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Effect of consistent CRTM coefficients on M-O bias and DDs in MICROS

Effect of consistent CRTM coefficients on M-O bias and DDs in MICROS. Xingming Liang and Alexander Ignatov. Motivation. Cross-platform inconsistencies are at least in part due to inconsistent CRTM coefficients for different sensors/platforms

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Effect of consistent CRTM coefficients on M-O bias and DDs in MICROS

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  1. Effect of consistent CRTM coefficients on M-O bias and DDs in MICROS Xingming Liang and Alexander Ignatov CRTM Coefficients in MICROS

  2. Motivation • Cross-platform inconsistencies are at least in part due to inconsistent CRTM coefficients for different sensors/platforms • Sensitivity analysis of CRTM Coefficients is critically important for understanding and minimizing model effect on MICROS double differences MODIS CRTM Coefficients Recalculated Metop-B CRTM Coefficients: Calculated Correctly? from www.star.nesdis.noaa.gov/sod/sst/micros CRTM Coefficients in MICROS

  3. CRTM Coefficients Analyzed in MICROS • 4 consistent CRTM Coefficients datasets were provided by Yong Chen and analyzed in MICROS using 1 day of global data (15 Jan 2013): • ODAS-ORD, ODAS-PW, ODPS-ORD, and ODPS- PW • Based on the same baseline LBLRTM v11.7 • All include CFC absorption CRTM Coefficients in MICROS

  4. Methodology • Compare 4 different results using 3 metrics • Global M-O biases. The expectation is that for better coefficients, global M-O biases are smaller • Global SDs of M-O biases. The expectation is that for better coefficients, STDs are smaller • Double differences for two pairs of platforms flying close orbits (For Hi-res, it’s Metop-A and -B, and NPP and Aqua. For GAC, it’s Metop-A and -B and NOAA-18 and -19). The expectation is that for better coefficients, DDs are smaller and more consistent across different pairs CRTM Coefficients in MICROS

  5. AVHRR GAC (IR37) Δ1 = N18 minus N19 Δ2 = M-A minus M-B σ >> IR37, ODAS_ORD IR37, ODPS_ORD Δ1=+0.133 K Δ1=+0.113 K Δ2=+0.082 K Δ2=+0.080 K σ > σ > σ >> IR37, ODAS_PW IR37, ODPS_PW Δ1=+0.127 K Δ1=+0.111 K Δ2=+0.101 K Δ2=+0.093 K CRTM Coefficients in MICROS

  6. Δ1 = Aqua minus S-NPP Hi-Res Sensors (IR37) Δ2 = M-A minus M-B σ ~ IR37, ODAS_ORD IR37, ODPS_ORD Δ1=+0.237 K Δ1=+0.223 K Δ2=+0.085 K Δ2=+0.086 K σ > σ > σ ~ IR37, ODAS_PW IR37, ODPS_PW Δ1=+0.155 K Δ1=+0.141 K Δ2=+0.105 K Δ2=+0.099 K CRTM Coefficients in MICROS

  7. Observation in IR37 • Global M-O biases • Generally smaller for PW by ~0.06 K (except for VIIRS, where it’s larger by ~0.05 K) • For GAC, generally smaller for ODPS • N-16 ODAS has a large anomaly up to 1K, looks much better for ODPS • SDs • SDs significantly smaller for ODPS for all GAC AVHRRs. Hi-res sensors are only minimally affected. • If this accuracy is deemed sufficient, then any combination of these options is good • DDs • Are insensitive to the choice of ORD-PW, ODAS-ODPS to within 0.02K for all platforms, except Aqua and NPP. For Aqua-NPP, DDs are very sensitive to the combination. This sensitivity is alarming (should we understand why??) smallest for ODPS-PW • If this accuracy is deemed sufficient, then any combination of these options is good • Recommendation • Overall, between SST team, CRTM team and sensor calibration team is needed to resolve cross-platform bias using ODPS-PW • Understand large anomaly in N-16 ODAS CRTM Coefficients in MICROS

  8. CRTM Coefficients in MICROS

  9. AVHRR GAC (IR11) Δ1 = N18 minus N19 Δ2 = M-A minus M-B σ > IR37, ODAS_ORD IR37, ODPS_ORD Δ1=+0.077 K Δ1=+0.074 K Δ2=+0.000 K Δ2=-0.003 K σ ~ σ ~ σ > IR37, ODAS_PW IR37, ODPS_PW Δ1=+0.071 K Δ1=+0.076 K Δ2=+0.013 K Δ2=-0.007 K CRTM Coefficients in MICROS

  10. Δ1 = Aqua minus S-NPP High Resolution Sensors (IR11) Δ2 = M-A minus M-B σ > IR37, ODAS_ORD IR37, ODPS_ORD Δ1=+0.052 K Δ1=+0.015 K Δ2=+0.005 K Δ2=0.000 K σ ~ σ ~ σ > IR37, ODAS_PW IR37, ODPS_PW Δ1=+0.006 K Δ1=+0.047 K Δ2=+0.017 K Δ2=-0.002 K CRTM Coefficients in MICROS

  11. Observation in IR11 • Global M-O biases • Larger in ODPS than ODAS by ~0.1 K for MODIS, by ~0.05 K for VIIRS, and by ~0.03 K for AVHRR. (why are opposed w/rt IR37 ?) • Comparable between PW and ORD • SDs • Smaller in ODPS than ODAS • Comparable between PW and ORD • DDs • Are insensitive to the choice of ORD-PW, ODAS-ODPS to within 0.02K for all platforms, except Aqua and NPP. • Have 0.4 K inconsistencies between AVHRR and MODIS&VIIRS. • Recommendation • Since the inconsistencies between AVHRR and MODIS&VIIRS are within 0.1 K in official MICROS, further analysis for new coefficients is needed. Specially for new addition – CFC absorption. CRTM Coefficients in MICROS

  12. CRTM Coefficients in MICROS

  13. AVHRR GAC (IR12) Δ1 = N18 minus N19 Δ2 = M-A minus M-B σ > IR12, ODAS_ORD IR12, ODPS_ORD Δ1=+0.020 K Δ1=+0.010 K Δ2=-0.227 K Δ2=-0.241 K σ ~ σ ~ σ > IR12, ODPS_PW IR12, ODAS_PW Δ1=+0.015 K Δ1=+0.003 K Δ2=-0.239 K Δ2=-0.226 K CRTM Coefficients in MICROS

  14. Δ1 = Aqua minus S-NPP High Resolution Sensors (IR12) Δ2 = M-A minus M-B σ > IR12, ODPS_ORD IR12, ODAS_ORD Δ1=+0.060 K Δ1=+0.071 K Δ2=-0.237 K Δ2=-0.225 K σ ~ σ ~ σ > IR12, ODPS_PW IR12, ODAS_PW Δ1=+0.067 K Δ1=+0.079 K Δ2=-0.234 K Δ2=-0.223 K CRTM Coefficients in MICROS

  15. Observation in IR12 • Global M-O biases • Larger by ~0.04 K in ODPS than ODAS • Generally smaller in PW compared to ORD • SD • Smaller for ODPS. • Comparable between PW and ORD • Consistencies: • All AVHRRs are consistent within 0.1 K, except for Metop-B, out of AVHRR family by ~0.25 K. • Inconsistencies between AVHRR and MODIS&VIIRS are ~0.4 K. • Recommendation • Since the inconsistencies between AVHRR and MODIS&VIIRS are within 0.1 K in official MICROS, further analysis for new coefficients is needed. Specially for new addition – CFC absorption. • Joint work between SST team, CRTM team and sensor calibration team is needed to resolve cross-platform bias between Metop-A and –B. CRTM Coefficients in MICROS

  16. CRTM Coefficients in MICROS

  17. Δ1 = N18 minus N19 AVHRR GAC (SST) Δ2 = M-A minus M-B σ ~ SST, ODAS_ORD SST, ODPS_ORD Δ1=-0.112 K Δ1=-0.111 K Δ2=+0.028 K Δ2=+0.028 K σ ~ σ ~ σ ~ SST, ODPS_PW SST, ODAS_PW Δ1=-0.111 K Δ1=-0.111 K Δ2=-0.028 K Δ2=+0.028 K CRTM Coefficients in MICROS

  18. Δ1 = Aqua minus S-NPP High Resolution Sensors (SST) Δ2 = M-A minus M-B σ ~ SST, ODAS_ORD SST, ODPS_ORD Δ1=+0.013 K Δ1=+0.014 K Δ2=+0.025 K Δ2=+0.024 K σ ~ σ ~ σ ~ SST, ODPS_PW SST, ODAS_PW Δ1=+0.013 K Δ1=+0.014 K Δ2=+0.025 K Δ2=-0.024 K CRTM Coefficients in MICROS

  19. Observation in SST • M-O mean biases, SDs and DDs are insensitive to the choice of ORD-PW, ODAS-ODPS for all platforms. CRTM Coefficients in MICROS

  20. CRTM Coefficients in MICROS

  21. Conclusion • 4 CRTM Coeffs. data set were used to check the sensitivities on the three metrics: M-O mean bias, SDs, and cross-platform consistency. • SDs are generally smaller in ODPS than ODAS, and in PW than ORD. • Overall, ODPS-PW is recommended to use for model simulation. • N-16 ODAS has a large anomaly up to 1K, looks much better for ODPS. Understanding this issue is needed. • Inconsistencies between AVHRR and MODIS&VIIRS are ~0.4 K. further analysis is needed. • Inconsistencies between Metop-A and –B are ~0.25 K in IR12. Joint work between SST team, CRTM team and sensor calibration team is needed to resolve cross-platform bias. CRTM Coefficients in MICROS

  22. Observation in IR37 - Old • Using ODPS instead of ODAS, • Mean biases were changed largest for High Res. for the PW cases (increased by 0.03 K, except for NOAA16), and slightly changed for other cases (changed by ±0.01 K) • SDs were improved for all GAC AVHRRs, but not affect high Res. Sensor significantly. • Using PW instead of ORD, • Mean biases were reduced by ~0.06 K for all cases, except for VIIRS, which increased by 0.05 K. • SDs were slightly improved for all sensors • NOAA16 increased by -1.0 K when ODAS_PW instead of ODAS_ORD, and by 0.2 K when ODPS_PW instead of ODPS_ORD due to out of band effect issue in Ch3B. • Consistencies: • All AVHRRs (except for NOAA16), MODIS/Terra, and VIIRS are consistent within ±0.1 K for all cases. • Inconsistency between Terra and Aqua are ~0.3 K, due to sensor calibration issue. CRTM Coefficients in MICROS

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