Achieving Satellite Instrument Calibration for Climate Change, May 17, 2006, Lansdowne, VA 1...

Achieving Satellite Instrument Calibration for Climate Change, May 17, 2006, Lansdowne, VA 1

Vicarious Calibration Using Earth Targets

Xiangqian (Fred) Wu

Sensor Physics Branch

Satellite Meteorology and Climatology Division

Center for Satellite Applications and Research (STAR, formally ORA)

National Environmental Satellite, Data, and Information Service (NESDIS)

National Oceanic and Atmospheric Administration (NOAA)

With help from many colleagues



Outline of the assignments: Overview of the technique Relation to ASIC3

Present and planned capabilities Impediments to progress Recommendations



Context


Necessary conditions for ASIC3

Common practices




Context

Some Necessary Conditions for ASIC3: Pre-launch

Sensor be fully characterized

Post-launchSensor performance be Continuously monitored Independently validated Deficiency/Anomaly be identified, resolved, documented, and

feedback for • re-analysis of historical data

• development of future sensors



Context Some common avenues to ASIC3 (Integrated Cal/Val System): Verification of internal consistency of onboard calibration Cross calibration with reference radiances

Dedicated sensor for on-orbit reference Terrestrial Targets Celestial targets: Moon, Star

Cross calibration with measured radiances Among any sensors, e.g., POES vs. GOES, operational vs. research Same S/C (temporal, geometric), e.g., imager vs. sounder Same series (spectral, spatial), e.g., POES vs. POES SNO

Cross calibration with simulated radiances NWP and CRTM

Monitoring, archiving, and disseminating the results in near real time throughout the sensor's mission life.

Weng



Overview

Outline of the assignments: Overview of the technique

Definition and Scope Instrumented and non-instrumented targets Four types of stable earth targets

Relation to ASIC3




Overview

Calibration The extraction of signal from sensor’s measurements … … by means of reference signal

Vicarious Calibration the reference is external to the sensor Measurement

ArtifactAt-aperture radiance

Calibration signal



Overview

Calibration The extraction of signal from sensor’s measurements … … by means of reference signal

Vicarious Calibration the reference is external to the sensor

Scope of the discussion Limited to radiometric calibration Focused on VISNIR (METEOSAT also used it for IR) Stable earth targets



Overview

Instrumented Earth Targets Lake Tahoe, Qinghai Lake: IR imaging instruments

Hook Zhang et al



Overview

Instrumented Earth Targets Lake Tahoe, Qinghai Lake: IR imaging instruments Railroad Valley (playa), Dunhuang (desert): VISNIR

ThomeZhang et al



Overview

Instrumented Earth Targets Lake Tahoe, Qinghai Lake: IR imaging instruments Railroad Valley (playa), Dunhuang (desert): VISNIR MOBY: ocean color

NOAA/NESDIS/ORA



Overview

Instrumented Earth Targets Lake Tahoe, Qinghai Lake: IR imaging instruments Railroad Valley (playa), Dunhuang (desert): VISNIR MOBY: ocean color ARM Sites (SGP CART in particular): IR/MW

sounding instruments



Overview


sounding instruments Cal/Val Campaign with aircraft/ship

CIMSS

Scripps



Overview


sounding instruments Cal/Val Campaign with aircraft/ship

Stable Earth Targets Scene Statistics Scattering & Reflection Ice Sheet (Greenland, Antarctica) Desert (North Africa, Australia)



Overview

Scene Statistics Representative works

• Brest and Rossow (1992)• Tokunu and Itaya (1994)• Crosby et al (2005)

Reference• Selected scenes, global or regional, all or clouds

Assumptions• Statistical characteristics of the selected scenes

are invariant in time



Overview

Scene StatisticsHISTOGRAM OF VISIBLE CHANNEL VALUES INTENSITIES

GOES-10 FOR JANUARY 3, 2000

VISIBLE CHANNEL INTENSITIES (COUNTS)

FR

EQ

UE

NC

Y O

F O

CC

UR

EN

CE

0 50 100 150 200

02

*10

^64

*10

^66

*10

^68

*10

^6

SPACE VIEW INTENSITIES

79% OF INTENSITIES ARE LESS THAN 200

EARTH VIEW INTENSITIES

PLOT OF INTENSITIES WITH 5 MILLION COUNTS ABOVE FOR GOES-10

TIME (YEAR)

Y(t

) =

IN

TE

NS

ITY

WIT

H 5

MIL

LIO

N C

OU

NT

S A

BO

VE

2000 2001 2002 2003

35

04

00

45

0

FIT WITH ANNUAL AND SEMI-ANNUAL TERMSFIT WITH SOLAR CORRECTION

Crosby et al 2005



Overview

Scene Statistics Easy to implement

• No scene selection such as cloud/clear Fundamental flaw in assuming that

certain earth scenes are statistically invariant in time• Cannot detect climate change• Often violated in shorter time scale

Relative calibration only



Overview

Scattering and Reflection Representative works

• Fraser and Kaufman (1986)• Kaufman and Holben (1993)• Vermote and Kaufman (1995)

Reference• Molecular scattering and reflection from sun glint or cloud

Assumptions• F&K: VIS measurements at certain angle is dominated by

molecular scattering, which is invariant in time and space• K&H: Reflection from sun glint is spectrally invariant• V&K:

– Spectral difference of aerosol scattering is known– Reflection from cloud top is spectrally invariant



Overview

Scattering and Reflection



Overview

Scattering and Reflection Abundant targets

• Potential to have very large sample size

Absolute calibration (subject to uncertainty) Rely on model

• Uncertainty in model input• Sensitivity of model to input uncertainty

Molecular scattering signal is weak (~4%)



Overview

Ice Sheet Representative works

• Loeb 1997• Tahnk and Coakley (2001)

Reference• Reflection from ice sheet over Greenland and

Antarctica

Assumptions• TOA reflectance is a quadratic function of solar

zenith angle



Overview

Ice SheetAntarctica Greenland

Channel 1

Channel 2



Overview

Ice Sheet Strong signal (~1/3 of dynamic range) Correction involves solar zenith angle

• Advantage in the presence of orbit drift

Relative calibration Difficulty in cloud detection (VIS or IR) Targets distribution – a lot of targets for

a short period of time



Overview

Desert Representative works

• Staylor (1990)• Rao and Chen (1996, 1999)

Reference• Reflection from selected desert sites

Assumptions• Surface characteristics is stable• TOA reflectance is well understood



Overview

Desert

From “Desert” by Christoph Heidelauf



Overview

Desert Strong signal Variety of signal

• Different desert

Relative calibration Noise (H2O, dust/aerosol, O3)



Capabilities


Present and planned capabilities Operational calibration at NOAA/NESDIS Requirements for climate may differ from those for operations

Impediments to progress Recommendations



Capabilities

Since 1996 Monthly update of AVHRR solar bands calibration coefficients

Second Tuesday every month

Disseminate the product Level 1B data stream Direct user notification Web (planned improvement)

All actions archived



Capabilities

Recent ImprovementsProduct monitoringSinusoidal FunctionMore checks for non-target pixels (cloud,

precipitation, dust)Target homogeneityPrecision

Current 5-10% Planned 3-5%



Capabilities

Product Monitoring & Precision

N16 – N17 AVHRR during SNO: Mean ~40%; Difference < 2%



Capabilities

Product Monitoring & Precision Standard Deviation

Ch. 1 Ch. 2 Ch. 3

1σ reflectance (%) 0.44 1.23 1.00

_ 3σ reflectance _

Mean reflectance3.5 8.7 4.5



Capabilities

Recent Improvements Product monitoring Sinusoidal Function More checks for non-target pixels (cloud, precipitation, dust) Target homogeneity Precision

Current 5-10% Planned 3-5%

Accuracy: Uncertain Earlier (Aircraft via NOAA-9): 37.8% for Channel 1 Lately (MODIS, supported by ATSR and MISR): ~41% Reconcile the difference Impact on users



Capabilities

Planned for near future Account for water vapor variation

Refl=α+βt+A*cos(ωt+φ0) Heidinger



Capabilities

Planned for near future Account for water vapor variation Other model of target BRDF

Refl=α+βt+A*cos(ωt+φ0)

cosρ=cosθcosθ0 + sinθsinθ0cos(azm)

θ≈0 → cosρ≈cosθ0

Stable orbit → θ0~t

• Are θ and θ0 reciprocal?• Is Refl linear function of cosρ?• Account for orbit drift (METEOSAT)?



Impediments


Present and planned capabilities Impediments to progress

Target characterization• Reference value• Diurnal/Annual variation• Atmospheric effect (water vapor, aerosol, O3)

Sensor characterization Multiple good targets

Recommendations



Impediments



Impediments

Sensor Characterization Spectral Response Function

• Inadequately specified

• Many unknowns

• Effort to archive all online …

• … and quantify their uncertainty

Radiometric Calibration• Pre-launch calibration procedure


Perfect target generates the same signal … At different time

On synoptic (“weather”), seasonal (vegetation), and inter-annual (El Niño) scales High altitude (less water vapor and dust variation)

From different parts Sensor’s IFOV, navigation error, cloud detection

In different spectral band Difference/Uncertainty in SRF of sensors

To different directions (sun/sensor geometry) Flat Low latitude

Near the upper limit of sensor’s dynamic range To increase S/N ratio and To reduce uncertainty when extrapolated

Not contaminated (by clouds) More for GEO


Impediments



Recommendations

Outline of the assignments: Overview of the technique Relation to asic3




Recommendations Continue the effort in vicarious calibration using stable earth targets

No other way to measure and calibrate the climate in the past

Collaboration International (sites, sensors, creativity) GEO and LEO Research and operation Producer and user. Find a good application.

• NDVI

• Aerosol

• Cryosphere

• Radiation budget

Learn the lesson Channel alignment (GOES-R ABI with VIIRS) Better specifications Operation overlap


Backup


Backup

Some were modified to be aligned with VIIRS

Some differences remain

Channel Index Pixel Size (m) Central (nm) (nm) Aligned With

ABI VIIRS ABI VIIRS ABI VIIRS ABI VIIRS VIIRS?

1 M3 1000 750 470 488 40 20 No

2 I1 500 375 640 640 100 80 No

3 I2 1000 375 860 865 40 39 Yes

4 M9 2000 750 1380 1378 30 15 Yes

5 I3 1000 375 1610 1610 60 60 Yes

6 M11 2000 750 2260 2250 50 50 Yes


Backup

Channel 1 Reflectance of a Corn Field Relative to That of NOAA-14(due to differences among sensors' spectral response functions)

0.75

0.80

0.85

0.90

0.95

1.00

1 2 3 4 5 6

05/21, 06/06, 06/13, 06/19, 06/27, and 07/03 in 2002

Rat

io t

o A

204

(NO

AA

-14)

N07

N09

N11

N16

N15

N17


Backup

Channel 2 Reflectance of a Corn Field Relative to That of NOAA-14(due to differences among sensors' spectral response functions)

0.97

0.98

0.99

1.00

1.01

1.02

1.03

1.04

1.05

1.06

1.07

1 2 3 4 5 6

05/21, 06/06, 06/13, 06/19, 06/27, and 07/03 in 2002

Rat

io t

o A

204

(NO

AA

-14)

N07

N09

N11

N16

N15

N17


Backup

NDVI of a Corn Field Relative to NOAA-14 Estimate(due to differences among sensors' spectral response functions)

0.98

1.00

1.02

1.04

1.06

1.08

1.10

1.12

1.14

1.16

1 2 3 4 5 6

05/21, 06/06, 06/13, 06/19, 06/27, and 07/03 in 2002

Rat

io t

o A

204

(NO

AA

-14)

N07

N09

N11

N16

N15

N17


Backup

Achieving Satellite Instrument Calibration for Climate Change, May 17, 2006, Lansdowne, VA 1...

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