Climatology of snow cover and snow water equivalent

• Chapter II: Physical snow characteristics determined from space
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• Satellite instruments' sensitivity
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• Snow detection in the visible spectrum
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• Snow detection in the infrared spectrum
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• Snow detection in the microwave spectrum
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• Factors which may lead to misidentification of snow

Snow detection in the infrared spectrum

Snow and ice are good reflectors of visible radiation but reflect near-infrared (NIR) poorly. NIR data shows high reflectance for water clouds, medium reflectance for ice clouds, and very low reflectance for snow cover. A comparison of the spectral response patterns of snow and other land cover types reveals that: 1) snow has a higher contrast between the VIS and SWIR spectral regions; 2) snow has relatively higher reflectance in the VIS region compared to that of other land types like water, soil and vegetation; 3) snow, like clouds, has higher reflectance values in VIS, while in the SWIR region it has much lower reflectance. This can be used to differentiate snow from clouds. Thermal infrared data can be used to identify the edges of snow cover. Short-wave and thermal infrared data combined with visible channels are useful for discriminating between clouds and snow (WMO CHy-14, 2012). Stronger absorption by snow and ice at short-wave infrared wavelengths helps to distinguish these features from liquid-phase clouds, but some uncertainty remains between snow on the ground and ice-phase clouds.

Figure 2: Snow cover in the visible and thermal MSG channels (4 February 2014): in the top image in VIS 0.6 μm, in the bottom image in IR 10.6 μm. It is difficult to distinguish snow and clouds in both the visible and infrared spectrum, although a combination of information from VIS and NIR can help (see Chapter 2).