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VIIRS Insitu data for Vicarious Calibration and Validation

1) Define a VIIRS Proxy Data Stream. 2) Define the required in situ data stream for Cal/Val. 3) Tuning of algorithms and LUTS (Vicarious calibration and SDR feedback). 4) Ocean Algorithm, stability evaluation and uncertainty. 5) Product validation and product long-term stability.

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VIIRS Insitu data for Vicarious Calibration and Validation

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  1. 1) Define a VIIRS Proxy Data Stream 2) Define the required in situ data stream for Cal/Val 3) Tuning of algorithms and LUTS (Vicarious calibration and SDR feedback) 4) Ocean Algorithm, stability evaluation and uncertainty 5) Product validation and product long-term stability 6) Satellite inter- comparisons, robustness, seasonal and product stability VIIRS Insitu data for Vicarious Calibration and Validation Presenter: Michael Ondrusek NOAA/NESDIS/STAR Performers: Michael Ondrusek, Heng Gu, Igor Appel, Michael Sorroco Thrust area: 2: "In-situ"data collection 3: Vicarious calibration and LUT tuning 5: Product Validation Award date: May, 2009 Total Man-Months Effort: FY09 2.5 mm FY10 2.5 mm FY11 2.5 mm

  2. VIIRS Insitu data for Vicarious Calibration and Validation Project Objectives Major Challenges/Issues Define the procedures which in situ ocean color data can be used for Vicarious calibration and validation of the NPOESS cal/val effort. The effort defines the uncertainty of different data sets and their impact on vicarious calibration. Develop protocols to provide real time data stream for vicarious calibration. MOBY Funding Regional processing at NOAA Major Progress Supports: Ocean cal/val plan elements 6,9,12,15,21,23,24 Developed measurement/satellite match-up tools Collected historical MOBY/Satellite match up data set for Aqua and SeaWiFS from launch to March 2009 Data is currently being implemented into new MOBY/OceanWatch web page. (http://coastwatch.noaa.gov/) Analyzed vicarious calibration exclusion criteria. Milestones / Deliverables

  3. VIIRS Insitu data for Vicarious Calibration and Validation Collaboration and Coordination with Inside and Outside Activities Transition Partners NRL: Arnone, Rhea, Wiederman, Gould NIST: Johnson, Brown NASA: MODIS / SeaWIFS – Science team, VOST - Turpie NOAA: NCDDC/ NOS/ NESDIS IPO: /NPP/ NPOESS Cal/Val NOAA - Coastwatch - Kent Hughes,Heng Gu, Michael Sorroco NOAA - MOBY NASA – SeaBass (J.Werdell), OCBG MLML - MOBY IPO – Cal/Val Leveraged RDT&E Projects International Partnerships NRL – HICO NASA – MODIS NOAA- GOES_R NOAA-- MOBY NOAA – NMAO NOAA – ORS NOAA - CBO Examples: ESA – Kathryn Barker, MERMAID

  4. FY 09- MILESTONES Completed In Progress Milestone 1. Assemble historical / real time match up data set used for vicarious calibration for SeaWiFS and MODIS OC sensors.(files) 12 # Milestone 2. Deliver historical / real time vicarious data set available to VIIRS Cal/Val investigators through web site and / or Gravite. (demonstration) # 9, 12 Milestone 3. Analyze exclusion criteria during initialization and how these criteria change during maturation of the characterization of these instruments. Presentation #12 VIIRS Insitu data for Vicarious Calibration and Validation

  5. VIIRS Insitu data for Vicarious Calibration and Validation Milestone 1 – Progress and Accomplishments Jan 2010- Assemble historical / real time match up data set used for vicarious calibration for SeaWiFS and MODIS OC sensors. (files) -Developed IDL measurement/satellite match-up tools for this project. Options: Flags to exclude Pixel layers surrounding central pixel to include in averaging. Minimum number of good pixels required for averaging. Output: Granule identification Averaged Satellite value corresponding to in situ measurement Comparison to in situ measurement Number of good (pass flag criteria above) pixels used in box surrounding location -Collected historical MOBY/Satellite match up data set for Aqua and SeaWiFS from launch to March 2009. (5x5 pixels, all good).

  6. VIIRS Insitu data for Vicarious Calibration and Validation Figure 1. Example of all MOBY and Satellite match-up (443 nm) for all good data (no flags and all good quality) and mean of 5 x 5 pixels around MOBY.

  7. VIIRS Insitu data for Vicarious Calibration and Validation Milestone 2. Progress and Accomplishments Jan 2010 - Deliver historical / real time vicarious data set available to VIIRS Cal/Val investigators through web site and / or Gravite. (demonstration) Data is currently being implemented into new MOBY/OceanWatch web page. (http://coastwatch.noaa.gov/) MOBY Satellite data currently available at ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/ondrusek/MOBY/

  8. VIIRS Insitu data for Vicarious Calibration and Validation Milestone 3, March 2010 Analyze exclusion criteria during initialization and how these criteria change during maturation of the characterization of these instruments. -Currently collecting historical match up data sets and reports collected and analyzed during initialization of SeaWiFs and MODIS sensors. -Concentrate report today on SeaWiFS (9/97) – Better documentation. CZCS 78 to86 – Identified the need for vicarious calibration mooring. Could not achieve enough good matchups by ship. -Miami initiated the vicarious calibration of Terra (10/99) and Aqua (5/02). Utilized only center pixel to avoid any variability in water characteristics. -MODIS Processing transitioned to NASA In Feb. 2004. Since then vicarious calibration techniques and exclusion criteria followed that of SeaWiFs -MODIS does not tilt to avoid glint, reduces number of matchups. -using 5x5 matchups with no flags from 2003 to 2008 MODIS on average retrieves ~50% of days as SeaWiFs over MOBY.

  9. Eplee et al., 1998, 15 MOBY matchups in first 3 months. Exclusion Criteria: 3x3 pixels, cloud free, no flags Band 412 433 490 510 555 670 Gain 0.995 0.9645 0.9323 0.9534 0.9629 0.98

  10. Barnes and McClain 1999, Proc. SPIE, 53 MOBY match ups in 8 months. Exclusion Criteria: 3x3 pixels, cloud free, no flags Band 412 433 490 510 555 670 765 865 Gain 1.014 1.00 0.97 0.99 1.00 0.968 0.956 1.00 Eplee et., 2001, Applied Optics, 125 MOBY match ups in 906 days. Exclusion Criteria: 3x3 pixels, at least 5 pixels pass all criteria, Land, Clouds, Ice, glint (AOD in band 8 >0.1), Stray light, Band 5 < 0.15 mW cm-2sr-1um-1, Atmos. Corr failure, Satellite zenith angle >56 degrees, Solar Zenith >70degree, Turbid water, Cocco, Aerosol optical depth in band 8>0.1, K’s consistent between depths. Used computed Es, measured is variable. Band 412 433 490 510 555 670 765 865 Gain 1.00324 0.991554 0.962221 0.983602 0.991394 0.9959477 0.946 1.00

  11. Eplee 2003, 4th reprocessing, 23 MOBY matchups in 5 years. Only used straylight corrected MOBY data, reduced potential to 163. Started using inverse vicarious calibration: TOA to TOA, reduces iterative processing to force satellite to match MOBY. Agrees with forward method within 0.04%. MOBY Exclusion Criteria: Must have data from top and middle arm. Reduced potential to 45 Combined uncertainty in Lw for all bands calculated from both arms must be less than 10%. New Satellite Exclusion Criteria: Reduced number to 23 5x5 pixels, all 25 must be good. No Clouds, cloud shadows, stray light, sun glint, high satellite or soar z3enith angles, high light in bands 7 and 8, and aerosol optical depth greater than 0.1. Band 412 433 490 510 555 670 765 865 Gain 1.013007 0.996384 0.962951 0.982130 0.991338 0.956581 0.938 1.00

  12. Franz et al., 2007, Applied Optics, 150 MOBY matchups in 9 years. New MOBY Exclusion Criteria: Combined uncertainty in Lw for all bands calculated from both arms must be less than 5%. Excluded if radiances differ from modeled clear sky radiance by more than 10%, Same Satellite Exclusion Criteria: 5x5 pixels, all 25 must be good. No Clouds, cloud shadows, stray light, sun glint, high satellite or soar z3enith angles, high light in bands 7 and 8, and aerosol optical depth greater than 0.1. Band 412 433 490 510 555 670 765 865 Gain 1.0377 1.014 0.9927 0.9993 1.00 0.9738 0.972 1.00

  13. Summary Eplee 98, N = 15 Band 412 443 490 510 555 670 Gain 0.995 0.9645 0.9323 0.9534 0.9629 0.98 Barnes 99, N = 53 Band 412 443 490 510 555 670 765 865 Gain 1.014 1.00 0.97 0.99 1.00 0.968 0.956 1.00 Eplee 01, N = 125 Band 412 443 490 510 555 670 765 865 Gain 1.00324 0.991554 0.962221 0.983602 0.991394 0.9959477 0.946 1.00 Eplee 03, N = 23 Band 412 443 490 510 555 670 765 865 Gain 1.013007 0.996384 0.962951 0.982130 0.991338 0.956581 0.938 1.00 Franz 07, N = 150 Band 412 443 490 510 555 670 765 865 Gain 1.0377 1.014 0.9927 0.9993 1.00 0.9738 0.972 1.00

  14. 2607 in situ validation water leaving radiance records, 6% meet criteria Reprocessing 3, 2000, relaxed criteria Reprocessing 4, 2002, enhanced criteria

  15. Reprocessing 4, 2002, enhanced criteria Franz et al 2007

  16. FY 10- MILESTONES Deliverables Plans Upgrade the insitu web site with near real - time data and MODIS/ SeaWIFS/ MERIS products and develop joint coordination with NRL/ NASA web sites. Integrate the insitu data into Seabass, Gravite and or location designated by cal/val working group. Demonstrate how in situ data is integrated in vicarious calibration procedures of other SME/ Agencies in real time. VIIRS Insitu data for Vicarious Calibration and Validation

  17. VIIRS Insitu data for Vicarious Calibration and Validation • Deliverable: Jan 2010 - Upgrade the insitu web site with near real - time data and MODIS/ SeaWIFS/ MERIS products and develop joint coordination with NRL/ NASA web sites. (demo) • Member of VIIRS Cal/Val working group to provide automated matchup / uncertainty of in-situ data with satellite data team. - MODIS Data Extractor (MDE) - JAVA application. Originally developed by Heng Gu for Menghua Wang funded by IPO. • Options: • Flags to include in calculations. • Pixel layers surrounding central pixel to include in averaging. • Can select number of nearest pixels to selected location. • Output: • Value for each pixel specified in option criteria • Mean, medium, and Stdev for each file • Time-series

  18. VIIRS Insitu data for Vicarious Calibration and Validation Currently working on developing Batch capabilities. Currently developing automatic realtime MOBY match-ups.

  19. MODIS Data Extractor (Screenshot)

  20. MODIS Data Extractor (Screenshot)

  21. MODIS Data Extractor (Screenshot)

  22. VIIRS Insitu data for Vicarious Calibration and Validation Major Technical Issues and ongoing work: Do not have operational access to global data. CoastWatch region only. Need to automate MOBY/MODIS matchup utilizing the MODIS Data Extractor (MDE) and display data onto CoastWatch MOBY Cal/Val web page. Set up one to two month sliding granule storage for CoastWatch region so need extract near-realtime satellite matchups within the period of the sliding window. Leave capability to add granules manually for locations and periods outside Coastwatch region and the sliding window. Can only be run in house. Add Automated satellite extractions for SeaPrism locations.

  23. VIIRS Insitu data for Vicarious Calibration and Validation FY10 Milestone Status and Issues (cont): 2. Integrate the insitu data into into Seabass, Gravite and or location designated by cal/val working group. • Continue development of the MDE QA tool. • Need to analyze needs of cal/val working groups. 3. Demonstrate how insitu data is integrated in vicarious calibration procedures of other SME/ Agencies in real time • Assure the continuation of available MOBY data to all agencies. • Assure the quality meets requirements for MOBY and validation data. • Continue working with cal/val working groups to identify needs.

  24. VIIRS Insitu data for Vicarious Calibration and Validation Ocean EDR Product Calibration & Validation Working Groups • 4. In-situ data collection/management - Identify field activities, sites, protocols, data QA/QC, data management Fargion Davis, Stumpf, Ondrusek, Trees, Arnone, Turpie • 5. Automated matchup / uncertainty of in-situ data with satellite data - AERONET match up software; MOBY matchup procedures; validation data matchup procedures; develop common tools. Arnone Turpie, Davis, Stumpf, Ondrusek, Fargion, Wang, Lawson • 6. Vicarious calibration methods - Using MOBY, central gyres, coastal/open ocean, etc. Wang, Davis, Stumpf, Ondrusek, Fargion, Gould. • 7. Demonstrate real time continuity of ocean color data products in preparation for VIIRS products - Establish Protocols for Data Continuity; Review the approach used by GLOBCOLOUR and other programs to merge MERIS, MODIS and SeaWiFS data; Combining data from multiple satellites; Cross satellite comparisons for coastal water types; Atmospheric correction issues Stumpf, Davis, Ondrusek, Fargion, Wang, Arnone, Trees • 8. Coastal Ocean Algorithms Validate with US coastal sites; take advantage of the international sites; test and validate algorithms; using SeaPRISM and other matchups. Lee, Davis, Arnone, Stumpf, Wang, Gao

  25. VIIRS Insitu data for Vicarious Calibration and Validation 4. In-situ data collection/management - Identify field activities, sites, protocols, data QA/QC, data management Data availible at: ftp://ftp.star.nesdis.noaa.gov/pub/sod/osb/ondrusek/Seabass/ and Seabass Secured NOAA shiptime for validation and initialization cruise

  26. VIIRS Insitu data for Vicarious Calibration and Validation 8. Coastal Ocean Algorithms

  27. VIIRS Insitu data for Vicarious Calibration and Validation In-situ data collection/management • Conducted inter-calibration of Satlantic Hyperpro and MOBY utilizing MOBY calibration source. • Plot showing agreement between source and field instrument • MOBY Hyperpro matchup • Annual calibration at Satlantic • Straylight correction of Hyperpro instrument. • Strength: increased accuracy and consistency with MOBY • Weakness: expensive and difficult. • Solution: Developed general straylight correction to apply to all Satlantic Hyperpros. • Benefit: Provides calibration traceability to MOBY at other locations.

  28. VIIRS Insitu data for Vicarious Calibration and Validation Schedule with Major Deliverables Milestones S – Start, C – Complete, D – Demo, I-Issues, M - Manual/Documentation, R – Final Report, T- Transition

  29. 1) Define a VIIRS Proxy Data Stream 2) Define the required in situ data stream for Cal/Val 3) Tuning of algorithms and LUTS (Vicarious calibration and SDR feedback) 4) Ocean Algorithm, stability evaluation and uncertainty 5) Product validation and product long-term stability 6) Satellite inter- comparisons, robustness, seasonal and product stability VIIRS In situ data for Vicarious Calibration and Validation Questions ?

  30. VIIRS Insitu data for Vicarious Calibration and Validation In situ matchups by Aug 1998 MOBY matchups by Aug 1998

  31. VIIRS Insitu data for Vicarious Calibration and Validation http://oceancolor.gsfc.nasa.gov/VALIDATION/gains.html Table 1

  32. VIIRS Insitu data for Vicarious Calibration and Validation USE OF CIMEL AT MOBY • In the 2001 NASA/TM-2001-209982 -explored vicarious calibration gains utilizing CIMEL measurements off lanai to the traditional method Conclusion – eliminates of assumption that vicarious gain at 865 nm is 1. • Marked improvement in SeaWiFS retrieved aerosol optical thickness but minor changes in the SeaWiFS retrieved water-leaving radiances. • NASA has not utilized the CIMEL data in operational calibrations but would welcome use as sanity check.

  33. MODIS Data Extractor (Screenshot)

  34. MODIS Data Extractor (Screenshot)

  35. MODIS Data Extractor (Screenshot)

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