Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Evaluation of temporal-spatial precipitation variability and prediction using seasonal ARIMA model in Mongolia
Abstract In this paper, spatial and temporal characteristics of precipitation time series were studied for Mongolia. Precipitation chronological data sets were encoded from the GPCC (Global Precipitation Climatology Center) grid containing 1° × 1° resolutions during the 1986–2007 periods. For this study, regionally 39 and globally 24083 gridded products were employed to analyze the precipitation anomalies. The Mann-Kendall and Cumulative Sum of non-parametric tests are used in order to identify trends and change points in the summer precipitation time series. Through the statistical point of view among the Hangai and Khentai mountainous regions were found the major variation. Associated eigenvalues of the EOF (Empirical Orthogonal Function) and PCA (Principal Component Analysis) were applied to determine the amount of total explained variance and significant shifts into the temporal trends. First four EOF are accounted with a total 80.1% explained variance for annual precipitation while the first EOF was 48.7%, second EOF was 18.3%, third EOF was 9% and fourth EOF was 4.1% respectively. Nevertheless, individual summer season’s gridded precipitation time series were fitted and predicted through the adequate ARIMA (Autoregressive Integrated Moving Average) model which was presented in this paper.
Evaluation of temporal-spatial precipitation variability and prediction using seasonal ARIMA model in Mongolia
Abstract In this paper, spatial and temporal characteristics of precipitation time series were studied for Mongolia. Precipitation chronological data sets were encoded from the GPCC (Global Precipitation Climatology Center) grid containing 1° × 1° resolutions during the 1986–2007 periods. For this study, regionally 39 and globally 24083 gridded products were employed to analyze the precipitation anomalies. The Mann-Kendall and Cumulative Sum of non-parametric tests are used in order to identify trends and change points in the summer precipitation time series. Through the statistical point of view among the Hangai and Khentai mountainous regions were found the major variation. Associated eigenvalues of the EOF (Empirical Orthogonal Function) and PCA (Principal Component Analysis) were applied to determine the amount of total explained variance and significant shifts into the temporal trends. First four EOF are accounted with a total 80.1% explained variance for annual precipitation while the first EOF was 48.7%, second EOF was 18.3%, third EOF was 9% and fourth EOF was 4.1% respectively. Nevertheless, individual summer season’s gridded precipitation time series were fitted and predicted through the adequate ARIMA (Autoregressive Integrated Moving Average) model which was presented in this paper.
Evaluation of temporal-spatial precipitation variability and prediction using seasonal ARIMA model in Mongolia
Kim, Byung Sik (Autor:in) / Hossein, Syed Zakir (Autor:in) / Choi, Gyewoon (Autor:in)
KSCE Journal of Civil Engineering ; 15 ; 917-925
12.04.2011
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Spatial and temporal variability of Canadian seasonal precipitation (1900-2000)
| British Library Online Contents | 2006
A seasonal ARIMA model based on the gravitational search algorithm (GSA) for runoff prediction
| DOAJ | 2022
Spatial and Temporal Variability of Precipitation Complexity in Northeast Brazil
| DOAJ | 2022