There are compelling reasons for collecting accurate information on snowfall. First, accurate precipitation data (adjusted for systematic errors) are essential to balance the energy and water cycle in the climate system, for climate monitoring, for determining the global and regional hydrological balance, and for understanding key components of the cryosphere such as the snow-covered area, snow water equivalent, and glacier mass balance. Precipitation is expected to increase in response to global warming (IPCC, 1996) and there is evidence (Bradley et al., 1987; Vin-nikov et al., 1990; Groisman and Easterling, 1994; Mekis and Hogg, 1999) that precipitation has exhibited an upward trend during the twentieth century. Warming is also likely to result in changes in the solid-liquid fraction of precipitation in shoulder seasons. Accurate information on precipitation intensity, timing, and the solid/liquid fraction are also needed to correctly simulate snowpack development and snowmelt.
Snowfall, however, is notoriously difficult to observe accurately. Before elaborating on some of these difficulties, it is important to make clear the distinction between snowfall and snowfall precipitation (or solid precipitation). Snowfall is the depth of freshly fallen snow that accumulates on a snow board (Fig. 5.1b) during the observing period and has been traditionally measured with a ruler. Snowfall precipitation is the amount of liquid water in the snowfall intercepted by a precipitation gauge. At climate stations the depth of new snowfall is measured once or twice per day using a ruler and snow board (Fig. 5.1b). In many countries, snowfall precipitation is estimated from daily total snowfall assuming a fresh snowfall density of 100 kgm-3. However, the density of freshly fallen snow varies widely as snowfall density is a function of air temperature and crystal type (Judson and Doesken, 2000). Values can range from 10-30 kgm-3 for dry, cold "wild snow" (Seligman, 1980) to more than 150 kg m-3 for warm, wet snow. Most fresh snowfall densities fall within a range of 30-150 kg m-3 (Pomeroy and Gray, 1995; Judson and Doesken, 2000). Manual ruler observations of snowfall are subject to numerous sources of error; the most important are the blowing and drifting of snow, and the melting or rapid settling of snow when it reaches the ground. Therefore, new snow density also depends strongly on the length of the observation period (1 h, 24 h etc.). For example, Goodison et al.(1981) monitored average density increases between 8 and 13 kg m-3 h-1 during snow storms with a duration of less than 12 h. Doesken and Judson (1997) provide a good overview of some of the practical problems associated with observing snowfall.
Snowfall precipitation is measured using a snowfall gauge; gauges can range from a standard rain gauge to a specially shielded snowfall gauge. A fundamental problem of gauge measurement of snowfall is that most precipitation gauges catch less snowfall than the "true" amount because accelerated wind flow over the top of the gauge reduces the number of snowflakes able to enter the orifice. In alpine regions, catch efficiency is at most 80% with shielded devices placed 1.5 m above the snow surface (Fohn, 1985). The under-catch effect increases with wind strength, and for a relatively modest wind speed of 15 km hr-1, an unshielded US standard 8 inch precipitation gauge is estimated to catch only ~50% of the "true" snowfall (Yang et al., 1998). This effect can be reduced by using shielding devices such as the Alter shield shown in Figure 5.1e, which will increase the catch by 20-70% (Yang et al., 1999). However, this obviously creates a discontinuity in precipitation time series that must be corrected if the data are to be used in climate change studies (Yang et al., 1999). Precipitation gauges, shields, and observing practices vary considerably from country to country, and over time, e.g. USSR (Groisman et al., 1991), U.S.A. (Groisman and Easterling, 1994), and Canada
(Metcalfe et al., 1997). Other important systematic sources of error include instrument siting, trace precipitation amounts, and wetting loss (the amount of water sticking to the side of a gauge each time it is emptied). Metcalfe and Goodison (1993) showed that when trace precipitation amounts were adjusted for wetting loss, they could account for a significant increase in corrected precipitation totals (~30% for a prairie site). This correction is particularly important in the Arctic where some stations report over 80% of precipitation observations as trace amounts (Metcalfe and Goodison, 1993).
Correction of these systematic sources of error is required to obtain unbiased, homogeneous estimates of snowfall precipitation. The World Meteorological Organization recognized this problem in 1985 when it initiated a gauge intercomparison project to document sources of systematic error in the various national systems for precipitation measurement (Goodison et al., 1998b). The recent trend toward increased automation of climate observations also has important consequences for the homogeneity of precipitation measurement series. Goodison et al. (1998b) concluded that heated tipping bucket rain gauges were not recommended for winter use due to excessive evaporation loss. Weighing gauges were found to be the most practical but these can introduce a "timing" error due to snow or freezing precipitation sticking to the inside of the gauge and melting at some later time. Automated gauges can also catch blowing snow and provide no information on the liquid/solid fraction of precipitation. These problems complicate the real-time interpretation of the data as well as the application of procedures to adjust for systematic errors.
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