CLARREO RSS Reference Inter-Calibration: Method and Sampling Estimates

1Pre-decisional / For Planning Purposes Only7/5/2010

CLARREO RSS Reference Inter-Calibration: Method and Sampling Estimates

CLARREO STM, July 2010, Hampton, VA

Constantine Lukashin

Bruce Wielicki, Paul Speth, Carlos Roithmayr,

CLARREO Engineering Team

LaRC NASA, Hampton, VA


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

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-1 data 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

- 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 Strategy1) CLARREO RSS will create benchmark climate data records using two complementary approaches:

- Benchmark using only CLARREO RSS data: spectral optimal fingerprinting (see Zhonghai Jin’s presentation)- Benchmark using CLARREO for reference inter- calibration of operational sensors

2) RI Method: Comparison of sensor measurements with high accuracy standard in orbit (CLARREO RSS).

3) CLARREO RSS measurements to be used as reference for:- Sensor offset 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 of 18 months (Leroy et al., 2008) RI Error is considered to be random (D. Tobin’s presentation)


CLARREO RSS Inter-Calibration Goals

Parameter Time scale Variable RI Error, k=2 (%)

Offset monthly All Data ≤ 1.2

Gain monthly All Data ≤ 1.2

SRF Degradation seasonally Scene Type (clro) ≤ 0.7

Non-Linearity Validation Annually, RI Error 0.3%(k=2)

Sensitivity to Polarization Not Sensitive, Validation Annually, RI Error 0.3%(k=2)

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: VIIRSParameter Time scale Variable RI Error, k=2 (%)

Baseline Offset monthly VZA(7), DOP, HAM ≤ 1.2

Baseline Gain monthly VZA(7), DOP, HAM ≤ 1.2

Sensitivity to Polarization seasonally VZA(7), DOP, χ (9), HAM ≤ 0.7

SRF CW Shift Validation Annually, RI Error 0.3 %(k=2)

Non-Linearity Validation Annually, RI Error 0.3%(k=2)


Example: CERES SRF Degradation Test clear 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.

FIT RESULTS:Scene OFFSET

(Wm-2sr-1)GAIN (%)

CLRO -0.183 ± 0.028 -0.31 ± 0.18

MCLD 0.021 ± 0.108 -0.73 ± 0.10

* CLRO: Offset error (2σ) = 0.21%* MCLD: Offset error (2σ) = 0.10%


CLARREO Sampling: Error ScalingAssuming 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.

Error versus N samples:N Samples RI Error (%, k=2)

16,000 0.118,000 0.154,000 0.212,000 0.31,000 0.42500 0.6250 0.85125 1.2

From simulation using SCIAMACHY spectral data (clear-sky ocean case)


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)

2005 CERES SSF, Fraction of Clear - Sky:Surface Type Tropic Clear

(%)Non-Tropic Clear

(%)Ocean 2.145 0.829Evergreen Forest 0.093 0.146Deciduous Forest 0.057 0.235Shrubs & Crops 1.127 0.784Dark Desert 0.598 0.255Bright Desert 0.926 0.088Snow 0.039 5.809

CLEAR SKY: Cloud fraction < 0.1%.


Distribution of DOP (RI global sampling)

Relative fraction of data (%) with DOP(490 nm) < X (fractional):DOP Range < 0.05 < 0.1 < 0.2 < 0.3 < 0.4 < 0.5 < 0.75

Global Data (%) 24.2 55.0 79.8 89.5 94.6 97.6 99.98


Global Data (%) 46.4 71.8 87.3 93.9 97.2 98.9 99.77


Global Data (%) 65.6 81.6 91.5 96.1 98.4 99.5 99.98

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: MonthlyN Samples CERES N Samples VIIRS RI Errors, k=2 (%)

16,000 448,000 0.11

8,000 224,000 0.15

4,000 112,000 0.21

2,000 56,000 0.3

1,000 28,000 0.42

500 14,000 0.6

250 7,000 0.85

125 3,500 1.2

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

N Samples (CERES) N Samples (VIIRS) RI Errors, k=2 (%)480,000 20.0 M 0.11

240,000 10.0 M 0.15

120,000 5.0 M 0.21

60,000 2.5 M 0.3

30,000 1.25 M 0.42

15,000 0.6 M 0.6 (0.7)

7,500 0.3 M 0.85

3,750 0.15 M 1.2

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)

RSS located on nadir deck.No bus maneuver required for CLARREO RSS RI operations.

Double-axis (2D) gimbal to provide angular data matching in both yaw and roll angles.


DAC-5 CLARREO Observatory Configuration:RSS + GNSS-RO

(CLARREO Engineering Team, Current Baseline)

Nadir (+Z)

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

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

OFF Nadir +55o OFF Nadir -55o

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


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 match within 1.4°, SZA < 75o

• At least 10 km effective width of CLARREO swath

CLARREO-1 RS boresightlocations matching JPSScross-track data over one year time period


Geometry of RI Event Diagrams for DAC-5 Operation Option

Projection in JPSS cross-track plane

Top view

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)

CLARREO-1 Mission START: Autumn Equinox, P90 orbit, Ω = 0o (orbital plane parallel to Earth-Sundirection)

CLARREO-2 Mission START: Autumn Equinox, P90 orbit, Ω = 90o (orbital plane perpendicular to Earth-Sun direction).

Inter-Calibration Time per Day: CLARREO RSS is matched to JPSS in 833 km sun synch orbit.

CLARREO Orbits should be optimized:

Study is in progress…

* Ω = right ascension of the ascending node, or RAAN


Orbital Simulations: CLARREO-1 (2017) with JPSS and METOP

(Carlos Roithmayr & Paul Speth)

RI Events on 2018.03.03: no overlap.

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).

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

CLARREO-1 Mission START: Autumn Equinox, P90 orbit, Ω = 0o (orbital plane parallel to Earth-Sundirection)

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.

Pre-decisional / For Planning Purposes Only7/5/2010


Orbital Simulations: RI and Operation Time(Carlos Roithmayr & Paul Speth)

DAC-5 CLARREO RSS Bus:Yaw Time = 30.8 + 2.1×|q1| - 0.01×|q1|2

CLARREO-1 Inter-Calibration time:Time of RI Event with all data matching restrictions (space/time/angles)

CLARREO-1 Operation time:Inter-Calibration time + 2 Yaw Time intervals

Schedule of this Operation Time for CLARREO-1RI 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 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 Estimate and Constrains


Sampling Summary for CLARREO-1/JPSSMonthly (top) and seasonal (bottom) sampling with VIIRS and CERES

Red Lines: Required number of samples for RI seasonal error contribution 0.7% (k=2)

Red Errors: Required number of samples for RI monthly error contribution 1.2% (k=2)

WARNING: The required number of RI samples is derived under assumption of uniform sampling distribution in relevant parameters to VIIRS sensitivity to polarization: DOP and polarization angle.


Distribution of DOP, PARASOL Data, 2006.10.02Average 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 AnglePARASOL Data, 12 days 2006, simulated cross-track RI sampling

- if (χ < 0) χmod = 180o + χ - λ = 490 nm

Forward Scatter Back Scatter

* Color scale = Relative sampling


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 be increased (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 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):

Ip 2 = 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 (χ angle)

(MODIS Characterization, Sun and Xiong, 2007)

Lmes = (1 + DOP × mQU) Ltoa (from Menghua Wang’s VIIRS memo)

mQU = sqrt (mQ2 + mU

2) (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

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 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 ?


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/(m2 sr).

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

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).


Backup Slides


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 Only7/5/2010 31


DAC5 Configuration: 1 Observatory in 90o orbit

Month N Samples CERES

RI Error k=2 (%)

N SamplesVIIRS

RI Error k=2 (%)

1 September 48.5 K ≤ 0.1 6.1 M ≤ 0.1

2 October 1.4 K 0.42 0.18 M 0.15

3 November 0.3 K 0.85 0.09 M 0.2

4 December 3.1 K 0.3 0.54 M 0.1

5 January 16.8 K 0.1 2.2 M ≤ 0.1

6 February 54.1 K ≤ 0.1 6.7 M ≤ 0.1

7 March 57.1 K ≤ 0.1 7.1 M ≤ 0.1

8 April 14.5 K 0.1 1.9 M ≤ 0.1

9 May 2.9 K 0.3 0.53 M 0.1

10 June 2.9 K 0.3 0.52 M 0.1

11 July 6.2 K 0.2 0.85 M ≤ 0.1

12 August 34.8 K ≤ 0.1 4.4 M ≤ 0.1

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.


Season N Samples RI Errors, k=2 (%)

S1 50 K 0.4

S2 74 K 0.3

S3 73 K 0.3

S4 43 K 0.4

Seasonal N samples for CERES:

Operation Option DAC5: 1 Observatory in 90o orbit

Season N Samples RI Errors, k=2 (%)

S1 6.3 M 0.2

S2 9.4 M 0.15

S3 9.5 M 0.15

S4 5.7 M 0.2

Seasonal N samples for VIIRS:

Documents

CLARREO RSS Reference Inter-Calibration: Method and Sampling Estimates