Incorporation of Aerosol Optical Properties into 

Climate Models

Mark Z. Jacobson

Atmosphere/Energy Program

Dept. of Civil & Environmental Engineering

Stanford University

Aerosol Meteorology for Climate Workshop

National Institute of Standards and Technology

Washington D.C., March 14-15, 2011
Boomerang 

Effect: Indirect + 

Cloud 

Absorption+ 

Semidirect Effects 

Can’t be 

Separated

In-cloud COD v. AOD 

Over Bio-Burning in 

Ten Hoeve Brazil Sept ‘06 , Remer, Jacobson (2010)

MODIS-Aqua

GATOR-GCMOM

Model
Greater Solar Heating Rate of In-Cloud-Drop BC Over Interstitial 

Cloud BC Over Clear-Sky BC For Same Aerosol Profile

BC Inclusions Can Double Heating Rate Compared With Interstitial BC 

CAOD = 0.027 DEMA

= 0.019 CSA

AAOD = 0.033 no/cloud

= 0.017 w/cloud
Why Does In-Cloud-Drop BC Heat More Than Interstitial Cloud 

(IC) BC and IC BC More Than Clear-Sky BC?

1) Internally-mixed aerosol BC enhances heating over externallymixed aerosol BC due to optical focusing effect.

2) BC between cloud drops (interstitial) heats more than aerosol BC 

due to enhanced scattering of light between cloud drops thus more 

photons hitting BC in the cloud than outside the cloud.

3) BC in cloud drops heats more than BC between cloud drops due to 

optical focusing of enhanced scatter cloud light into drops and 

multiple internal reflections of such light to BC inclusions.
Cloud Absorption Should be Treated with DEMA 

(Multiple BC Inclusions in Drops)

Jacobson, J. Phys. 

Chem. (2006)

Absorption Efficiency 12.6-Micron Cloud Drops

DEMA1,2=0.1-, 0.2-micron BC inclusions; Brug=Bruggeman (BC well-mixed); Core/shell=single BC core

Model vs. Analytical Solution to Drop 

Breakup 

Jacobson, JAS, 2010, in press; analytical solution from Feingold et al., 1988
Modeled vs. Measured Annual Lightning Flash Rate

Data from NASA LIS/OTD Science Team

Model (4ox5o resolution) calculates lightning by accounting for size-resolved 

bounceoffs and charge separation in clouds. Results follow from new drop 

breakup algorithms.
Model v. Data for RH at 200 hPa

Jul AURA data 2x2.5o

Jul model 4x5o

Excellent agreement given data and model 

uncertainties and missing high-lat data

Oct model 4x5o

Oct AURA data
Models v. HIPPO BC Data Pacific

Schwartz et al. (2010) 14 Models vs. HIPPO

(“Models overpredict by factor of five”)

GATOR-GCMOM vs HIPPO

(1.4% column diff. all data)

60 

- 80N 20S 

- 20N 67 

- 60S

60 

– 20S 20 

- 60N All Data

60 

– 20S 20 

- 60N All Data

60 

- 80N 20S 

- 20N 67 

- 60S
Comparison of Modeled Vertical Profiles with Data

BC: Hansen and Novakov, 1989; Quinn 2007; Others: Morgan et al., 2009

BC Organic Matter Sulfate Nitrate
Modeled vs. Measured Paired in Space Monthly T/Td

Data from FSL (2008)

Global domain

U.S. domain

Little numerical diffusion of water vapor or energy to stratosphere
Model v. Data for BV Freq/Trop Height

Jan COSMIC/CHAMP data 2x20o 100 m

Jan model 4x5o x 500 m Jul model 4x5 degrees

Jul COSMIC/CHAMP data

Tropopause-relative coordinates (Whitt et al., 2011)
Modeled vs. Measured 500-hPa January Temperature

Model AIRs Satellite
Modeled vs. Measured Precipitation

Data from Huffman et al (2007)

Despite factor of 20 lower resolution than data, model predicts locations of 

main features of observed precipitation and, with no flux adjustment, correctly 

does not produce a double ITCZ
Modeled vs. Measured Sea Ice Area

Antarctic

Model (at 4 x 5 degree resolution) predicts stable sea ice area

Data from NASA Team (2009)

Arctic
Black Carbon From Fossil- and Bio-fuel Soot

BC from FF soot is about half that of BC from FF+BF soot
Black Carbon in Snow and Sea Ice
Black Carbon Absorption in Clouds
Surface Air Temperature Changes Due FossilFuel Soot Plus Biofuel Soot and Gases
Fossil-Fuel Soot and Biofuel Soot & Gas Controls 

may be Fastest Method of Slowing Global Warming 

and Saving Arctic Ice

www.stanford.edu/group/efmh/jacobson/controlfossilfuel.html
nsidc.org/arcticseaicenews

11.5% loss/decade

81,400 km2 loss/year
Contributors to Global Warming

Jacobson (2010, JGR 115, D14209)
Some Climate Response Estimates of BC

Ramanathan and Carmichael (2008) 0.5-1 K (all BC) 

Chung and Seinfeld (2005) 0.37 K (all BC internally mixed)

Hansen et al. (2005) > 0.3 K (BC from fossil fuels)

Jacobson (2010) 0.4-0.7 K (BC, organic matter, and other 

particle components from fossil fuels and biofuels)
Annual Deaths Due to Fossil-Fuel and Biofuel

Soot

Deaths due to BF soot (1.5 million/yr) ~7 times those due to FF 

soot (200,000/yr)
Summary

FSBSG soot may be the second-leading cause of global warming behind

CO2 and ahead of CH4. FS causes 3 x the warming of BSG, but BSG

causes ~7x more deaths than FS.

Strong warming mainly due to cloud absorption effect, semidirect effect, internal mixing of aerosol, snow absorption effect, and feedback to water

evaporation.

Net global warming (0.7-0.8 K) appears due primarily to gross warming from FF GHGs (2-2.4 K) and FSBSG (0.4-0.7 K) offset by cooling due to

non-FSBSG aerosol particles (-1.7 to -2.3 K).

FS and FSBSG may contribute to 13-16% and 17-23% of gross warming due to atmospheric pollutants.

Control of FS, FSBSG is fastest method of reducing Arctic loss

www.stanford.edu/group/efmh/jacobson/controlfossilfuel.html
FF Soot, BC Global Warming Potential

20-yr STRE (GWP) 100-yr STRE

BC+POC in FS 2400 - 3800 1200 - 1900

BC in FS 4500 - 7200 2900 - 4600

BC+POC in BSG 380 - 720 190 - 360

BC in BSG 2100 - 4000 1060 - 2020

Methane 52-92 29 - 63

STRE = Near-surface temperature change after 20 or 100

years per unit continuous emission of X relative to

the same for CO2 (similar to GWP e.g., 20-, 100- yr GWPs for CH4 are 72, 25)