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Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model

View Article: PubMed Central

ABSTRACT

It is important to understand reflective properties of snow, for example for remote sensing applications and for modeling of energy balances in snow packs. We present a method with which we can compare reflectance measurements and calculations for the same snow sample structures. Therefore, we first tomograph snow samples to acquire snow structure images (6 × 2 mm). Second, we calculated the sample reflectance by modeling the radiative transfer, using a beam tracing model. This model calculates the biconical reflectance (BR) derived from an arbitrary number of incident beams. The incident beams represent a diffuse light source. We applied our method to four different snow samples: Fresh snow, metamorphosed snow, depth hoar, and wet snow. The results show that (i) the calculated and measured reflectances agree well and (ii) the model produces different biconical reflectances for different snow types. The ratio of the structure to the wavelength is large. We estimated that the size parameter is larger than 50 in all cases we analyzed. Specific surface area of the snow samples explains most of the difference in radiance, but not the different biconical reflectance distributions. The presented method overcomes the limitations of common radiative transfer models which use idealized grain shapes such as spheres, plates, needles and hexagonal particles. With this method we could improve our understanding for changes in biconical reflectance distribution associated with changes in specific surface area.

No MeSH data available.


Measured (boxplots, showing maxima, minima, and quartiles) and calculated reflectance (circles) plotted against the square root of the effective optical diameter. These results are calculated by taking the radiance at 68° from Fig. 8.
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f9-sensors-08-03482: Measured (boxplots, showing maxima, minima, and quartiles) and calculated reflectance (circles) plotted against the square root of the effective optical diameter. These results are calculated by taking the radiance at 68° from Fig. 8.

Mentions: The calculated reflectance against the effective optical diameter calculated with the relation [37, 6](1)D=6SSAis shown in Figure 9. Here, we compare how well the computed reflectances fit the measured reflectances.


Reflectance Modeling for Real Snow Structures Using a Beam Tracing Model
Measured (boxplots, showing maxima, minima, and quartiles) and calculated reflectance (circles) plotted against the square root of the effective optical diameter. These results are calculated by taking the radiance at 68° from Fig. 8.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3675556&req=5

f9-sensors-08-03482: Measured (boxplots, showing maxima, minima, and quartiles) and calculated reflectance (circles) plotted against the square root of the effective optical diameter. These results are calculated by taking the radiance at 68° from Fig. 8.
Mentions: The calculated reflectance against the effective optical diameter calculated with the relation [37, 6](1)D=6SSAis shown in Figure 9. Here, we compare how well the computed reflectances fit the measured reflectances.

View Article: PubMed Central

ABSTRACT

It is important to understand reflective properties of snow, for example for remote sensing applications and for modeling of energy balances in snow packs. We present a method with which we can compare reflectance measurements and calculations for the same snow sample structures. Therefore, we first tomograph snow samples to acquire snow structure images (6 × 2 mm). Second, we calculated the sample reflectance by modeling the radiative transfer, using a beam tracing model. This model calculates the biconical reflectance (BR) derived from an arbitrary number of incident beams. The incident beams represent a diffuse light source. We applied our method to four different snow samples: Fresh snow, metamorphosed snow, depth hoar, and wet snow. The results show that (i) the calculated and measured reflectances agree well and (ii) the model produces different biconical reflectances for different snow types. The ratio of the structure to the wavelength is large. We estimated that the size parameter is larger than 50 in all cases we analyzed. Specific surface area of the snow samples explains most of the difference in radiance, but not the different biconical reflectance distributions. The presented method overcomes the limitations of common radiative transfer models which use idealized grain shapes such as spheres, plates, needles and hexagonal particles. With this method we could improve our understanding for changes in biconical reflectance distribution associated with changes in specific surface area.

No MeSH data available.