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

    • Search Google Scholar
    • Export Citation
  • Collard, A., and Coauthors, 2010: An overview of the assimilation of AIRS and IASI radiances at operational NWP Centres. Proc. Int. TOVS Study Conf., ITSC-XVII, Monterey, CA, ITWG, 7.9. [Available online at http://cimss.ssec.wisc.edu/itwg/itsc/itsc17/session7/7.9_collard.pdf.]

    • Search Google Scholar
    • Export Citation
  • Hanafin, J. A., , and P. J. Minnett, 2005: Measurements of the infrared emissivity of a wind-roughened sea surface. Appl. Opt., 44, 398411.

    • Search Google Scholar
    • Export Citation
  • Hulley, G. C., , S. J. Hook, , E. Manning, , S.-Y. Lee, , and E. Fetzer, 2009: Validation of the Atmospheric Infrared Sounder (AIRS) version 5 land surface emissivity product over the Namib and Kalahari deserts. J. Geophys. Res., 114, D19104, doi:10.1029/2009JD012351.

    • Search Google Scholar
    • Export Citation
  • Jin, X., , and J. Li, 2010: Improving moisture profile retrieval from broadband infrared radiances with an optimized first-guess scheme. Remote Sens. Lett., 1, 231238.

    • Search Google Scholar
    • Export Citation
  • Labed, J., , and M. P. Stoll, 1991: Angular variation of land surface spectral emissivity in the thermal infrared: Laboratory investigations on bare soils. Int. J. Remote Sens., 12, 22992310.

    • Search Google Scholar
    • Export Citation
  • Li, J., , and J. Li, 2008: Derivation of global hyperspectral resolution surface emissivity spectra from Advanced Infrared Sounder radiance measurements. Geophys. Res. Lett., 35, L15807, doi:10.1029/2008GL034559.

    • Search Google Scholar
    • Export Citation
  • Li, J., , W. Wolf, , W. P. Menzel, , W. Zhang, , H.-L. Huang, , and T. H. Achtor, 2000: Global soundings of the atmosphere from ATOVS measurements: The algorithm and validation. J. Appl. Meteor., 39, 12481268.

    • Search Google Scholar
    • Export Citation
  • Li, J., , W. P. Menzel, , F. Sun, , T. J. Schmit, , and J. Gurka, 2004: AIRS subpixel cloud characterization using MODIS cloud products. J. Appl. Meteor., 43, 10831094.

    • Search Google Scholar
    • Export Citation
  • Li, J., , J. Li, , E. Weisz, , and D. K. Zhou, 2007: Physical retrieval of surface emissivity spectrum from hyperspectral infrared radiances. Geophys. Res. Lett., 34, L16812, doi:10.1029/2007GL030543.

    • Search Google Scholar
    • Export Citation
  • Li, Z., , J. Li, , X. Jin, , T. J. Schmit, , E. E. Borbas, , and M. D. Goldberg, 2010: An objective methodology for infrared land surface emissivity evaluation. J. Geophys. Res., 115, D22308, doi:10.1029/2010JD014249.

    • Search Google Scholar
    • Export Citation
  • Liu, C.-Y., , J. Li, , E. Weisz, , T. J. Schmit, , S. A. Ackerman, , and H.-L. Huang, 2008: Synergistic use of AIRS and MODIS radiance measurements for atmospheric profiling. Geophys. Res. Lett., 35, L21802, doi:10.1029/2008GL035859.

    • Search Google Scholar
    • Export Citation
  • Moy, L., , E. Borbas, , S. Seemann, , H.-L. Huang, , R. Knuteson, , I. Trigo, , and L. Zhou, 2006: Comparison of land surface infrared emissivity from MODIS, AIRS, and SEVIRI. Eos, Trans. Amer. Geophys. Union, 87 (Fall Meeting Suppl.), Abstract A21D-0850.

    • Search Google Scholar
    • Export Citation
  • Nalli, N. R., , P. J. Minnett, , and P. van Delst, 2008a: Emissivity and reflection model for calculating unpolarized isotropic water surface-leaving radiance in the infrared. 1. Theoretical development and calculations. Appl. Opt., 47, 37013721.

    • Search Google Scholar
    • Export Citation
  • Nalli, N. R., , P. J. Minnett, , E. Maddy, , W. W. McMillan, , and M. D. Goldberg, 2008b: Emissivity and reflection model for calculating unpolarized isotropic water surface-leaving radiance in the infrared. 2. Validation using Fourier transform spectrometers. Appl. Opt., 47, 46494671.

    • Search Google Scholar
    • Export Citation
  • Péquignot, E., , A. Chédin, , and N. A. Scott, 2008: Infrared continental surface emissivity spectra retrieved from AIRS hyperspectral sensor. J. Appl. Meteor. Climatol., 47, 16191633.

    • Search Google Scholar
    • Export Citation
  • Plokhenko, Y., , and W. P. Menzel, 2000: The effects of surface reflection on estimating the vertical temperature–humidity distribution from spectral infrared measurements. J. Appl. Meteor., 39, 314.

    • Search Google Scholar
    • Export Citation
  • Seemann, S. W., , E. E. Borbas, , R. O. Knuteson, , G. R. Stephenson, , and H.-L. Huang, 2008: Development of a global infrared land surface emissivity database for application to clear sky sounding retrievals from multispectral satellite radiance measurements. J. Appl. Meteor. Climatol., 47, 108123.

    • Search Google Scholar
    • Export Citation
  • Smith, W. L., and Coauthors, 1996: Observations of the infrared radiative properties of the ocean—Implications for the measurement of sea surface temperature via satellite remote sensing. Bull. Amer. Meteor. Soc., 77, 4151.

    • Search Google Scholar
    • Export Citation
  • Wu, X., , and W. L. Smith, 1997: Emissivity of rough sea surface for 8–13 μm: Modeling and verification. Appl. Opt., 36, 26092619.

  • Zhou, D. K., and Coauthors, 2002: Thermodynamic product retrieval methodology and validation for NAST-I. Appl. Opt., 41, 69576967, doi:10.1364/AO.41.006957.

    • Search Google Scholar
    • Export Citation
  • Zhou, D. K., , A. M. Larar, , W. L. Smith, , and X. Liu, 2006: Surface emissivity effects on thermodynamic retrieval of IR spectral radiance. Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications, W. L. Smith Sr. et al., Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 6405), doi:10.1117/12.694283.

    • Search Google Scholar
    • Export Citation
  • Zhou, D. K., , W. L. Smith, , A. M. Larar, , X. Liu, , J. P. Taylor, , P. Schlüssel, , L. L. Strow, , and S. A. Mango, 2009: All weather IASI single field-of-view retrievals: Case study—Validation with JAIVEx data. Atmos. Chem. Phys., 9, 22412255, doi:10.5194/acp-9-2241-2009.

    • Search Google Scholar
    • Export Citation
  • Zhou, D. K., , A. M. Larar, , X. Liu, , W. L. Smith, , L. L. Strow, , P. Yang, , P. Schlüssel, , and X. Calbet, 2011: Global land surface emissivity retrieved from satellite ultraspectral ir measurements. IEEE Trans. Geosci. Remote Sens., 49, 12771290, doi:10.1109/TGRS.2010.2051036.

    • Search Google Scholar
    • Export Citation
  • Zhou, L., and Coauthors, 2008: Regression of surface spectral emissivity from hyperspectral instruments. IEEE Trans. Geosci. Remote Sens., 46, 328333.

    • Search Google Scholar
    • Export Citation
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Surface Emissivity Impact on Temperature and Moisture Soundings from Hyperspectral Infrared Radiance Measurements

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  • 1 Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin
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Abstract

An accurate land surface emissivity (LSE) is critical for the retrieval of atmospheric temperature and moisture profiles along with land surface temperature from hyperspectral infrared (IR) sounder radiances; it is also critical to assimilating IR radiances in numerical weather prediction models over land. To investigate the impact of different LSE datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational (1DVAR) retrieval algorithm. Sounding retrievals using constant LSE, the LSE dataset from the Infrared Atmospheric Sounding Interferometer (IASI), and the baseline fit dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) are performed. AIRS observations over northern Africa on 1–7 January and 1–7 July 2007 are used in the experiments. From the limited regional comparisons presented here, it is revealed that the LSE from the IASI obtained the best agreement between the retrieval results and the ECMWF reanalysis, whereas the constant LSE gets the worst results when the emissivities are fixed in the retrieval process. The results also confirm that the simultaneous retrieval of atmospheric profile and surface parameters could reduce the dependence of soundings on the LSE choice and finally improve sounding accuracy when the emissivities are adjusted in the iterative retrieval. In addition, emissivity angle dependence is investigated with AIRS radiance measurements. The retrieved emissivity spectra from AIRS over the ocean reveal weak angle dependence, which is consistent with that from an ocean emissivity model. This result demonstrates the reliability of the 1DVAR simultaneous algorithm for emissivity retrieval from hyperspectral IR radiance measurements.

Corresponding author address: Zhigang Yao, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, 1225 West Dayton St., Madison, WI 53706. E-mail: zyao6@wisc.edu

Abstract

An accurate land surface emissivity (LSE) is critical for the retrieval of atmospheric temperature and moisture profiles along with land surface temperature from hyperspectral infrared (IR) sounder radiances; it is also critical to assimilating IR radiances in numerical weather prediction models over land. To investigate the impact of different LSE datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational (1DVAR) retrieval algorithm. Sounding retrievals using constant LSE, the LSE dataset from the Infrared Atmospheric Sounding Interferometer (IASI), and the baseline fit dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) are performed. AIRS observations over northern Africa on 1–7 January and 1–7 July 2007 are used in the experiments. From the limited regional comparisons presented here, it is revealed that the LSE from the IASI obtained the best agreement between the retrieval results and the ECMWF reanalysis, whereas the constant LSE gets the worst results when the emissivities are fixed in the retrieval process. The results also confirm that the simultaneous retrieval of atmospheric profile and surface parameters could reduce the dependence of soundings on the LSE choice and finally improve sounding accuracy when the emissivities are adjusted in the iterative retrieval. In addition, emissivity angle dependence is investigated with AIRS radiance measurements. The retrieved emissivity spectra from AIRS over the ocean reveal weak angle dependence, which is consistent with that from an ocean emissivity model. This result demonstrates the reliability of the 1DVAR simultaneous algorithm for emissivity retrieval from hyperspectral IR radiance measurements.

Corresponding author address: Zhigang Yao, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, 1225 West Dayton St., Madison, WI 53706. E-mail: zyao6@wisc.edu
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