From Measurements to Models: 

What Satellite and Sub-Orbital Instruments 

Can and Must Contribute 

Ralph Kahn NASA Goddard Space Flight Center

Eyjafjalljökull Volcano Ash Plume – MISR Aerosol Retrieval – April 19, 2010

MISR Team, JPL and GSFC
D. Nelson and the MISR Team, JPL and GSFC

North

5

4

3

2

1

0

km

MISR Stereo-Derived Plume Heights

07 May 2010 Orbit 55238 Path 216 Blk 40 UT 12:39

km 0

2

4

6

Plume 1

Plume 2
D. Nelson and the MISR Team

MISR Stereo-Derived Plume Heights

07 May 2010 Orbit 55238 Path 216 Blk 40 UT 12:39

Height: Blue = Wind-corrected

Plume 1

Plume 2

Ht ~ 2.25 – 6 km

Mode ~ 4.8 km

Plume 1

Ht ~ 0.25 - 2 km

Mode < 1 km

Plume 2
Even DARF and Anthropogenic DARF 

are NOT Solved Problems (Yet)

IPCC AR3, 2001

(Pre-EOS)

IPCC AR4, 2007

(EOS + ~ 6 years)
• Aerosol SSA, Vert. Dist., and Surface Albedo critical, esp. for Surface Forcing

From: Zhao et al., JGR 2005

Direct Aerosol Radiative Forcing Efficiency per unit AOD

AOD Alone is Not Enough –

Even for Direct Aerosol Radiative Forcing

• For Semi-direct Forcing, Aerosol SSA and Vertical Distribution are critical
Constraining DARF – The Next Big Challenge

Ae= AERONET; S*= MISR-MODIS composite Kinne et al., ACP 2006

• Agreement among models is increasingly good for AOD, 

given the combined AERONET, MISR, and MODIS constraints

• The next big observational challenge: 

Producing monthly, global maps of Aerosol Type

How Good is Good Enough?

Instantaneous AOD & SSA uncertainty upper bounds for ~1 W/m2 TOA DARF accuracy: ~ 0.02

CCSP - SAP 2.3, 2009
Aerosol-Climate Prediction

Satellites

Model Validation

• Parameterizations

• Climate Sensitivity

• Underlying mechanisms

CURRENT STATE

• Initial Conditions

• Assimilation

Remote-sensing Analysis

• Retrieval Validation

• Assumption Refinement

frequent, global 

snapshots;

aerosol amount & 

aerosol type maps, 

plume & layer heights

space-time interpolation, 

PREDICTION

Sub-orbital

targeted chemical & 

microphysical detail

point-location

time series

Regional Context 

R. Kahn
The NASA Earth Observing System’s 

Terra Satellite

ASTER

First Light: 

February 24, 2000

MODIS

CERES

MISR

MOPITT

Terra Project Office / NASA Goddard Space Flight Center
• NASA, Terra & Aqua

– launches 1999, 2001

– 705 km polar orbits, descending 

(10:30 a.m.) & ascending (1:30 p.m.)

• Sensor Characteristics

– 36 spectral bands ranging from 0.41 

to 14.385 μm

– cross-track scan mirror with 2330 

km swath width

– Spatial resolutions:

• 250 m (bands 1 - 2)

• 500 m (bands 3 - 7)

• 1000 m (bands 8 - 36)

– 2% reflectance calibration accuracy

– onboard solar diffuser & solar 

diffuser stability monitor

MODerate-resolution Imaging 

Spectroradiometer [MODIS]

MODIS Team, NASA/GSFC

Improved over AVHRR: 

• Calibration 

• Spatial Resolution 

• Spectral Range & # Bands 
MODIS Monthly Global Aerosol Products

• Water & some Land

• Globe ~ Every 2 days

• ~ 10:30 AM & 1:30 PM

Mid-vis AOT

• Fine/Coarse Ratio

• Sensitivity to PM10

MODIS Atmospheres Web Site

Direct Downlink
Multi-angle Imaging 

SpectroRadiometer

• Nine CCD push-broom cameras

• Nine view angles at Earth surface:

70.5o forward to 70.5o aft

• Four spectral bands at each angle:

446, 558, 672, 866 nm

• Studies Aerosols, Clouds, & Surface

http://www-misr.jpl.nasa.gov

http://eosweb.larc.nasa.gov
Aerosol Retrievals –

Aerosol Optical Depth
Ten Years of Seasonally Averaged 

Mid-visible Aerosol Optical Depth from MISR

...includes bright desert dust source regions MISR Team, JPL and GSFC

2000 2001 2002 2003 2004 2005 2006 2007

Dec-Feb

Mar-May

Jun-Aug

Sep-Nov

2008 2009
MISR-AERONET AOD Comparison for 5,156 Coincidences

MISR Version 22 – Stratified by expected aerosol air mass type 

Kahn, Gaitley et al., JGR 2010

0.05 or 20% AOT

0.03 or 10% AOT

Solid = Version 22

Dashed = Version 12

Biomass Burning

Continental

Dust

Maritime

Urban

Smoke-Dust Hybrid

AOD accuracy generally high; varies with conditions
Over-ocean regression coefficient 0.90

Regression line slope 0.75

MODIS QC ≥ 1

Over-land regression coefficient 0.71

Regression line slope 0.60

MODIS QC = 3

Kahn, Nelson, Garay et al., TGARS 2009

MISR = 0.09 + 0.60 x MODIS

Correlation Coeff = 0.713

Std Dev (MISR-MODIS) = 0.117

Ocean Land MISR = 0.04 + 0.75 x MODIS

Correlation Coeff = 0.902

Std Dev (MISR-MODIS) = 0.041
MISR-MODIS Coincident AOD Outlier Clusters

Dark Blue [MISR > MODIS] – N. Africa Mixed Dust & Smoke

Cyan [MODIS > MISR, AOD large] – Indo-Gangetic Plain Dark Pollution Aerosol

Green [MODIS >> MISR] – Patagonia and N. Australia MODIS Unscreened Bright Surface

Kahn et al., TGARS 2009
Aerosol Retrievals –

Aerosol Microphysical Properties
One MODIS Aerosol Type Classification: 

Low AOT (blue), High AOT+Coarse (green), High AOT+Fine (red)

Kaufman et al., JGR, 2005
Smoke from Mexico -- 02 May 2002

0.0 1.2 -.25 3.0 0.0 1.0

Aerosol:

Amount

Size

Shape

Medium

Spherical

Smoke

Particles

Dust blowing off the Sahara Desert -- 6 February 2004

Large

Non-Spherical

Dust

Particles

0.0 1.2 -.25 3.0 0.0 1.0
MISR Aerosol Type Distribution

Kahn, Gaitley, Garay, et al., JGR 2010

Biomass

Burning Dusty Continental Urban Maritime

Hybrid

(smoke + dust)

Mixture # Mixture # Mixture # Mixture # Mixture # Mixture #

# Occurrences

Spherical Non-Absorbing Spherical Absorbing Non-Spherical
MISR Aerosol Type Distribution

Spherical Non-Absorbing

Spherical Absorbing

Non-Spherical

Kahn, Gaitley, Garay, et al., JGR 2010

Sensitivity to particle properties varies enormously with conditions –

Low sensitivity for AOD <~ 0.15 or 0.2
Ouarzazate

(30.93, -6.91)

AOT(558) ~0.30-0.45

Tinfou

(30.23, -5.61)

AOT(558) ~0.45-0.55

0.3

0.35

0.4

0.45

0.5

6:00 8:00 10:00 12:00 14:00

Spectral Optical Depth

Time (UTC)

AOT (440 nm)

AOT (500 nm)

AOT (675 nm)

MISR AOT(558)

~ 0.30-0.45

Ouarzazate AERONET

A. Ansmann

0.4

0.5

0.6

0.7

0.8

0.9

6:00 8:00 10:00 12:00 14:00

Spectral Optical Depth

Time (UTC)

AOT (440 nm)

AOT (500 nm)

AOT (670 nm)

Tinfou Sun Photometer

W. von Hoyningen-Huene & T. Dinter

MISR AOT(558)

~ 0.45-0.55

Falcon HSRL

SAMUM Campaign Morocco – June 04, 2006 
MISR SAMUM Aerosol Air Masses (V19) - June 04, 2006 

Orbit 34369, Path 201, Blocks 65-68, 11:11 UTC 

0.0 0.5 1.0

Ouarzazate

AOT(558) ~0.30-0.45

Tinfou

AOT(558) ~0.45-0.55

(27.9, -5.6)

a

0.0 0.9 1.5

Ouarzazate

ANG ~0.5-0.6

Tinfou

ANG ~0.1-0.7

(30.1, -6.4)

b

0.94 0.97 1.0

Ouarzazate

SSA(558) ~0.95-0.99

Tinfou

SSA(558) ~0.99-1.0

c

0.3 0.7 1.0

Ouarzazate

FrSph ~0.4-0.6

Tinfou

FrSph ~0.6-0.8

d

Kahn et al., Tellus 2009

• A dust-laden density flow in the SE corner of the MISR swath 

• High SSA, ANG & Fraction Spherical region SE of Ouarzazate, includes Zagora
1

1

2

2

2

2

1

3

3

3

3

1

Kahn et al., Tellus 2009

MISR SAMUM Aerosol Air Mass Validation - June 04, 2006 

Falcon F-20 HSRL

- Thin layers of small,

bright particles

NOAA/HYSPLIT 

Back Trajectories

-Source in N Algeria

for 2, 3 but not 1.
We are aiming for Regional-to-Global

Aerosol-Air Mass-Type Discrimination 

Something like this...

13 Groupings Based on Transport Model Aerosol Property Simulations

Kahn et al., JGR 2001
Constraints on Aspects of

Aerosol Climate Forcing
Global, TOA, anthropogenic

DARF (Obs.-based shown at top)

Global Aerosol Forcing Patterns: 

Measured, Modeled, & Merged

Seasonal (MAM)

Mid-vis AOD

Seasonal (MAM), Clear-sky 

Diurnal-average TOA DARF

From: CCSP - SAP 2.3, 2009

Although spatial patterns are similar,

Model DARF estimates are generally

smaller than observation-based ones

Annual, clear-sky, TOA DARF
Over-Land Aerosol Short-wave Radiative Forcing w/Consistent Data

Y. Chen et al. JGR 2009

The slope of: 

TOA albedo vs. AOD 

For data stratified by:

Surface BHR 

Produces: 

Spectral aerosol 

radiative efficiency 

MISR AOD MISR SSA

MISR ANG MISR Surf. BHR

Bright surface

+ dark aerosol

= decreasing

albedo w/AOD

(daTOA/dtmid-vis)

Depends on aerosol microphysical properties relative to surface albedo
MODIS/Terra 7-Year Regional/Seasonal AOD Trends 

• Decrease over land, except E Asia + tropical Africa, S America, Indonesia burning seasons

• Increase over ocean, especially downwind of biomass burning areas

Remer et al. 
Zhang & Reid, ACP 2010

MODIS 10-Year Global/Regional

Over-Water AOD Trends 

• Statistically negligible (±0.003/decade) global-average over-water AOD trend 

• Statistically significant increases over the Bay of Bengal, E. Asia coast, Arabian Sea

Trend

Statistical

Significance
Overall, about 15% Land + Ocean

of Earth’s surface 

produces successful 

MISR automatic 

aerosol retrievals

(about the same 

fraction for MODIS)

Dark blue = Ocean retrieval

Light blue = Land retrieval

MISR Retrieval Status Distribution

Kahn, Nelson, Garay et al., TGARS, 2009

From experience with MISR & MODIS:

For global, ~ 1 ̊  1 ̊ AOD, in general, MISR data need to be 

aggregated to ~ 3-month sampling to converge with MODIS 
Key Attributes of the MISR Version 22 Aerosol Product

• AOT Coverage – Global but limited sampling on a monthly basis

• AOT Accuracy – Maintained even when particle property information is poor

• Particle Size – 2-3 groupings reliably; quantitative results vary w/conditions

• Particle Shape – spherical vs. non-spherical robust, except for coarse dust

• Particle SSA – useful for qualitative distinctions

• Aerosol Type Information – diminished when AOT < 0.15 or 0.2

• Particle Property Retrievals – improvement expected w/algorithm upgrades

• Aerosol Air-mass Types – more robust than individual properties

• Sensitivity to particle properties varies enormously with conditions!

PLEASE READ THE QUALITY STATEMENT!!!

... and more details are in publications referenced therein
Current MISR & MODIS Mid-Visible AOD Sensitivities

• MISR: 0.05 or 20% * AOD overall; better over dark water 

[Kahn et al., 2005; 2010]

• MODIS: 0.05 or 20% * AOD over land

0.03 or 5% * AOD over dark water 

[Remer et al. 2005; 2008; Levy et al. 2010]

Based on AERONET coincidences (cloud screened by both sensors)

 Direct Aerosol Radiative Forcing (DARF): Need AOD to <~ 0.02

 Particle Properties are Categorical rather than continuous Quantities
Aerosol-Climate Prediction

Satellites

Model Validation

• Parameterizations

• Climate Sensitivity

• Underlying mechanisms

CURRENT STATE

• Initial Conditions

• Assimilation

Remote-sensing Analysis

• Retrieval Validation

• Assumption Refinement

frequent, global 

snapshots;

aerosol amount & 

aerosol type maps, 

plume & layer heights

space-time interpolation, 

PREDICTION

Sub-orbital

targeted chemical & 

microphysical detail

point-location

time series

Regional Context 

R. Kahn
Next Steps

• Global Aerosol-Air-Mass-Type Maps 

– Upgraded MISR retrievals + future missions

• Aerosol Size, SSA, Shape PDFs for Major Sources

– Systematic aircraft + surface measurements, of global scope

• Aerosol Source Strength

– MODIS + MISR AOD snapshots as constraints on model sources

(Forward and/or Inverse Modeling, Data Assimilation)

• Aerosol Vertical Distribution

– CALIOP global lidar (downwind) + MISR stereo (near-source)

• Aerosol Transports

– Global AOD Maps: MODIS + MISR + TOMS/OMI + POLDER + ... 

• Plan for Future Satellite Missions
Backup Slides
Aerosol Material Fluxes: Atlantic Dust & Asian Pollution

MODIS AOD & Type

Low AOD, Fine BioBurn, Coarse Dust

NCEP W Wind - MODIS AOD

Correlation 2.6-5 km; May-October

Dust Transport Estimate (Tg)

May-October (Top) January-April (Bot)

Yu et al., JGR 2008

Kaufman et al., JGR 2005

MODIS AOD & type, Field Campaign aerosol properties & vertical distribution, GEOS model winds;

Compared with GOCART and GMI model Fine-particle mass fluxes
0.0 500 1000 1500 2000 0.0 0.5 1.0 1.5 2.0 2.5

Saharan Dust Source Plume

Bodele Depression Chad June 3, 2005 Orbit 29038

MISR

Dust is injected near-surface...

MODIS

Kahn et al., JGR 2007
dust.22399.b74 Sub2_hist

0 100 200 300

0.5

1.5

2.5

3.5

4.5

5.5

6.5

7.5

8.5

9.5

Height (km)

Number of Pixels

22399 - Site 2

0

2

4

6

8

10

0 3 6 9 12 15

Atmospheric Stability

Height (km)

Transported Dust Plume

Atlantic, off Mauritania March 4, 2004 Orbit 22399

MODIS

MISR

Transported dust finds elevated layer of relative stability... Kahn et al., JGR 2007
Constraining Aerosol Sources, Transports, & Sinks

Complementary MISR & MODIS AOD; Saharan Dust Plume over Atlantic June 19-23, 2000

Contours: AOT=0.15 (yellow); AOT=0.5 (purple) Kalashnikova and Kahn, JGR 2008

ANG (~1/Size)

Non-sphericity

Plume Age 

AOD
Aerosol Sources, Processing, Transports, Sinks: Lidar + Model

August 2007 Saharan dust “D” and smoke “S” event 

mapped by CALIPSO 532 nm backscatter, with superposed

model back trajectories and airborne HSRL observations

Liu et al., JGR 2008

Piecing together the bigger picture. Consistency requires –

• An understanding of the mechanisms governing aerosol evolution

• Adequately constrained initial & boundary conditions
Seasonal Changes in Anthropogenic and Natural Aerosol Types 

Over India

Winter (Dec-Feb) Pre-monsoon (Mar-May) Monsoon (Jun-Sep) Post-monsoon (Oct-Nov)

Dey & Di Girolamo JGR 2010

Pre-monsoon influx of 

dust from the Great 

Indian Desert and 

Arabian Peninsula

Large influence of 

anthropogenic particles 

due to pre-monsoon 

biomass burning

Additional influence of 

maritime particles 

produced by high surface 

wind

Large influence of 

anthropogenic particles due 

to seasonal peak in biomass 

burning and reduced dust 

transport

Increased 

wintertime 

transport of 

anthropogenic 

pollution

fNatural fAnthro.

Index

Reduced dust 

loading due to 

monsoon 

precipitation

Himalayan foothills -

advection of 

anthropogenic 

particles from IndoGangetic Basin

Index uses MISR-retrieved particle shape and size constraints 

to separate natural from anthorpogenic aerosol