Effects of snow physical parameters on spectral albedo and bidirectional reflectance of snow surface

Aoki, Teruo; Aoki, Tadao; Fukabori, Masashi; Hachikubo, Akihiro; Tachibana, Yukio; Nishio, Fumihiko

doi:10.1029/1999jd901122

Cited by 271 publications

(312 citation statements)

References 36 publications

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“…Snow grain size has long been used as a substitute for SSA (Gow, 1969), but given the variety of grain shapes, from dendritic to rounded to hollow, the definition of grain size is ambiguous and observer-dependent (Aoki et al, 2000). With the example of hollow depth hoar crystals, Taillandier et al (2007) have shown that effective grain size deduced from SSA (Eq.…”

Section: Introductionmentioning

confidence: 99%

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

et al. 2009

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Abstract. Even though the specific surface area (SSA) and the snow area index (SAI) of snow are crucial variables to determine the chemical and climatic impact of the snow cover, few data are available on the subject. We propose here a novel method to measure snow SSA and SAI. It is based on the measurement of the hemispherical infrared reflectance of snow samples using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement). DUFISSS uses the 1310 or 1550 nm radiation of laser diodes, an integrating sphere 15 cm in diameter, and InGaAs photodiodes. For SSA<60 m 2 kg −1 , we use the 1310 nm radiation, reflectance is between 15 and 50% and the accuracy of SSA determination is 10%. For SSA>60 m 2 kg −1 , snow is usually of low density (typically 30 to 100 kg m −3 ), resulting in insufficient optical depth and 1310 nm radiation reaches the bottom of the sample, causing artifacts. The 1550 nm radiation is therefore used for SSA>60 m 2 kg −1 . Reflectance is then in the range 5 to 12% and the accuracy on SSA is 12%. We propose empirical equations to determine SSA from reflectance at both wavelengths, with that for 1310 nm taking into account the snow density. DUFISSS has been used to measure the SSA of snow and the SAI of snowpacks in polar and Alpine regions.

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Section: Introductionmentioning

confidence: 99%

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

et al. 2009

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“…The grain diameter is not unequivocally defined in the literature, which is understandable since the definition of snow grain itself is often ambiguous. There is a consensus for expressing grain effective diameter as proportional to the ratio of crystal volume to projected area, but the value of the multiplier can vary according to the specific choice of the author Kokhanovsky and Zege, 2004;Aoki et al, 2000). In line with several recent publications (see, for example, Zege et al, 2011;Jin et al, 2008), we define it as 3/2 times the ratio of the crystal volume over its surface area, as outlined in Appendix A, which includes the details of the relationship to geometric size.…”

Section: Methodsmentioning

confidence: 91%

“…For the retrieval of crystal habit, the polarized reflectance at 864 nm is used because of the very weak ice absorption at this wavelength and the relatively weak Rayleigh scattering contribution. Ice crystals are found to vary within a virtually countless set of shapes, but, limited by the lack of constraints on the correct optical properties, very few studies have departed from the common practice of assuming spherical shapes for the snow grains, an approximation which can negatively impact the quality of the albedo products (Tedesco and Kokhanovsky, 2007;Aoki et al, 2000). Among the available optical models for non-spherical grains are for example those of Baum et al (2011Baum et al ( , 2014 and Yang et al (2013).…”

Section: Methodsmentioning

confidence: 99%

Photopolarimetric retrievals of snow properties

2015

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Abstract. Polarimetric observations of snow surfaces, obtained in the 410-2264 nm range with the Research Scanning Polarimeter onboard the NASA ER-2 high-altitude aircraft, are analyzed and presented. These novel measurements are of interest to the remote sensing community because the overwhelming brightness of snow plagues aerosol and cloud retrievals based on airborne and spaceborne total reflection measurements. The spectral signatures of the polarized reflectance of snow are therefore worthwhile investigating in order to provide guidance for the adaptation of algorithms currently employed for the retrieval of aerosol properties over soil and vegetated surfaces. At the same time, the increased information content of polarimetric measurements allows for a meaningful characterization of the snow medium. In our case, the grains are modeled as hexagonal prisms of variable aspect ratios and microscale roughness, yielding retrievals of the grains' scattering asymmetry parameter, shape and size. The results agree with our previous findings based on a more limited data set, with the majority of retrievals leading to moderately rough crystals of extreme aspect ratios, for each scene corresponding to a single value of the asymmetry parameter.

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“…Hence, precise estimation of the radiation budget is necessary for detecting such drastic environmental changes in the cryosphere, quantifying the areas and volume of melting ice, and understanding the effects of ice-albedo feedback mechanisms. The relationships between shortwave albedo and snow physical parameters such as snow grain size and impurities have been studied frequently (Aoki et al, 2000;Stamnes et al, 2007;Aoki, et al, 2007;Hori et al, 2007;Painter et al, 2009;Kuchiki et al, 2009). On the contrary, longwave emission from snow cover is usually considered to exhibit blackbody-like behavior, and the dependences of emissivity on snow type are usually ignored in remote sensing applications.…”

Section: Introductionmentioning

confidence: 99%

Dependence of thermal infrared emissive behaviors of snow cover on the surface snow type

Hori

Aoki²,

Tanikawa

et al. 2014

Bulletin of Glacier Research

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The potential of the thermal infrared (TIR) remote sensing for discriminating surface snow types was examined by analyzing TIR radiances acquired from space over the Greenland ice sheet. The brightness temperature difference (BTD) between TIR wavelengths of 11 and 12 m was found to increase in accordance with in situ observed evolutions of surface snow type. Spatial and temporal distributions of BTD over the entire ice sheet indicated that BTD has a sensitivity of about 1.2 K for variations of the possible snow types. The observed behaviors of BTD were coincident with those predicted by a radiative transfer calculation using previous in situ measured snow emissivities, although some biases on the order of 0.1-0.3 K remain. The dependence of BTD on the surface snow type was also consistent with the behaviors of snow reflectance at the shortwave infrared (SWIR) wavelength 1.6 m, which is a measure of snow grain size, except for the case of melting wet snow. The inconsistency in the wet snow case was considered to be due to the different optical responses of the TIR and SWIR signals to wet snow, which suggested the possibility of using TIR signals to discriminate wet/dry conditions of snow cover in an old stage. As a result, it is determined that TIR remote sensing has potential not only as an approach supplementary to the SWIR method for assessing surface snow types in daytime but also as the only method for simultaneous retrieval of snow type and surface temperature in nighttime.

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Effects of snow physical parameters on spectral albedo and bidirectional reflectance of snow surface

Cited by 271 publications

References 36 publications

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

Photopolarimetric retrievals of snow properties

Dependence of thermal infrared emissive behaviors of snow cover on the surface snow type

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