How good are our models?

Transcription

1 direct Estimates of regional and global forcing: ^ How good are our models? Bill Collins with Andrew Conley, David Fillmore, and Phil Rasch National Center for Atmospheric Research Boulder, Colorado

2 Models for Global and Regional Forcing Chemical Transport Models Aerosol mixing ratio q i Aerosol Optical Models Optical depth τ i, asymmetry g i, ssa ω i Radiative Transfer Models Radiative Forcing

3 Chemical Transport Models ()SourceiiemischemwetdrychsSinksemqqvSSSSSt + =+ Dust Mass Dust Emissions 0 g m Precipitation Scavenging 0 kg m -2 day -1 3 x 10-4 Dry Deposition 0 kg m -2 day -1 4 x kg m -2 day -1 5 x 10-5

4 Model Calculation of Aerosol Forcing (Clear Sky) Collins et al, 2004

5 Aerosol Absorption by Species (Clear Sky) Carbon Dust Aerosols are 3 rd most important absorber, after H 2 O and O 3.

6 What is Measure of a Good Model? 1. Agreement at the process level for sources, sinks, and transport 2. Agreement with global data for q i, τ i, etc. 3. Agreement among models

7 Topics Range of modeled τ and mass Observational constraints on global models Properties of hybrid, or nudged, models Global direct forcing from hybrid models Sensitivity of global forcing to uncertainties in: Aerosols Clouds Surface properties

8 Global Aerosol Model Intercomparison: AEROCOM Targets of intercomparison: Global mass and optical depth Optical properties Fine/coarse mode partitioning Radiative forcing (new) Cloud properties (new) Simulations: Standard emissions: Fixed emissions: 2000 Participants: 14 nudged GCMs and CTMs

9 AEROCOM Results: Optical Depths Species Median Max/ AOD Min SO BC OC Dust Seasalt All Kinne et al, 2004

10 AEROCOM Results: Aerosol Mass (mg/m 2 ) Species Median Max/ Mass Min SO BC OC Dust Seasalt All Kinne et al, 2004

11 Evaluation in AEROCOM using AERONET Kinne et al, 2004; Holben et al, 2001

12 Evaluation in AEROCOM using Surface Sites

13 Hybrid Models adjusted to Satellite Data Chemical Transport Models Aerosol mixing ratio q i Aerosol Optical Models Optical depth τ i, asymmetry g i, ssa ω i Radiative Transfer Models Radiative Forcing

14 First Hybrid Model using MODIS Global Forcing: TOA: 4.5 Wm -2 Srf: 9.9 Wm -2 Atm: 5.4 Wm -2 Yu et al, 2004

15 MODIS Observations Fraction of days with measurement MODIS AOD

16 Aerosol Optical Depth MATCH 0.3 MATCH with MODIS Assimilation 0

17 AOD Assimilation Correction AOD Difference MATCH with MODIS Assimilation - MATCH

18 Organic Carbon Mass Budgets MATCH Mass ~ 1.7 Tg Emissions ~ 0.24 Tg day -1 Dry Deposition ~ 0.06 Tg day -1 Wet Deposition ~ 0.18 Tg day -1 t ~ 7.2 days MATCH with MODIS Assimilation Mass ~ 2.2 Tg Emissions ~ 0.24 Tg day -1 Assimilation ~ 0.04 Tg day -1 Dry Deposition ~ 0.06 Tg day -1 Wet Deposition ~ 0.22 Tg day -1 Organic Carbon Mass t ~ 7.6 days 0 g m

19 National Centers for Environmental Prediction NCEP T62 MODIS AOD 1 x 1 deg MATCH Aerosol Climatology Mar 2000 Feb year monthly cyclic CAM (Community Atmosphere Model) T42 MODIS Surface Albedo Fluxes CERES 2.5 x 2.5 deg Mar 2000 Feb 2003

20 Aerosol TOA SW Radiative Forcing (Clear-Sky) from CAM with MATCH/MODIS Aerosol Climatology Dust Sulfate Carbon Sea-Salt W m

21 TOA Net Shortwave Clear-Sky Fluxes CAM W m -2 CERES* Satellite *ERBE-Like Algorithm 150.0

22 TOA Net Flux Bias over Oceans 10.0 CAM-CERES No Aerosol W m -2 0 CAM-CERES With Aerosol -10.0

23 Uncertainties in BC from Fossil Fuels Bond et al, 2002

24 Uncertainties in BC from Fossil Fuels (cont). India China/ SE Asia Europe N. Asia N. America Bond et al, 2002

25 Uncertainties in Global Carbon Aerosol Burdens Low Central High Prev 84 Emissions (Tg/year) BC Total FF only OC Total FF only Burden (Tg) BC OC Lifetime (days) BC OC Bond et al, 2002

26 Uncertainty in Column Burden of BC Bond et al, 2002

27 Uncertainty in Radiative Forcing by BC Bond et al, 2002

28 All-Sky Aerosol Radiative Forcing Differences in clouds yield 3 Wm -2 changes in forcing, approximately 40% of TOA forcing. Ramanathan et al, 2001; Collins et al, 2002

29 Uncertainties due to Surface Albedo Community Land Model MODIS Albedo Oleson et al, 2003

30 Differences in Diffuse Surface Albedos Model with MODIS Surface Albedo Uncorrected Model 0.1 SW 0 NIR -0.1

31 Changes in Forcing due to Surface Albedo Dust Sulfate -5.0 W m Carbon Differences in global, annual-mean clear-sky forcing are 0.02 Wm -2.

32 Conclusions Modeled τ and mass vary by factor of ~2. Modeled specific extinctions vary by factor of ~2. Range of direct forcing for current models is not known, but will be soon. Global observational estimates of TOA forcing are not available, but will be soon. Knowledge of carbon emissions is a leading source of uncertainty.