A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part II: Validation

David R. Doelling NASA Langley Research Center, Hampton, Virginia

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Rajendra Bhatt Science Systems and Applications, Inc., Hampton, Virginia

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Benjamin R. Scarino Science Systems and Applications, Inc., Hampton, Virginia

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Arun Gopalan Science Systems and Applications, Inc., Hampton, Virginia

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Conor O. Haney Science Systems and Applications, Inc., Hampton, Virginia

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Patrick Minnis NASA Langley Research Center, Hampton, Virginia

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Kristopher M. Bedka NASA Langley Research Center, Hampton, Virginia

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Abstract

Consistent cross-sensor Advanced Very High Resolution Radiometer (AVHRR) calibration coefficients are determined using desert, polar ice, and deep convective cloud (DCC) invariant Earth targets. The greatest AVHRR calibration challenge is the slow orbit degradation of the host satellite, which precesses toward a terminator orbit. This issue is solved by characterizing the invariant targets with NOAA-16 AVHRR observed radiances that have been referenced to the Aqua Moderate Resolution Imaging Spectrometer (MODIS) calibration using simultaneous nadir overpass (SNO) observations. Another benefit of the NOAA-16 invariant target–modeled reflectance method is that, because of the similarities among the AVHRR spectral response functions, a smaller spectral band adjustment factor is required than when establishing calibrations relative to a non-AVHRR reference instrument. The sensor- and band-specific calibration uncertainties, with respect to the calibration reference, are, on average, 2% and 3% for channels 1 and 2, respectively. The uncertainties are smaller for sensors that are in afternoon orbits, have longer records, and spend less time in terminator conditions.

The multiple invariant targets referenced to Aqua MODIS (MITRAM) AVHRR calibration coefficients are evaluated for individual target consistency, compared against Aqua MODIS/AVHRR SNOs, and selected published calibration gains. The MITRAM and SNO relative calibration biases mostly agree to within 1% for channels 1 and 2, respectively. The individual invariant target and MITRAM sensor relative calibration biases are mostly consistent to within 1% and 2% for channels 1 and 2, respectively. The differences between the MITRAM and other published calibrations are mostly attributed to the reference instrument calibration differences.

Corresponding author address: David Doelling, NASA Langley Research Center, MS 420, Hampton, VA 23681-2199. E-mail: david.r.doelling@nasa.gov

Abstract

Consistent cross-sensor Advanced Very High Resolution Radiometer (AVHRR) calibration coefficients are determined using desert, polar ice, and deep convective cloud (DCC) invariant Earth targets. The greatest AVHRR calibration challenge is the slow orbit degradation of the host satellite, which precesses toward a terminator orbit. This issue is solved by characterizing the invariant targets with NOAA-16 AVHRR observed radiances that have been referenced to the Aqua Moderate Resolution Imaging Spectrometer (MODIS) calibration using simultaneous nadir overpass (SNO) observations. Another benefit of the NOAA-16 invariant target–modeled reflectance method is that, because of the similarities among the AVHRR spectral response functions, a smaller spectral band adjustment factor is required than when establishing calibrations relative to a non-AVHRR reference instrument. The sensor- and band-specific calibration uncertainties, with respect to the calibration reference, are, on average, 2% and 3% for channels 1 and 2, respectively. The uncertainties are smaller for sensors that are in afternoon orbits, have longer records, and spend less time in terminator conditions.

The multiple invariant targets referenced to Aqua MODIS (MITRAM) AVHRR calibration coefficients are evaluated for individual target consistency, compared against Aqua MODIS/AVHRR SNOs, and selected published calibration gains. The MITRAM and SNO relative calibration biases mostly agree to within 1% for channels 1 and 2, respectively. The individual invariant target and MITRAM sensor relative calibration biases are mostly consistent to within 1% and 2% for channels 1 and 2, respectively. The differences between the MITRAM and other published calibrations are mostly attributed to the reference instrument calibration differences.

Corresponding author address: David Doelling, NASA Langley Research Center, MS 420, Hampton, VA 23681-2199. E-mail: david.r.doelling@nasa.gov
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  • Bhatt, R., Doelling D. R. , Scarino B. R. , Gopalan A. , Haney C. O. , Minnis P. , and Bedka K. , 2016: A consistent AVHRR visible calibration record based on multiple methods applicable for the NOAA degrading orbits. Part I: Methodology. J. Atmos. Oceanic Technol., 33, 24992515, doi:10.1175/JTECH-D-16-0044.1.

  • Cao, C., and Heidinger A. , 2002: Inter-comparison of the longwave infrared channels of MODIS and AVHRR/NOAA-16 using simultaneous nadir observations at orbit intersections. Earth Observing Systems VII, W. L. Barnes, Ed., International Society for Optical Engineering (SPIE Proceedings, Vol. 4814), 306, doi:10.1117/12.451690.

    • Search Google Scholar
    • Export Citation
  • Cao, C., Xiong X. , Wu A. , and Wu X. , 2008: Assessing the consistency of AVHRR and MODIS L1B reflectance for generating Fundamental Climate Data Records. J. Geophys. Res., 113, D09114, doi:10.1029/2007JD009363.

    • Search Google Scholar
    • Export Citation
  • Che, N., and Price J. C. , 1992: Survey of radiometric calibration results and methods for visible and near infrared channels of NOAA-7, -9 and -11 AVHRRs. Remote Sens. Environ., 41, 1927, doi:10.1016/0034-4257(92)90057-Q.

    • Search Google Scholar
    • Export Citation
  • Cosnefroy, H., Leroy M. , and Briottet X. , 1996: Selection and characterization of Saharan and Arabian desert sites for the calibration of optical satellite sensors. Remote Sens. Environ., 58, 101114, doi:10.1016/0034-4257(95)00211-1.

    • Search Google Scholar
    • Export Citation
  • Doelling, D. R., and Minnis P. , 2016: Calibration of historical and future AVHRR and GOES visible and near-infrared sensors. Algorithm Theoretical Basis Doc. CDRP-ATBD-0823, 50 pp. [Available online at https://www.ncdc.noaa.gov/sites/default/files/cdr-documentation/%3Cem%3EEdit%20Climate%20Data%20Record%3C/em%3E%20AVHRR%20Radiances%20-%20NASA/CDRP-ATBD-0823%20AVHRR%20Radiances%20-%20NASA%20C-ATBD%20(01B-30a)%20(DSR-1048).pdf.]

  • Doelling, D. R., Garber D. P. , Avey L. A. , Nguyen L. , and Minnis P. , 2007: The calibration of AVHRR visible dual gain using Meteosat-8 for NOAA-16 to 18. Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS, M. D. Goldberg et al., Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 6684), 668409, doi:10.1117/12.736080.

  • Doelling, D. R., Lukashin C. , Minnis P. , Scarino B. , and Morstad D. , 2012: Spectral reflectance corrections for satellite intercalibrations using SCIAMACHY data. Geosci. Remote Sens. Lett., 9, 119123, doi:10.1109/LGRS.2011.2161751.

    • Search Google Scholar
    • Export Citation
  • Doelling, D. R., Morstad D. , Scarino B. R. , Bhatt R. , and Gopalan A. , 2013: The characterization of deep convective clouds as an invariant calibration target and as a visible calibration technique. IEEE Trans. Geosci. Remote Sens., 51, 11471159, doi:10.1109/TGRS.2012.2225066.

    • Search Google Scholar
    • Export Citation
  • Doelling, D. R., Wu A. , Xiong X. , Scarino B. R. , Bhatt R. , Haney C. O. , Morstad D. , and Gopalan A. , 2015: The radiometric stability and scaling of Collection 6 Terra and Aqua-MODIS VIS, NIR, and SWIR spectral bands. IEEE Trans. Geosci. Remote Sens., 53, 45204535, doi:10.1109/TGRS.2015.2400928.

    • Search Google Scholar
    • Export Citation
  • Eplee, R. E., Jr., Sun J. , Meister G. , Patt F. S. , Xiong X. , and McClain C. R. , 2011: Cross calibration of SeaWiFS and MODIS using on-orbit observations of the Moon. Appl. Opt., 50, 120133, doi:10.1364/AO.50.000120.

    • Search Google Scholar
    • Export Citation
  • Fougnie, B., Doelling D. R. , Crespin A. , Lafrance B. , and Labonnote L. , 2014: Bidirectional reflectance distribution function (BRDF) of deep convective clouds (DCC) derived from PARASOL measurements and compared to radiative transfer computation and model. 2014 CALCON Tech. Conf., Logan, UT, Utah State University. [Available online at http://digitalcommons.usu.edu/calcon/CALCON2014/All2014Content/7/.]

  • Heidinger, A. K., Cao C. , and Sullivan J. T. , 2002: Using Moderate Resolution Imaging Spectrometer (MODIS) to calibrate advanced very high resolution radiometer reflectance channels. J. Geophys. Res., 107, 4702, doi:10.1029/2001JD002035.

    • Search Google Scholar
    • Export Citation
  • Heidinger, A. K., Straka W. C. III, Molling C. C. , and Sullivan J. T. , 2010: Deriving an inter-sensor consistent calibration for the AVHRR solar reflectance data record. Int. J. Remote Sens., 31, 64936517, doi:10.1080/01431161.2010.496472.

    • Search Google Scholar
    • Export Citation
  • Li, C., Xue Y. , Liu Q. , Guang J. , He X. , Zhang J. , Wang T. , and Liu X. , 2014: Post calibration of channels 1 and 2 of long-term AVHRR data record based on SeaWiFS data and pseudo-invariant targets. Remote Sens. Environ., 150, 104119, doi:10.1016/j.rse.2014.04.020.

    • Search Google Scholar
    • Export Citation
  • Li, C., Xue Y. , Liu Q. , Ouzzane K. , and Zhang J. , 2015: Using SeaWiFS measurements to evaluate radiometric stability of pseudo-invariant calibration sites at top of atmosphere. IEEE Geosci. Remote Sens. Lett., 12, 125129, doi:10.1109/LGRS.2014.2329138.

    • Search Google Scholar
    • Export Citation
  • Lyapustin, A., and Coauthors, 2007: Analysis of MODIS–MISR calibration differences using surface albedo around AERONET sites and cloud reflectance. Remote Sens. Environ., 107, 1221, doi:10.1016/j.rse.2006.09.028.

    • Search Google Scholar
    • Export Citation
  • Mittaz, J., and Harris A. , 2011: A physical method for the calibration of the AVHRR/3 thermal IR channels. Part II: An in-orbit comparison of the AVHRR longwave thermal IR channels on board MetOp-A with IASI. J. Atmos. Oceanic Technol., 28, 10721087, doi:10.1175/2011JTECHA1517.1.

    • Search Google Scholar
    • Export Citation
  • Molling, C. C., Heidinger A. K. , Straka W. C. , and Wu X. , 2010: Calibrations for AVHRR channels 1 and 2: Review and path towards consensus. Int. J. Remote Sens., 31, 65196540, doi:10.1080/01431161.2010.496473.

    • Search Google Scholar
    • Export Citation
  • Nagaraja Rao, C. R., and Chen J. , 1995: Inter-satellite calibration linkages for the visible and near-infrared channels of the Advanced Very High Resolution Radiometer on the NOAA-7, -9, and -11 spacecraft. Int. J. Remote Sens., 16, 19311942, doi:10.1080/01431169508954530.

    • Search Google Scholar
    • Export Citation
  • Nagaraja Rao, C. R., and Chen J. , 1999: Revised post-launch calibration of the visible and near-infrared channels of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-14 spacecraft. Int. J. Remote Sens., 20, 34853491, doi:10.1080/014311699211147.

    • Search Google Scholar
    • Export Citation
  • Nagaraja Rao, C. R., Weinreb M. P. , and Chen J. , 1994: Recalibration of the Advanced Very High Resolution Radiometer for climate change research. Adv. Space Res., 14A, 117120, doi:10.1016/0273-1177(94)90359-X.

    • Search Google Scholar
    • Export Citation
  • Price, J. C., 1991: Timing of NOAA afternoon passes. Int. J. Remote Sens., 12, 193198, doi:10.1080/01431169108929644.

  • Rossow, W. B., and Ferrier J. , 2015: Evaluation of long-term calibrations of the AVHRR visible radiances. J. Atmos. Oceanic Technol., 32, 744766, doi:10.1175/JTECH-D-14-00134.1.

    • Search Google Scholar
    • Export Citation
  • Scarino, B., Doelling D. R. , Minnis P. , Gopalan A. , Chee T. , Bhatt R. , Lukashin C. , and Haney C. O. , 2016: A web-based tool for calculating spectral band difference adjustment factors derived from SCIAMACHY hyper-spectral data. IEEE Trans. Geosci. Remote Sens., 54, 25292542, doi:10.1109/TGRS.2015.2502904.

    • Search Google Scholar
    • Export Citation
  • Smith, G. R., Levin R. H. , Abel P. , and Jacobowitz H. , 1998: Calibration of the solar channels of the NOAA-9 AVHRR using high altitude aircraft measurements. J. Atmos. Oceanic Technol., 19, 18261833, doi:10.1175/1520-0426(1988)005<0631:COTSCO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sun, J., Angal A. , Xiong X. , Chen H. , Geng X. , Wu A. , Choi T. , and Chu M. , 2012: MODIS reflective solar bands calibration improvements in Collection 6. Earth Observing Missions and Sensors: Development, Implementation, and Characterization II, H. Shimoda et al., Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 8528), 85280N, doi:10.1117/12.979733.

    • Search Google Scholar
    • Export Citation
  • Sun, J., Xiong X. , Angal A. , Chen H. , Wu A. , and Geng X. , 2014: Time-dependent response versus scan angle for MODIS reflective solar bands. IEEE Trans. Geosci. Remote Sens., 52, 31593174, doi:10.1109/TGRS.2013.2271448.

    • Search Google Scholar
    • Export Citation
  • Weatherhead, E. C., and Coauthors, 1998: Factors affecting the detection of trends: Statistical considerations and applications to environmental data. J. Geophys. Res., 103, 17 14917 161, doi:10.1029/98JD00995.

    • Search Google Scholar
    • Export Citation
  • Wielicki, B. A., Doelling D. R. , Young D. F. , Loeb N. G. , Garber D. P. , and MacDonnel D. G. , 2008: Climate quality broadband and narrowband solar reflected radiance calibration between sensors in orbit. 2008 IEEE International Geoscience and Remote Sensing Symposium, Vol. 1, IEEE, I-257I-260, doi:10.1109/IGARSS.2008.4778842.

  • Wielicki, B. A., and Coauthors, 2013: Achieving climate change absolute accuracy in orbit. Bull. Amer. Meteor. Soc., 94, 15191539, doi:10.1175/BAMS-D-12-00149.1.

    • Search Google Scholar
    • Export Citation
  • Wu, A., Xiong X. , and Angal A. , 2013a: Deriving a MODIS-based calibration for the AVHRR reflective solar channels of the NOAA KLM operational satellites. IEEE Trans. Geosci. Remote Sens., 51, 14051413, doi:10.1109/TGRS.2012.2220780.

    • Search Google Scholar
    • Export Citation
  • Wu, X., Sullivan J. T. , and Heidinger A. K. , 2010: Operational calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible and near-infrared channels. Can. J. Remote Sens., 36, 602616, doi:10.5589/m10-080.

    • Search Google Scholar
    • Export Citation
  • Xiong, X., Barnes W. , Chiang K. , Erives H. , Che N. , and Sun J. , 2004: Status of Aqua MODIS on-orbit calibration and characterization. Sensors, Systems, and Next-Generation Satellites VIII, R. Meynart, S. P. Neeck, and H. Shimoda, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 5570), 317–327, doi:10.1117/12.564940.

    • Search Google Scholar
    • Export Citation
  • Xiong, X., Sun J. , Wu A. , Chiang K -F. , Esposito J. , and Barnes W. , 2005: Terra and Aqua MODIS calibration algorithms and uncertainty analysis. Sensors, Systems, and Next-Generation Satellites IX, R. Meynart, S. P. Neeck, and H. Shimoda, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 5978), 59780V, doi:10.1117/12.627631.

    • Search Google Scholar
    • Export Citation
  • Yu, F., and Wu X. , 2010: Water vapor correction to improve the operational calibration for NOAA AVHRR/3 channel 2 (0.85 µm) over a desert target. Can. J. Remote Sens., 36, 514526, doi:10.5589/m10-077.

    • Search Google Scholar
    • Export Citation
  • Yu, F., Wu X. , Grotenhuis M. , and Qian H. , 2014: Intercalibration of GOES Imager visible channels over the Sonoran Desert. J. Geophys. Res. Atmos., 119, 86398658, doi:10.1002/2013JD020702.

    • Search Google Scholar
    • Export Citation
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