Analysing snow from space
Snow is an important yet complicated form of precipitation that forms part of the Earth's hydrologic cycle. The problem derives from the time lag between when snow falls to when it actually melts, produces runoff and reintroduces liquid water into the cycle. Packed snow can remain frozen for varying periods of time, from days to years to decades (e.g. glaciers). Understanding the extent of snow coverage (snow covered area or SCA) and the amount of water contained within the snow (snow water equivalent or SWE) can assist the proper planning and use of water resources dependent on snowmelt for replenishment. Areas of snow, particularly in the winter months, can extend up to hundreds of kilometres. Therefore it is not possible, either in terms of cost or time, to measure SCA, SWE and other snow characteristics from the ground. Fortunately, snow is sensitive to several bands in the electromagnetic spectrum, particularly the microwave portion of the spectrum, and thus a fine candidate for remote sensing. Active microwave remote sensing works by emitting microwaves and measuring the magnitude of the return signal received after the microwaves bounce off the Earth's surface. Synthetic Aperture Radar (SAR) is the most common form of active microwave remote sensing, but it requires rigorous data processing techniques. SAR equipment can be positioned on an airplane or an earth-orbiting satellite. Scientists from some of Northern Europe's finest research institutes have discovered new methods to derive SCA and SWE from SAR data. The team developed novel algorithms to interpret the data collected by SAR, allowing them to create Digital Elevation Models (DEMs) of SCA, even in highly mountainous regions. The group is seeking support to fund the additional research necessary to refine the SWE algorithm. DEMs of SCA, SWE and other snow parameters will support future water planning efforts, particularly in regions of Europe dependent on snowmelt as a source of water.
