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Effect of consistent CRTM coefficients on M-O biases & Double Differences in MICROS

Xingming Liang 1,2 , Sasha Ignatov 1 ,and Yong Chen 1,3 1 NOAA/NESDIS/STAR, 2 CSU/CIRA, 3 UMD/ESSIC. Effect of consistent CRTM coefficients on M-O biases & Double Differences in MICROS. www.star.nesdis.noaa.gov/sod/sst/micros/. Slide 1 of 20.

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Effect of consistent CRTM coefficients on M-O biases & Double Differences in MICROS

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  1. Xingming Liang1,2, Sasha Ignatov1,and Yong Chen1,3 1NOAA/NESDIS/STAR, 2CSU/CIRA,3UMD/ESSIC Effect of consistent CRTM coefficients on M-O biases & Double Differences in MICROS www.star.nesdis.noaa.gov/sod/sst/micros/ Slide 1 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  2. Acknowledgments Advanced Clear-Sky Processor for Oceans (ACSPO; NESDIS SST System): Sensor Radiances over Oceans with Clear-Sky Mask and QC J. Sapper, Y. Kihai, B. Petrenko, J. Stroup, P. Dash, F. Xu, X. Zhou – NESDIS SST Team Community Radiative Transfer Model (CRTM) implemented in ACSPO F. Weng, Q. Liu, P. Van Delst, D. Groff, E. Borbas, C. Mueller – CRTM Team AVHRR, MODIS, VIIRS Characterization & Cross-platform Consistency, including Double Differences (DD) for Global Space-based Inter-Calibration System (GSICS) T. Hewison, F. Yu, F. Wu, C. Cao, M. Goldberg, L. Wang, F. Weng, X. Hu– GSICS Team A. Wu, J. Xiong– MODIS Calibration Support Team (MCST) Slide 2 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  3. Background & Motivation Objective & Methodology 4 Consistent CRTM Coefficient (C3) data sets and 3 Metrics Effect of C3 on M-O bias Effect of C3 on MICROS DD Factors affecting M-O bias and MICROS DDs Errors in Sensor Response Functions (SRF) Missing Absorbers and/or Incorrect parameterizations (e.g., CFC Absorption) Conclusion and Future Work Outline Slide 3 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  4. Background • Advanced Clear-Sky Processor for Oceans (ACSPO): • Operational NOAA SST and clear-radiances system • Generates clear-sky radiances and SSTs in AVHRR like bands • Integrated CRTM generates model BTs with first guess fields: • SST: Reynolds 0.25° or CMC L4 Analysis • Upper Air: NCEP GFS 1° or ECMWF 0.25° fields • Monitoring of IR Clear-sky Radiances over Ocean for SST (MICROS) • Monitors Model (CRTM) minus Obs (Sensor) BTs (“M-O Biases”) • Near-Real Time; Global ocean; Clear-sky condition • Double Differences (DDs) are used to evaluate sensor radiances for stability and cross-platform consistency Slide 4 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  5. Motivation • MICROS DDs are expected to cancel out systematic errors or instabilities in the ‘‘M’’ term • DDs are good to evaluate sensor stability • Cross-platform differences are partly due to inconsistent calculation in CRTM coefficient • Coefficient are calculated using • LBLRTM, for a set of atmospheric profiles and various absorber gases • Two fitting methods for wide sensor bands: ORD and PW • Two transmittance algorithms: ODAS (CRTM) and ODPS (RTTOV) • Coefficients in different CRTM releases may not be calculated consistently CRTM V2.02 CRTM V2.1 ORD: Ordinary ODAS: Optical Depth in Absorption Space PW: Planck-Weighted ODPS: Optical Depth in Pressure Space Slide 5 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  6. Objective Perform sensitivity analysis to CRTM coefficients Compare to current coefficient used in MICROS Final goal is to select best C3 used in MICROS 4 C3 datasets were generated and analyzed in MICROS using 1 day of global data (15 Jan 2013): ODAS-ORD, ODAS-PW, ODPS-ORD, ODPS-PW (Y. Chen et al., 2010, 2011) The same baseline LBLRTM v11.7 was used All calculations include CFC absorption Slide 6 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  7. Methodology Compare 4 results using the following metrics Global M-O biases: M-O biases are expected to be (1) closer to zero and (2) coherent across bands (in particular, IR11 & IR12) Global STDs of M-O biases: STDs are expected to be smaller Double Differences: Compared for pairs of platforms in close orbits: For Hi-Res, (1) Metop-A and -B, and (2) NPP and Aqua. For GAC, (1) Metop-A and -B and (2) NOAA-18 and -19. DDs are expected to be slightly smaller and more consistent across different pairs. Slide 7 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  8. M-O biases and STDs in IR37 M-O biases PW biases smaller than ORD by ~-0.06 K (except for VIIRS, where it’s larger by ~+0.05 K) ODPS and ODAS biases are within ~±(0.01..0.03)K of each other. However, ODPS removes the large N16 anomaly ~1K seen in ODAS PW-ODPS provides most favorable M-O biases. Need resolve VIIRS & N16 anomalies STDs Much smaller, for all AVHRR GACs. But Hi-res sensors are only minimally affected PW STDs are slightly but consistently smaller than ORD STDs Overall, PW-ODPS combination provides smallest STDs M-O Biases STDs Slide 8 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  9. M-O bias and STD in IR11 M-O Biases PW biases comparable with ORD to within ~±0.01K Large difference between MODIS/VIIRS and AVHRR sensors up to 0.4K – need resolve STDs ODPS STDs slightly but consistently smaller PW STDs are comparable with ORD STDs M-O Biases STDs Slide 9 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  10. M-O bias and STD in IR12 M-O Biases PW biases are generally slightly but consistently smaller than ORD by ~0.01-0.02K ODPS Biases larger than ODAS by ~+0.03K Difference between MODIS/VIIRS and AVHRR sensors up to 0.3K (consistent with IR11) IR11 and IR12 are more consistent for ODPS than for ODAS STDs ODPS STDs are slightly but consistently smaller PW STDs are comparable with ORD STDs M-O Biases STDs Slide 10 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  11. M-O bias and STD in SST M-O mean biases and STDs for regression SST are insensitive to the choice of ORD-PW, ODAS-ODPS for all platforms The sample size (indirect effect through the ACSPO clear-sky mask) comparable for AVHRR GAC, but largest for PW-ODPS combination M-O Biases STDs Slide 11 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  12. Double Differences Metop-A & B, NOAA-18 & 19, and Aqua & NPP IR37: (Aqua-NPP) DD=+0.14K (MB - MA) DD=-0.10K - real sensor biases IR12: (Aqua-NPP)DD=+0.07K; (MB – MA) DD=0.23K - real sensor biases SST DDs are insensitive to the choice of ORD-PW, ODAS-ODPS for all platforms IR11 IR37 SST IR12 Slide 12 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  13. Time series of DD for all platforms-- Official MICROS vs ODPS-PW in IR37 -- ODPS-PW showed better cross-platform consistency, except for NOAA-16 and Aqua VIIRS DDs were changed from +0.069 to -0.075 K in ODPS-PW, resulting a more clearly diurnal cycle pattern Temporary stability (σ) are comparable Official MICROS ODPS-PW Slide 13 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  14. Time series of DD for all platforms-- Official MICROS vs ODPS-PW in IR11 -- Metop-B is out of AVHRR family by ~0.3 K in MICROS, but back in family in ODPS-PW. This is because CFC absorption was taken into account for Metop-B, but not for other AVHRRs in the official MICROS Cross-platform inconsistencies between AVHRR and MODIS/VIIRS is ~0.41 K Need to resolve Official MICROS ODPS-PW Slide 14 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  15. Time series of DD for all platforms-- Official MICROS vs ODPS-PW in IR12 -- Metop-B is consistent with other AVHRR in MICROS, but out of family by ~0.2 K for ODPS-PW. This is likely due to sensor calibration issue. Cross-platform inconsistencies between AVHRR and MODIS/VIIRS is ~0.32 K Need to resolve Official MICROS ODPS-PW Slide 15 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  16. Time series of DD for all platforms-- Official MICROS vs ODPS-PW in SST -- SST DDs are comparable between official MICROS and ODPS-PW. This also indicates that SST DDs are insensitive to the choice of ORD-PW, ODAS-ODPS for all platforms Official MICROS ODPS-PW Slide 16 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  17. Factors affecting to AVHRR - MODIS/VIIRS inconsistency SRF difference SST bands are not identical between different platforms, particularly for different sensor. MODIS SRFs are much narrower than AVHRR and VIIRS The band covered spectral extent are different for different platform Commonly, SRF differences for window band affecting DDs are expected small and negligible. They may be large when the band is close to gas absorption lines. for instance, the right side of AVHRR & VIIRS SRFs is close to gas absorption continuous Next step will be doing more sensitivity analysis of gas absorption to spectral radiances to explore real effect on SRF differences. Slide 17 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  18. Recent research showed that CFC have a significant absorption in AVHRR long wave bands (Chen et al, 2012) 3 CFC amounts used for CRTM coefficient training: CFC free, 50%CFC, and 100% CFC, to test CFC effect on M-O biases. Factors affecting to AVHRR - MODIS/VIIRS inconsistency CFC absorption • For AVHRR, MODIS and VIIRS: • The effect on the M-O biases is minimal for IR37. • For IR11, the M-O biases reduced by ~0.21 K, ~0.36 K, and ~0.22 K • For IR12, the M-O biases reduced by ~0.15 K, ~0.22 K, and ~0.18 K • This suggested that CFC absorption is a non-negligible effect to M-O biases and DDs. Slide 18 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  19. Conclusion and plan • DDs can not cancel out systematic bias completely due to inconsistent CRTM coefficients used. Generating C3are critically important • 4 C3data sets were generated and compared, and 3 metrics were used to select a best C3for MICROS. • 4 C3 s: ODAS-ORD, ODAS-PW, ODPS-ORD, ODPS-PW • 3 metrics: M-O mean bias, STD, and DD • PW-ODPS combinations provides most favorable M-O biases and smallest STDs • In IR37, ODPS-PW showed better cross-platform consistency. • Aqua minus SNPP=+0.14K and MB - MA = -0.10K are real sensor biases • In IR11 & 12, Cross-platform inconsistencies between AVHRR and MODIS/VIIRS is ~0.41K and ~0.32K. • ODPS-PW showed cross-platform biases Metop-B minus Metop-A were improved in IR37 and IR11, but worsened in IR12 • IR37: reduced to -0.1 K, IR11: now show exemplarily consistency, IR12: +0.23 K cross-platform biases. • Factors affecting to ODPS-PW cross-platform inconsistency are deem to SRF differences and CFC absorption • MODIS SRFs are narrower than AVHRR & VIIRS • The AVHRR & VIIRS SRFs are close to gas absorption lines • The difference between with and without CFC absorption is ~0.36 K for long wave bands • Future work will focus on sensitivity analysis of different SRF and CFC absorption effect on DDs. Slide 19 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  20. Thank you! Slide 20 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

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