FIGURE 1

Time series of fall (September-November), winter (December-February), and spring (March-May) days with =7.5 cm of snow cover at Denison, Iowa. Missing years are marked with an X.

lengths by sensors on board geostationary and polar orbiting satellites. Retrieval techniques, the strengths and limitations of each spectral region for sensing snow, and the snow products derived using short-wave and microwave input are discussed in this section. The secular remote sensing of snow over Northern Hemisphere lands will be the principal focus; only a few efforts have addressed this over Southern Hemisphere lands (Dewey and Heim, 1983) or Arctic sea ice (Robinson et al., 1992).

Short-Wave and Microwave Snow Charting

Short-wave data provide continental coverage of snow extent at a relatively high spatial resolution. Snow is identified by recognizing characteristic textured surface features and brightness. Information on surface albedo and percentage of snow coverage (patchiness) is also gleaned from the data. Shortcomings include (1) the inability to detect snow cover when solar illumination is low or when skies are cloudy, (2) the underestimation of cover where dense forests mask the underlying snow, (3) difficulties in distinguishing snow from clouds in mountainous regions and in uniform, lightly vegetated areas that have a high surface brightness when covered with snow, and (4) the lack of all but the most general information on snow depth (Kukla and Robinson, 1979; Dewey and Heim, 1982).

Microwave radiation emitted by the earth's surface penetrates winter clouds, permitting an unobstructed signal from the surface to reach a satellite. The detection of snow cover from microwave data is possible mainly because of differences in emissivity between snow-covered and snow-free surfaces. Estimates of the spatial extent, as well as of the depth or water equivalent, of the snowpack are derived from equations that employ measurements of radiation sensed by multiple channels in the microwave portion of the spectrum (e.g., Kunzi et al., 1982; McFarland et al., 1987). Estimates of snow cover have been made using microwave data since the launch of the Scanning Multichannel Microwave Radiometer (SMMR) in late 1978. The spatial resolution of the data is approximately several tens of kilometers. Since 1987, close to the time of SMMR failure, the Special Sensor Microwave Imager (SSM/I) has provided data. Both sensors, having nearly the same spectral characteristics, have similar levels of success in monitoring snow extent (cf. the SMMR analyses below).

As with short-wave products, the microwave charting of snow extent is not without its limitations. The resolution of the data makes the detailed recognition of snow cover difficult, particularly where snow is patchy, and it is difficult to identify shallow or wet snow using microwaves. Also, the lack of sufficient ground-truth data on snow volume, wetness, and grain size makes an adequate assessment of the reliability of microwave estimates uncertain. The influence of a forest canopy on microwave emissions in snow-



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