page 1 radiative transfer modeling for the retrieval of co 2 from space vijay natraj june 11, 2007...

Radiative Transfer Modeling for the Retrieval of Radiative Transfer Modeling for the Retrieval of COCO22 from Space from Space

Vijay Natraj

June 11, 2007

Thesis Defense Seminar

Outline

• Motivation

• OCO mission

• Column O2 retrievals

• Aerosol characterization

• Polarization

• Future Work

Introduction: Carbon Sinks?

• Atmospheric Carbon dioxide (CO2)

– Primary man-made greenhouse gas

– Mixing ratios increased by ~25% since 1860

– Only half of the CO2 from fossil fuel emissions in atmosphere

• Outstanding Issues– Where are the CO2 sinks?

– Why does atmospheric buildup vary with uniform emission rates?

– How will CO2 sinks respond to climate change?

Climate Change Discussions at the G8

Why Measure CO2 from Space?

• Studies from GV-CO2 stations – Flux residuals exceed 1 GtC/yr in

some zones – Network is too sparse

• Inversion tests– Global XCO2 pseudo-data with 1

ppm accuracy – Flux errors reduced to < 0.5

GtC/yr/zone for all zones– Global flux error reduced by a

factor of ~3

Courtesy: Rayner and O’Brien, 2001

1.2

0.6

0.0

Flu

x Re

sidu

als (G

t/yr/zon

e)

1.2

0.6

0.0

Flu

x Re

sidu

als (G

t/yr/zon

e)

Precise CO2 Measurements Needed

• Space-based XCO2 estimates will improve constraints on CO2 fluxes

– Near global coverage on monthly intervals

– Precisions of 1–2 ppm (0.3–0.5%) on regional scales

– No spatially coherent biases > 1–2 ppm (0.3 to 0.5%) on regional scales

CO

2 M

ixin

g R

atio

(p

pm

)

356

360

364

Lat

itu

de

90

-90

0

356

360

364

Lat

itu

de

90

-90

0

Effects of Gaussian Noise on XCO2

The Orbiting Carbon Observatory (OCO)

• Spectra of CO2 and O2 absorption in reflected sunlight used to estimate XCO2

• Random errors and biases no larger than 1 - 2 ppm (0.3 - 0.5%) on regional scales at monthly intervals

OCO will make the first space-based measurements with the precision and resolutions needed to quantify CO2 sources and sinks and monitor their variability.

OCO Fills a Critical Measurement Gap

OCO will make precise global measurements of XCO2 needed to monitor CO2 fluxes on regional to continental scales.

Spatial Scale (km)

1

2

3

4

5

6

CO

2 E

rror

(pp

m)

1 10 100 1000 10000

OCO

FlaskSite

AquaAIRS

Aircraft

0

FluxTower

Globalview Network

NOAATOVS

ENVISATSCIAMACHY

Spectroscopy

Clouds/Aerosols, Surface Pressure Clouds/Aerosols, H2O, TemperatureColumn CO2

O2 A-band CO2 1.61m

CO2 2.06 m

• Column-integrated CO2 abundance– Maximum contribution from surface

• Why high spectral resolution?– Enhances sensitivity, minimizes biases

OCO Observation Strategy

• Nadir Mode: tracks local nadir– Small footprint (< 3 km2) isolates cloud-

free scenes and reduces biases from spatial inhomogeneities over land

– Low Signal/Noise over dark ocean

• Glint Mode: views “glint” spot– Improves Signal/Noise over oceans

– More interference from clouds

• Target Mode– Tracks a stationary surface calibration

site to collect large numbers of soundings

Local Nadir

Glint Spot

Ground Track

OCO Retrieval Algorithm

Retrieval of Column O2

• High precision, high resolution O2 A band spectra of sunlight reflected from ocean surface [O’Brien et al., 1997, 1998]

Can we retrieve column O2 with precisions required for OCO?

Retrieval: First Cut

rms residual = 8.8%

Green - computed

Black - measured

Black - residual

Continuum Level, Tilt, Zero Offset, ILS Width Fits

rms residual = 1.4%

Brown - computed

Black - measured

Black - residual

Conclusions

• Algorithm developed to retrieve XCO2 from spectroscopic measurements of absorption in NIR bands

• Retrieved column O2 with precision ~ 1%

• Demonstrates potential to retrieve column O2 with precisions around 0.1% by averaging sufficient soundings

• Indicates feasibility of retrieving XCO2 with precisions better than 0.3%

Aerosols: Major Source of Retrieval Uncertainty

Ground surface

Aerosol Layer 1

Aerosol Layer 2

Light reaching

the detector

Photon path length is modified

through multiple scattering by

aerosols

Incident light

Global Aerosol Climatology

Courtesy: Kahn et al., 2001

Aerosol Optical Properties

• Each mixing group is a combination of 4 different aerosol components from a basic set of 7 [Kahn et al., 2001].

• Sulfate (land/water), seasalt, carbonaceous, black carbon: spherical => Mie code [de Rooij and van der Stap, 1984]

• Mineral dust (accumulated/coarse): mixture of oblate and prolate spheroids => T-matrix code [Mishchenko and Travis, 1998]

• Lognormal distribution

• Polarization fully considered

Scattering Matrix (755 nm)

Forward Model Details

• Park Falls, Wisconsin, July (SZA = 31°)

• Exponential drop-off in aerosol extinction (scale height: ~ 1 km, optical depth: 0.1)

• Forward model: RADIANT [Christi and Stephens, 2004] + single scattering approximation for polarization

• Lorentzian instrument lineshape function (resolving powers: O2 A band: 17000, CO2 bands: 20000)

Weighting Functions (O2 A band)

0.758 0.760 0.762 0.764 0.766 0.768 0.770 0.772-10

-8

-6

-4

-2

0

2

4

6

8

Nor

mal

ized

Jac

obia

n

Wavelength [m]

Type 1a 1b 1c 2a 2b 3a 3b 4a 4b 4c 5a 5b 5c

Weighting Functions (1.61 µm CO2 band)

1.590 1.595 1.600 1.605 1.610 1.615 1.620

-0.4

-0.2

0.0

0.2

0.4 Type 1a 1b 1c 2a 2b 3a 3b 4a 4b 4c 5a 5b 5c

Nor

mal

ized

Jac

obia

n

Wavelength [m]

Weighting Functions (2.06 µm CO2 band)

2.04 2.05 2.06 2.07 2.08

-0.10

-0.05

0.00

0.05

0.10

No

rma

lize

d J

aco

bia

n

Type 1a 1b 1c 2a 2b 3a 3b 4a 4b 4c 5a 5b 5c

Wavelength [m]

Normalized Extinction Coefficient

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

Norm

aliz

ed

Extinction C

oeffic

ient

Type 5b

Wavelength [m]

Group 4

Type 3b

Group 5

Type 2b 4b 4c

Norm

aliz

ed

Extinction C

oeff

icie

nt

Group 2

Type 3a 5a 5c

Group 3

Norm

aliz

ed

Extinction C

oeffic

ient

Type 1a 1b 1c 2a 4a

Group 1

Single Scattering Albedo

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

Type 5b

Wavelength [m]

Sin

gle

Scatt

ering A

lbedo

Group 4Type

3b

Group 5

Type 2b 4b 4c

Sin

gle

Scatt

ering A

lbedo

Group 2

Type 3a 5a 5c

Group 3

Type 1a 1b 1c 2a 4a

Sin

gle

Scatt

ering A

lbedo

Group 1

Normalized Extinction Coefficient

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

0.755 0.785 1.56 1.65 2.03 2.090.10.20.30.40.50.60.70.80.91.01.1

Norm

aliz

ed

Extinction C

oeffic

ient

Type 5b

Wavelength [m]

Group 4

Type 3b

Group 5

Type 2b 4b 4c

Norm

aliz

ed

Extinction C

oeff

icie

nt

Group 2

Type 3a 5a 5c

Group 3

Norm

aliz

ed

Extinction C

oeffic

ient

Type 1a 1b 1c 2a 4a

Group 1


0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

0.755 0.785 1.56 1.65 2.03 2.090.80

0.85

0.90

0.95

1.00

Type 5b

Wavelength [m]

Sin

gle

Scatt

ering A

lbedo

Group 4Type

3b

Group 5

Type 2b 4b 4c

Sin

gle

Scatt

ering A

lbedo

Group 2

Type 3a 5a 5c

Group 3

Type 1a 1b 1c 2a 4a

Sin

gle

Scatt

ering A

lbedo

Group 1

Sensitivity Tests I

• Measurement error: 0.43 ppm

• Smoothing error: 0.29 ppm

• Maximum error due to incorrect assumption of aerosol type within retrieval group

– Group 1: 0.27 ppm



Sensitivity Tests II

Type 8 Type 9

1 2 3 4 5 6 7 8 9 10 11 12 130.00.20.40.60.81.01.21.41.6

Aerosol Type

1 2 3 4 5 6 7 8 9 10 11 12 130.00.20.40.60.81.01.21.41.6

Phase Matrix


XC

O2 E

rror

(pp

m)

1 2 3 4 5 6 7 8 9 10 11 12 130.00.20.40.60.81.01.21.41.6 All Properties

1 2 3 4 5 6 7 8 9 10 11 12 130.00.10.20.30.40.50.60.70.8

Phase Matrix

Aerosol Type

1 2 3 4 5 6 7 8 9 10 11 12 130.00.10.20.30.40.50.60.70.8


XC

O2

Err

or (

ppm

)

1 2 3 4 5 6 7 8 9 10 11 12 130.00.10.20.30.40.50.60.70.8

All Properties

Conclusions

• Incorrect knowledge of aerosol type could lead to significant XCO2 errors.

• Retrieval of aerosol optical properties (extinction, single scattering albedo, scattering matrix)– Scattering matrix

• Retrieval of microphysical parameters (characteristic radius, width of distribution, refractive index– Particle shape

– Aerosol components

• Statistical Approach

Polarization and the Stokes Parameters

• Electromagnetic radiation can be described in terms of the Stokes parameters: I, Q, U and V– I - total intensity

– Q & U - linear polarization

– V - circular polarization

• Degree of Polarization

(for OCO)I

Qp

I

VUQp

22

2

Importance of Polarization

• Polarization is a result of scattering

• Atmosphere: molecules, aerosols and clouds

• Surfaces can also polarize, in some cases significantly (e.g., ocean)

• The satellite instrument could be sensitive to polarization– OCO measures the radiation polarized perpendicular to the principal plane

• Polarization depends on solar and viewing angles

– Spatial biases in retrieved trace gas column densities

Two Orders of Scattering (2OS) to Compute Polarization

• Full multiple-scattering vector RT codes too slow to meet large-scale operational processing requirements

• Scalar computation causes two kinds of errors– Polarization components of the Stokes vector neglected

– Intensity incorrectly calculated

• Major contribution to polarization comes from first few orders of scattering (multiple scattering is depolarizing)

• Single scattering does not account for the correction to intensity due to polarization

2OS Model Schematic

2OS Model Outline

• Intensity still calculated with full multiple scattering scalar model

• S = Isca+Icor-Q2

• Fast correction to standard scalar code

• Exact through second order

• Analytic Jacobians

Simulation Scenarios

Darwin Park FallsNy Alesund

Algeria South PacificLauder

These locations are OCO validation sites

Simulation Details

– Aerosol loadings [: 0-0.3]

– Aerosol type according to Kahn et al. [2001]

– Lambertian surfaces [albedos from ASTER library]

– T, H2O: ECMWF

– CO2, P: Match/CASA model data [Olsen and Randerson, 2004]

– Realistic Measurement Noise [SNR: ~450, 350, 275]

Radiance Spectra

Different colors represent different aerosol amounts

Spectral Residuals


Scalar Spectral Residuals


XCO2 and Surface Pressure Errors - I

Algeria (Jan)

Darwin (Jan)

Ny Alesund (Apr)

XCO2 and Surface Pressure Errors - II

Lauder (Jan)

South Pacific (Jan)

Park Falls (Jan)

XCO2 and Surface Pressure Errors - III

Algeria (Jan)

Darwin (Jan)

Ny Alesund (Apr)

XCO2 and Surface Pressure Errors - IV

Lauder (Jan)

South Pacific (Jan)

Park Falls (Jan)

Forward Model Error vs. Measurement Noise

2OS

Scalar

Conclusions

• Ignoring polarization could lead to significant (~ 10 ppm) errors in XCO2 retrievals

• 2OS model gives XCO2 errors that are much smaller than other biases

• Two orders of magnitude faster than a full vector calculation

• Additional overhead in the range of 10% of the scalar computation

Future Work

• Cirrus

• Surface Types

• Aerosol vertical distribution

• Spectroscopy

• Line Mixing

• Speed Improvements

Acknowledgments

• Yuk Yung

• John Seinfeld, Rick Flagan, Paul Wennberg

• Hartmut Boesch, Rob Spurr

• David Crisp, Charles Miller, Geoff Toon, Bhaswar Sen, Hari Nair, James McDuffie, Denis O’Brien, Mick Christi

• Run-Lie Shia, Jack Margolis, Zhiming Kuang, Mao-Chang Liang, Xun Jiang, Dan Feldman, Xin Guo

• Friends

• Family

To be continued …

page 1 radiative transfer modeling for the retrieval of co 2 from space vijay natraj june 11, 2007...

Documents

x co2 slide

g8 slide

oco retrieval algorithm

flux residuals gtyrzone

retrieval of column

monthly intervals oco

thesis defense seminar

high resolution o