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Climatic Change

, Volume 109, Supplement 1, pp 95–117 | Cite as

Simulating cold season snowpack: Impacts of snow albedo and multi-layer snow physics

  • D. Waliser
  • J. KimEmail author
  • Y. Xue
  • Y. Chao
  • A. Eldering
  • R. Fovell
  • A. Hall
  • Q. Li
  • K. N. Liou
  • J. McWilliams
  • S. Kapnick
  • R. Vasic
  • F. De Sale
  • Y. Yu
Article

Abstract

This study used numerical experiments to investigate two important concerns in simulating the cold season snowpack: the impact of the alterations of snow albedo due to anthropogenic aerosol deposition on snowpack and the treatment of snow physics using a multi-layer snow model. The snow albedo component considered qualitatively future changes in anthropogenic emissions and the subsequent increase or decrease of black carbon deposition on the Sierra Nevada snowpack by altering the prescribed snow albedo values. The alterations in the snow albedo primarily affect the snowpack via surface energy budget with little impact on precipitation. It was found that a decrease in snow albedo (by as little as 5–10% of the reference values) due to an increase in local emissions enhances snowmelt and runoff (by as much as 30–50%) in the early part of a cold season, resulting in reduced snowmelt-driven runoff (by as much as 30–50%) in the later part of the cold season, with the greatest impacts at higher elevations. An increase in snow albedo associated with reduced anthropogenic emissions results in the opposite effects. Thus, the most notable impact of the decrease in snow albedo is to enhance early-season snowmelt and to reduce late-season snowmelt, resulting in an adverse impact on warm season water resources in California. The timing of the sensitivity of snow water equivalent (SWE), snowmelt, and runoff vary systematically according to terrain elevation; as terrain elevation increases, the peak response of these fields occurs later in the cold season. The response of SWE and surface energy budget to the alterations in snow albedo found in this study shows that the effects of snow albedo on snowpack are further enhanced via local snow-albedo feedback. Results from this experiment suggest that a reduction in local emissions, which would increase snow albedo, could alleviate the early snowmelt and reduced runoff in late winter and early spring caused by global climate change, at least partially. The most serious uncertainties associated with this part of the study are a quantification of the relationship between the amount of black carbon deposition and snow albedo—a subject of future study. The comparison of the spring snowpack simulated with a single- and multi-layer snow model during the spring of 1998 shows that a more realistic treatment of snow physics in a multi-layer snow model could improve snowpack simulations, especially during spring when snow ablation is significant, or in conjunction with climate change projections.

Keywords

Surface Albedo Snow Water Equivalent Aerosol Deposition Snow Albedo Terrain Elevation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The research described in this paper was performed as an activity of the Joint Institute for Regional Earth System Science and Engineering (JIFRESSE) via a Memorandum of Understanding between the UCLA and the JPL/CALTECH. This work was supported by the NASA Energy and Water Cycle Study (NEWS), NA07OAR4310226, the Ministry of Environment, Korea (Grant No. 1600-1637-301-210-13), and University of California Lab Fees Research Program (Award No. 09-LR-09-116849-SORS). Jet Propulsion Laboratory’s Supercomputing and Visualization Facility and the NASA Advanced Supercomputing (NAS) Division provided the data storage and computational resources for this study.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • D. Waliser
    • 1
  • J. Kim
    • 2
    Email author
  • Y. Xue
    • 2
  • Y. Chao
    • 1
  • A. Eldering
    • 1
  • R. Fovell
    • 2
  • A. Hall
    • 2
  • Q. Li
    • 2
  • K. N. Liou
    • 2
  • J. McWilliams
    • 2
  • S. Kapnick
    • 2
  • R. Vasic
    • 2
    • 3
  • F. De Sale
    • 2
  • Y. Yu
    • 2
  1. 1.JPL/CALTECHPasadenaUSA
  2. 2.UCLALos AngelesUSA
  3. 3.National Centers for Environmental PredictionSilver SpringsUSA

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