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Detecting climate-induced patterns using wavelet analysis.

G A Bradshaw1, B A McIntosh

  • 1Forest Sciences Laboratory, Pacific Northwest Research Station, Corvallis, Oregon 97331, USA.

Environmental Pollution (Barking, Essex : 1987)
|January 1, 1994
PubMed
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This study introduces wavelet analysis to differentiate climate impacts on stream discharge from other factors. The method successfully isolated climate-driven patterns in eastern Oregon

Area of Science:

  • Hydrology
  • Ecology
  • Climate Science

Background:

  • Distinguishing climate change impacts on ecosystems from other influences (land use, local factors) is challenging.
  • Stream discharge records reflect combined effects of climate, land use, and basin characteristics.
  • Quantifying temporal and spatial patterns across scales is crucial for assessing climate-induced ecosystem changes.

Purpose of the Study:

  • To introduce wavelet analysis as a method for identifying and isolating climate-induced components in hydrologic records.
  • To demonstrate the utility of wavelet analysis in discerning patterns in stream discharge data.
  • To apply wavelet cross-covariance to precipitation and discharge records to isolate climatic influences.

Main Methods:

  • Wavelet analysis was employed for time series decomposition and pattern identification.

Related Experiment Videos

  • Wavelet cross-covariance was used to link precipitation and stream discharge records.
  • Signal reconstruction was performed to isolate dominant climatic frequencies in the discharge data.

    • Main Results:

    • Wavelet analysis successfully identified and isolated climate-related patterns in eastern Oregon stream discharge.
    • Two dominant scales of pattern in discharge were found to coincide with precipitation patterns.
    • A 3-year periodic pattern in discharge correlated with the Southern Oscillation Index was identified.

    Conclusions:

    • Wavelet analysis is a valuable tool for discerning climate-driven changes in hydrologic systems.
    • The methodology provides an informed approach for signal decomposition and pattern analysis.
    • Climate variability, including influences like the Southern Oscillation Index, significantly impacts stream discharge patterns.