1. AM and ChemClim WG - February, 2008
Aerosol-Climate Interactions in the CAM-Oslo atmospheric GCM and Investigation of Associated Basic Shortcomings * Øyvind Seland 1 Trond Iversen, 1,2 Alf Kirkevåg, 1 Trude Storelvmo, 2,3 1) Norwegian Meteorological Institute 2) University of Oslo 3) ETH Zurich Thanks to: Jon Egill Kristjansson, Phil J. Rasch, Steve Ghan, Richard Easter
* In press in Tellus 60A (2008) (RegClim Special issue)
Also CAM-Oslo with slab ocean: Kirkevåg et al (2008)
AM and ChemClim WG - February, 2008

2. First: Under development: Norwegian GCM/ESM Bjerknes Centre / met
First: Under development: Norwegian GCM/ESM Bjerknes Centre / met.no / Univ. Of Oslo
”CAM-Oslo” based on CAM3 + aerosols
CLM3
CICE4
BCM version of MICOM isopycnic ocean model
Prism (Oasis 4) coupling (alternative to CPL6/7)
Later:
Photochemistry (simplified)
Carbon cycle emphasizing on ocean processes
CAM4 ?

3. This Talk Aerosol-cloud-climate in ”CAM-Oslo” Brief on validation
Direct radiative forcing (DRF)
Is absorption in CAM-Oslo abnormal?
Indirect radiative forcing (IRF) and the role of prognostic cloud droplet number
Influence of natural aerosols on IRF

4. Aerosol-cloud-climate in ”CAM-Oslo”
Major extensions to NCAR CAM3:
Aerosol lifecycling and physical properties
Sea-Salt, Dust, SO4, OM, BC
Size-modes of emitted primary particles are presumed
Concentrations are tagged to production and size mode
Process-specific mixing state
Tables for size, optical, and physical properties
Aerosol interactions with radiation
Refractive index according to mixing state and size
Optical Mie scattering and absorption
Aerosol interaction with clouds
CCN activation by realized super-saturations
Cloud droplet aging and autoconversion

5. Vavrus ”freeze-dry” parameterisation:
Aerosol-cloud-climate in ”CAM-Oslo” Other changes and adjustments of CAM3 physics
Vavrus ”freeze-dry” parameterisation:
Cloud fraction reduced for low specific humidities
Critical mean volume radius for onset of warm-cloud auto-conversion is set to:
r3lcrit =15 mm (not 10 mm);
Critical precipitation for reduction of auto-conversion collection efficiency by a factor 10:
Paut,crit=5 mm/day (not 0.5 mm/day)

6. Brief on validation Regular Surface Measurement verification: Modeled vs. Measured annual concentrations
SO4 BC OM SS DU
SO4: over-estimated
remotely
BC: under-estimated
SS: over-estimated
DU: under-estimated

7. Brief on validation: AODAerosol Optical Depth
CAM-Oslo Model calculated clear sky (0.120)
Brief on validation: AODAerosol Optical Depth
CAM-Oslo
Modis + MISR Satellite Retrievals (0.137)
Modis + MISR Satellite Retrievals (0.137)
Aeronet
General: under-estimate
Tropics (biomass reg.): under-estimate
Extratropics ocean: over-estimate

8. Brief on validation Ångström parameter: Indicating dominating particle size
Accumulation
Mode particles
CAM-Oslo
Coarse
particles
Aeronet
Coarse
particles
Accumulation
Mode particles
Slightly too large particles in CAM-Oslo

9. Year 2000 vs. ”pre-industrial” (1750)
Direct radiative forcing (DRF):
CAM-Oslo DRF
Year vs. ”pre-industrial” (1750)
Top of the Atmosphere W/m2
Ground Surface W/m2
TOA global DRF is approximately zero.

10. Direct radiative forcing (DRF) AerosolDirect Radiative Forcing (since 1750) Our aerosol absorbes more than average
AeroCom Mean
DRF
TOA
(W m-2)
CAM-Oslo
Total
-0.22
+0.031
Contribution by
SO4 only
-0.35
-0.338
SO4 and OM
-0.47
-0.504
SO4 and BC
-0.05
+0.164
BC and OM
+0.13
+0.379
Aerocom average: Total: Wm-2; SO4: W m-2; OM: W m-2 BC: 0.25 Wm-2

11. Is absorption in CAM-Oslo abnormal? Absorption part of AOD
Aeronet
ECHAM5-HAM
Stier et al 2005
The aerosol does not appear to be too absorptive
- If anything it absorbs too little.

12. Is absorption in CAM-Oslo abnormal
Is absorption in CAM-Oslo abnormal? Assumptions influencing aerosol absorption
TEST
CAM-Oslo
DRF
TOA
(W m-2)
Standard set-up
0.031
BC assumed externally mixed
-0.175
No OM absorption assumed
-0.018
No primary BC(ac) emitted
(all in Nucleation / Aitken)
-0.021
Assuming external mixing has serious implications for climate impacts of BC

13. Direct radiative forcing (DRF) Surface albedo
CAM-Oslo (0.147)
Aerocom aver.(0.170)
Modis + SSMI (0.153) (S. Kinne)
CAM-Oslo surface albedo large at high latitudes and in some mid-latitude areas

14. 1st indirect effect (cloud albedo).
IRF and the role of prognostic CDNC
Simulated TOA IRF;
1st indirect effect (cloud albedo).
Prognostic CDNC: W/m2
CDNC=CCN: W/m2
Compensating effects in cloud droplet generation and aging are important

15. Influence of natural aerosols on IRF Sensitivity of 1st and 2nd IRF to increased pre-ind CDNC ( +15 cm-3 to account for missing natural aerosols; e.g. SOA)

16. Points of Concern AOD 10-25% underestimated  Missing aerosols ?
Non-desert mineral dust
Nitrate
Natural and anthropogenic SOA
Bio-aerosols
Slightly positive direct aerosol forcing;
Internal mixing increases absorption efficiency
Surface albedo and ABL cloudiness
Water cloud indirect forcing is sensitive to
Cloud droplet number concentrations (CDNC)
in pristine areas
Compensating effects in CCN and CDNC modeling

17. Thank You