Vegetative and Atmospheric Corrections for the Soil Moisture Retrieval from Passive Microwave Remote Sensing Data: Results from the Southern Great Plains Hydrology Experiment 1997

Matthias Drusch Department of Civil and Environmental Engineering, Princeton University, New Jersey

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Eric F. Wood Department of Civil and Environmental Engineering, Princeton University, New Jersey

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Thomas J. Jackson USDA Hydrology Laboratory, Beltsville, Maryland

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Abstract

A radiative transfer model and data from the Southern Great Plains 1997 Hydrology Experiment were used to analyze the dependency of surface emissivity retrieval at 19 GHz on atmospheric and vegetative effects. Volumetric soil moisture obtained from ground measurements in the Central Facility area that show a dynamic range of 25% was highly correlated with the corresponding L-band electronically steered thinned array radiometer (ESTAR) 1.4-GHz and Special Sensor Microwave Imager 19-GHz brightness temperatures. For the Little Washita area, only the ESTAR measurements were well correlated with volumetric soil moisture. Atmospheric corrections, which were calculated from collocated radiosonde measurements, did not improve the soil moisture retrieval significantly. However, a sensitivity study at 19 GHz using a larger dataset of 241 radiosonde ascents indicates that the variability in integrated atmospheric water vapor introduces variations of 0.023 in surface emissivity. This value is ∼36% of the variability caused by changes in soil moisture. Therefore, atmospheric corrections should generally improve the soil moisture retrieval at 19 GHz. Different water vapor absorption schemes and absorption by nonraining clouds do not affect this result. Even for sparse vegetation (vegetation water content of 0.33 kg m−2), the effect on soil emissivity retrieval is significant. Because of the lack of appropriate data for vegetation cover and single scattering albedo, the effects of the vegetation had to be estimated. Within a reasonable parameter range they were comparable to the effects caused by soil moisture changes. To quantify the effect of surface emissivity changes on integrated water vapor retrieval, brightness temperatures were modeled using actual soil and atmospheric parameters. The radiative transfer equation was then inverted with respect to the atmospheric contribution using an average value for the surface emissivity. An uncertainty of 5% in volumetric soil moisture caused an error of 30 kg m−2 in integrated water vapor.

Corresponding author’s address: Dr. Matthias Drusch, Meteorologisches Institut, Universität Bonn, Auf dem Hügel 20, 53121 Bonn, Germany.

Email: mdrusch@uni-bonn.de

Abstract

A radiative transfer model and data from the Southern Great Plains 1997 Hydrology Experiment were used to analyze the dependency of surface emissivity retrieval at 19 GHz on atmospheric and vegetative effects. Volumetric soil moisture obtained from ground measurements in the Central Facility area that show a dynamic range of 25% was highly correlated with the corresponding L-band electronically steered thinned array radiometer (ESTAR) 1.4-GHz and Special Sensor Microwave Imager 19-GHz brightness temperatures. For the Little Washita area, only the ESTAR measurements were well correlated with volumetric soil moisture. Atmospheric corrections, which were calculated from collocated radiosonde measurements, did not improve the soil moisture retrieval significantly. However, a sensitivity study at 19 GHz using a larger dataset of 241 radiosonde ascents indicates that the variability in integrated atmospheric water vapor introduces variations of 0.023 in surface emissivity. This value is ∼36% of the variability caused by changes in soil moisture. Therefore, atmospheric corrections should generally improve the soil moisture retrieval at 19 GHz. Different water vapor absorption schemes and absorption by nonraining clouds do not affect this result. Even for sparse vegetation (vegetation water content of 0.33 kg m−2), the effect on soil emissivity retrieval is significant. Because of the lack of appropriate data for vegetation cover and single scattering albedo, the effects of the vegetation had to be estimated. Within a reasonable parameter range they were comparable to the effects caused by soil moisture changes. To quantify the effect of surface emissivity changes on integrated water vapor retrieval, brightness temperatures were modeled using actual soil and atmospheric parameters. The radiative transfer equation was then inverted with respect to the atmospheric contribution using an average value for the surface emissivity. An uncertainty of 5% in volumetric soil moisture caused an error of 30 kg m−2 in integrated water vapor.

Corresponding author’s address: Dr. Matthias Drusch, Meteorologisches Institut, Universität Bonn, Auf dem Hügel 20, 53121 Bonn, Germany.

Email: mdrusch@uni-bonn.de

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  • Brunfelt, D. R., and F. T. Ulaby, 1984: Measured microwave emission and scattering in vegetation canopies. IEEE Trans. Geosci. Remote Sens.,22, 520–524.

    • Crossref
    • Export Citation
  • Choudhury, B. J., 1993: Reflectivities of selected land-surface types at 19 and 37 GHz from SSM/I observations. Remote Sens. Environ.,46, 1–17.

    • Crossref
    • Export Citation
  • ——, T. J. Schmugge, A. Chang, and R. W. Newton, 1979: Effect of surface roughness on the microwave emission from soils. J. Geophys. Res.,84, 5699–5706.

    • Crossref
    • Export Citation
  • Deirmendjian, D., 1975: Far-infrared and submillimeter wave attenuation by clouds and rain. J. Appl. Meteor.,14, 1584–1593.

    • Crossref
    • Export Citation
  • Dobson, M. C., F. T. Ulaby, M. T. Hallikainen, and M. A. El-Rayes, 1985: Microwave dielectric behavior of wet soil—part II: Dielectric mixing models. IEEE Trans. Geosci. Remote Sens.,23, 35–46.

    • Crossref
    • Export Citation
  • Drusch, M., 1998: Fernerkundung von Landoberflächen mit multispektralen Satellitendaten (Remote sensing of land surfaces using multispectral satellite data). Ph.D. thesis, Meteorologisches Institut Universität Bonn, 110 pp. [Available from Meteorologishes, Institut Universtät Bonn, Auf dem Hügel 10, 5321 Bonn, Germany.].

  • ——, C. Simmer, and E. F. Wood, 1999a: Up-scaling effects in passive microwave remote sensing: ESTAR 1.4 GHz measurements during SGP ’97. Geophys. Res. Lett.,26, 879–882.

    • Crossref
    • Export Citation
  • ——, R. Lindau, and E. F. Wood, 1999b: The impact of the SSM/I antenna gain function on land surface parameter retrieval. Geophys. Res. Lett.,26, 3481–3484.

    • Crossref
    • Export Citation
  • Ferraro, R. R., N. C. Grody, and G. F. Marks, 1994: Effects of surface conditions on rain identification using the SSM/I. Remote Sens. Environ.,11, 195–209.

    • Crossref
    • Export Citation
  • Greenwald, T. J., C. L. Combs, A. S. Jones, D. L. Randel, and T. H. VonderHaar, 1997: Further developments in estimating cloud liquid water over land using microwave and infrared satellite measurements. J. Appl. Meteor.,36, 389–405.

    • Crossref
    • Export Citation
  • Han, Y., and E. R. Westwater, 1995: Remote sensing of tropospheric water vapor and cloud liquid water by integrated ground-based sensors. J. Atmos. Oceanic Technol.,12, 1050–1059.

    • Crossref
    • Export Citation
  • Heymsfield, G. A., and R. Fulton, 1992: Modulation of SSM/I microwave soil radiances by rainfall. Remote Sens. Environ.,29, 187–202.

    • Crossref
    • Export Citation
  • Hollinger, J. P., R. Lo, G. Poe, R. Savage, and J. Peirce, 1987: Special Sensor Microwave/Imager user’s guide: Technical report. Naval Research Laboratory Tech. Rep., 120 pp. [Available from NRL, Stennis Space Center, MS 39529-5004.].

  • ——, J. L. Peirce, and G. A. Poe, 1990: SSM/I instrument evaluation. IEEE Trans. Geosci. Remote Sens.,28, 781–790.

    • Crossref
    • Export Citation
  • Hsu, A. Y., T. J. Jackson, and P. E. O’Neill, 1999: Comparison of ESTAR and SSM/I derived surface soil moisture. IGARSS ’99, Vol. IV, Hamburg, Germany, IEEE, 1911–1913.

  • Jackson, T. J., 1997: Soil moisture estimation using Special Sensor Microwave/Imager satellite data over a grassland region. Water Resour. Res.,33, 1475–1484.

    • Crossref
    • Export Citation
  • ——, D. M. Le Vine, A. Y. Hsu, A. Oldak, P. J. Starks, C. T. Swift, J. D. Isham, and M. Haken, 1999: Soil moisture mapping at regional scales using microwave radiometry: The Southern Great Plains Hydrology Experiment. IEEE Trans. Geosci. Remote Sens.,37, 2136–2151.

    • Crossref
    • Export Citation
  • Jones, A. S., and T. H. VonderHaar, 1990: Passive microwave remote sensing of cloud liquid water over land regions. J. Geophys. Res.,95, 16 673–16 683.

    • Crossref
    • Export Citation
  • ——, and ——, 1997: Retrieval of microwave surface emittance over land using coincident microwave and infrared satellite measurements. J. Geophys. Res.,102, 13 609–13 626.

  • Joseph, J. H., W. J. Wiscombe, and J. A. Weinman, 1976: The Delta–Eddington approximation for radiative flux transfer. J. Atmos. Sci.,33, 2452–2459.

    • Crossref
    • Export Citation
  • Karstens, U., C. Simmer, and E. Ruprecht, 1994: Remote sensing of cloud liquid water. Meteor. Atmos. Phys.,54, 157–171.

    • Crossref
    • Export Citation
  • Kerr, Y. H., and E. G. Njoku, 1990: A semiempirical model for interpreting microwave emission from semiarid land surfaces as seen from space. IEEE Trans. Geosci. Remote Sens.,28, 384–393.

    • Crossref
    • Export Citation
  • ——, and J. P. Wigneron, 1995: Vegetation models and observations—a review. Passive Microwave Remote Sensing of Land–Atmosphere Interactions, B. J. Choudhury et al., Eds., VSP, 317–344.

    • Crossref
    • Export Citation
  • Kirdyashev, K. P., A. A. Chukhlantsev, and A. M. Shuko, 1979: Microwave radiation of the earth’s surface in the presence of a vegetation cover. Radio Eng. Electron. Phys.,24, 37–44.

  • Liebe, H. J., 1989: MPM—an atmospheric millimeter-wave propagation model. Int. J. Infrared Millimeter Waves,10, 631–650.

  • ——, G. A. Hufford, and M. G. Cotton, 1993: Propagation modeling of moist air and suspended water/ice particles at frequencies below 1000 GHz. AGARD 52d Specialists Meeting of the Electromagnetic Wave Propagation Panel, Palma de Mallorca, Spain, AGARD, 3-1–3-10.

  • Mo, T., B. J. Choudhury, T. J. Schmugge, J. R. Wang, and T. J. Jackson, 1982: A model for microwave emission from vegetation covered fields. J. Geophys. Res.,87, 11 229–11 237.

    • Crossref
    • Export Citation
  • Pampaloni, P., and S. Paloscia, 1986: Microwave emission and plant water content: A comparison between field measurements and theory. IEEE Trans. Geosci. Remote Sens.,24, 900–905.

    • Crossref
    • Export Citation
  • Simmer, C., 1994: Satellitenfernerkundung Hydrologischer Parameter der Atmosphäre mit Mikrowellen (Satellite Remote Sensing of Atmospheric Hydrological Parameters Using Microwaves). Dr. Kovac, 313 pp.

  • Slingo, A., R. Brown, and C. L. Wrench, 1982: A field study of nocturnal stratocumulus III: High resolution radiative and microphysical observations. Quart. J. Roy. Meteor. Soc.,108, 145–165.

    • Crossref
    • Export Citation
  • Tsang, L., J. A. Kong and R. T. Shin, 1985: Theory of Microwave Remote Sensing. John Wiley and Sons, 613 pp.

  • Ulaby, F. T., R. K. Moore, and A. K. Fung, 1981: Microwave Remote Sensing, Active and Passive. Vol. I. Fundamentals and Radiometry. Addison-Wesley, 56 pp.

  • Warner, J., 1955: The water content of cumuliform cloud. Tellus,7, 449–457.

    • Crossref
    • Export Citation
  • ——, and P. Squires, 1957: Liquid water content and the adiabatic model of cumulus clouds. Tellus,10, 390–394.

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