6 research outputs found
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The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
A critical component of hydrologic modeling in cold and temperate regions is partitioning precipitation into snow and rain, yet little is known about how uncertainty in precipitation phase propagates into variability in simulated snow accumulation and melt. Given the wide variety of methods for distinguishing between snow and rain, it is imperative to evaluate the sensitivity of snowpack model output to precipitation phase determination methods, especially considering the potential of snow-to-rain shifts associated with climate warming to fundamentally change the hydrology of snow-dominated areas. To address these needs we quantified the sensitivity of simulated snow accumulation and melt to rain–snow partitioning methods at sites in the western United States using the SNOWPACK model without the canopy module activated. The methods in this study included different permutations of air, wet bulb and dew point temperature thresholds, air temperature ranges, and binary logistic regression models. Compared to observations of snow depth and snow water equivalent (SWE), the binary logistic regression models produced the lowest mean biases, while high and low air temperature thresholds tended to overpredict and underpredict snow accumulation, respectively. Relative differences between the minimum and maximum annual snowfall fractions predicted by the different methods sometimes exceeded 100 % at elevations less than 2000 m in the Oregon Cascades and California's Sierra Nevada. This led to ranges in annual peak SWE typically greater than 200 mm, exceeding 400 mm in certain years. At the warmer sites, ranges in snowmelt timing predicted by the different methods were generally larger than 2 weeks, while ranges in snow cover duration approached 1 month and greater. Conversely, the three coldest sites in this work were relatively insensitive to the choice of a precipitation phase method, with average ranges in annual snowfall fraction, peak SWE, snowmelt timing, and snow cover duration of less than 18 %, 62 mm, 10 d, and 15 d, respectively. Average ranges in snowmelt rate were typically less than 4 mm d−1 and exhibited a small relationship to seasonal climate. Overall, sites with a greater proportion of precipitation falling at air temperatures between 0 and 4 ∘C exhibited the greatest sensitivity to method selection, suggesting that the identification and use of an optimal precipitation phase method is most important at the warmer fringes of the seasonal snow zone.
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Modeling streamflow sensitivity to climate warming and surface water inputs in a montane catchment
Study region
Gordon Gulch, an upper-montane forest watershed in the Colorado Front Range.
Study focus
As the climate warms, the fraction of precipitation falling as snow is expected to decrease and the timing of snowmelt is expected to shift earlier in spring. In snow-dominated regions, these changes in snow accumulation and melt prompt us to examine downstream changes in streamflow. The objective of this study is to understand how changes in precipitation phase and snowmelt timing alter the timing of surface water inputs (i.e. rainfall and snowmelt) and the partitioning of these inputs between evapotranspiration and streamflow. We used the Distributed Hydrology Soil Vegetation Model and Weather Research and Forecasting Model-based projections of future climatic conditions to simulate streamflow.
New hydrological insights for the region
Modeled annual streamflow decreased by 22% for the period 2071–2100. Surface water inputs increased during winter when atmospheric water demand was relatively low. Subsequently, the winter-period partitioning of water (as rain or snowmelt) to streamflow (as opposed to evapotranspiration) increased, by 15%, while partitioning to evapotranspiration decreased, effectively buffering what would have otherwise been a larger net streamflow decline associated with warming. Seasonal streamflow buffering is unique to snow-influenced systems, as the magnitude and timing of water released from snowpacks is sensitive to warming. This effect may diminish as warming drives snow-influenced systems toward rain-dominance, with implications for hydrological and ecological processes and water-resource management.
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Algae drive enhanced darkening of bare ice on the Greenland ice sheet
Surface ablation of the Greenland ice sheet is amplified by surface darkening caused by light-absorbing impurities such as mineral dust, black carbon, and pigmented microbial cells. We present the first quantitative assessment of the microbial contribution to the ice sheet surface darkening, based on field measurements of surface reflectance and concentrations of light-absorbing impurities, including pigmented algae, during the 2014 melt season in the southwestern part of the ice sheet. The impact of algae on bare ice darkening in the study area was greater than that of non-algal impurities and yielded a net albedo reduction of 0.038 ± 0.0035 for each algal population doubling. We argue that algal growth is a crucial control of bare ice darkening, and incorporating the algal darkening effect will improve mass balance and sea level projections of the Greenland ice sheet and ice masses elsewhere
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Energy budget increases reduce mean streamflow more than snow–rain transitions: using integrated modeling to isolate climate change impacts on Rocky Mountain hydrology
In snow-dominated mountain regions, a warming climate is expected to alter two drivers of hydrology: (1) decrease the fraction of precipitation falling as snow; and (2) increase surface energy available to drive evapotranspiration. This study uses a novel integrated modeling approach to explicitly separate energy budget increases via warming from precipitation phase transitions from snow to rain in two mountain headwaters transects of the central Rocky Mountains. Both phase transitions and energy increases had significant, though unique, impacts on semi-arid mountain hydrology in our simulations. A complete shift in precipitation from snow to rain reduced streamflow between 11% and 18%, while 4 °C of uniform warming reduced streamflow between 19% and 23%, suggesting that changes in energy-driven evaporative loss, between 27% and 29% for these uniform warming scenarios, may be the dominant driver of annual mean streamflow in a warming climate. Phase changes induced a flashier system, making water availability more susceptible to precipitation variability and eliminating the runoff signature characteristic of snowmelt-dominated systems. The impact of a phase change on mean streamflow was reduced as aridity increased from west to east of the continental divide