HR: 0830h
AN: C41B-0973    [PDF]
TI: Spectral Signatures of Snow Depth Time Series
AU: * Deems, J S
EM: deems@cnr.colostate.edu
AF: Colorado State University, Department of Geosciences, Fort Collins, CO 80523-1482 United States
AU: Elder, K
EM: kelder@fs.fed.us
AF: Rocky Mountain Research Station, USDA Forest Service 240 West Prospect Road, Fort Collins, CO 80526 United States
AB: Studies of complex systems have demonstrated that system behavior can be characterized from analysis of a single observable parameter. Initial results from this study suggest that one measured variable, change in snow depth, exhibits nonlinear behavior characteristic of a self-organizing complex system. Investigation of the behavior of this parameter provides insight into the complex nature of the seasonal snow system and sources of nonlinearity in system interactions. A pilot study, using data from a single observing station, demonstrated a "1/Ÿ" power spectrum in a time series of change in snow depth, a time scaling consistent with self-organization in a complex system. Further, this "1/Ÿ" power spectrum existed only within the accumulation (positive depth change) subset of the data, while the ablation (negative depth change) subset exhibited a "white noise" spectrum; this suggests that complex atmospheric dynamics and resultant precipitation patterns are significant forcing agents potentially driving nonlinear interactions in the seasonal snow system. To further explore the dynamics revealed by the change in snow depth parameter, a second analysis has been undertaken, using data from several observing stations. Snow depth measurements are used from meteorologic stations implemented through the NASA Cold Lands Processes Experiment (CLPX) in the 2001/2002 and 2002/2003 snow seasons. The data is averaged to produce an hourly measurement interval, and detrended by first difference to remove seasonal accumulation trends, leading to the "hourly change in snow depth" parameter used for analysis. Power spectra for each of the time series in the study display a range of frequency exponents consistent with the pilot study results, in that the ablation subset tends toward a white noise signature, while the accumulation subset commonly shows "1/Ÿ" scaling.
DE: 1854 Precipitation (3354)
DE: 1863 Snow and ice (1827)
DE: 1869 Stochastic processes
DE: 1894 Instruments and techniques
DE: 3220 Nonlinear dynamics
SC: Cryosphere [C]
MN: 2003 Fall Meeting