Conference Proceeding

Emissivities of rough surface over layered media in microwave remote sensing of snow

Nat. Central Univ., Chungli
08/2007; DOI:10.1109/IGARSS.2007.4423077 pp.1436 - 1439 In proceeding of: Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Source: IEEE Xplore

ABSTRACT The rough surfaces in Greenland are exhibited as sastrugi. The roughness heights are less than 8 cm for much of the year except in late winter and spring, when they increase to 25 cm or less. Roughness profiles were also related to snow and firn ventilation. WindSat, launched in January 2003, was the first spaceborne polarimetric radiometer to measure all 4 elements of Stokes vector, viz., the vertical polarized brightness temperatures, the horizontal polarized brightness temperatures, and the real and imaginary part of the cross-correlations of the vertical and horizontal polarizations. It was shown by Tsang (1984, 1990) that azimuthal asymmetry will create nonzero third and fourth Stokes parameter in passive microwave remote sensing. Thus the third and fourth Stokes parameters contain information of the azimuthal structure. Usually the third and fourth Stokes parameters are quite small between 0.5 K to 1 K over land and less than plusmn2.5 K over ocean. However, measurements of third and Stokes parameters over Greenland show surprising values of 10 K for the third Stokes parameter and between -10 K and 20 K for the fourth Stokes parameter. In this paper, we use physically based electromagnetic model to study the passive polarimetric remote sensing of snow in Greenland by consider the scattering and emission from a random rough surface over multi-layered media. We consider the random rough surface varied in only one horizontal direction so that azimuthal asymmetry exists in the 3-D problem. Dyadic Green's functions of multilayered medium (Tsang et al., 2000) is used to formulate the surface integral equation so that the polarization dependence of emission and scattering is accounted for systematically. The surface integral equations are solved by using the method of moments in conjunction with fast numerical algorithms such as the multilevel UV method. Numerical results of brightness temperatures are illustrated for all four Stokes parameters to demonstrate the si-
gnatures of sastrugi in passive microwave remote sensing. To account for the large third and fourth Stokes parameters, we also consider the case of anisotropic scatterers in volume scattering. Full multiple volume scattering are studied with numerical solutions of the radiative transfer equations for non-spherical scatterers with preferred orientation.

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    Article: WindSat Passive Microwave Polarimetric Signatures of the Greenland Ice Sheet
    L. Li, P. Gaiser, M.R. Albert, D.G. Long, E.M. Twarog
    [show abstract] [hide abstract]
    ABSTRACT: WindSat has systematically collected the first global fully polarimetric passive microwave data over both land and ocean. As the first spaceborne polarimetric microwave radiometer, it was designed to measure ocean surface wind speed and direction by including the third and fourth Stokes parameters, which are mostly related to the asymmetric structures of the ocean surface roughness. Although designed for wind vector retrieval, WindSat data are also collected over land and ice, and this new data has revealed, for the first time, significant land signals in the third and fourth Stokes parameter channels, particularly over Greenland and the Antarctic ice sheets. The third and fourth Stokes parameters show well-defined large azimuth modulations that appear to be correlated with geophysical variations, particularly snow structure, melting, and metamorphism, and have distinct seasonal variation. The polarimetric signatures are relatively weak in the summer and are strongest around spring. This corresponds well with the formation and erosion of the sastrugi in the dry snow zone and snowmelt in the soaked zone. In this paper, we present the full polarimetric signatures obtained from WindSat over Greenland, and use a simple empirical observation model to quantify the azimuthal variations of the signatures in space and time.
    IEEE Transactions on Geoscience and Remote Sensing 10/2008; · 2.89 Impact Factor
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Keywords

anisotropic scatterers
 
brightness temperatures
 
electromagnetic model
 
fast numerical algorithms
 
firn ventilation
 
first spaceborne polarimetric radiometer
 
four Stokes parameters
 
fourth Stokes parameter
 
Full multiple volume scattering
 
horizontal polarizations
 
horizontal polarized brightness temperatures
 
multilevel UV method
 
non-spherical scatterers
 
numerical solutions
 
preferred orientation
 
roughness heights
 
surface integral equation
 
third Stokes parameter
 
vertical polarized brightness temperatures
 
volume scattering