Comparison of AIRS and IASI Radiances Using GOES Imagers as Transfer Radiometers toward Climate Data Records

Likun Wang Perot Systems Government Services, Fairfax, Virginia

Search for other papers by Likun Wang in
Current site
Google Scholar
PubMed
Close
,
Xiangqian Wu NOAA/NESDIS Center for Satellite Applications and Research, Camp Springs, Maryland

Search for other papers by Xiangqian Wu in
Current site
Google Scholar
PubMed
Close
,
Mitch Goldberg NOAA/NESDIS Center for Satellite Applications and Research, Camp Springs, Maryland

Search for other papers by Mitch Goldberg in
Current site
Google Scholar
PubMed
Close
,
Changyong Cao NOAA/NESDIS Center for Satellite Applications and Research, Camp Springs, Maryland

Search for other papers by Changyong Cao in
Current site
Google Scholar
PubMed
Close
,
Yaping Li I. M. Systems Group, Rockville, Maryland

Search for other papers by Yaping Li in
Current site
Google Scholar
PubMed
Close
, and
Seung-Hee Sohn NOAA/NESDIS Center for Satellite Applications and Research, Camp Springs, Maryland
Korea Meteorological Administration, Seoul, Korea

Search for other papers by Seung-Hee Sohn in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), together with the future Cross-track Infrared Sounder, will provide long-term hyperspectral measurements of the earth and its atmosphere at ∼10 km spatial resolution. Quantifying the radiometric difference between AIRS and IASI is crucial for creating fundamental climate data records and establishing the space-based infrared calibration standard. Since AIRS and IASI have different local equator crossing times, a direct comparison of these two instruments over the tropical regions is not feasible. Using the Geostationary Operational Environmental Satellite (GOES) imagers as transfer radiometers, this study compares AIRS and IASI over warm scenes in the tropical regions for a time period of 16 months. The double differences between AIRS and IASI radiance biases relative to the GOES-11 and -12 imagers are used to quantify the radiance differences between AIRS and IASI within the GOES imager spectral channels. The results indicate that, at the 95% confidence level, the mean values of the IASI − AIRS brightness temperature differences for warm scenes are very small, that is, −0.0641 ± 0.0074 K, −0.0432 ± 0.0114 K, and −0.0095 ± 0.0151 K for the GOES-11 6.7-, 10.7-, and 12.0-μm channels, respectively, and −0.0490 ± 0.0100 K, −0.0419 ± 0.0224 K, and −0.0884 ± 0.0160 K for the GOES-12 6.5-, 10.7-, and 13.3-μm channels, respectively. The brightness temperature biases between AIRS and IASI within the GOES imager spectral range are less than 0.1 K although the AIRS measurements are slightly warmer than those of IASI.

Corresponding author address: Dr. Likun Wang, Rm. 810, 5200 Auth Rd., Camp Springs, MD 20746. Email: likun.wang@noaa.gov

Abstract

The Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), together with the future Cross-track Infrared Sounder, will provide long-term hyperspectral measurements of the earth and its atmosphere at ∼10 km spatial resolution. Quantifying the radiometric difference between AIRS and IASI is crucial for creating fundamental climate data records and establishing the space-based infrared calibration standard. Since AIRS and IASI have different local equator crossing times, a direct comparison of these two instruments over the tropical regions is not feasible. Using the Geostationary Operational Environmental Satellite (GOES) imagers as transfer radiometers, this study compares AIRS and IASI over warm scenes in the tropical regions for a time period of 16 months. The double differences between AIRS and IASI radiance biases relative to the GOES-11 and -12 imagers are used to quantify the radiance differences between AIRS and IASI within the GOES imager spectral channels. The results indicate that, at the 95% confidence level, the mean values of the IASI − AIRS brightness temperature differences for warm scenes are very small, that is, −0.0641 ± 0.0074 K, −0.0432 ± 0.0114 K, and −0.0095 ± 0.0151 K for the GOES-11 6.7-, 10.7-, and 12.0-μm channels, respectively, and −0.0490 ± 0.0100 K, −0.0419 ± 0.0224 K, and −0.0884 ± 0.0160 K for the GOES-12 6.5-, 10.7-, and 13.3-μm channels, respectively. The brightness temperature biases between AIRS and IASI within the GOES imager spectral range are less than 0.1 K although the AIRS measurements are slightly warmer than those of IASI.

Corresponding author address: Dr. Likun Wang, Rm. 810, 5200 Auth Rd., Camp Springs, MD 20746. Email: likun.wang@noaa.gov

Save
  • Aumann, H. H., and T. S. Pagano, 2008: Using AIRS and IASI data to evaluate absolute radiometric accuracy and stability for climate applications. Atmospheric and Environmental Remote Sensing Data Processing and Utilization IV: Readiness for GEOSS II, M. D. Goldberg et al., Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 7085), doi:10.1117/12.795225.

    • Search Google Scholar
    • Export Citation
  • Bevington, P. R., and D. K. Robinson, 2003: Data Reduction and Error Analysis for the Physical Sciences. 3rd ed. McGraw-Hill, 320 pp.

  • Blumstein, D., and Coauthors, 2004: IASI instrument: Technical overview and measured performances. Infrared Spaceborne Remote Sensing XII, M. Strojnik, Ed., International Society for Optical Engineering (SPIE Proceedings, Vol. 5543), 196–207.

    • Search Google Scholar
    • Export Citation
  • Blumstein, D., B. Tournier, F. R. Cayla, T. Phulpin, R. Fjortoft, C. Buil, and G. Ponce, 2007: In-flight performance of the infrared atmospheric sounding interferometer (IASI) on METOP-A. 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), doi:10.1117/12.734162.

    • Search Google Scholar
    • Export Citation
  • Boeing, 2006: GOES-N data user book. NASA GSFC Contract NAS5-98069, 220 pp.

  • Cao, C., M. Goldberg, and L. Wang, 2009: Spectral bias estimation of historical HIRS using IASI observations for improved fundamental climate data records. J. Atmos. Oceanic Technol., 26 , 13781387.

    • Search Google Scholar
    • Export Citation
  • Chahine, M. T., and Coauthors, 2006: Improving weather forecasting and providing new data on greenhouse gases. Bull. Amer. Meteor. Soc., 87 , 911926.

    • Search Google Scholar
    • Export Citation
  • Goody, R., and R. Haskins, 1998: Calibration of radiances from space. J. Climate, 11 , 754758.

  • Gunshor, M. M., T. J. Schmit, W. P. Menzel, and D. C. Tobin, 2009: Intercalibration of broadband geostationary imagers using AIRS. J. Atmos. Oceanic Technol., 26 , 746758.

    • Search Google Scholar
    • Export Citation
  • Johnson, R. X., and M. P. Weinreb, 1996: GOES-8 imager midnight effects and slope correction in GOES-8 and beyond. GOES-8 and Beyond, E. R. Washwell, Ed., International Society for Optical Engineering (SPIE Proceedings, Vol. 2812), 2812, 596–607.

    • Search Google Scholar
    • Export Citation
  • Klaes, K. D., and Coauthors, 2007: An introduction to the EUMETSAT Polar System. Bull. Amer. Meteor. Soc., 88 , 10851096.

  • Santer, B. D., T. M. L. Wigley, J. S. Boyle, D. J. Gaffen, J. J. Hnilo, D. Nychka, D. E. Parker, and K. E. Taylor, 2000: Statistical significance of trends and trend differences in layer-average atmospheric temperature time series. J. Geophys. Res., 105 , 73377356.

    • Search Google Scholar
    • Export Citation
  • Schmit, T. J., E. M. Prins, A. J. Schreiner, and J. J. Gurka, 2001: Introducing the GOES-M imager. Natl. Wea. Dig., 25 , (3–4). 2837.

    • Search Google Scholar
    • Export Citation
  • Strow, L., S. Hannon, D. Tobin, and H. Revercomb, 2008: Inter-calibration of the AIRS and IASI operational infrared sensors. Proc. 17th Annual Conf. on Characterization and Radiometric Calibration for Remote Sensing (CALCON), Logan, UT, Utah State University Research Foundation, CD-ROM.

    • Search Google Scholar
    • Export Citation
  • Tahara, Y., and K. Kato, 2008: New spectral compensation method for intercalibration with high spectral resolution sounder. Japan Meteorological Agency Meteorological Satellite Center Tech. Note 52, 37 pp. [Available online at http://mscweb.kishou.go.jp/monitoring/gsics/ir/techinfo.htm].

    • Search Google Scholar
    • Export Citation
  • Tobin, D. C., H. E. Revercomb, C. C. Moeller, and T. S. Pagano, 2006: Use of atmospheric infrared sounder high-spectral resolution spectra to assess the calibration of Moderate resolution Imaging Spectroradiometer on EOS Aqua. J. Geophys. Res., 111 , D09S05. doi:10.1029/2005JD006095.

    • Search Google Scholar
    • Export Citation
  • Tobin, D. C., H. E. Revercomb, F. Nagle, and R. Holz, 2008: Evaluation of IASI and AIRS spectral radiances using simultaneous nadir overpasses. Proc. 16th Int. TOVS Study Conf., Angra dos Reis, Brazil, Int. TOVS Working Group. [Available online at http://cimss.ssec.wisc.edu/itwg/itsc/itsc16/posters/B07_dave_tobin.pdf].

    • Search Google Scholar
    • Export Citation
  • Wang, L., and C. Cao, 2008: On-orbit calibration assessment of AVHRR longwave channels on MetOp-A using IASI. IEEE Trans. Geosci. Remote Sens., 46 , 40054013.

    • Search Google Scholar
    • Export Citation
  • Wang, L., C. Cao, and P. Ciren, 2007: Assessing NOAA-16 HIRS radiance accuracy using simultaneous nadir overpass observations from AIRS. J. Atmos. Oceanic Technol., 24 , 15461561.

    • Search Google Scholar
    • Export Citation
  • Wang, L., C. Cao, and M. D. Goldberg, 2009: Intercalibration of GOES-11 and GOES-12 water vapor channels with MetOp/IASI hyperspectral measurements. J. Atmos. Oceanic Technol., 26 , 18431855.

    • Search Google Scholar
    • Export Citation
  • Wu, A., X. Xiong, and C. Cao, 2008: Terra and Aqua MODIS inter-comparison of three reflective solar bands using AVHRR onboard the NOAA-KLM satellites. Int. J. Remote Sens., 29 , 19972010.

    • Search Google Scholar
    • Export Citation
  • Wu, X., and M. Goldberg, 2007: Global space-based inter-calibration system (GSICS): A status report. 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), doi:10.1117/12.734127.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1943 1591 56
PDF Downloads 244 54 10