Prediction of seasonal snow accumulation in cold climate forests

Pomeroy, John W.; Gray, David B.; Hedstrom, N.; Rasouli, Kabir

doi:10.1002/hyp.1228

Cited by 208 publications

(230 citation statements)

References 10 publications

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“…The typical mountain environment includes dense boreal forest at lower elevations, sparse forest, open meadow and shrub tundra at the higher elevations, and exposed alpine areas with mostly bare rock at the highest elevations. WCB and WCF are situated at two different areas of tall shrub tundra (Pomeroy et al, 2006) and mature white spruce forest (Pomeroy et al, 2002), respectively. The subarctic continental climate is characterized by a large variation in air temperature, low relative humidity, and relatively low precipitation (Wahl et al, 1987).…”

Section: Sites and Datamentioning

confidence: 99%

Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada

Xiong

Yang

et al. 2016

The Cryosphere

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Abstract. This study assesses a filtering procedure on accumulating precipitation gauge measurements and quantifies the effects of bias corrections for wind-induced undercatch across four ecoclimatic regions in western Canada, including the permafrost regions of the subarctic, the Western Cordillera, the boreal forest, and the prairies. The bias corrections increased monthly precipitation by up to 163 % at windy sites with short vegetation and sometimes modified the seasonal precipitation regime, whereas the increases were less than 13 % at sites shielded by forest. On a yearly basis, the increase of total precipitation ranged from 8 to 20 mm (3-4 %) at sites shielded by vegetation and 60 to 384 mm (about 15-34 %) at open sites. In addition, the bias corrections altered the seasonal precipitation patterns at some windy sites with high snow percentage ( > 50 %). This study highlights the need for and importance of precipitation bias corrections at both research sites and operational networks for water balance assessment and the validation of global/regional climate-hydrology models.

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Section: Sites and Datamentioning

confidence: 99%

Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada

Xiong

Yang

et al. 2016

The Cryosphere

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“…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. …”

Section: Vegetation Effects On Snow Distribution Along Elevationmentioning

confidence: 99%

“…California's multi-billion-dollar agricultural economy as well as multi-trillion-dollar urban economy depend on these predictions (California Department of Water Resources, 2013). Both topographic and vegetation factors are important in influencing the snowpack conditions, as they closely interact with meteorological conditions to affect precipitation and snow distribution in the mountains (McMillen, 1988;Raupach, 1991;Wigmosta et al, 1994). However, mountain precipitation is poorly understood at multiple spatial scales because it is governed by processes that are neither well measured nor accurately predicted (Kirchner et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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

2016

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Abstract. Airborne light detection and ranging (lidar) measurements carried out in the southern Sierra Nevada in 2010 in the snow-free and peak-snow-accumulation periods were analyzed for topographic and vegetation effects on snow accumulation. Point-cloud data were processed from four primarily mixed-conifer forest sites covering the main snow-accumulation zone, with a total surveyed area of over 106 km 2 . The percentage of pixels with at least one snowdepth measurement was observed to increase from 65-90 to 99 % as the sampling resolution of the lidar point cloud was increased from 1 to 5 m. However, a coarser resolution risks undersampling the under-canopy snow relative to snow in open areas and was estimated to result in at least a 10 cm overestimate of snow depth over the main snowaccumulation region between 2000 and 3000 m, where 28 % of the area had no measurements. Analysis of the 1 m gridded data showed consistent patterns across the four sites, dominated by orographic effects on precipitation. Elevation explained 43 % of snow-depth variability, with slope, aspect and canopy penetration fraction explaining another 14 % over the elevation range of 1500-3300 m. The relative importance of the four variables varied with elevation and canopy cover, but all were statistically significant over the area studied. The difference between mean snow depth in open versus under-canopy areas increased with elevation in the rain-snow transition zone (1500-1800 m) and was about 35 ± 10 cm above 1800 m. Lidar has the potential to transform estimation of snow depth across mountain basins, and including local canopy effects is both feasible and important for accurate assessments.

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“…where is the air emissivity, is the fractional cloud cover, is the fractional canopy cover (estimated from following (Liston and Elder, 2006;Pomeroy et al, 2002)), is the canopy emissivity (assumed equal to 1 following Sicart et al (2004)), and is the canopy temperature (°C) which is assumed equal to following DeWalle and Rango (2008).…”

Section: Rti Snowpack Modelmentioning

confidence: 99%

A Simple Temperature-Based Method to Estimate Heterogeneous Frozen Ground within a Distributed Watershed Model

Follum¹,

Niemann²,

Parno³

et al. 2017

Preprint

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Frozen ground can be important to flood production and is often heterogeneous within a watershed due to spatial 10 variations in the available energy, insulation by snowpack and ground cover, and the thermal and moisture properties of the soil. The widely-used Continuous Frozen Ground Index (CFGI) model is a degree-day approach and identifies frozen ground using a simple frost index, which varies mainly with elevation through a temperature-elevation relationship.Similarly, snow depth and its insulating effect are also estimated based on elevation. The objective of this work is to more accurately represent the spatial heterogeneity of frozen ground in a distributed hydrologic model, Gridded Surface 15 Subsurface Hydrologic Analysis (GSSHA), by modifying the CFGI method. Among the modifications, the snowpack and frost indices are simulated by replacing air temperature (a surrogate for the available energy) with a radiation-derived temperature that aims to better represent spatial variations in available energy. Ground cover is also included as an additional insulator of the soil. Furthermore, the modified Berggren Equation, which accounts for soil thermal conductivity and soil moisture, is used to convert the frost index into frost depth. The modified CFGI model is tested by application at six 20 test sites within the Sleepers River Experimental Watershed in Vermont. Compared to the CFGI model, the modified CFGI model more accurately captures the variations in frozen ground between the sites, inter-annual variations in frozen ground depths at a given site, and the occurrence of frozen ground.

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Prediction of seasonal snow accumulation in cold climate forests

Cited by 208 publications

References 10 publications

Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada

Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada

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

A Simple Temperature-Based Method to Estimate Heterogeneous Frozen Ground within a Distributed Watershed Model

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