Articles | Volume 19, issue 7
https://doi.org/10.5194/hess-19-3153-2015
https://doi.org/10.5194/hess-19-3153-2015
Research article
 | 
20 Jul 2015
Research article |  | 20 Jul 2015

Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

M. S. Raleigh, J. D. Lundquist, and M. P. Clark

Viewed

Total article views: 4,150 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,396 1,567 187 4,150 181 177
  • HTML: 2,396
  • PDF: 1,567
  • XML: 187
  • Total: 4,150
  • BibTeX: 181
  • EndNote: 177
Views and downloads (calculated since 16 Dec 2014)
Cumulative views and downloads (calculated since 16 Dec 2014)

Cited

Saved (final revised paper)

Saved (preprint)

Latest update: 23 Nov 2024
Download
Short summary
A sensitivity analysis is used to examine how error characteristics (type, distributions, and magnitudes) in meteorological forcing data impact outputs from a physics-based snow model in four climates. Bias and error magnitudes were key factors in model sensitivity and precipitation bias often dominated. However, the relative importance of forcings depended somewhat on the selected model output. Forcing uncertainty was comparable to model structural uncertainty as found in other studies.