Simulation of a Daily Precipitation Time Series Using a Stochastic Model with Filtering

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Abstract

After we modified raw data for anomalies, we conducted spectral analysis using the data. In the frequency, the spectrum is best described by a decaying exponential function. For this reason, stochastic models characterized by a spectrum attenuated according to a power law cannot be used to model precipitation anomaly. We introduced a new model, the e-model, which properly reproduces the spectrum of the precipitation anomaly. After using the data to infer the parameter values of the e-model, we used the e-model to generate synthetic daily precipitation time series. Comparison with recorded data shows a good agreement. This e-model resembles fractional Brown motion (fBm)/fractional Lévy motion (fLm), especially the spectral method. That is, we transform white noise Xt to the precipitation daily time series. Our analyses show that the frequency of extreme precipitation events is best described by a Lévy law and cannot be accounted with a Gaussian distribution.

Journal

  • Open Journal of Modern Hydrology

    Open Journal of Modern Hydrology 3(4), 206-213, 2013-10-23

    Scientific Research Publishing

Codes

  • NII Article ID (NAID)
    120005341808
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    2163-0461
  • Data Source
    IR 
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