Snow tartes webapp

Snow TARTES

Online computation of snow albedo using the two-stream and asymptotic radiative transfer theory

Snowpack layers ?

The properties of each layer in the snowpack is given as a space or comma separated table. The rows define the layers from top to bottom. The columns meaning can be chosen using the "Columns" selector. 3 or 4 columns are required to define a layer depending on this choice. The value of the cells is usually a number but one (or a few cells) can be given as a range using the syntax (start:end:step). In this case, curves are plotted for each value in the range. Multiple ranges are combined but a maximum of 10 curves is plotted for performance and clarity reasons.

Grain shape ?

Snow is represented in TARTES by a collection of identical particles with a given shape. In the two-stream and asymptotic approximation theory, shape is prescribed through the asymmetry factor g and absorption enhancement parameter B. Libois et al. 2013 give details on the theory and provide B, g values for several shapes. They are available here.

Substrate albedo ?

Spectral albedo of the lowest interface. To plot this alebdo, remove any layer from the snowpack or set the thickness to 0.

Diffuse ?

If checked the incoming radiation is 100% diffuse. In TARTES this is approximated by the computation with a direct beam at 53° incidence angle.

Incidence angle (°) ?

Zenith incidence angle (in degrees with respect to the vertical) of the direct beam when "diffuse" is unchecked. Can be specified as a number or a range (start:end:step) to plot several curves.

Ice absorption spectrum ?

The ice absorption coefficient spectrum is not well known in the range 400-600nm where the ice is highly transparent. Different formulations are proposed, Picard et al. 2016 is intermediate between Warren 1984 (high absorption) and Warren and Brandt 2008 (low absorption). The effect on albedo is small and most visible for snow without impurities.

Wavelength range (nm) ?

The computation is performed for the given wavelength range and resolution specified as start:end:step. For instance 300:2500:10 computes the albedo from 300nm to 2500nm by 10nm steps.

Snow TARTES is an educational and research purpose web application to compute the reflection (albedo) from multi-layered snowpack.

Getting started

First specify the properties of each layer of the snowpack: layer thickness, snow density and snow grain optical diameter (or SSA) are the three compulsary parameters. Soot can also be added. Then select the shape of the grains and if the illumination is diffuse or direct beam. In the latter case, setting the angle of incidence is compulsary. Soil, grass or ice can be also selected for the bottom interface but this only impacts albedo for ~10 cm of snow or less. Several ice absorption spectra are available, the effect on albedo is weak in the visible (400-600 nm) and near infrared (1550-1910 nm), null elsewhere. Press "Compute!" to plot the spectral albedo, or "Download data" to get the data in csv format. For all numerical parameters, instead of using a single number, it is possible to use a range with the syntax: (start:end:step), which plots several curves. It is also possible to select a group of shapes or all bottom interface spectrum to explore the sensitivity to these parameters.

How does this work ?

The Two-streAm Radiative TransfEr in Snow (TARTES) model performs the calculation. This model uses the asymptotic approximation of the radiative transfer theory (AART) detailled in Kokhanovsky and Zege, (2004) to compute the optical properties in each layer from the snow properties. The albedo is then calculated for the entire snowpack using the two-stream approximation. Detailled equations can be found in Libois et al. 2013. TARTES is implemented in Python and is open-source. Installation and documentation are available from TARTES web site. TARTES is easy to use and can do more than the webapp, give it a try if the webapp appears to be limited.

About

This webapp was implemented by Ghislain Picard using: TARTES python package, Flask and Bootstrap web framework, Bokeh plotting library and ASTER spectra (reproduced from the ASTER Spectral Library through the courtesy of the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California. Copyright © 1999, California Institute of Technology. ALL RIGHTS RESERVED).

References

Q. Libois, G. Picard, J. France, L. Arnaud, M. Dumont , C. Carmagnola , and M. D. King, Influence of grain shape on light penetration in snow, The Cryosphere, 7, 1803-1818, 2013, doi:10.5194/tc-7-1803-2013
Kokhanovsky, A. A., and Zege, E. P. (2004). Scattering optics of snow. Applied Optics, 43(7), 1589-1602, doi: 10.1364/AO.43.001589
Baldridge, A. M., S.J. Hook, C.I. Grove and G. Rivera, 2009.. The ASTER Spectral Library Version 2.0. Remote Sensing of Environment, vol 113, pp. 711-715, doi:10.1016/j.rse.2008.11.007
G. Picard, Libois, Q., and Arnaud, L., (2016) Refinement of the ice absorption spectrum in the visible using radiance profile measurements in Antarctic snow, The Cryosphere Discussion, doi:10.5194/tc-2016-146, in review
Warren, S. G., and R. E. Brandt (2008), Optical constants of ice from the ultraviolet to the microwave: A revised compilation. J. Geophys. Res., 113, D14220, doi:10.1029/2007JD009744
Warren, S. G. (1984) Optical constants of ice from the ultraviolet to the microwave, Applied Optics, 23, 8, 1206-1225, doi: 10.1364/AO.23.001206