Trends in Average Snow Depth Across the Western United States

Grundstein, Andrew; Mote, Thomas L.

doi:10.2747/0272-3646.31.2.172

Cited by 15 publications

(17 citation statements)

References 21 publications

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“…The regions where winter temperatures hover well below this band will likely not experience this strong trend because snow will still form, and regions with average temperatures well above this band will still see most of their precipitation as rain, with the occasional (less frequent) snow. This physical mechanism agrees with arguments in the literature [ Dettinger and Cayan , 1995; Knowles et al , 2006; Das et al , 2009; Grundstein and Mote , 2010; Mote et al , 2008]. In general the previous studies find that middle altitudes are the most sensitive, here we argue that there is also a strong latitudinal component to the sensitivities, and southern regions within the basin experience strong snowfall trends at high elevations.…”

Section: Discussionsupporting

confidence: 92%

“…In this region, snow acts as the largest storage of precipitation in the winter, with release of water during the critical spring and summer months [ Mote et al , 2005]. Observations over the past 50 years show a decrease in April 1 snow water equivalent (SWE) and a shift to earlier onset of snowmelt‐driven streamflow in both the Upper and Lower Colorado River Basins [ Mote et al , 2005; Grundstein and Mote , 2010; Stewart et al , 2005]. However, high‐elevation stations in the Rocky Mountains of Colorado show no trends or positive trends for the SWE and the timing of streamflow [ Mote et al , 2005; Stewart et al , 2005].…”

Section: Introductionmentioning

confidence: 99%

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Climate change projection of snowfall in the Colorado River Basin using dynamical downscaling

Domínguez

Durcik

et al. 2012

Water Resources Research

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[1] Recent observations show a decrease in the fraction of precipitation falling as snowfall in the western United States. In this work we evaluate a historical and future climate simulation over the Colorado River Basin using a 35 km continuous 111 year simulation of the Weather Research and Forecasting (WRF) regional climate model with boundary forcing from the Hadley Centre for Climate Prediction and Research/Met Office's HadCM3 model with A2 emission scenario. The focus of this work is to (1) evaluate the simulated spatiotemporal variability of snowfall in the historical period when compared to observations and (2) project changes in snowfall and the fraction of precipitation that falls as snow during the 21st century. We find that the spatial variability in modeled snowfall in the historical period is realistically represented when compared to observations. The trends of modeled snowfall are similar to the observed trends except at higher elevations. Examining the continuous 111 year simulation, we find the future projections show statistically significant increases in temperature with larger increases in the northern part of the basin. There are statistically insignificant increases in precipitation, while snowfall shows a statistically significant decrease throughout the period in all but the highest elevations and latitudes. The fraction of total precipitation falling as snow shows statistically significant declines in all regions. The strongest decrease in snowfall is seen at high elevations in the southern part of the basin and low elevations in the northern part of the basin. The regions of most intense decreases in snow experience a decline of approximately 50% in snowfall throughout the 111 year simulation period. The regions of strongest declines in snowfall roughly correspond to the region of migration of the zero degree Celsius line and emphasize snowfall dependence on both altitude and latitude.Citation: Wi, S., F. Dominguez, M. Durcik, J. Valdes, H. F. Diaz, and C. L. Castro (2012), Climate change projection of snowfall in the Colorado River Basin using dynamical downscaling, Water Resour. Res., 48, W05504,

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Climate change projection of snowfall in the Colorado River Basin using dynamical downscaling

Domínguez

Durcik

et al. 2012

Water Resources Research

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“…These include a warming climate, changes in precipitation, an accelerated nitrogen cycle, and invasions by non‐native species. These forces of change have become increasingly evident in recent years (Overpeck and Udall 2010), and their effects, as highlighted in Wilcox (2010), are seen in (i) changing patterns in snow accumulation and melt (Grundstein and Mote 2010; Regonda et al. 2005); (ii) increasing frequency and intensity of fires (Westerling et al.…”

Section: Understanding a Changing Landscape: A Research Imperative Fomentioning

confidence: 99%

Dryland Ecohydrology in the Anthropocene: Taking Stock of Human-Ecological Interactions

2011

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Drylands have been radically through transformed forces set in motion by humans – including agricultural conversion, overgrazing, and invasion by non‐native plants. Relatively new global change drivers will ensure that drylands will continue their transformation. In this review, we discuss recent progress in understanding how global climate and land cover changes are affecting the ecohydrology of drylands, and we highlight some challenges faced by the research community. We argue that an imperative for dryland ecohydrologists is to not only work to better understand and anticipate global changes, but to devise strategies for adapting to and, where possible, mitigating the effects of these changes. The fundamental challenge we face is how to ensure clean water and adequate food for humanity while at the same time maintaining the Earth’s life‐support systems. Moreover, we suggest that scientific efforts and social policy can – and indeed must – become more strongly linked. The ecological and earth science communities benefit from interactions with social scientists, and social policy made without consideration of the long‐term impacts on dryland processes can jeopardize the sustainability of natural resources.

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“…Studies that have examined temporal trends in snowpack provide insight into the effects of temperature and precipitation on snowpack. Numerous empirical and model‐based studies have found strong evidence of negative temporal trends in snowpack within the western US, including Oregon (Hamlet et al , 2005; Knowles et al , 2006; Mote, 2006; Barnett et al , 2008; Casola et al , 2009; Grundstein and Mote, 2010). This includes not only declines in 1 April SWE, but also trends in earlier snow melt, earlier peak stream flows, and reduced stream flow.…”

Section: Methodsmentioning

confidence: 99%

“…However, these two factors are differentially important at different locations. Increased temperatures, which have the dual effect of reducing the proportion of precipitation that occurs as snow and increasing the amount of snow melt, have a larger impact at lower elevations and on the Pacific coast, where temperatures are closer to freezing (Hamlet et al , 2005; Knowles et al , 2006; Mote, 2006; Grundstein and Mote, 2010). Higher elevation locations, such as the Sierra Nevada and the Rockies, are cold enough that warming trends have not impacted snowpack, and so temperature is less of a factor.…”

Section: Methodsmentioning

confidence: 99%

A temperature‐precipitation‐based model of thirty‐year mean snowpack accumulation and melt in Oregon, USA

Leibowitz

Wigington

Comeleo

et al. 2011

Hydrological Processes

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Abstract:High-resolution, spatially extensive climate grids can be useful in regional hydrologic applications. However, in regions where precipitation is dominated by snow, snowmelt models are often used to account for timing and magnitude of water delivery. We developed an empirical, nonlinear model to estimate 30-year means of monthly snowpack and snowmelt throughout Oregon. Precipitation and temperature for the period 1971-2000, derived from 400-m resolution PRISM data, and potential evapotranspiration (estimated from temperature and day length) drive the model. The model was calibrated using mean monthly data from 45 SNOTEL sites and accurately estimated snowpack at 25 validation sites: R 2 D 0Ð76, Nash-Sutcliffe Efficiency (NSE) D 0Ð80. Calibrating it with data from all 70 SNOTEL sites gave somewhat better results (R 2 D 0Ð84, NSE D 0Ð85). We separately applied the model to SNOTEL stations located <200 and ½200 km from the Oregon coast, since they have different climatic conditions. The model performed equally well for both areas. We used the model to modify moisture surplus (precipitation minus potential evapotranspiration) to account for snowpack accumulation and snowmelt. The resulting values accurately reflect the shape and magnitude of runoff at a snow-dominated basin, with low winter values and a June peak. Our findings suggest that the model is robust with respect to different climatic conditions, and that it can be used to estimate potential runoff in snow-dominated basins. The model may allow high-resolution, regional hydrologic comparisons to be made across basins that are differentially affected by snowpack, and may prove useful for investigating regional hydrologic response to climate change.

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Trends in Average Snow Depth Across the Western United States

Cited by 15 publications

References 21 publications

Climate change projection of snowfall in the Colorado River Basin using dynamical downscaling

Climate change projection of snowfall in the Colorado River Basin using dynamical downscaling

Dryland Ecohydrology in the Anthropocene: Taking Stock of Human-Ecological Interactions

A temperature‐precipitation‐based model of thirty‐year mean snowpack accumulation and melt in Oregon, USA

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