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Snow cover is an important climate change variable because of its influence on energy and moisture budgets. Snow cover accounts for the large differences between summer and winter land surface albedo, both annually and inter-annually. Snow may reflect as much as 80 to 90 percent of the incoming solar energy, whereas a snow-free surface such as soil or vegetation may reflect only 10 to 20 percent. A warming trend results in decreased snow cover. With the resulting decrease in reflected energy, absorption of solar radiation increases, adding heat to the system, thereby causing even more snow to melt. This is the classic positive temperature-albedo feedback mechanism, which is a key component in climate models. Surface temperature is highly dependent on the presence or absence of snow cover, and temperature trends have been linked to changes in snow cover (Groisman et al. 1994). In addition to the albedo effect, snow cover represents a significant heat sink during the melt period of the seasonal cycle due to a relatively high latent heat of fusion. As a result, the seasonal snow cover provides a major source of thermal inertia within the total climate system, as it takes in and releases large amounts of energy with little or no fluctuation in temperature. During the past four decades, satellite remote sensing has provided valuable information on hemispheric-scale snow extent. Since 1966, the National Oceanic and Atmospheric Administration (NOAA) has produced weekly snow extent maps for Northern Hemisphere land surfaces using visible-band satellite imagery (Robinson and Frei 2000). Because snow has such a high albedo compared to other surfaces on Earth, snow-covered areas appear much brighter in satellite imagery than most other surface types. Remote sensing data sets from the microwave portion of the electromagnetic spectrum can also be used to derive snow cover maps. When snow covers the ground, some of the microwave energy emitted by the underlying soil is scattered by the snow grains; therefore, when moving from snow-free to snow-covered land surfaces, a sharp decrease in emissivity indicates the presence of dry snow. These remote sensing data sets are derived using different types of analyses and separate regions of the electromagnetic spectrum, yet their results are strikingly similar. Both visible and passive microwave data sets show similar patterns of inter-annual variability, and both consistently indicate maximum snow extent that exceeds 40 million square kilometers for the Northern Hemisphere.
The time series of differences between the snow-covered area for each month in a given year and the long term average for that month (departure from the mean) indicate similar trends in the two data sets.
The 28 year trend in snow extent derived from visible and passive microwave satellite data indicates an annual decrease of approximately 1 to 3 percent per decade with greater deceases of approximately 3 to 5 percent during spring and summer. Precipitation in regions of seasonal snow cover appears to be constant or increasing slightly in some locations over the same time period, which suggests that diminishing snow cover is the result of increasing temperatures. One region where the snow appears to be diminishing rapidly is the Western United States, especially in spring when the duration of snow cover has been decreasing by 2-3 days per decade (see blue-colored areas in the Spring Duration figure). This satellite-derived trend agrees with direct measurement of snow depth and extent on the ground (Mote et al. 2005).
Last updated: 14 May 2008
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