Conical electromagnetic waves diffraction from sastrugi type surfaces of layered snow dunes on Greenland ice sheets in passive microwave remote sensing

Chang, Wenmo; Tsang, Leung

doi:10.1109/igarss.2011.6048913

Cited by 5 publications

(6 citation statements)

References 7 publications

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“…The roughness of this interface due to ripples, sastrugi and other dunes (Watanabe, 1978) may contribute especially at horizontal polarization and grazing incidence angles (Lacroix et al, 2009), but the existing formulations of the bi-static reflection coefficient are based on the method of moments and are therefore computationally intensive and limited to low frequencies (<18 GHz; Liang et al, 2009;Chang and Tsang, 2011). For flat interfaces, the reflection coefficient only depends on the zenith angle and the refractive indexes of both sides of the interface.…”

Section: Properties Of the Interfacesmentioning

confidence: 99%

“…Once the extinction and scattering coefficients of every layer and the reflection coefficients at all the interfaces are known, the radiative transfer equation is solved using the DISORT method (Chandrasekhar, 1960). This method takes into account multiple scattering within and between the layers, which is an asset with respect to the iterative method (Tsang et al, 1985;Jin, 1994;Ishimaru, 1997) for which the number of calculated order of scattering is limited.…”

Section: Solution Of the Radiative Transfer Equation Using The Disortmentioning

confidence: 99%

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Simulation of the microwave emission of multi-layered snowpacks using the Dense Media Radiative transfer theory: the DMRT-ML model

et al. 2013

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Abstract. DMRT-ML is a physically based numerical model designed to compute the thermal microwave emission of a given snowpack. Its main application is the simulation of brightness temperatures at frequencies in the range 1-200 GHz similar to those acquired routinely by spacebased microwave radiometers. The model is based on the Dense Media Radiative Transfer (DMRT) theory for the computation of the snow scattering and extinction coefficients and on the Discrete Ordinate Method (DISORT) to numerically solve the radiative transfer equation. The snowpack is modeled as a stack of multiple horizontal snow layers and an optional underlying interface representing the soil or the bottom ice. The model handles both dry and wet snow conditions. Such a general design allows the model to account for a wide range of snow conditions. Hitherto, the model has been used to simulate the thermal emission of the deep firn on ice sheets, shallow snowpacks overlying soil in Arctic and Alpine regions, and overlying ice on the large icesheet margins and glaciers. DMRT-ML has thus been validated in three very different conditions: Antarctica, Barnes Ice Cap (Canada) and Canadian tundra. It has been recently used in conjunction with inverse methods to retrieve snow grain size from remote sensing data. The model is written in Fortran90 and available to the snow remote sensing community as an open-source software. A convenient user interface is provided in Python.

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Section: Properties Of the Interfacesmentioning

confidence: 99%

Section: Solution Of the Radiative Transfer Equation Using The Disortmentioning

confidence: 99%

Simulation of the microwave emission of multi-layered snowpacks using the Dense Media Radiative transfer theory: the DMRT-ML model

et al. 2013

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“…Little is known, in general, on the impact of sastrugi on the passive microwave signal. Several mechanisms may be significant according to Liang et al (2009) and Chang and Tsang (2011) local slope of the surface and total reflections of emerging radiation, or an indirect effect involving the internal structure of the snowpack (Liang et al, 2009). These mechanisms would be more efficient at grazing angles, which corresponds with the discrepancy in Fig.…”

Section: Relationship Between Brightness Temperature and Snow Propertiesmentioning

confidence: 99%

Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica

et al. 2014

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Abstract. Space-borne passive microwave radiometers are widely used to retrieve information in snowy regions by exploiting the high sensitivity of microwave emission to snow properties. For the Antarctic Plateau, many studies presenting retrieval algorithms or numerical simulations have assumed, explicitly or not, that the subpixel-scale heterogeneity is negligible and that the retrieved properties were representative of whole pixels. In this paper, we investigate the spatial variations of brightness temperature over a range of a few kilometers in the Dome C area. Using ground-based radiometers towed by a vehicle, we collected brightness temperature at 11, 19 and 37 GHz at horizontal and vertical polarizations along transects with meter resolution. The most remarkable observation was a series of regular undulations of the signal with a significant amplitude reaching 10 K at 37 GHz and a quasi-period of 30-50 m. In contrast, the variability at longer length scales seemed to be weak in the investigated area, and the mean brightness temperature was close to SSM/I and WindSat satellite observations for all the frequencies and polarizations. To establish a link between the snow characteristics and the microwave emission undulations, we collected detailed snow grain size and density profiles at two points where opposite extrema of brightness temperature were observed. Numerical simulations with the DMRT-ML microwave emission model revealed that the difference in density in the upper first meter explained most of the brightness temperature variations. In addition, we found that these variations of density near the surface were linked to snow hardness. Patches of hard snow -probably formed by wind compaction -were clearly visible and covered as much as 39 % of the investigated area. Their brightness temperature was higher than in normal areas. This result implies that the microwave emission measured by satellites over Dome C is more complex than expected and very likely depends on the year-to-year areal proportion of the two different types of snow.

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“…For the interfaces within the snowpack and at the airsnow interface, DMRT-ML considers smooth interfaces. The roughness of this interface due to ripples, sastrugi and other dunes (Watanabe, 1978) may contribute especially at horizontal polarization and grazing incidence angles (Lacroix et al, 2009), but the existing formulations of the bi-static reflection coefficient are based on the method of moments and are therefore computationally intensive and limited to low frequencies (<18 GHz; Liang et al, 2009;Chang and Tsang, 2011). For flat interfaces, the reflection coefficient only depends on the zenith angle and the refractive indexes of both sides of the interface.…”

Section: Properties Of the Interfacesmentioning

confidence: 99%

Simulation of the microwave emission of multi-layered snowpacks using the dense media radiative transfer theory: the DMRT-ML model

Picard¹,

Brucker²,

Roy³

et al. 2012

Preprint

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DMRT-ML is a physically-based numerical model designed to compute the thermal microwave emission of a given snowpack. Its main application is the simulation of brightness temperatures at frequencies in the range 1–200 GHz similar to those acquired routinely by space-based microwave radiometers. The model is based on the Dense Media Radiative Transfer (DMRT) theory for the computation of the snow scattering and extinction coefficients and on the Discrete Ordinate Method (DISORT) to numerically solve the radiative transfer equation. The snowpack is modeled as a stack of multiple horizontal snow layers and an optional underlying interface representing the soil or the bottom ice. The model handles both dry and wet snow conditions. Such a general design allows the user to account for a wide range of snow conditions. Hitherto, the model has been used to simulate the thermal emission of the deep firn on ice sheets, shallow snowpacks overlying soil in Arctic and Alpine regions, and overlying ice on the large ice-sheet margins and glaciers. DMRT-ML has thus been validated in three very different conditions: Antarctica, Barnes Ice Cap (Canada) and Canadian tundra. It has been recently used in conjunction with inverse methods to retrieve snow grain size from remote sensing data. The model is written in Fortran90 and available to the snow remote sensing community as an open-source software

show abstract

Conical electromagnetic waves diffraction from sastrugi type surfaces of layered snow dunes on Greenland ice sheets in passive microwave remote sensing

Cited by 5 publications

References 7 publications

Simulation of the microwave emission of multi-layered snowpacks using the Dense Media Radiative transfer theory: the DMRT-ML model

Simulation of the microwave emission of multi-layered snowpacks using the Dense Media Radiative transfer theory: the DMRT-ML model

Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica

Simulation of the microwave emission of multi-layered snowpacks using the dense media radiative transfer theory: the DMRT-ML model

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