1. Status Report and Synergetic Approach to GOES Visible Channel Calibration
NOAA GPRC
23 March 2011

2. Outline Progresses in GOES visible calibration Synergetic approach
Desert
MODIS
DCC
Lunar
Star
Rayleigh
Sun glint
Water Cloud
Synergetic approach
22-25 March 2011, Daejeon, Korea

3. Desert
22-25 March 2011, Daejeon, Korea 3

4. Desert Collected more data
Plan to characterize the sites with air borne instruments (AVIRIS etc.)
Implement the spatial variance threshold (D. Doelling).
22-25 March 2011, Daejeon, Korea

5. MODIS
22-25 March 2011, Daejeon, Korea

6. MODIS
22-25 March 2011, Daejeon, Korea

7. MODIS
Operational update of GOES visible channel calibration coefficients
Developed March 2005
Implemented June 2008
Operational July 2010
Stabilized Feb 2011
Lessons learned
Operational system is hard to change, for good reasons.
~1 year for scan mirror emissivity but ~7 years for MBCC
Plan ahead
Monitoring and evaluation to follow
22-25 March 2011, Daejeon, Korea

8. DCC Target Characterization Spatial Temporal Angular Spectral
22-25 March 2011, Daejeon, Korea

9. Data
GOME_2 data during 06/2010 covering the region (15°S,15°N,90°W,60°W). It includes the observed earth radiance/solar spectrum with the geometry and observing time information. GOME_2 has different scanning modes and in our study we only use the 80kmx40km normal scanning mode and drop off other data(found one file containing 10kmx40km resolution on 06/02/2010).
Land sea mask: 8kmx8km land coverage percentage dataset (From Wei Guo) which is interpolated from USGS 1kmx1km land/sea dataset. 1kmx1km includes land(1) , ocean(0) and disrupted area(in fact, no such kind of grid found in the original data); 10x5 land sea grids will be averaged to identify land/sea flags for GOME-2 pixels.
GOES/MODIS/AVHRR imager spectrum response function (SRF) . These SRF will be interpolated into GOME_2 Band3+Band4 range, and then used to simulated the convoluted earth radiance/solar spectrum/reflectance.

10. Land/sea mask comes from interpolated 8kmx8km land percentage coverage dataset (originally from USGS 1kmx1km dataset).
Ocean flag is assigned when land coverage (8kmx8km)<1%, and land flag is assigned when land coverage >90%. Others grid is treated as mixed.
Land: 53%
Sea : 43%
Mixed: 4%
Grids with rivers on land is treated as mix or land dependent on its coverage. Island also is treated as mix or land dependent on the coverage. (The above boxed region is for the study of river region and island case, see zooming below)
All below is purely based on the USGS land sea mask data, not for GOME_2. GOME_2 pixels cover 10x5 grids. So the land/sea type on GOME2 pixels level will be decided soon.

11. GOME2 pixels in the selected region
GOME2 pixels select criteria:
±4 pixels off nadirs: (zenith angle <25°), (9th-17th pixels along the scan line) ,
The total pixels amount depends on the pixels off nadirs
GOME-2 pixels size is 80kmx40km, 10x5 grids of 8kmx8km land sea mask. Because of the river and island effect, after average the 10x5 grids of land sea mask, Land is assigned to GOME2_pixels when averaged coverage> 80% and sea is assigned with coverage <1%, others are treated as “mix” pixels.
Total pixels
21285
100%
Land pixels
10595
50%
Sea pixels
9700
45%
Mix pixels
980 5%

12. Interpolated GOES8/GOES9/GOES11/GOES12/GOES13/MODIS Imager SRF based on the GOME2 band3 ( nm) + band4 ( nm) . Total channel after merge is The SRF will be used to convolute GOME2 radiance to simulate sensors’ radiance. Note: GOES10 (not shown) is almost overlapped by GOES12. GOES14 (not shown) is overlapped by GOES13 after 700nm.

13. Solar spectrum comparison

14. Dark sea and highest reflectance pixel radiance
An example
dark sea with simulated reflectance (lat:1.04 /lon: / 01-JUN / 14:56:31);
very high simulated reflectance (lat:10.42 / lon: / 01-JUN / 14:53:36)

15. Relative percentage: (GOES-MODIS) /MODIS vs. MODIS
Land
Relative percentage: (GOES-MODIS) /MODIS vs. MODIS

16. Land+Ocean+Mix
Relative percentage: (GOES-MODIS) /MODIS vs. MODIS

17. Ocean
Relative percentage: (GOES-MODIS) /MODIS vs. MODIS

18. Mix
Relative percentage: (GOES-MODIS) /MODIS vs. MODIS

19. Composite land/ocean/mix plotting
Land:green
Ocean:blue
Mix:red
Outlier ?
Relative percentage: (GOES-MODIS) /MODIS vs. MODIS

20. DCC Conclusions On-going Ocean DCC (reflectivity >60%) seems better
Slight dependence on target reflection, though
Varies among GOES, i.e., SRF.
Need to confirm invariance with time and space
22-25 March 2011, Daejeon, Korea

21. Lunar Calibration Review LUNAR SURFACE REFLECTANCE PROPERTIES
Excellent temporal stability: changes less then 1/108 per year.
No atmospheric attenuation for space borne instruments .
Accessible by all spacecraft, regardless of orbit
Utilizes a spacecraft instrument’s normal Earth-viewing optical path
Appropriate brightness for terrestrial environmental sensors at visible to SWIR wavelengths
Not Lambertian (not spatially uniform) : changes brightness all the time
“lunar ocean” is large spatially stable target.
Lunar “Ocean”
APPLICATIONS
Relative Response trending with respect to a lunar irradiance model (ROLO).
Radiance trending for a well defined ROI on lunar surface.
Monitoring on board calibration targets.
Cross-calibration between sensors.
Initial checking of pre-launch calibration during PLT.
Channel-to-channel registration.
On orbit testing of the light angle of incidence on scan mirror effect .
Modulation Transfer Function on orbit calculation.
22-25 March 2011, Daejeon, Korea

22. GOES Imagers Data Collection
Need unclipped images of gibbous moon: 50—90% of lunar surface illuminated, short time before or after full moon.
Unscheduled moon images: catch the moon in one of 4 corners of GOES FOR.
Scheduled moon observations, replacing star window, started in November 2005: once a month till January 2008, twice a month since then .
Special acquisition during GOES-NOP PLT science test: consecutive lunar images were taken within seconds of each other.
Currently, GOES11/13 collects data both by scheduled moon only observations and by unscheduled moon observed during routine observations.
22-25 March 2011, Daejeon, Korea

23. Relative Response Trending: Observed vs. ROLO modeled Lunar Irradiance
METHOD
GOES-12 moon scans were remapped to account for moon’s apparent motion across FOR to recreate smooth lunar edge
Ellipse is fitted via least squares fit to the smoothed edge of the moon
Edge is detected using SOBEL operator for edge enhancement.
Ellipse size is increased 20 pixels in each direction to include “corona”
Lunar observed irradiance within enlarged ellipse
Space counts are estimated for each line as mean of counts outside of large ellipse
ACCURACY ~ 1.6%
Ratio = coeff*e -slope*t
95% Confidence Interval
22-25 March 2011, Daejeon, Korea

24. Moon Visible Image Edge Detection Issues
Moon visible channel corona
Mean edge count
Detector 7 is crossing top edge of the moon
Uncertainty of lunar edge due to diffraction/stray light issues
Corona around Moon due to diffraction/Stray light
22-25 March 2011, Daejeon, Korea

25. On orbit Verification of Light Angle of Incidence on Scan Mirror Effect on ABI Solar Reflectance Channels
Laboratory measurements of the GOES-N Reflectance dependence on light angle of incidence was found channel dependant.
Method for on orbit verification of laboratory measurements utilizes consecutive lunar images scheduled and obtained during PLT/Science Phase.
22-25 March 2011, Daejeon, Korea

26. Lunar Calibration – Reflectance Properties
Characterization of spectral and spatial stability of the Lunar surface reflectance using EO-1 Hyperion Full Moon collect data
Identify potential for spatially, spectrally and temporarily invariant calibration sites on lunar surface
Spectral Variability
Spatial Variability
Principle Component Analysis (PCA) identified 2 PCA bands:
Lunar surface does not contain much VNIR spectral variability [196 Hyperion bands reduced to 2]
Spatial/Spectral stability identified by classifying the “bulk” Lunar surface material types into 5-7 large lunar classes
4 classes
6 classes
8 classes
PCA 1
PCA 2
PCA 3
22-25 March 2011, Daejeon, Korea
Lunar “Ocean” – Large Stable Target 26

27. Band Ratio Potential Absolute Lunar Calibration is not yet established
Relative calibration between bands is reliable long-term
Band Ratio
Spatial/spectral variability can be large for surface reflectance, however the band ratio variability can be small [Cao et al. (2009)]
Different Band combinations and locations
Develop a standard
Significance
Is the band ratio of selected sites less variable than the band ratio of the entire moon?
One well calibrated channel can be used to calibrate the other channels through the moon
AVHRR lunar observations in the space view can be used to study instrument response and lunar band ratio drifts for climate change detection Cao (2009)
Brightness variations are complex as a result of spatial variegation of lunar albedo, physical and optical librations (month, year, 18 years) and strong dependence on phase angle.
22-25 March 2011, Daejeon, Korea

28. Project: On-Orbit ABI MTF Validation
The Modulation Transfer Function (MTF) is the quantified relationship at a spatial frequency between the modulation of image brightness in the object being imaged to that of the image. Simply put, it quantifies how much brightness contrast in the object is transferred to the image.
where L is brightness
Lunar movement between scans causes discontinuities (striping).
Lunar edge
(curvature exaggerated here) is approximately vertical (vertical is mathematically ideal) around the equator.
Several lines of data across the lunar edge around the equator are acquired.
Combining the pixels
from each line relative to the lunar edge position creates a sub-pixel measurement.
GOES-15 lunar image acquired on Sept. 24th, 2010, after the science test.
The North-South diameter is
approximately 280 pixels.
The lunar edge was tracked at the sub-pixel level. This was validated with lunar images, as shown here.

29. Preliminary MTF Calculation
Edge Spread Function (ESF) Data
Created by combining 13 lines of data relative to the lunar edge around the equator. Inhomogeneous surface is greatest source of error.
Smoothed
(straight average)
2 lines chosen
Points after edge
feature forced to be
equal
Preliminary Edge Spread Function
in East-West direction.
LSF padded with zeros on both sides
Non-Uniform Discrete
Fourier Transform (NDFT) used because the LSF points are not evenly spaced. Avoids interpolation.
Normalized: MTF(0)=1.0
Preliminary GOES-15 East-West MTF
When comparing to spec and pre-launch tests, please note that results are preliminary. High vales are desired (1.0 is ideal).
Preliminary Line Spread Function (LSF)
Imager response to perfectly thin line.

30. Lunar Summary
Noise (~5%) in GOES derived lunar irradiance has not decreased substantially since initial study.
Instrumentation limitations other than radiometric calibration is suspected.
Under investigation
Radiance
HYPERION, LROC
Ratio
Moon look
MTF
22-25 March 2011, Daejeon, Korea

31. Stable irradiance is available for navigation …
Star
Stable irradiance is available for navigation …

32. … but not properly processed for calibration
Star
… but not properly processed for calibration

33. … but not properly processed for calibration
Star
… but not properly processed for calibration

34. … but not properly processed for calibration
Star
… but not properly processed for calibration

35. Reprocessed data look good … too good
Star
Reprocessed data look good … too good

36. Reprocessed data look good … too good
Star
Reprocessed data look good … too good

37. A star is observed at different time of the day on different date of year
earth
GOES
Sun ☼
earth
GOES
40-60K

38. All Vicarious Calibrations
DCC is monthly average so it should look better
Desert has the worst seasonal variation, however star and DCC may have it, too. 38 38

39. Star
22-25 March 2011, Daejeon, Korea

40. Star
22-25 March 2011, Daejeon, Korea

41. Star
22-25 March 2011, Daejeon, Korea

42. Star
22-25 March 2011, Daejeon, Korea

43. Star
22-25 March 2011, Daejeon, Korea

44. Star
22-25 March 2011, Daejeon, Korea

45. Star
22-25 March 2011, Daejeon, Korea

46. All Vicarious Calibrations
DCC is monthly average so it should look better
Desert has the worst seasonal variation, however star and DCC may have it, too. 46 46

47. Conclusions
Use star to experience various synergetic methods of using vicarious calibration results.
22-25 March 2011, Daejeon, Korea