%0 Journal Article
%T Simulation of a Daily Precipitation Time Series Using a Stochastic Model with Filtering
%A Chieko Gomi
%A Yasuhisa Kuzuha
%J Open Journal of Modern Hydrology
%P 206-213
%@ 2163-0496
%D 2013
%I Scientific Research Publishing
%R 10.4236/ojmh.2013.34025
%X <span>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 pa</span><span>rameter 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 L¨¦vy motion (fLm), especially the spectral method. That is, we transform white noise <i>X<sub>t</sub></i> to the precipitation daily time series. Our analyses show that the frequency of extreme precipitation events is best described by a L¨¦vy law and cannot be ac</span><span>counted with a Gaussian distribution.</span><span></span>
%K e-Model
%K Daily Precipitation Time Series
%K Filtering
%K Fractional Brownian Motion
%K Fractional L&#233
%K vy Motion
%K Stochastic Model
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=38392