1 Radiative Effect of Clouds on Tropospheric Chemistry in a Global 3-D Chemical Transport Model Hongyu Liu ( National Institute of Aerospace NASA Langley 2 nd GEOS-CHEM Users’ Meeting April 4-6, 2005 Acknowledgements - LaRC: Jim Crawford, Brad Pierce, Gao Chen GSFC: Peter Norris, Steve Platnick Harvard: Jennifer Logan, Daniel Jacob, Bob Yantosca

2 Outline  Research Objectives  GEOS-CHEM (Fast-J)  GEOS-3 Cloud Distributions and Evaluation  Radiative Effect of Clouds  Photolysis Rates  Key Oxidants  Sensitivity to Cloud Vertical Distributions  GEOS1-STRAT  GEOS-3  GEOS-4  Conclusions

3 Research Objectives  To improve our understanding of the radiative effect of clouds on global trop chem  To quantify the radiative effect of clouds on photolysis rates and key oxidants, as well as associated uncertainties  To assess the impact of cloud overlap assumptions

4 GEOS-CHEM Global Chemical Transport Model v5.5 (  Driven by the NASA Goddard Earth Observing System (GEOS-3) assimilated meteorology from the Global Modeling and Assimilation Office (GMAO)  Horizontal resolution 1 o x1 o to 4 o x5 o, 48 levels in vertical  Ozone-NO x -CO-VOC coupled to aerosol (sulfate-nitrate- ammonium and carbonaceous) chemistry [Bey et al., 2001; Park et al., 2004]  Extensively evaluated with surf / in situ / remote sens obs  Sensitivity simulation period: Aug 2000 – Dec 2001  Photolysis rate calculation: Fast-J [Wild et al., 2000] with GEOS-3 surface albedo, 3-D cloud optical depth, and cloud fraction

5 Global Distribution of Cloud Optical Depth GEOS-3 vs. Satellite Retrievals Mean Cloud Optical Depth (grid-scale) for March 2001 MODIS (MOD08_M3) ISCCP (D2) GEOS-3 MODIS ISCCP GEOS-3 Probability Distribution Functions Global Average GEOS3-OD / MODIS-OD = 0.91 GEOS3-OD / ISCCP-OD = 1.31

6 Latitudinal Distribution of Cloud Optical Depth GEOS-3 vs. Satellite Retrievals GEOS-3 MODIS ISCCP GEOS-3 cloud OD reasonably agree with MODIS and ISCCP cloud retrieval products, but tend to be larger in the tropics and SH marine stratiform clouds region.

7 Model Representations of the Vertical Coherence of Clouds  LIN: Linear Assumption [Wild et al., 2000] τ c ' = τ c · f  RAN: Approximate Random Overlap [Briegleb, 1992] τ c ' = τ c · f 3/2  MRAN: Maximum-Random Overlap  clouds in adjacent layers (a cloud block) are maximally overlapped; cloud blocks are randomly overlapped.  version 1: Stubenrauch et al. [1997];Tie et al. [2003]  version 2: Collins [2001]; Feng et al. [2004] grid-scale OD in-cloud OD cloud fraction

8 Effect of clouds on J[O 1 D] calculated by off-line Fast-J (Test case of Feng et al. [2004]) Cloud layers at 3-4km: f = 0.2, km: f = 0.1, 0.8 Latitude = 45N Albedo=0.1 Mean OD = 54 Enhancement above cloud Reduction below cloud a). Small cloud fraction: LIN > RAN > MRAN b). Large cloud fraction: Small differences between schemes SZA=0 CLEAR RAN MRAN LIN a). small cloud fraction b). large cloud fraction

9 Changes (%) in daily mean J[O 1 D] due to cloud June 2001  RAN and MRAN differs by ~2%

10 Changes (%) in daily mean J[NO 2 ] due to cloud June 2001  RAN and MRAN differs by ~2%

11 Changes (%) in daily mean OH due to cloud June 2001

12 O 3 and CO changes (%) due to cloud, June (GEOS-CHEM vs. MOZART-2) GEOS-CHEM MRAN [this work] MOZART-2 MRAN [Tie et al., 2003] O3O3 CO hPa Why are the sensitivities to cloud so different ?

13 GEOS-CHEM [this work] MOZART-2 [Tie et al.,2003] LIN RAN MRANLINMRAN OH O NO x HO CH 2 O CO J[O 1 D] J[NO 2 ] J[CH 2 O] Global (troposphere) mean changes (%) due to cloud, June

14 GEOS1-STRAT, GEOS-3 and GEOS-4 Cloud Optical Depths per KM (June) GEOS1-S (1996) GEOS-3 (2001) GEOS-4 ( 2001) ISCCP MODIS GEOS-3 GEOS-4 GEOS1-S Global Average: GEOS-3 / GEOS1-S = 5.1 GEOS-3 / GEOS-4 = 1.9 GEOS1-S COD: too small optically too thin

15 Changes (%) in daily mean OH due to cloud (LIN, June) changes of global mean OH due to cloud GEOS1-S: -1% GEOS-3: 1% GEOS-4: 14% GEOS1-S, 1996 GEOS-3, 2001 GEOS-4, 2001 Cloud vertical distribution is more important than the magnitude of COD in terms of the radiative impact on global tropospheric chemistry!

16 Conclusions  The dominant radiative effect of clouds is to influence the vertical redistribution of the intensity of photochemical activity while the global average effect remains modest. This contrasts with previous studies.  For global CTMs, the approximate random overlap scheme ( τ c ' = τ c · f 3/2 ) is a good approximation of the maximum-random overlap scheme; the former is computationally much cheaper.  Using the maximum-random overlap scheme or the random overlap scheme (vs. linear assumption) reduces the impact of clouds on photochemistry, but global average effect remains modest.  Cloud vertical distribution is more important than the magnitude of cloud optical depth in terms of the radiative impact on global tropospheric chemistry.