The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient

<p>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...

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Main Authors: K. S. Jennings, N. P. Molotch
Format: Article
Language:English
Published: Copernicus Publications 2019-09-01
Series:Hydrology and Earth System Sciences
Online Access:https://www.hydrol-earth-syst-sci.net/23/3765/2019/hess-23-3765-2019.pdf
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spelling doaj-e26814e191e34a75bd78adadf813d8642020-11-25T02:05:22ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382019-09-01233765378610.5194/hess-23-3765-2019The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradientK. S. Jennings0K. S. Jennings1K. S. Jennings2K. S. Jennings3N. P. Molotch4N. P. Molotch5N. P. Molotch6Geography Department, University of Colorado Boulder, 260 UCB, Boulder, Colorado 80309, USAInstitute of Arctic and Alpine Research, University of Colorado Boulder, 450 UCB, Boulder, Colorado 80309, USADepartment of Geography, University of Nevada, Reno, 1664 N. Virginia Street, Reno, Nevada 89557, USADesert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, USAGeography Department, University of Colorado Boulder, 260 UCB, Boulder, Colorado 80309, USAInstitute of Arctic and Alpine Research, University of Colorado Boulder, 450 UCB, Boulder, Colorado 80309, USANASA Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California 91109, USA<p>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&thinsp;% at elevations less than 2000&thinsp;m in the Oregon Cascades and California's Sierra Nevada. This led to ranges in annual peak SWE typically greater than 200&thinsp;mm, exceeding 400&thinsp;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&thinsp;%, 62&thinsp;mm, 10&thinsp;d, and 15&thinsp;d, respectively. Average ranges in snowmelt rate were typically less than 4&thinsp;mm&thinsp;d<span class="inline-formula"><sup>−1</sup></span> and exhibited a small relationship to seasonal climate. Overall, sites with a greater proportion of precipitation falling at air temperatures between 0 and 4&thinsp;<span class="inline-formula"><sup>∘</sup></span>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.</p>https://www.hydrol-earth-syst-sci.net/23/3765/2019/hess-23-3765-2019.pdf
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language English
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author K. S. Jennings
K. S. Jennings
K. S. Jennings
K. S. Jennings
N. P. Molotch
N. P. Molotch
N. P. Molotch
spellingShingle K. S. Jennings
K. S. Jennings
K. S. Jennings
K. S. Jennings
N. P. Molotch
N. P. Molotch
N. P. Molotch
The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
Hydrology and Earth System Sciences
author_facet K. S. Jennings
K. S. Jennings
K. S. Jennings
K. S. Jennings
N. P. Molotch
N. P. Molotch
N. P. Molotch
author_sort K. S. Jennings
title The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
title_short The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
title_full The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
title_fullStr The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
title_full_unstemmed The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
title_sort sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2019-09-01
description <p>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&thinsp;% at elevations less than 2000&thinsp;m in the Oregon Cascades and California's Sierra Nevada. This led to ranges in annual peak SWE typically greater than 200&thinsp;mm, exceeding 400&thinsp;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&thinsp;%, 62&thinsp;mm, 10&thinsp;d, and 15&thinsp;d, respectively. Average ranges in snowmelt rate were typically less than 4&thinsp;mm&thinsp;d<span class="inline-formula"><sup>−1</sup></span> and exhibited a small relationship to seasonal climate. Overall, sites with a greater proportion of precipitation falling at air temperatures between 0 and 4&thinsp;<span class="inline-formula"><sup>∘</sup></span>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.</p>
url https://www.hydrol-earth-syst-sci.net/23/3765/2019/hess-23-3765-2019.pdf
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