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Characterization and Evaluation of NPP VIIRS Aerosol EDR Performance Based Upon Prelaunch Analysis

Evaluation of VIIRS Aerosol EDR performance prelaunch; impact of sensor and algorithm on aerosol retrievals using methods and comparisons.

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Characterization and Evaluation of NPP VIIRS Aerosol EDR Performance Based Upon Prelaunch Analysis

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  1. Characterization and Evaluation of NPP VIIRS Aerosol EDR Performance Based Upon Prelaunch Analysis N. Christina Hsu (NASA/GSFC) Istvan Laszlo (NOAA/STAR) Jingfeng Huang (NASA/GSFC, Morgan State University)* Myeong-Jae Jeong (Gangneung-Wonju National University, Korea) David O. Starr (NASA/GSFC) Heather Q. Cronk (IMSG at NOAA/STAR) Hongqing Liu (Dell Services at NOAA/STAR) Robert Holz (UW/PEATE) Min Oo (UW/PEATE) Acknowledgement to: Sid Jackson (NGAS) and other VIIRS Aerosol/Cloud Cal/Val Team Members for valuable feedbacks and discussions, and Raytheon algorithm conversation team for additional data support * Email: Jingfeng.huang@nasa.gov

  2. VIIRS CrIS CERES ATMS OMPS Limb OMPS Nadir VIIRS– Visible Infrared Imager Radiometer Suite VIIRS 24 EDRs Land, Ocean, Atmosphere, Snow NPP Satellite * Product has a Key Performance attribute

  3. Outline Part I. Sensor Performance: 1.1 What is optical crosstalk? 1.2 Method to evaluate VIIRS sensor crosstalk 1.3 VIIRS Crosstalk Impact on Aerosol Retrieval 1.4 Crosstalk Summary Part II. Algorithm Performance: 2.1 VIIRS-MODIS Comparison 2.1.1 MODIS-Like NOAA/STAR VIIRS Product vs. MODIS 2.1.2 MODIS-Like PEATE VIIRS Product vs. MODIS 2.1.3 VIIRS-Like IDPS Product vs. MODIS 2.2 VIIRS-AERONET Comparisons Summary

  4. Quality of Coatings, Top of IFA Part I: Sensor Performance 1.1 What is Optical Crosstalk? Optical : Dominant VISNIR crosstalk. Linear with signal, spectral and spatial component. Believed to be largely due to filter defects. Magnitude primarily depends on number of defects in spectral filters (‘spits’). Defects from coatings of Integrated Filter Assembly cause large angle scattering. Quality of Coatings, Bottom of IFA From XtalkTim5_Mills.ppt by Steve Mills (NGST); Courtesy: Chris Moeller.

  5. 1.2 Crosstalk Impact - Evaluation Method • Assess the impact of VIIRS VisNIRxtalk on aerosol EDR using MODIS Deep Bluealgorithm and MODIS standard Dark Target algorithm. • Investigate how aerosol property statistics changes using VIIRS proxy (MODIS) data with and without xtalk, based upon TV influence coefficients. Effects of out-of-band response and polarization sensitivity are not considered in this analysis. • Two scenes are selected to test aerosol EDR for a range of aerosol loadings from low to heavy plumes over both water as well as vegetated and arid land surfaces.

  6. 95% 75% 50% Mean 25% 5% 1.3 Crosstalk Impact on VIIRS AOT (Land, Deep Blue) (c) AOT with XTalk (a) RGB (b) AOT w/o XTalk (d) Difference: (c)-(b) Arabian Desert Scene • Crosstalk impact on Deep Blue AOT retrieval (land) is within 0.01.

  7. 95% 75% 50% Mean 25% 5% 1.3 Crosstalk Impact on VIIRS AOT (Ocean & Land, Dark Target) (c) AOT with XTalk (a) RGB (b) AOT w/o XTalk (d) Difference: (c)-(b) China Scene • Crosstalk impact on Dark Target AOT retrieval is within 0.005, for both land and ocean.

  8. 1.4 Crosstalk Impact on VIIRS Aerosol - Summary • Without considering out-of-band response and polarization sensitivity, the impact of xtalk is moderate on SDR and aerosol EDR performance over land and ocean for both test granules. • In general, the effects of xtalk on SDR are within 0.1% for most of the wavelengths. However, they are larger for 470 nm (mostly contributed by the 443 nm channel) over land and ocean (~0.2%), as well as for 865 nm band over ocean (~0.4-0.6%). • The resulting errors in AOT due to xtalk are within 0.01 over land and ocean for both darker surface and bright desert scenes retrieved from Deep Blue and Dark Target algorithms, which meet the NPP requirements of aerosol EDR performance.

  9. Part II: Algorithm Performance 2.1 VIIRS-MODIS Comparison 2.1.1 MODIS-Like NOAA/STAR Product (Science code Drop 4.9.3) (Note: MODIS data run through VIIRS algorithm with MODIS LUT at NOAA/STAR; close to final drop of 4.9.4) 2.1.2 MODIS-Like PEATE/LEOCAT Product (IDPS build 1.5.0.48) (Note: MODIS data run through VIIRS algorithm with MODIS LUT at Atmosphere PEATE; It is a relatively old ops code build from 2009 based on Drop 4.9) 2.1.3 VIIRS-Like IDPS Product (Final Drop 4.9.4) (Note: a quick glance of VIIRS-Like granules)

  10. 2.1.1 VIIRS(STAR) vs. MODIS: 2010.214-218,LAND 215 216 214 217 218 218, all QA • VIIRS (land) aerosol retrieval (drop 4.9.3) achieves comparable performances to MODIS, except some low biases when AOT is higher than 1.5; • Some high biases when AOT is less than 0.5 is also observed with all QA, but not significant with best QA.

  11. 2.1.1 VIIRS(STAR) vs. MODIS: 2010.214-218,OCEAN 215 216 214 217 218 218, all QA • VIIRS (ocean) aerosol retrieval (drop 4.9.3) achieves comparable performances to MODIS overall; • There are some systematic low biases from VIIRS to MODIS with both all QA and best QA.

  12. 2.1.1 VIIRS (STAR) vs. MODIS: 2010.218 (08/06) VIIRS 2010218 MODIS 2010218 ALL QA ALL QA QA=3 QA=3 • Top panel: with all QA; bottom panel: with best QA. • 131 granules on 08/06/2010

  13. 2.1.1 VIIRS (STAR) vs. MODIS: 2010.218 (08/06) • AOT Difference between VIIRS and MODIS are different for land and ocean; • Significant AOT discrepancy were found for high AOT values over land;

  14. 2.1.1 VIIRS (STAR) vs. MODIS: Heavy Aerosol Events VIIRS MODIS 08/05/10 VIIRS MODIS 08/06/10 Observation of the huge wildfire event over West Russia in August 2010: VIIRS (QA3) is significant lower than MODIS (QA3) when AOT > 1.5.

  15. 2.1.2 VIIRS (PEATE) vs. VIIRS (STAR) vs. MODIS VIIRS (STAR) vs. MODIS (Land) VIIRS (PEATE) vs. MODIS (Land) 4.9  4.9.3 LAND VIIRS (STAR) vs. MODIS (Ocean) VIIRS (PEATE) vs. MODIS (Ocean) OCEAN 4.9  4.9.3 • Data from 15 collocated Terra Granules

  16. 2.1.2 VIIRS (PEATE) vs. VIIRS (STAR) vs. MODIS MODIS VIIRS(PEATE), Drop 4.9 VIIRS(STAR), Drop 4.9.3 • There are significant discrepancy between MODIS and both drop versions of VIIRS (with best QA): Heavy aerosol and cloud screening

  17. 2.1.2 VIIRS (PEATE): Amazon Smoke, 10/2007 VIIRS MODIS 2007275.1750 VIIRS MODIS 2007274.1705 • More challenging heavy aerosol cases: Amazon smoke, 10/2007

  18. 2.1.3 VIIRS-Like (IDPS, Drop 4.9.4) vs. MODIS 80 second 400*96 6km resolution 09/06/2002, DOY249 5 minute 203*135 10km resolution Land Ocean • There is wavelength difference issue in this comparison: MODIS B3 is 470 nm, and VIIRS M3 is 488 nm, resulting in a possible 0.2 AOT difference over land (Sid Jackson, NGAS).

  19. 2.1.3 VIIRS-Like (IDPS, Drop 4.9.4) vs. MODIS 01/25/2003, DOY025 Land Ocean • There is wavelength difference issue in this comparison: MODIS B3 is 470 nm, and VIIRS M3 is 488 nm, resulting in a possible 0.2 AOT difference over land (Sid Jackson, NGAS).

  20. Part 2: Algorithm Performance 2.2 VIIRS – AERONET Comparison VIIRS(ABI) AOT vs. AERONET AOT @ 126 AERONET ocean/island sites 2000-2009 • Over water, the Advanced Baseline Imager (ABI) adopts VIIRS aerosol algorithm and uses MODIS VIS-NIR reflectances from 10-km MODIS aerosol product • VIIRS aerosol retrieval over ocean achieves comparable performances to MODIS (Results provided by Istvan Laszlo NOAA/NESDIS/STAR)

  21. Sensor performance • VIIRS sensor optical crosstalk does not have significant impact on VIIRS aerosol EDR • Algorithm performance: • Use of latest VIIRS aerosol algorithm is essential in making the VIIRS-MODIS comparisons to evaluate algorithm performance (drop 4.9 vs. 4.9.3 vs. 4.9.4); • VIIRS (drop 4.9.3) achieves comparable results to MODIS over land and ocean when AOT<1.5; VIIRS seems lower than MODIS when AOT > 1.5. • There are still challenging issues with VIIRS algorithm, such as heavy aerosol observations and cloud screening; • The VIIRS(ABI, Ocean) algorithm also produces comparable AOT to the AERONET AOT observations. SUMMARY

  22. VIIRS +MODIS THANK YOU! • AQUA MODIS AOT Seasonal Climatology, to be continued by VIIRS Jingfeng Huang@NASA/GSFC: jingfeng.huang@nasa.gov

  23. Backup slide Q: How comparable are the MODIS Dark Target AOT retrievals to the AERONET AOT retrievals? A: Aqua MODIS DT AOT (Best QA) vs. AERONET AOT (2002-2010). The expected error ranges are ±0.05±0.15AOT for Land, and ±0.03±0.05AOT for Ocean. Land Ocean

  24. Backup slide: Algorithms

  25. Backup slide: VIIRS Bands

  26. VIIRS(PEATE): Heavy Aerosol Case on 2009.182.1500 (Aqua) MODIS-Like VIIRS (10km) QA=best (3), using best QA (0) only from IP (1km) MODIS (10km) QA=3 VIIRS IP bad SDR qualify flag: All seems good SDR. VIIRS IP AOT out of range quality flag: Only a small portion seems to have AOT out of range. VIIRS IP (1km), QA=best (0),degraded (1): It seems the heavy aerosol pixels were degraded. VIIRS IP Cloud Confidence Flag: It seems the region is fairly confidently cloud free. VIIRS IP VOLCANIC ASH The question is: why those heavy aerosol pixels were degraded from QA=0 to QA=1 at IP level? It seems VCM is not the cause, bad SDR is not the cause either, nor the AOT range, BUT THE VOLCANIC ASH!

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