentrations?”, dead? • NO! Because there are so many things to consider with ozone chemistry. • More accurate depiction of clouds • Many situations where the chemistry is much more complex, e.g. cloud-topped boundary layers with nearby hydrocarbon and NOx emissions • Volatile organic compounds participation will then need to be assessed Organic Aqueous Chemistry

31. phase cloud microphysics and chemical species size How clouds affect chemical species

32. Freezing Riming Melting Collision/Coalescence Condensation Cloud Drop Activation Microphysics and Chemistry

33. Representing Cloud Physics in Large-scale Models Represent cloud drops as one reservoir, rain as another reservoir, and ice and snow as separate reservoirs. This is termed bulk-water microphysics. Water vapor Ice Cloud water Rain Snow

34. ? • Represent aerosols, cloud drops, and rain drops using size bins • Parcel model results should be closer to the truth Cloud chemistry SO2 SO4 Collision/Coalescence Condensation Representing Cloud Physics in Parcel Models Cloud Drop Activation

35. Simulating Size-Varying Cloud Drop Population vs. Cloud Water with a Mean Radius • Hegg and Larson (1990) condensational growth only • Roelofs (1993) condensation and collision/coalescence • Gurciullo and Pandis (1997) condensational growth only • Kreidenweis et al. (2003) condensational growth only; intercomparison of 7 aerosol parcel models

36. Sulfate Production from Explicit Models vs. Bulk-Water Models mmol/L

37. Observations have shown that the chemical composition varies with the size of the cloud drop Noone et al. (1988), Ogren et al. (1989, 1992) Munger et al. (1989), Collett et al. (1993, 1994) Why is there more sulfate production with explicit microphysics? • pH varies across the droplet spectrum

38. Percent Change in Ozone for a Cloud-topped Marine Boundary Layer (z<2 km) near Hawaii (regional chemistry transport model results)  Is there an important effect of drop size (pH variability) on cloud photochemistry?

39. Freezing Riming Melting Collision/Coalescence Condensation Cloud Drop Activation Microphysics and Chemistry

40. ? ? ? Microphysics and Chemistry

41. Snow Accreting Cloud Water (riming)

42. Test the Importance of Retaining Gas Species in Frozen Hydrometeors • Convective Cloud Model coupled with Gas and Aqueous Phase Chemistry • Simulate a storm that was observed in northeastern Colorado (Dye et al., 2000) • Evaluate how well the model represents observed convection • Evaluate passive tracer transport • Skamarock et al. (2000)

43. Convective Cloud SimulationHydrometeor Mixing Ratios Barth et al. (2001)

44. SO2 and H2O2 in outflow region Barth et al. (2000)

45. Yin et al. (2002) used a 2-d axisymmetric cloud model to investigate retention during riming and adsorption.

46. KH 0 102 103 104 105 M/atm Crutzen and Lawrence (2000) found the mixing ratio of trace gases with KH = 103, 104, 105 M/atm reduced in the middle to upper troposphere by 20%, 60%, 90% from global model calculations.

47. Microphysics and Chemistry Size of drops is important to cloud chemistry Phase of cloud is important to cloud chemistry (generally aqueous chemistry does not happen in ice) and scavenging (wet deposition).

48. Ice chemistry HNO3 ice NO3- + hn NO2 Heterogeneous Chlorine chemistry, e.g.: HCl + ClONO2 Cl2 + HNO3 Other chemistry?

49. high photolysis rates low photolysis rates How clouds affect chemical species

50. Radiative Effects on Photolysis Rates O3 + hn O('D) + O2 photodissociation rate jO3 jO3 Matthijsen et al. (1998) ACE-1 observations and modeling jO3 jO3