1. Using Double Differences in MICROS for Cross-Sensor Consistency Checks
Xingming Liang1,2, Sasha Ignatov1 and Korak Saha1,2
1NOAA/NESDIS/STAR 2CSU/CIRA
GSICS Annual Meeting, Beijing, 5-8 March 2012
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2. GSICS Annual Meeting, Beijing, 5-8 March 2012
Acknowledgments
Advanced Clear-Sky Processor for Oceans (ACSPO; NESDIS Sea Surface Temperature System): Sensor Radiances over Oceans with Clear-Sky Mask and QC
J. Sapper, Y. Kihai, B. Petrenko, J. Stroup, P. Dash, F. Xu, M. Bouali – NESDIS SST Team
Sensor Characterization & Cross-platform Consistency, including Double Differences (DD)
F. Wu, F. Yu, C. Cao, L. Wang, F. Weng, M. Goldberg, T. Hewison, J. Xiong, X. Hu, T. Chang – GSICS
Community Radiative Transfer Model (CRTM)
F. Weng, Y. Han, Q. Liu, P. Van Delst, Y. Chen, D. Groff – CRTM
N. Nalli - Surface emissivity model
GSICS Annual Meeting, Beijing, 5-8 March 2012
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3. GSICS Annual Meeting, Beijing, 5-8 March 2012
Outline
MICROS overview
MICROS Double-Differences (DD)
Relative Merits: SNO, Hyper-Spectral DDs
Conclusion
Future plans
GSICS Annual Meeting, Beijing, 5-8 March 2012
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4. GSICS Annual Meeting, Beijing, 5-8 March 2012
MICROS Overview
Objectives
Sensors monitored
System set-up & Processing time
MICROS Hightlights
Ways to present M-O bias
GSICS Annual Meeting, Beijing, 5-8 March 2012
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5. GSICS Annual Meeting, Beijing, 5-8 March 2012
MICROS Objectives
Monitor clear-sky sensor radiances (BTs) over global ocean in NRT (“OBS”) , against CRTM with first-guess input fields (“Model”)
Understand & minimize M-O biases in BT & SST
minimize need for empirical “bias correction”
Evaluate sensor radiances for stability
Check for cross-platform consistency
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6. Platforms/Sensors monitored in MICROS
Routinely processing 5 AVHRRs Jul’2008-on
Metop-A (GAC and FRAC) - Good
NOAA19 - Good
NOAA18 – Good
NOAA17 - stopped processing 2/10; sensor issues
NOAA16 - out of family
Under testing / In pipeline
NPP/VIIRS
Terra/MODIS
Aqua/MODIS
MSG/SEVIRI
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7. System Set-Up & Processing Time
Fully automated
Scripted/Cronned
Back-up processing
ACSPO: Identify clear-sky pixels (Fortran 95)
MICROS: Generate stats (IDL)
Post to web: Html/JS/JQuery/JQplot
Processing Time (ACSPO/MICROS): Process 24hrs of Day (N-2)
5 GAC AVHRRs
(NOAA16-19, MetopA)
1 FRAC AVHRR (Metop-A)
MODIS/Terra & Aqua
VIIRS/NPP
ACSPO/MICROS
3/0.5
4/1
10/3 (under opt.)
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8. GSICS Annual Meeting, Beijing, 5-8 March 2012
Model - Obs
Advanced Clear-Sky Processor for Oceans (ACSPO)
“M” = MODEL Clear-Sky BT (currently, in SST bands only)
Calculated using CRTM, with first guess SST (daily 0.25º Reynolds) and upper air fields (NCEP GFS 6hr 1º) as input
Fast CRTM allows for real-time processing
“O”= OBS: Clear-Sky Ocean Sensor BTs
Clear-Sky Ocean pixels identified using ACSPO Cloud Mask and QC
Monitoring IR Clear-sky Radiances over Oceans for SST
Calculates M-O bias & Runs global daily statistics on it
Processing fully automated, performed in NRT
Also, Double-Differences calculated w.r.t. a Reference sensor
Graphic summaries reported on the web
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9. GSICS Annual Meeting, Beijing, 5-8 March 2012
MICROS Highlights
End-to-end system
Web-Based
Near-Real Time
MICROS
Both conventional & robust statistics used
Statistical analyses performed in global clear-sky ocean domain
Analyses stratified by Day/Night
Only Night data used for sensor analyses
Presently, daytime data not used due to sub-optimal treatment of solar reflectance & diurnal cycle
Double-differences used to evaluate sensor radiances for cross-platform consistency
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10. Ways to present M-O Bias
Maps
Four ways to present
M-O Biases in MICROS
Histograms
Time series
Dependencies
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11. GSICS Annual Meeting, Beijing, 5-8 March 2012
Maps
The M-O biases: Close to zero; Uniformly distributed
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12. GSICS Annual Meeting, Beijing, 5-8 March 2012
Dependencies
View Angle dependencies of M-O bias: Close to zero
GSICS Annual Meeting, Beijing, 5-8 March 2012
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13. GSICS Annual Meeting, Beijing, 5-8 March 2012
Histograms
Near-Gaussian
# clear-sky oceans pixels ~3Million/night (global GAC)
M-O bias is close to zero
In fact, it’s slightly warm: Expected (Discussed next slide)
Cross-platform biases close to zero (~0.2 K)
Overpass times from 9:30pm-5am (Diurnal effects)
Errors in sensor SRFs (CRTM coefficients) & CAL
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14. GSICS Annual Meeting, Beijing, 5-8 March 2012
Time Series for GAC
M-O bias in Ch3B
M-O Biases in Ch3B
BT are in sync with SST oscillations
ACSPO version
V1.30
V1.40
V1.10
V1.00
V1.02
Warm M-O biases result from: (1) Missing aerosols; (2) Using bulk SST (instead of skin); (3) Using daily mean Reynolds SST (to represent nighttime SST); (4) Residual cloud
Temporal variability: Due to unstable Reynolds SST (input into CRTM)
N16: Out of family/Unstable (CAL problems)
N17: Scan motor spiked in Feb’2010
SST Biases (Regression-Reynolds)
GSICS Annual Meeting, Beijing, 5-8 March 2012
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15. Double Differences (DD) Cross-platform consistency in MICROS
Day-to-day noise and spurious variability hinder accurate measurement of cross-platform bias
Double-differences (DD) employed to differentiate the “cross-platform bias” signal from “noise”
Metop-A used as a Reference Satellite
Stable; Overpass time close to N17/Terra
CRTM (Reynolds SST) is used as a ‘Transfer Standard’
DDs cancel out/minimize effect of systematic errors & instabilities in BTs and SSTs arising from e.g.:
Errors/Instabilities in reference SST & GFS
Missing aerosol
Possible systemic biases in CRTM
Updates to ACSPO algorithm
GSICS Annual Meeting, Beijing, 5-8 March 2012
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16. DDs (Ref = Metop-A) Cross-platform consistency in IR37
Double Differences (DDs) in IR37
NOAA16
V1.30
V1.40
V1.02
V1.10
V1.00
DDs cancel out most errors/noise in M-O biases
Relative to Metop-A , biases are
N16: unstable
N17: ± 0.02 K (scan motor failed Feb’10)
N18: ± 0.05 K (not very stable)
N19: ± 0.02 K
GSICS Annual Meeting, Beijing, 5-8 March 2012
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17. DDs in other bands Cross-platform consistency in IR11&12
Double Differences in IR11
N16: Unstable in all 3 bands
N17: biased +0.05K high in IR11; K low in IR12
N18: biased -0.02K low in IR11; K high in IR12
N19: biased -0.07K low in IR11; K low in IR12
N18: Similar pattern in IR11 and IR12 with IR37.
Double Differences in IR12
Cross-platform biases are due to
CAL errors
SRFs deviation from those used in CRTM
Local time differences (diurnal cycle in SST/GFS)
Work is underway to attribute the causes & reconcile platforms
GSICS Annual Meeting, Beijing, 5-8 March 2012
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18. GSICS Inter-Calibration Methodologies
Simultaneous Nadir Overpasses
Hyper-Spectral Double-Differences (integrate HS radiances with wide- band spectral response)
MICROS Double Differences (integrate RTM simulations with wide-band spectral response) – Fit?
GSICS Annual Meeting, Beijing, 5-8 March 2012
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19. Simultaneous Nadir Overpasses (SNO)
Cross-platform consistency in GSICS: 1 of 2
SNO matches two satellites in space and time at nadir
Objectives
Eliminate uncertainties associated with
Atmospheric path
View geometry
Time difference
And estimate cross sensor inconsistency
SNO in Ch3 (NOAA16~ NOAA17)
SNO in Ch4 (NOAA16~ NOAA17)
From SNO web:
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20. Cross-platform consistency in GSICS: 2 of 2
Hyper-Spectral (HS) DDs
Cross-platform consistency in GSICS: 2 of 2
HS DD use GOES as the transfer standard to match up each pair of satellites in space and time at nadir (Wang and Cao, 2008; Hewison and Konig, 2008)
(from GSICS Quarterly v )
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21. GSICS Annual Meeting, Beijing, 5-8 March 2012
MICROS vs SNO & HS DDs
MICROS DDs
SNO
Hyper-Spectral (HS) DDs
Real-time
Online
NRT Jul’2008-present No
Domain
Global ocean
Clear-Sky only
Full sensor swath
Polar areas
Ice/Ocean/Land All-Sky
Nadir only
Global match-ups
Nadir Only
NOBS
~3Mln/Day (AVHRR GAC)
Several match-ups/Day
Sensors-specific QC
ACSPO Clear-Sky Mask
No QC
Data Distribution
Gaussian
Asymmetric
Transfer Standard
CRTM; No match-up in space/time required
Direct Comparisons; Match-up in space/time required
GOES; Match-up in space/time required
Effect of Solar reflectance
Currently, only used during nighttime (no daytime)
Renders data in mid-IR (Ch3B) unusable
Shortwave bands not always covered by HS measurements
Spectral Response
Considered
Not considered
Cross-platform bias precision
~0.01 K
~1K
~0.1K
MICROS supplements GSICS Inter-calibration Techniques
GSICS Annual Meeting, Beijing, 5-8 March 2012
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22. GSICS Annual Meeting, Beijing, 5-8 March 2012
Conclusions
M-O biases & Double-Differences (DD) in MICROS
Functional with 5 AVHRR; Terra/Aqua MODIS & NPP/VIIRS being tested
DDs Cancel out most errors in M-O biases
AVHRR Cross-sensor biases (DDs): ~10-2K to ~10-1K
Cross-sensor biases (DDs) are due to errors in
Sensor Calibration
Sensor Spectral Response Functions
CRTM Coefficients
Need to unscramble cross-platform biases seen in MICROS DDs
With GSICS Colleagues (T. Chang, F. Wu, F. Yu) – Sensor Cal and SRFs
CRTM Colleagues – Verify CRTM coefficients
MICROS DDs supplement GSICS Hyper-Spectral DDs and SNO
Global clear-sky night ocean domain
Difference between M and O: Narrow Gaussian distribution, centered at ~0
Large data volume (GAC: 3M pixels / 24hr): Instrumental to beat down noise
No collocation with other sensors required
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23. GSICS Annual Meeting, Beijing, 5-8 March 2012
Future Plans 1
Extend MICROS to more polar sensors and GOES
Work with GSICS Colleagues to
Reconcile cross-platform differences
Evaluate MICROS DDs for consistency w/Hyper-Spectral DDs & SNO
AVHRRs
Continue monitoring all sensors in orbit; Add Metop-B (May 2012)
Extend back in time to include all AVHRR (1978-pr)
Add Terra/Aqua MODIS & NPP VIIRS in MICROS
Fine tune CRTM and ACSPO Cloud Mask
Evaluate for stability & cross-consistency with AVHRRs
Reprocess MODIS historical data back to (where is L1B data ?)
Add new sensors
GEO: MSG SEVIRI in progress; and GOES-R/ABI (~2015)
ATSR (NRA joint proposal w/JPL/S. Hook and U. Leicester/G. Corlett)
Discussions underway w/CMA on FY1/VIRR & FY3/MERIS
GSICS Annual Meeting, Beijing, 5-8 March 2012
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24. PROXY MODIS & VIIRS streams
MICROS ver 5
PROXY MODIS & VIIRS streams
MODIS & VIIRS proxy have been trended in MICROS5 since mid-2011
Quantitative analyses pending fine-tuning ACSPO Processor
Will report MODIS-VIIRS- AVHRR consistency in GSICS Meeting
MICROS Version 5:
In preparation for launch of NPP/VIIRS in Oct’2011, MICROS5 was set up
Added proxy NPP VIIRS & Proxy Terra/Aqua MODIS
Added interactive plots for flexible display of multiple platforms
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25. GSICS Annual Meeting, Beijing, 5-8 March 2012
Future Plans 2
Extend MICROS to Include Reflectance Bands
Aerosol Quality Monitor (AQUAM) was set up to prepare for adding aerosol in CRTM
GOCART and NAAPS identified as sources of 3D aerosol fields inputs into CRTM
Initially, use solar reflectance bands to evaluate DDs and CRTM/GOCART&NAAPS
First-guess reflectances will improve ACSPO clear-sky mask
Subsequently, extend aerosol analyses into thermal IR bands
M-O bias in emission bands will become closer to zero & STD reduced
DDs in emission bands are expected to be improved
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26. Improve Accuracy of MICROS DDs
Future Plans 3
Improve Accuracy of MICROS DDs
DDs largely cancel out uncertain/unknown factors
However, they can be further improved by
Using more accurate first guess fields (SST, GFS)
Using Improved CRTM (especially daytime)
Modeling diurnal variation in first-guess SST
So far, checked sensitivity of DDs to first-guess SST (major factor in SST bands)
Overall, very small  MICROS DDs are reliable
However, temporal noise may be reduced and DDs estimated more accurately
From MICROS paper:
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27. GSICS Annual Meeting, Beijing, 5-8 March 2012
Thank you!
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