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Simulation of a Daily Precipitation Time Series Using a Stochastic Model with Filtering
http://hdl.handle.net/10076/13295
http://hdl.handle.net/10076/1329501bae798-7a53-4e70-a06a-e784e9d63313
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
50A16561.pdf (637.9 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||||
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| 公開日 | 2013-10-25 | |||||||||
| タイトル | ||||||||||
| タイトル | Simulation of a Daily Precipitation Time Series Using a Stochastic Model with Filtering | |||||||||
| 言語 | en | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | e-Model | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Daily Precipitation Time Series | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Filtering | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Fractional Brownian Motion | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Fractional Lévy Motion | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Stochastic Model | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者 |
Gomi, Chieko
× Gomi, Chieko
× Kuzuha, Yasuhisa
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| 抄録 | ||||||||||
| 内容記述タイプ | Abstract | |||||||||
| 内容記述 | 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. | |||||||||
| 書誌情報 |
Open Journal of Modern Hydrology 巻 3, 号 4, p. 206-213, 発行日 2013-10-23 |
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| 収録物識別子タイプ | PISSN | |||||||||
| 収録物識別子 | 2163-0461 | |||||||||
| 権利 | ||||||||||
| 権利情報 | Copyright © 2006-2013 Scientific Research Publishing Inc. All rights reserved. | |||||||||
| フォーマット | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | application/pdf | |||||||||
| 著者版フラグ | ||||||||||
| 出版タイプ | VoR | |||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||
| 出版者 | ||||||||||
| 出版者 | Scientific Research Publishing | |||||||||
| 関係URI | ||||||||||
| 関連名称 | http://www.scirp.org/journal/PaperInformation.aspx?PaperID=38392 | |||||||||
| 資源タイプ（三重大） | ||||||||||
| 値 | Journal Article / 学術雑誌論文 | |||||||||
