Snowpack variability and trends at long-term stations in northern Colorado, USA

Fassnacht, S. R.; Hultstrand, M.

doi:10.5194/piahs-371-131-2015

Cited by 18 publications

(24 citation statements)

References 18 publications

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“…Annual accumulations vary with elevation in most locations [23,24], with small declines (1-3 cm/decade) seen along the northern Front Range of Colorado [15]. Temporal variability of snow accumulation occurs on annual, seasonal, and monthly timescales and is also dependent on the period of record analyzed [25,26]. Melt rates from ablation at the end of the winter have been shown to vary [27,28].…”

Section: Introductionmentioning

confidence: 99%

Sub-Seasonal Snowpack Trends in the Rocky Mountain National Park Area, Colorado, USA

Fassnacht

Venable

McGrath

et al. 2018

Water

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We present a detailed study of the snowpack trends in the Rocky Mountain National Park (RMNP) using snow telemetry and snow course data at a monthly resolution. We examine the past 35 years (1981 to 2016) to explore monthly patterns over 36 locations and used some additional data to help interpret the changes. The analysis is at a finer spatial and temporal scale than previous studies that focused more on aggregate-or regional-scale changes. The trends in the first of the month's snow water equivalent (SWE) varied more than the change in the monthly SWE, monthly precipitation or mean temperature. There was greater variability in SWE trends on the west side of the study area, and on average the declines in the west were greater. At higher elevations, there was more of a decline in the SWE. Changes in the climate were much less in winter than in summer. Per decade, the average decline in the winter precipitation was 4 mm and temperatures warmed by 0.29 • C, while the summer precipitation declined by 9 mm and temperatures rose by 0.66 • C. In general, November and March became warmer and drier, yielding a decline of the SWE on December 1 st and April 1 st , while December through February and May became wetter. February and May became cooler.

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Section: Introductionmentioning

confidence: 99%

Sub-Seasonal Snowpack Trends in the Rocky Mountain National Park Area, Colorado, USA

Fassnacht

Venable

McGrath

et al. 2018

Water

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“…Snowmelt can be linked to vital water resources such as groundwater (Flint et al ., ; Clilverd et al ., ; Cao et al ., ), streamflow connectivity (McNamara et al ., ; Hunsaker et al ., ; Kampf et al ., ), soil moisture dynamics (Harpold et al ., ; Webb et al ., ), and forest ecosystem dynamics (Williams et al ., ; Smith et al ., ; Harpold et al ., ). With past and projected changes to snowpack accumulation and melt rates that vary from river basin to river basin (Adam et al ., ; Clow, ; Harpold et al ., ; Fassnacht and Hultstrand, ), it is important to accurately represent the physical process of snowmelt to estimate how hydrological processes will be impacted.…”

Section: Introductionmentioning

confidence: 99%

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Webb

Fassnacht

Gooseff

2017

J American Water Resour Assoc

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Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.

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“…The distribution of point SNOTEL stations should be considered (Meromy et al, 2013), as the stations tend to be located in an elevation zone with deep snow but rarely in the alpine and thus do not represent the highest elevations (Fassnacht et al, 2012). It may be useful to consider the small spatial extent SWE variability that can be derived from snow course data (Fassnacht and Hultstrand, 2015).…”

Section: Uses and Limitations Of The Snow-cover Depletion Curvesmentioning

confidence: 99%

Deriving snow-cover depletion curves for different spatial scales from remote sensing and snow telemetry data

et al. 2015

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Abstract:During the melting of a snowpack, snow water equivalent (SWE) can be correlated to snow-covered area (SCA) once snow-free areas appear, which is when SCA begins to decrease below 100%. This amount of SWE is called the threshold SWE. Daily SWE data from snow telemetry stations were related to SCA derived from moderate-resolution imaging spectroradiometer images to produce snow-cover depletion curves. The snow depletion curves were created for an 80 000 km 2 domain across southern Wyoming and northern Colorado encompassing 54 snow telemetry stations. Eight yearly snow depletion curves were compared, and it is shown that the slope of each is a function of the amount of snow received. Snow-cover depletion curves were also derived for all the individual stations, for which the threshold SWE could be estimated from peak SWE and the topography around each station. A station's peak SWE was much more important than the main topographic variables that included location, elevation, slope, and modelled clear sky solar radiation. The threshold SWE mostly illustrated inter-annual consistency.

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Snowpack variability and trends at long-term stations in northern Colorado, USA

Cited by 18 publications

References 18 publications

Sub-Seasonal Snowpack Trends in the Rocky Mountain National Park Area, Colorado, USA

Sub-Seasonal Snowpack Trends in the Rocky Mountain National Park Area, Colorado, USA

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Deriving snow-cover depletion curves for different spatial scales from remote sensing and snow telemetry data

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