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CLARREO RSS Reference Inter-Calibration: Method and Sampling Estimates . Constantine Lukashin Bruce Wielicki , Paul Speth , Carlos Roithmayr , CLARREO Engineering Team LaRC NASA, Hampton, VA. CLARREO STM, July 2010, Hampton, VA. Presentation Outline.

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clarreo rss reference inter calibration method and sampling estimates
CLARREO RSS Reference Inter-Calibration: Method and Sampling Estimates

Constantine Lukashin

Bruce Wielicki, Paul Speth, Carlos Roithmayr,

CLARREO Engineering Team

LaRC NASA, Hampton, VA

CLARREO STM, July 2010, Hampton, VA

presentation outline
Presentation Outline
  • Reference Inter-calibration strategy & method
  • CLARREO RS reference inter-calibration goals:
  • - inter-calibration of broadband sensor (JPSS/CERES)
  • - inter-calibration of an imager (JPSS/VIIRS)
  • DAC-5 Observatory Configuration and Orbital Simulations of orbit crossing with JPSS & MetOp
  • Reference Inter-calibration sampling estimates:
  • - JPSS/VIIRS (cross-track)
  • - JPSS/CERES (cross-track)
  • RI of VIIRS Sensitivity to Polarization: uncertainty
  • CLARREO RS instrument noise contribution to RI
  • Recommendation for mission requirements
acknowledgment for data 1 used in reference inter calibration studies
Acknowledgment for Data (1)Used in Reference Inter-Calibration Studies
  • SCIAMACHY Level-1 spectral radiance data obtained from ESA.
  • - Used to simulate CLARREO spectral radiances, CERES broadband and
  • VIIRS narrowband radiances, 250 – 1750 nm wavelength range, seasonal months 2003 – 2007.
  • - Used by MODIS team to demonstrate sensitivity to detection of MODIS
  • band SRF Central Wavelength shift (to be published soon).
  • - Used by CERES TISA group for inter-calibration of Geo S/C.
  • CERES/MODIS/Terra SSF data is used to provide scene description for SCIAMACHY field-of-view (5 locations per FOV).
  • POLDER-3/PARASOL Level-1data obtained from CNES, and Level-2 Clouds & Radiance Budget data from ICARE, France.
  • - Used to simulate distributions of observed polarization for inter-calibration sampling, development of empirical polarization distribution models.
acknowledgment for data 2 used in reference inter calibration studies
Acknowledgment for Data (2)Used in Reference Inter-Calibration Studies
  • - Used to derive requirement for CLARREO RS sensitivity to polarization.
  • CERES/MODIS/Aqua SSF data used to simulate scene type distributions within reference inter-calibration sampling of CLARREO RSS and JPSS sensors.
clarreo rss inter calibration strategy
CLARREO RSS Inter-Calibration Strategy
    • 1) CLARREO RSS will create benchmark climate data records
    • using two complementary approaches:
      • - Benchmark using only CLARREO RSS data: spectral
      • optimal fingerprinting (see ZhonghaiJin’s presentation)
      • - Benchmark using CLARREO for reference inter-
      • calibration of operational sensors
    • 2) RI Method: Comparison of sensor measurementswith high
    • accuracy standard in orbit (CLARREO RSS).
    • 3) CLARREO RSS measurements to be used as reference for:
      • -Sensoroffset and gain
      • - Spectral response function degradation or shift
      • - Sensitivity to Polarization
      • - Non-linearity
  • 4) CLARREO RSS RI goal: Error contribution ≤ 0.3% (k=2)
  • over autocorrelation time period of18 months (Leroy et al., 2008)
  • RI Error is considered to be random (D. Tobin’s presentation)
clarreo rss inter calibration goals
CLARREO RSS Inter-Calibration Goals
  • Goals are set at noise level ≈ 1% (sources: instrument + data matching )
  • RI error ≤ 0.3% (k=2) over auto-correlation time period = 18 months

1) CLARREO Inter-Calibration Goal: CERES

2) CLARREO Inter-Calibration Goal: VIIRS

example ceres srf degradation test clear ocean n 1800 and marine clouds scenes n 7000
Example: CERES SRF Degradation Testclear ocean (N = 1800) and marine clouds scenes (N = 7000)
  • CERES RSR Degradation:
  • α = 9.8155 (D=0.999 @ λ=0.7 μm)
  • Plots:
  • Top: CERES – CLARREO difference versus CLARREO signals (%).
  • Middle: CERES – CLARREO difference versus CLARREO signals (%) with 1% matching noise.
  • Bottom: Relative difference between
  • CLARREO and CERES signals with noise reduced by averaging.

* CLRO: Offset error (2σ) = 0.21%

* MCLD: Offset error (2σ) = 0.10%

clarreo sampling error scaling
CLARREO Sampling: Error Scaling

Assuming 1% space/time/angles data matching (Wielicki et al., IGARSS 2008), only linear case differences with CLARREO (offset and gain only), the reference inter-calibration error should be reduced as sqrt(N) as number of samples decreases.

 From simulation using

SCIAMACHY spectral data

(clear-sky ocean case)

clarreo sampling fractions of scene types
CLARREO Sampling: Fractions of Scene Types
  • Based on near-nadir CERES/MODIS/Aqua data (VZA < 10o, 20 km FOV).
  • SZA < 75o.
  • Distribution in latitude similar to CLARREO-JPSS inter-calibration
  • sampling (Studies by Speth & Roithmayr)

CLEAR SKY: Cloud fraction < 0.1%.

distribution of dop ri global sampling
Distribution of DOP (RI global sampling)
  • PARASOL Level-1 data: 12 days of 2006, accuracy 2-3%.
  • (1 day per month, “cross-track” sampling)
  • Distribution in latitude similar to CLARREO-JPSS RI sampling.
  • SZA < 75o.
  • DOP = linear degree of polarization
clarreo rs ri required sampling monthly
CLARREO RS RI Required Sampling: Monthly
  • CERES RI: All collected data together.
  • For VIIRS RI: Factor 2 for DOP ≤ 0.05 (670 nm), factor 7 for VZA, and
  • factor 2 for HAM sides. Total = factor 28.
clarreo rs ri required sampling seasonally
CLARREO RS RI Required Sampling: Seasonally
  • CERES RI: Factor of 30 for clear-sky ocean scene (3% of global sampling).
  • For VIIRS RI: factor 10 for DOP = 0.2 – 0.4 (670 nm), 7 for VZA, 9 for χ,
  • and factor of 2 for HAM side. Total = factor of 1,260.

DAC-4 CLARREO Observatory Configuration:

Both Spectrometers + GNSS-RO

(CLARREO Engineering Team, January 2010)

Double-axis (2D) gimbal to provide angular

data matching in both yaw and roll angles.

RSS located on nadir deck.

No bus maneuver required for

CLARREO RSS RI operations.


DAC-5 CLARREO Observatory Configuration:


(CLARREO Engineering Team, Current Baseline)

Single axis gimbal provides for “Roll” or cross-track pointing

DAC-5 concepts require “yaw” or +Z rotation by the S/C bus.

  • Angular matching:
  • “Yaw” maneuver allows to
  • match azimuth angle.
  • Gimbal “Roll” allows to
  • match scan/VZA angle



OFF Nadir +55o

OFF Nadir -55o


Orbital Simulations

(Carlos Roithmayr & Paul Speth)

DAC-5 CLARREO RSS RI Operations option:

1) S/C Yaw (azimuth angle) q1 match = constant (matching within 0.5o)

2) Continuous Gimbal Roll (scan angle) q2 match = q2(t)

  • Goal:
    • Time/space/angle matching to obtain ensemble of
    • samples with data matching noise ≤ 1%
    • Wielicki et al., IGARSS 2008
  • Matching requirements:
    • 5 min within JPSS passing
    • Viewing Zenith Angle matchwithin1.4°, SZA < 75o
    • At least 10 km effective width of CLARREO swath

CLARREO-1 RS boresight

locations matching JPSS

cross-track data over one year time period


Geometry of RI Event

Diagrams for DAC-5 Operation Option

Top view

Projection in JPSS cross-track plane

Note: All matched data (red parallelogram) is aligned with

JPSS cross-track direction


Orbital Simulations:

CLARREO-1 (2017) and 2 (2020) with JPSS

(Carlos Roithmayr & Paul Speth)

Inter-Calibration Time per Day:

CLARREO RSS is matched to JPSS in 833 km sun synch orbit.


Autumn Equinox, P90 orbit, Ω = 0o (orbital plane parallel to Earth-Sun


*Ω = right ascension of the ascending

node, or RAAN


Autumn Equinox, P90 orbit, Ω = 90o

(orbital plane perpendicular to Earth-Sun direction).

CLARREO Orbits should be optimized:

Study is in progress…


Orbital Simulations: CLARREO-1 (2017)

with JPSS and METOP

(Carlos Roithmayr & Paul Speth)

Inter-Calibration Time per Day:

CLARREO RSS is matched to JPSS in 1:30 pm (top); and METOP in 9:30 a.m. sun synch orbit. Both SS target orbits

are at 833 km altitude.


Autumn Equinox, P90 orbit, Ω = 0o (orbital plane parallel to Earth-Sun


RI Events on 2018.03.03: no overlap.

Yaw Time = 30.8 + 2.1×|q1| - 0.01×|q1|2

Inter-Calibration Operation Schedule:

Taking into account time for yaw maneuver 134 RI JPSS/METOP events overlap over one year time period (out of total 1,330 events).


Pre-decisional / For Planning Purposes Only


Orbital Simulations: RI and Operation Time

(Carlos Roithmayr & Paul Speth)

CLARREO-1 Inter-Calibration time:

Time of RI Event with all data matching restrictions (space/time/angles)


Yaw Time = 30.8 + 2.1×|q1| - 0.01×|q1|2

CLARREO-1 Operation time:

Inter-Calibration time + 2 Yaw Time intervals

Schedule of this Operation Time for CLARREO-1

RI with JPSS and METOP is generated.

  • Examples of Scheduling Priorities:
  • - RI Time interval (minimum duration/number of samples);
  • - RI Time versus Operation time (efficiency);
  • - Tropics versus polar regions (clear-sky ocean scene), oversampling in high latitudes;
  • RI versus Solar/Lunar calibration operations (potential scheduling conflict);
  • Minimization of RI impact on the benchmark (D. Doelling Group).

Sampling Estimate and Constrains

  • Sampling for AVHRR/VIIRS is nadir equivalent 10×10 km area in angular space,
  • 1o CLARREO elevation angle. To estimate number of samples with independent
  • spatial noise 1 km shift (0.1o in elevation angle ) is required from one sample to
  • the next in both spatial directions (along CLARREO frame and along ground
  • track). With CLARREO spatial resolution of 0.5×0.5 km the 1 km shift ensures
  • that only 2 boundary pixels are common.
  • - This approach of forming a CLARREO/VIIRS RI sample does not allow inter-
  • calibration on detector-by-detector basis. Relative calibration (flat-fielding)
  • is required using VIIRS data alone.
  • CERES IR sampling is estimated taking into account CERES FOV size of 25 km
  • at nadir (from JPSS orbit, 2.5o in CLARREO elevation angle), and data acquisition
  • rate 330/180 = 1.8 footprints per degree of scan angle every 3.3 seconds.
  • Constrains:
  • SZA < 75o (to ensure high SNR);
  • CLARREO effective swath > 10 km in VIIRS case, and > 25 km in CERES case.
  • VZA difference < 1.4o, SZA and RAZ are matched within 1o.

Sampling Summary for CLARREO-1/JPSS

Monthly (top) and seasonal (bottom) sampling withVIIRS andCERES

Red Errors: Required number

of samples for RI monthly error contribution 1.2% (k=2)

Red Lines: Required number

of samples for RI seasonal error contribution 0.7% (k=2)

WARNING: The required number of RI samples is derived under assumption of

uniform sampling distributionin relevant parameters to VIIRS

sensitivity to polarization: DOP and polarization angle.


Distribution of DOP, PARASOL Data, 2006.10.02

Average on 1o×1o grid, fractional units, “cross-track” mode

λ =490 nm

* RAZ < 90o is to the left of the ground track

* RAZ > 90o is to the right of the ground track

λ =670 nm

λ =865 nm

* For cross-track data tacking mode DOP

distribution is has systematic dependence

on viewing geometry.


Distributions of DOP and Polarization Angle

PARASOL Data, 12 days 2006, simulated cross-track RI sampling

- λ =490 nm

- if (χ < 0) χmod = 180o + χ

* Color scale =

Relative sampling

Forward Scatter

Back Scatter


Possible RI of VIIRS on detector-by-detector basis,

Diagram, Sampling plots, more studies

- Angular matching within 1.4o VZA

  • Spatial matching: about
  • 300 pixels VIIRS and 400 CLARREO
  • (2 consecutive frames)
  • Study needed to estimate spatial
  • matching noise (using MODIS
  • 250 m resolution data)
  • CLARREO reading data rate could
  • beincreased (to reduce spatial
  • noise)

Note: VIIRS scans cross-track with

16 detectors/band in a-track direction

every 1.5 sec or every 11 km. 11 km

swath is built by 16 detectors.

sensitivity to polarization
Sensitivity to Polarization
  • For a particular instrument design instrument response function
  • can depend on polarization of reflected light (DOP) and phase
  • angle of polarization.
  • Definitions (consistent with PARASOL definitions):
  • Ip2 = Q 2 + U 2 ( V 2 is small ); DOP = Ip/ I ; χ = tan -1(U/Q) / 2
  • where Ip = polarized radiance; DOP = Degree of Linear Polarization;
  • χ = angle of polarization relative to view plane.
  • Sensitivity to polarization of instrument optics translates into dependence of its effective gain on DOP, and viewing geometry of instrument (χangle)
  • (MODIS Characterization, Sun and Xiong, 2007)
  • Lmes = (1 + DOP × mQU) Ltoa(from Menghua Wang’s VIIRS memo)
  • mQU = sqrt (mQ2 + mU2) (mQU is function of χ)
  • If DOP ≈ 1 and uncertainties of DOP and mQU are large, error contribution
  • from polarization can be compatible with the radiometric errors, even the mQU is relatively small.
clarreo ri viirs sensitivity to polarization
CLARREO RI: VIIRS Sensitivity to Polarization
  • CLARREO RS Reference Inter-Calibration Approach:
  • 1. Gain correction from comparison of CLARREO high absolute accuracy radiances for samples
  • matched within defined state of polarization and viewing geometry.
  • CLARREO = SI-traceable calibration source in orbit.
  • 2. State of polarization is obtained by applying Polarization Distribution Models (PDM).
  • Estimated empirical PDM instantaneous error is about 10% (k=1). RT model errors ?

Prototype PDM and its STD, PARASOL

Data (12 days of 2006, 1 per month):

A-Train Orbit Cross-Track Sampling

(PARASOL 12 days of 2006):

clarreo ri viirs sensitivity to polarization1
CLARREO RI: VIIRS Sensitivity to Polarization
  • 3. Inter-calibration uncertainty.
  • Lclarreo = (1 + DOP × mQU) Lviirs
  • mQU = (Lclarreo/ Lviirs - 1) / DOP = (Gp – G0) / DOP = ΔG / DOP
  • σm/ mQU= sqrt [ (σΔG / ΔG)2 + (σDOP / DOP )2 ]
  • σΔG = sqrt [ (σGp )2 + (σG0 )2 ]
  • σDOP= PDM accuracy (not the inst. error which averages out)
  • Notes:
  • The uncertainty of mQU can be reduced by multiple inter-calibration in different DOP ranges
  • (linear case, factor sqrt(N), requires larger sampling to get high DOP.
  • For VIIRS mQU is function of of wavelength (band), detector, half angle mirror (HAM)
  • side, scan angle and χ:mQU( λ, Detector, HAM, scan angle,χ).
  • VIIRS has 16 detectors in 11 km along-track direction scanning within ± 56o at 40 rpm rate:
  • a scan every 1.5 seconds. For CLARREO RI method consistency between detectors is
  • required (flat-fielding or relative calibration, VIIRS instrument team)

CLARREO RS Instrument Noise Contribution

  • CLARREO RS instrument noise contribution when inter-calibrating with CERES: integration over broadband range, error summation.
  • SCIAMACHY data used for simulation (at 4 nm spectral resolution).
  • CLARREO RS instrument SNR, defined for reflectance 0.3 at solar zenith angle 75o (current requirement):
  • - SNR > 20 in 320 – 380 nm;
  • - SNR > 30 in 380 – 900 nm;
  • - SNR > 20 in 900 – 2300 nm;
  • SNR = 20 is used in simulation for entire range.
  • Estimated instrument noise at maximum level of spectral radiance,
  • 0.09 W/(m2 sr nm) at 470 nm wavelength. Estimated instrument noise for
  • singe spectral sample is 0.0045 W/(m2 sr nm). Assuming that instrument
  • noise is non-correlated the total noise for the broadband is 0.087 W/(m2sr).
  • Single CLARREO Pixel: For all-sky scenes relative error increases from
  • 0.5% (at SZA=25o) to about 2.5% (at SZA=85o). For clear-sky ocean scene
  • relative error increases from 0.8% (at SZA=25o) to about 3.0% (at SZA=85o).
  • CERES FOV (25 km at nadir): contains about 2,000 CLARREO pixels.
  • Averaging reduces instrument noise contribution factor 40.
summary recommendation for mission requirements
Summary: recommendation for mission requirements
  • CLARREO RSS accuracy, spectral range and resolution, spatial resolution
  • are required to be a reference in orbit.
  • 2D angular data matching (azimuth and elevation) is required:
  • constant in azimuth and varying in elevation within matching tent.
  • For mission baseline all reference inter-calibration goals are feasible from sampling point of view. CLARREO RS instrument in polar 90o orbit provides adequate sampling monthly, seasonally and annually for inter-calibration of
  • cross-track sensors on JPSS/METOP.
  • Polarization Distribution Models are required for inter-calibration sensor
  • sensitivity to polarization, and its stand-alone operation.
  • A global all-sky set of models should be built for DOP and polarization angle χ .
  • Future Work:
  • - Account for detailed distributions in DOP and polarization angle;
  • - CLARREO RSS orbit optimization;
  • - Develop operation / scheduling model;
  • - PDM development (one year of PARASOL data + RT model + APS data);
  • - Quantitative study on RI sample geometry and spatial noise (MODIS data).

CLARREO RS spectrometer baseline:

  • Radiance measurements with accuracy 0.3%(2σ) for the time of the mission, uncertainty due to sensitivity to polarization included.
  • Wavelength range from 320 to 2300 nm.
  • Spectral sampling = 4 nm.
  • Spatial resolution 0.5×0.5 km (65% of signal).
  • Pointing ability (gimbal or S/C).
  • Polarization Distribution Models to provide polarization information (both DOP and χ).
  • CLARREO RS Inter-Calibration Event:
  • orbits crossing of CLARREO with sensor
  • to be calibrated that allows time/angle/
  • space matching
  • CLARREO RS Swath: 100 km (nadir)
  • CLARREO/Solar Inter-Calibration Sample:
  • area of 10 km scale for reduction
  • of spatial matching noise to 1% level.
  • (Wielicki et al., IGARSS 2008)
  • CLARREO RS Pixel:
  • 0.5×0.5 km observed area (65% of signal).

Study needed to quantify sampling

Geometry (MODIS data 250 m resolution)


Pre-decisional / For Planning Purposes Only


dac5 configuration 1 observatory in 90 o orbit
DAC5 Configuration: 1 Observatory in 90o orbit

Estimated Monthly N samples for CERES and VIIRS:

Average error over one year period is 0.%(k=2) for CERES and 0.%(k=2) for VIIRS.


Operation Option DAC5: 1 Observatory in 90o orbit

Seasonal N samples for CERES:

Seasonal N samples for VIIRS: