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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; NOAA 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 3 Evaluation Metrics Effect of C3 on M-O Bias Double Differences Factors affecting M-O bias and MICROS DDs Errors in Sensor Response Functions (SRF) Missing Absorbers (e.g., CFC Absorption) (Not discussed here) Incorrect parameterizations 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-radiance system • Generates clear-sky radiances and SSTs in AVHRR like bands • Uses CRTM to generate model BTs with first guess fields: • SST: Reynolds 0.25° (or CMC L4 Analysis) • Upper Air: NCEP GFS 1° (or ECMWF 0.25° Analysis) • Monitoring of IR Clear-sky Radiances over Ocean for SST (MICROS) • Is a Near-Real Time monitoring system, over global ocean, under clear-sky conditions • Monitors Model (CRTM) minus Obs (Sensor) BTs (“M-O Biases”) • Monitors Double Differences (DDs) 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 sensors for 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) • Historically, coefficients in different CRTM releases have not been 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 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 Compare to current coefficient used in MICROS Final goal is to select best C3 used in MICROS 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 ODPS removes the large N16 anomaly ~1K seen in ODAS. (Need resolve N16 anomalies) STDs AVHRR GACs: ODPS STD smaller than ODAS (Hi-res sensors are only minimally affected) PW STDs are slightly but consistently smaller than ORD STDs ODPS-PW combination provides optimal Biases and 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 ODPS-PW combination provides optimal Biases and 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 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 ODPS-PW combination provides optimal Biases and 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 CRTM coefficients 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 NOAA-18 is unstable which affects all N18 DDs IR37: (Aqua-NPP) DD=+0.14K (MB - MA) DD=-0.10K cross-sensor biases (Aqua MODIS & Metop-B CAL problems) IR12: (Aqua-NPP)DD=+0.07K; (MB – MA) DD=0.23K cross-sensor biases (Aqua MODIS and Metop-B CAL problems) SST DDs are insensitive to the choice of CRTM coefficients IR11 IR37 SST IR12 Slide 12 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  13. Conclusion from Sensitivity Analysis • Based on sensitivity analyses, ODPS-PW combination provides best results • Initial European “pressure space” ODPS parameterization (used in RTTOV) outperforms the initial US “absorption space” ODAS parameterization (used in CRTM earlier). Now, both ODPS and ODAS are implemented in the CRTM • PW (Planck-Weighted convolution with band spectral response) outperforms the un-weighted (“Ordinary”) convolution • Next step is to compare the consistent ODPS-PW results with the current CRTM and MICROS, based on inconsistent coefficients Slide 13 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  14. DDs in IR37 ODPS-PW shows better cross-platform consistency (except for NOAA-16 and Aqua) VIIRS DDs changes from ~+0.07 to -0.07 K, resulting a more clear clustering of AM/PM platforms (diurnal cycle) Temporal stability (σ) is comparable Current CRTM / MICROS ODPS-PW Slide 14 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  15. Metop-B is out of AVHRR family by ~0.3 K, but is brought back in family in ODPS-PW This is because in current CRM, CFC absorption was taken into account for Metop-B, but not for other AVHRRs Cross-platform inconsistencies between AVHRR and MODIS/VIIRS is ~0.41 K Need to resolve DDs in IR11 Current CRTM / MICROS ODPS-PW Slide 15 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  16. Metop-B is consistent with other AVHRRs in current CRTM, but it is out of family by ~0.2 K for ODPS-PW. This is likely due to Metop-B AVHRR sensor calibration issue in IR12. Cross-platform inconsistencies between AVHRR and MODIS/VIIRS is ~0.32 K Need to resolve DDs in IR12 Current CRTM / MICROS ODPS-PW Slide 16 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  17. Factors likely causing AVHRR and MODIS/VIIRS inconsistency SRF difference SST bands are not identical between different platforms, particularly for different sensors MODIS SRFs are much narrower than AVHRR and VIIRS The spectral coverage are different for different platform Typically, SRF differences for window band affecting DDs are expected to be small and negligible. However, 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 analysis shows that CFC has a significant absorption in AVHRR long wave bands (Chen et al, 2012) To test the effect of CFC on M-O biases, 3 CFC concentrations were used for CRTM coefficient training: 0 (CFC free), 50%CFC, and 100% CFC. Factors affecting to AVHRR - MODIS/VIIRS inconsistency CFC absorption • When CFC concentration changes from free to 100%: • The effect on the M-O biases is minimal for IR37 • For IR11, M-O biases are reduced by ~0.21K/AVHRR, ~0.36K/MODIS, and ~0.22K/VIIRS • For IR12, M-O biases are reduced by ~0.15K/AVHRR, ~0.22K/MODIS, and ~0.18K/VIIRS • This result suggest that CFC can contribute to AVHRR - MODIS/VIIRS differences. • However the results are still inconclusive and more work is needed Slide 18 of 20 SPIE Ocean Sensing and Monitoring, 5 - 9 May 2014 in Baltimore, MD

  19. Conclusion and Future Work • DDs cannot cancel out systematic bias completely due to inconsistent CRTM coefficients used. Generating consistent CRTM coefficients is critically important • 4 C3 data sets were generated and compared. • PW-ODPS combinations provides most favorable M-O biases and smallest STDs • In IR37, ODPS-PW shows 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 are ~0.41K and ~0.32K. • ODPS-PW improves cross-platform biases Metop-B minus Metop-A in IR37 and IR11, but not in IR12 • IR37: reduced to -0.1 K, IR11: now exemplarily consistency, IR12: +0.23 K cross-platform biases (Metop-B CAL?). • Factors affecting ODPS-PW cross-platform biases maybe due to SRF differences and CFC absorption • MODIS SRFs are narrower than AVHRR & VIIRS • The AVHRR & VIIRS SRFs are close to gas absorption lines • The effect of including 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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