scholarly journals New shortwave infrared albedo measurements for snow specific surface area retrieval

2012 ◽  
Vol 58 (211) ◽  
pp. 941-952 ◽  
Author(s):  
B. Montpetit ◽  
A. Royer ◽  
A. Langlois ◽  
P. Cliche ◽  
A. Roy ◽  
...  
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Near Infrared ◽  
Infrared Camera ◽  
Optical Methods ◽  
Integrating Sphere ◽  
Snow Stratigraphy ◽  
Size Characterization ◽  
Shortwave Infrared

AbstractSnow grain-size characterization, its vertical and temporal evolution is a key parameter for the improvement and validation of snow and radiative transfer models (optical and microwave) as well as for remote-sensing retrieval methods. We describe two optical methods, one active and one passive shortwave infrared, for field determination of the specific surface area (SSA) of snow grains. We present a new shortwave infrared (SWIR) camera approach. This new method is compared with a SWIR laser- based system measuring snow albedo with an integrating sphere (InfraRed Integrating Sphere (IRIS)). Good accuracy (10%) and reproducibility in SSA measurements are obtained using the IRIS system on snow samples having densities greater than 200 kg m-3, validated against X-ray microtomography measurements. The SWIRcam approach shows improved sensitivity to snow SSA when compared to a near-infrared camera, giving a better contrast of the snow stratigraphy in a snow pit.

scholarly journals Measuring specific surface area of snow by near-infrared photography

2006 ◽  
Vol 52 (179) ◽  
pp. 558-564 ◽  
Author(s):  
Margret Matzl ◽  
Martin Schneebeli
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Near Infrared ◽  
Two Dimensions ◽  
Chemical Models ◽  
Snow Stratigraphy ◽  
Physical And Chemical

AbstractThe specific surface area (SSA) is considered an essential microstructural parameter for the characterization of snow. Photography in the near-infrared (NIR) spectrum is sensitive to the SSA. We calculated the snow reflectance from calibrated NIR images of snow-pit walls and measured the SSA of samples obtained at the same locations. This new method is used to map the snow stratigraphy. The correlation between reflectance and SSA was found to be 90%. Calibrated NIR photography allows quantitative determination of SSA and its spatial variation in a snow profile in two dimensions within an uncertainty of 15%. In an image covering 0.5–1.0 m2, even layers of 1mm thickness can be documented and measured. Spatial maps of SSA are an important tool in initializing and validating physical and chemical models of the snowpack.

scholarly journals Measuring the specific surface area of wet snow using 1310 nm reflectance

2014 ◽  
Vol 8 (4) ◽  
pp. 1139-1148 ◽  
Author(s):  
J.-C. Gallet ◽  
F. Domine ◽  
M. Dumont
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Volume Ratio ◽  
Liquid Water Content ◽  
Optical Methods ◽  
Integrating Sphere ◽  
Wet Snow ◽  
The Difference

Abstract. The specific surface area (SSA) of snow can be used as an objective measurement of grain size and is therefore a central variable to describe snow physical properties such as albedo. Snow SSA can now be easily measured in the field using optical methods based on infrared reflectance. However, existing optical methods have only been validated for dry snow. Here we test the possibility to use the DUFISSS instrument, based on the measurement of the 1310 nm reflectance of snow with an integrating sphere, to measure the SSA of wet snow. We perform cold room experiments where we measure the SSA of a wet snow sample, freeze it and measure it again, to quantify the difference in reflectance between frozen and wet snow. We study snow samples in the SSA range 12–37 m2 kg−1 and in the mass liquid water content (LWC) range 5–32%. We conclude that the SSA of wet snow can be obtained from the measurement of its 1310 nm reflectance using three simple steps. In most cases, the SSA thus obtained is less than 10 {%} different from the value that would have been obtained if the sample had been considered dry, so that the three simple steps constitute a minor correction. We also run two optical models to interpret the results, but no model reproduces correctly the water–ice distribution in wet snow, so that their predictions of wet snow reflectance are imperfect. The correction on the determination of wet snow SSA using the DUFISSS instrument gives an overall uncertainty better than 11%, even if the LWC is unknown. If SSA is expressed as a surface to volume ratio (e.g., in mm−1), the uncertainty is then 13% because of additional uncertainties in the determination of the volume of ice and water when the LWC is unknown.

scholarly journals Measuring the specific surface area of wet snow using 1310 nm reflectance

2013 ◽  
Vol 7 (5) ◽  
pp. 5255-5279 ◽  
Author(s):  
J.-C. Gallet ◽  
F. Domine ◽  
M. Dumont
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Liquid Water Content ◽  
Optical Methods ◽  
Integrating Sphere ◽  
Water Ice ◽  
Wet Snow ◽  
The Difference ◽  
A Minor

Abstract. The specific surface area (SSA) of snow can be used as an objective measurement of grain size and is therefore a central variable to describe snow physical properties such as albedo. Snow SSA can now be easily measured in the field using optical methods based on infrared reflectance. However, existing optical methods have only been validated for dry snow. Here we test the possibility to use the DUFISSS instrument, based on the measurement of the 1310 nm reflectance of snow with an integrating sphere, to measure the SSA of wet snow. We perform cold room experiments where we measure the SSA of a wet snow sample, freeze it and measure it again, to quantify the difference in reflectance between frozen and wet snow. We study snow samples in the SSA range 12–37 m2 kg−1 and in the mass liquid water content range 5–32%. We conclude that the SSA of wet snow can be obtained from the measurement of its 1310 nm reflectance using three simple steps. In most cases, the SSA thus obtained is less than 10% different from the value that would have been obtained if the sample had been considered dry, so that the three simple steps constitute a minor correction. We also run two optical models to interpret the results, but no model reproduces correctly the water-ice distribution in wet snow, so that their predictions of wet snow reflectance are imperfect.

scholarly journals Measuring Snow Specific Surface Area with 1.30 and 1.55 μm Bidirectional Reflectance Factors

2018 ◽  
Author(s):  
Adam Schneider ◽  
Mark Flanner ◽  
Roger De Roo
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Near Infrared ◽  
Light Emitting Diodes ◽  
Infrared Light ◽  
Micro Computed Tomography ◽  
Bidirectional Reflectance ◽  
Light Emitting ◽  
New Instrument

Abstract. Snow specific surface area (SSA) is an important physical property that directly affects solar absorption of snow cover. Instrumentation to measure snow SSA is commercially available for purchase, but these instruments are costly and/or remove and destroy snow samples during data collection. To obtain rapid, repeatable, and in situ surface snow SSA measurements, we mounted infrared light emitting diodes and photodiode detectors into a 17 cm diameter black styrene dome. By flashing light emitting diodes and measuring photodiode currents, we obtain accurate 1.30 and 1.55 micron bidirectional reflectance factors (BRFs). We compare measured snow BRFs with X-ray micro computed tomography scans and Monte Carlo photon modeling to relate BRFs to snow SSA. These comparisons show an exponential relationship between snow 1.30 micron BRFs and SSA from which we calculate calibration functions to approximate snow SSA. The techniques developed here enable rapid retrieval of snow SSA by a new instrument called the Near-Infrared Emitting and Reflectance-Monitoring Dome (NERD).

scholarly journals Combining visible near‐infrared spectroscopy and water vapor sorption for soil specific surface area estimation

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Maria Knadel ◽  
Lis Wollesen Jonge ◽  
Markus Tuller ◽  
Hafeez Ur Rehman ◽  
Peter Weber Jensen ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Water Vapor ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Water Vapor Sorption ◽  
Vapor Sorption ◽  
Area Estimation

scholarly journals Estimation of superficial snow specific surface area from spectral albedo time-series at Dome C, Antarctica

2016 ◽  
Author(s):  
G. Picard ◽  
Q. Libois ◽  
L. Arnaud ◽  
G. Vérin ◽  
M. Dumont
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Near Infrared ◽  
Ad Hoc ◽  
Vertical Gradient ◽  
Infrared Range ◽  
Angular Response ◽  
Careful Design ◽  
Better Than

Abstract. Abstract. Spectral albedo of the snow surface in the visible/near-infrared range has been measured for 3 years by an automatic spectral radiometer installed at Dome C (75°S, 123°E) in Antarctica in order to retrieve specific surface area (SSA) of superficial snow. This study focuses on the uncertainties of the SSA retrieval due to the instrument deficiencies and issues related to data processing. We find that when the solar zenith angle is high, the main source of error is the imperfect angular response of the light collectors. This imperfection introduces a small spurious wavelength-dependent trend in the albedo spectra which greatly affects the SSA retrieval. By modeling this effect, we show that for typical snow and illumination conditions encountered at Dome C, retrieving SSA with an accuracy better than 15% (our target), requires the slope of this trend not to exceed 2% between 400 and 1100 nm. Such a small slope can be achieved only by i) careful design of the collectors, ii) an ad hoc correction of the spectra using the actual measured angular response of the collectors, and iii) for solar zenith angles less than 75°. The comparison of the retrieved SSA with independent measurements made with an optical device operating at 1310 nm confirms the presence of a sharp and recurrent vertical gradient of SSA in the uppermost centimeter at Dome C, which challenges the assessment of the absolute accuracy from independent measurements. Nevertheless, with three-fold variations of SSA during the summer seasons, we conclude that the retrieved SSA is accurate enough to provide a detailed picture of the October-March evolution of the surface snow at Dome C.

scholarly journals Vertical profiles of the specific surface area of the snow at Dome C, Antarctica

2010 ◽  
Vol 4 (3) ◽  
pp. 1647-1708 ◽  
Author(s):  
J.-C. Gallet ◽  
F. Domine ◽  
L. Arnaud ◽  
G. Picard ◽  
J. Savarino
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Austral Summer ◽  
Radiative Transfer Model ◽  
Integrating Sphere ◽  
Transfer Model ◽  
Vertical Profiles ◽  
Antarctic Plateau ◽  
The Antarctic

Abstract. The specific surface area (SSA) of snow determines in Part the albedo of snow surfaces and the capacity of the snow to adsorb chemical species and catalyze reactions. Despite these crucial roles, almost no value of snow SSA are available for the largest permanent snow expanse on Earth, the Antarctic. We have measured the first vertical profiles of snow SSA near Dome C (DC: 75°06´ S, 123°20´ E, 3233 m a.s.l.) on the Antarctic plateau, and at seven sites during the logistical traverse between Dome C and the French coastal base Dumont D'Urville (DDU: 66°40´ S, 140°01´ E) during the Austral summer 2008–2009. We used the DUFISSS system, which measures the IR reflectance of snow at 1310 nm with an integrating sphere. At DC, the mean SSA of the snow in the top 1 cm is 38 m2 kg−1, decreasing monotonically to 14 m2 kg−1 at a depth of 15 cm. Along the traverse, the snow SSA profile is similar to that at DC in the first 600 km from DC. Closer to DDU, the SSA of the top 5 cm is 23 m2 kg−1, decreasing to 19 m2 kg−1 at 50 cm depth. This is attributed to wind, which causes a rapid decrease of surface snow SSA, but forms hard windpacks whose SSA decrease more slowly with time. Since light-absorbing impurities are not concentrated enough to affect albedo, the vertical profiles of SSA and density were used to calculate the spectral albedo of the snow for several realistic illumination conditions, using the DISORT radiative transfer model. A preliminary comparison with MODIS data is presented for use in energy balance calculations and for comparison with other satellite retrievals. These calculated albedos are compared to the few existing measurements on the Antarctic plateau. The interest of postulating a submillimetric, high-SSA layer at the snow surface to explain measured albedos is discussed.

scholarly journals Soil Specific Surface Area Determination by Visible Near-Infrared Spectroscopy

2018 ◽  
Vol 82 (5) ◽  
pp. 1046-1056 ◽  
Author(s):  
Maria Knadel ◽  
Emmanuel Arthur ◽  
Peter Weber ◽  
Per Moldrup ◽  
Mogens Humlekrog Greve ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Surface Area Determination ◽  
Area Determination

scholarly journals Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model

2013 ◽  
Vol 7 (2) ◽  
pp. 741-761 ◽  
Author(s):  
A. Mary ◽  
M. Dumont ◽  
J.-P. Dedieu ◽  
Y. Durand ◽  
P. Sirguey ◽  
...  
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Near Infrared ◽  
Winter Season ◽  
Added Value ◽  
Mountainous Terrain ◽  
Multiple Reflections ◽  
Topographic Correction ◽  
Wide Range

Abstract. This study compares different methods to retrieve the specific surface area (SSA) of snow from satellite radiance measurements in mountainous terrain. It aims at addressing the effect on the retrieval of topographic corrections of reflectance, namely slope and aspect of terrain, multiple reflections on neighbouring slopes and accounting (or not) for the anisotropy of snow reflectance. Using MODerate resolution Imaging Spectrometer (MODIS) data for six different clear sky scenes spanning a wide range of snow conditions during the winter season 2008–2009 over a domain of 46 × 50 km in the French Alps, we compared SSA retrievals with and without topographic correction, with a spherical or non-spherical snow reflectance model and, in spherical case, with or without anisotropy corrections. The retrieved SSA values were compared to field measurements and to the results of the detailed snowpack model Crocus, fed by driving data from the SAFRAN meteorological analysis. It was found that the difference in terms of surface SSA between retrieved values and SAFRAN-Crocus output was minimal when the topographic correction was taken into account, when using a retrieval method assuming disconnected spherical snow grains. In this case, the root mean square deviation was 9.4 m2 kg−1 and the mean difference was 0.1 m2 kg−1, based on 3170 pairs of observation and simulated values. The added-value of the anisotropy correction was not significant in our case, which may be explained by the presence of mixed pixels and surface roughness. MODIS retrieved data show SSA variations with elevation and aspect which are physically consistent and in good agreement with SAFRAN-Crocus outputs. The variability of the MODIS retrieved SSA within the topographic classes of the model was found to be relatively small (3.9 m2 kg−1). This indicates that semi-distributed snowpack simulations in mountainous terrain with a sufficiently large number of classes provides a representation of the snowpack variability consistent with the scale of MODIS 500 m pixels.

Sign in / Sign up

Export Citation Format

Share Document