EOS

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Study of Sensor Inter-calibrationUsing CLARREO

Jack Xiong, Jim Butler, and Steve Platnick NASA/GSFC, Greenbelt, MD 20771

with contributions fromMODIS Characterization Support Team (MCST), NASA/GSFC

CLARREO Workshop, 21-23 October 2008, Washington, DC

Outline

• Introduction– Applications of CLARREO– Requirements for CLARREO Observations

• Inter-calibration Approaches Using CLARREO– Lunar observations

• VIS/NIR/SWIR only

– Simultaneous nadir observations (SNO)– Ground observations (Dome C)

• Inter-comparison of Terra and Aqua MODIS calibration

• Sensitivity Study (future work)– RSR sensitivity study (using Schiamachy with LaRC)– Spectral and spatial sensitivity studies of Earth view

targets (Hyperion and AVIRIS)

• SummaryPage 2

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Introduction

• Applications of CLARREO

– Benchmark Observations

• Accurate, stable, SI traceable, spectrally resolved

– Inter-calibration for Other Sensors

• Consistent data records for long-term climate change

• Requirements for CLARREO Observations

– General Requirements

• Spectral; spatial; temporal; orbital

– Special Requirements

• Maneuver (pointing) capability

• Lunar observations

Inter-calibration Approaches Using CLARREO

• Lunar observations

– MODIS (T/A), SeaWiFS, Hyperion, VIRS/TRMM

• Simultaneous nadir observations (SNO)

– MODIS (T/A), AVHRR, AIRS, MISR, ASTR, Landsat, GLI,

VIRS/TRMM

• Ground observations

– Dome Concordia, Antarctica

– MODIS (T/A), AVHRR, AIRS, MISR, ASTR

– Inter-calibration of Terra and Aqua MODIS

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Collaboration with USGS (Moon), NOAA, JPL, JAXA, USGC (SNO/Dome C)

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Inter-calibration Using Lunar Observations

MODIS Lunar Observations:

via spacecraft maneuvers

at fixed phase angle

reference to a lunar model (USGS)

using integrated irradiance

/

/Terrr MODIS Modle

Aqua MODIS Modle

I IR

I I

Images form Aqua MODIS (band 1) Lunar Observations (Oct 04 – Jun 05)

Xiong and Sun (GRSL in press)

Advantages vs disadvantages:

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Inter-calibration Using SNO

Terra MODIS Aqua MODIS

AVHRR

SNOSNO

For RSB

1 2/ / /Terrr MODIS Ref-sensor t Aqua MODIS Ref-sensor tR r r r r

1 2Terrr MODIS Ref-sensor t Aqua MODIS Ref-sensor tT T T T T For TEB

Advantages vs disadvantages:

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Aqua MODIS SD Degradation (0.41 to 0.94m)

Any Impact on Calibration?

Inter-calibration Using a Ground Target

• Why using a ground target

– Validate on-board calibration; complement other cal/val approaches

– Monitor calibration long-term stability

– Support sensor inter-calibration

• Requirements for a ground “calibration” target

– Spectral and spatial uniformity and radiometric stability (minimum environmental impact)

– Site accessibility and data availability

– Ground measurements of radiometric traceability

Examples of Using Dome C for Inter-calibration

• Site Description

• Data Selection

• Methodology– Thermal emissive: reference to Automated Weather Station

(AWS) measurements

– Solar reflective: BRDF model based on ground measurements over Antarctic snow

• Results from MODIS– Recent presentation at SPIE Europe Remote Sensing (Xiong

et al. 2008)

• Future WorkPage 8

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Site Description

Dome ConcordiaAntarctica

• Located on Antarctic Plateau (75.1 S, 123.4 E)– One of the most homogeneous land surfaces

on earth in terms of surface temperature and emissivity.

• Uniformity over spatial scales typical of the ground footprint of satellite sensors

– High altitude (~3200 m) & minimal slope– Low snow accumulation rate– Extremely dry, cold & rarefied atmosphere

• Low fractional cloud coverage• Low atmospheric aerosol and water vapor

content

• Permanently manned Research Station now operational– AWS data available since 1995

• 10-minute averages of meteorological parameters (T, RH, WS, WD, P)

– Daily radiosonde measurements

• Frequent satellite overpass

CEOS Endorsed SiteNASA/NOAA/ESA Effort

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Data Selection

•MODIS Collection 5 Level 1B data

•Multiple MODIS observations each day (~8) at different angles of incidence.

•Only near-nadir overpasses used (nadir track within +/- 50 km of Dome C). One granule every 2-3 days.

•20x20 pixel average centered on Dome C

•No cloud screening applied for TEB. All granules used.

•Uniformity screening applied for RSB to eliminate any granules showing greater than 2% non-uniformity in reflectance over the 20x20 pixel area

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Methodology and Approach (TEB)

AWS surface temperature measurements are used as a proxy to track any trends in the relative bias between MODIS Terra & Aqua.

TMODIS = BTMODIS – TAWS

Relative Bias = TTerra – TAqua

Relative Bias calculated for each MODIS band and only for days with measurements from both Terra & Aqua.

Applications to other sensors: relative spectral response (RSR), spatial resolution (ground footprint)

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Methodology and Approach (RSB)

A BRDF model developed by Warren et al. (JGR 1998) based on near-surface reflectance measurements over the Antarctic snow

R (θ,ψ,φ) = c1 + c2cos(π- φ)+ c3cos[2(π- φ)]

c1, c2 and c3 are functions of cos(θ) and cos(ψ)

c1 = a0 + a1[1 - cos(ψ)], c2 = a2[1 - cos(ψ)], c3 = a3[1 - cos(ψ)]

ai = b0i + b1i cos(θ) + b2i cos2(θ) (i = 0, 1, and 2)

where θ is the incident solar zenith angle, ψ is the viewing zenith angle, and φ is the relative azimuth angle.

A ratio of the observed reflectance factor r to modeled reflectance factor R is calculated by Δr = r / R

Spectral BRDF of Antarctic snow from Hudson, Warren et al (JGR 2006)

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Sensor (11 and 12 m) and AWS Observations

Terra: Black diamonds; Aqua: Blue squares

Good correlation between sensor and AWS observations(focusing long-term behavior, not individual observations)

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Long-term draft (<10mK) for bands 31 and 32; high quality on-board TEB calibration

Excellent calibration consistency (11m: 0.025±2.984K; 12m: 0.013±3.010K)

No obvious temperature dependent bias (<20mK)

Relative Bias = TTerra – TAqua (time)

TMODIS = BTMODIS – TAWS

Terra: Black diamonds; Aqua: Blue squares

11m 12m

Relative Bias = TTerra – TAqua (temperature)

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-4

-3

-2

-1

0

1

2

3

4

180 190 200 210 220 230 240 250 260

MODIS B31 BT (K)

B

T (

MO

DIS

- A

IRS

)

Aqua MODIS 'Test' Collection at Dome C

One orbit – June 20, 2006(near nadir footprints)

Dome C data (near nadir)

190K – 330K

Inter-comparison of Aqua MODIS and AIRS at 11 m

(using Dome C observations)

Old version

New version

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Sensor (0.65 and 0.86 m) Observations

strong correlation between sensor observations and solar zenith angle

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Sensor (0.65 and 0.86 m) Observations versus Modeled Values

Averaged fitting residual: 1.3 – 1.9%

Model parameters derived using sensor first-year observations

Page 18Terra MODIS observations (0.65m) over Dome C (2002 - 2003)

Page 19Terra MODIS observations (0.86m) over Dome C (2002 - 2003)

Page 20Terra and Aqua MODIS observations over Dome C

Sensitivity Study (future work)

• RSR Sensitivity Study

– Extend from our previous study reported at

April/May CLARREO workshop (e.g., preferred inter-

calibration scene types vs. spectral band)

– Work with LaRC using Schiamachy data

• Spectral and Spatial Sensitivity Studies

– Hyperion observations, Dome C and other targets

• 0.4 to 2.5m, 30m IFOV (@705km altitude)

– AVIRIS observations

• 0.4 to 2.5m, 1 mrad IFOV

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http://eo1.usgs.gov/hyperion.php

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http://aviris.jpl.nasa.gov/html/aviris.instrument.html

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Summary

• Sensor Inter-calibration Using CLARREO– Improve current sensor inter-calibration approaches with

highly accurate, stable, and spectrally resolved observations

– Resolve calibration differences or establish calibration consistency among sensors with on-orbit SI traceable measurements

• Ground Target Characterization Using CLARREO – Extend consistent data records, using observations from

previous, current, and future missions/sensors, for studies of long-term climate changes

– Dome C site can be used to track sensor long-term stability and calibration consistency among sensors (challenges in VIS/NIR/SWIW)

• Other Approaches– Lunar observations; SNO