Snowfall interception on branches of three conifer species

Abstract

Measuring the mass of snow on cut branch tips soon after snowfalls during two winters provided comparisons of catch by Engelmann spruce (Piceaengelmannii Parry), subalpine fir (Abieslasiocarpa (Hook.) Nutt.), and lodgepole pine (Pinuscontorta var. latifolia Engelm.). Analysis of these and other reported measurements confirmed (i) snow bridging by cohesion, (ii) bouncing of snow crystals by elastic rebound, and (iii) branch bending as mechanisms that determine the sigmoidal growth curves characterizing snow interception relative to snowfall. The fraction of snowfall intercepted by the branches was largest when storm accumulations were 3–4 mm water equivalent, with low specific gravity (0.04–0.07). Percent catch in snowfalls with 10 mm water and low specific gravity was near 50% for Engelmann spruce and about 45% for subalpine fir and lodgepole pine, but values decreased to near 30% in 20-mm storms. Catch was inversely proportional to the density of snow accumulations in the specific gravity range 0.04–0.13. Average branch catch was only about 10% of a storm with 10 mm water equivalent at 0.13 specific gravity. Meteorological conditions were more important than branch growth form in determining snow interception amounts on the conifers tested. The results suggest, as a hypothesis, a computational function for the fraction of snowfall caught on conifer crowns.

Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data

“…Under-canopy snow distribution is governed by multiple factors that affect the energy environment, as observed by melting (Essery et al, 2008;Gelfan et al, 2004) and accumulation rates Schmidt and Gluns, 1991;Teti, 2003). Our results show different responses when comparing the snow-depth difference between open and canopycovered areas between study sites (Fig.…”

“…The interactions between topographic variables and vegetation are most likely attributable to the under-canopy snowpack being less sensitive to solar radiation versus snowpack in the open area (Courbaud et al, 2003;Dubayah, 1994;Essery et al, 2008;Musselman et al, 2008Musselman et al, , 2012. In spite of filtering the topographic effect, there is still about a 20 cm magnitude of fluctuation in the snow-depth difference, which might be attributed to various clearing sizes of open area at different locations and various vegetation types in forests Pomeroy et al, 2002;Schmidt and Gluns, 1991); however, we were not able to explore these features of the sites from the current lidar data set. …”

Modified snow algorithms in the Canadian land surface scheme: Model runs and sensitivity analysis at three boreal forest stands

“…For T a ≤ 0°C, C3.1 uses a variation with air temperature (Fig. 2b) developed by Hedstrom and Pomeroy (1998) from the data of Schmidt and Gluns (1991) and the US Army Corps of Engineers (1956), where ρ s,f = 67.92 + 51.25e T a /2.59 . For T a > 0°C a different variation with temperature is used with ρ s,f = min(200, 119.2 + 20T a ).…”

“…Hedstrom and Pomeroy (1998) estimated intercepted snow load (I s ) weekly using snow gauges located below the canopy and in a clearing, snow surveys, and by weighing jack pine and black spruce trees suspended in their respective canopies. They applied an expression for I * s following Schmidt and Gluns (1991),…”

Recent changes to the hydrological cycle of an Arctic basin at the tundra–taiga transition

“…Previous studies acknowledged the need for robust hydrological models suitable for cold regions to simulate Arctic hydrology (Quinton and Carey, 2008;Woo et al, 2008), particularly due to the complex interaction between subsurface and surface mass and energy fluxes (Kane et al, 1991;Krogh et al, 2017;Zhang et al, 2000). Physical processes that must be accounted for include snow accumulation and melt , snow interception and sublimation from forest canopies Schmidt and Gluns, 1991), blowing snow sublimation and redistribution Schmidt, 1982), evapotranspiration (Wessel and Rouse, 1994), infiltration into frozen and unfrozen soils Kane, 1980;Kane and Stein, 1983), water flow through snowpack (Colbeck, 1972;Marsh and Woo, 1984a, b), ground freeze and thaw (Juminikis, 1977), surface and subsurface flow (Quinton and Gray, 2001;Quinton and Marsh, 1999), and groundwater (Cederstrom et al, 1953) and streamflow routing (Woo and Sauriol, 1980). The Cold Regions Hydrological Model (CRHM) platform was used to create the Arctic Hydrology Model (AHM) configuration (CRHM-AHM) by Krogh et al (2017).…”