HR: 0830h
AN: C41B-0974    [PDF]
TI: Wavelet analysis of Snow course data within the Sierra Nevada Mountains
AU: * Rios, T
EM: trios@uclink.berkeley.edu
AF: University of California, 533 Davis Hall Mail Code 1710, Berkeley, CA 94720-1710 United States
AU: Dracup, J A
EM: dracup@ce.berkeley.edu
AF: University of California, 533 Davis Hall Mail Code 1710, Berkeley, CA 94720-1710 United States
AB: In recent years, an analytical method known as wavelet analysis has received increasing applications in geophysical fields (Foufoula-Georgiou and Kumar 1994). Wavelet analysis can be used to identify the time and frequency regime in data while still maintaining the time coordinate. By applying the wavelet analysis method to the Mount Shasta snow course for the time period from 1937-1997 using the continuous 1-D wavelet toolbox in MATLAB, we found that several frequency regimes are present within the signal. The inter-annual noise dominates the frequency regime below the seven-year scale, but there is a relatively consistent 9-13 year oscillation that is present within the snow data. This frequency regime is also observed to shift to lower scales as the time series progresses, possibly indicating a shift in the climate variability due to climate change. In addition, analyses of the depth and the water content data exhibit nearly identical wavelet images. We are currently in the process of identifying other climate variables that may exhibit similar periodicity with the continuous 1-D wavelet analysis, such as the PDO and ENSO. Preliminary results show that by analyzing the hydrologic variables of the Sierra Nevada snowpack depth and/or water content using the wavelet method, we may be able to provide useful insights into the synergy and expression of climate change and variability within the California Sierra Nevadas.
DE: 1800 HYDROLOGY
SC: Cryosphere [C]
MN: 2003 Fall Meeting