Long-term snow distribution observations in a mountain catchment: Assessing variability, time stability, and the representativeness of an index site

Abstract

1] This study presents an analysis of snow distribution heterogeneity and the factors affecting this variability. The analysis focuses on manually sampled data from 21 snow surveys covering 11 years at the drift-dominated Reynolds Mountain East catchment (0.36 km 2 ) in southwestern Idaho, USA. Surveys were conducted midwinter and in early spring. Interseason and intraseason trends were examined along with the time stability of distributions, goodness-of-fit to theoretical distributions, and the representativeness of an index site as a measure of basin-wide snow water equivalent. The average snow depth coefficient of variation (CV) over the entire time period was 0.71, which is in accordance with broad regional assessments. Higher wind speeds during snow events and increased melt led to increased heterogeneity and higher CVs. Forested sites produced lower CVs presumably due to moderated winds at these sites. Consistent wind directions produced accumulation patterns that were very stable from year-to-year. Many previous studies have suggested that vital subgrid snow heterogeneity in large-scale models can be approximated with parametric distributions. Gamma distributions were preferred over lognormal distributions in describing the overall distribution while in tree-covered regions with less variability there was little difference between the two. It was also found that an index site, akin to the majority of North American mountain weather observation stations, provided a reasonable approximation of catchment-averaged SWE in most years. However, the reliability of this measure decreased in years that deviated from normal patterns.Citation: Winstral, A., and D. Marks (2014), Long-term snow distribution observations in a mountain catchment: Assessing variability, time stability, and the representativeness of an index site, Water Resour. Res., 50, 293-305,

Topographic control of snowpack distribution in a small catchment in the central Spanish Pyrenees: intra- and inter-annual persistence

“…Also we have shown that its effect evolved during the snow accumulation and melting periods over two years having highly contrasting climatic conditions and snow accumulation amounts Many studies have analyzed the spatial distribution of SD in mountain areas considering both, intra-and inter-annual variability of the topographic control on the snowpack distribution (Anderton et al, 2004;Erickson et al, 2005;López-Moreno et al, 2010;McCreight et al, 2014). Other researches have also focused their attention in long-term interannual snow distribution analyses (Jepsen et al, 2012;Sturm and Wagner, 2010;Winstral and Marks, 2014). The results of these previous works have highlighted the difficulties in fully explaining the distribution of snow in complex mountainous terrain.…”

Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements

“…Even though depths can vary greatly over space in a snow pack, the overall distribution of snow has been found to exhibit spatial similarities from year to year (Hiemstra et al, 2006;Sturm and Wagner, 2010;Winstral and Marks, 2014). Repeated lidar surveys throughout single seasons and over multiple seasons (Deems et al, 2008) have found similar results through fractal analyses of the snow depth distributions.…”

31 years of hourly spatially distributed air temperature, humidity, and precipitation amount and phase from Reynolds Critical Zone Observatory

“…Precipitation station data were included based on (1) the degree of wind sheltering due to topography and vegetation and (2) the spatial arrangement of measurement locations. Wind-sheltered precipitation gauges were preferentially used over wind exposed sites following Winstral et al (2013) and Winstral and Marks (2014). However, some exposed precipitation stations were used because they were the only ones representing large portions of RCEW (e.g., 057, 049, and 127).…”