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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2019-82
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-82
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 05 Mar 2019

Research article | 05 Mar 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

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

Keith S. Jennings1,2,3,4 and Noah P. Molotch1,2,5 Keith S. Jennings and Noah P. Molotch
  • 1Geography Department, University of Colorado Boulder, 260 UCB, Boulder, Colorado 80309, USA
  • 2Institute of Arctic and Alpine Research, University of Colorado Boulder, 450 UCB, Boulder, CO 80309, USA
  • 3Department of Geography, University of Nevada, Reno, 1664 N. Virginia Street, Reno, NV 89557, USA
  • 4Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512, USA
  • 5NASA Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109, USA

Abstract. 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 modeled snow accumulation and melt to rain-snow partitioning at research sites in the western United States. Simulations using the physics-based SNOWPACK model and 12 different precipitation phase methods indicated maritime sites were the most sensitive to method selection. 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 mountains. This led to ranges in annual peak snow water equivalent (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 less than 18 %, 62 mm, 10 d, and 15 d, respectively. Overall, sites with a greater proportion of precipitation falling at air temperatures between 0 °C and 4 °C exhibited the greatest sensitivity to method selection. These findings have large implications for modeled snowpack water storage and land surface albedo at the warmer fringes of the seasonal snow zone.

Keith S. Jennings and Noah P. Molotch
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Keith S. Jennings and Noah P. Molotch
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Short summary
There is a wide variety of modeling methods to designate precipitation as rain, snow, or a mix of the two. Here we show that method choice introduces marked uncertainty to simulated snowpack water storage (> 200 mm) and snow cover duration (> 1 month) in areas that receive significant winter and spring precipitation at air temperatures at and near freezing. This marked uncertainty has implications for water resources management as well as simulations of past and future hydroclimatic states.
There is a wide variety of modeling methods to designate precipitation as rain, snow, or a mix...
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