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Apr 26, 2012
Understanding the Dynamics of Snowpack in Washington State-Part II: Complexity of Snowpack
Authors: Nian She and Deniel BasketfieldAuthor Affiliations
Publication: World Environmental and Water Resources Congress 2007: Restoring Our Natural Habitat
Abstract
In part I of this study the strong teleconnections between large-scale atmospheric circulation patterns and the peak of snowpack measured by snow water equivalent (SWE) in Washington State were established by a linear regression model. However, the underlying dynamics of snowpack for each snow telemetry (SNOTEL) site are unknown. The statistically significant correlations between the peaks of snowpack and large-scale climate indices do not necessarily imply linear relationships among them. Moreover, these correlations do not imply a deterministic or stochastic dynamic process underlying snowpack SWE data. To better understand the complexity of snowpack dynamics in Washington State, a technique developed from nonlinear time series analysis and dynamic theory called surrogate data testing was used to investigate the complexity of snowpack dynamics in terms of determinism vs. randomness. Some relatively new concepts, such as embedding dimensions, time delay, phase re-construction, correlation dimensions and prediction errors are introduced to hydrologists and water managers to characterize the complexity and predictability of the snowpack at specified sites.
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© 2007 American Society of Civil Engineers.
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Published online: Apr 26, 2012
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Nian She
Seattle Public Utilities, Seattle, Washington
Deniel Basketfield
Seattle Public Utilities, Seattle, Washington
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