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Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China

Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China
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摘要 Seasonal precipitation changes under the influence of large-scale climate oscillations in the East River basin were studied using daily precipitation data at 29 rain stations during 1959–2010. Seasonal and global models were developed and evaluated for probabilistic precipitation forecasting. Generalized additive model for location,scale, and shape was used for at-site precipitation forecasting. The results indicate that:(1) winter and spring precipitation processes at most stations are nonstationary,while summer and autumn precipitation processes at few of the stations are stationary. In this sense, nonstationary precipitation processes are dominant across the studyregion;(2) the magnitude of precipitation is influenced mainly by the Arctic Oscillation, the North Pacific Oscillation, and the Pacific Decadal Oscillation(PDO). The El Nin? o/Southern Oscillation(ENSO) also has a considerable effect on the variability of precipitation regimes across the East River basin;(3) taking the seasonal precipitation changes of the entire study period as a whole, the climate oscillations influence precipitation magnitude, and this is particularly clear for the PDO and the ENSO. The latter also impacts the dispersion of precipitation changes; and(4) the seasonal model is appropriate for modeling spring precipitation, but the global model performs better for summer, autumn, and winter precipitation. Seasonal precipitation changes under the influence of large-scale climate oscillations in the East River basin were studied using daily precipitation data at 29 rain stations during 1959–2010. Seasonal and global models were developed and evaluated for probabilistic precipitation forecasting. Generalized additive model for location,scale, and shape was used for at-site precipitation forecasting. The results indicate that:(1) winter and spring precipitation processes at most stations are nonstationary,while summer and autumn precipitation processes at few of the stations are stationary. In this sense, nonstationary precipitation processes are dominant across the studyregion;(2) the magnitude of precipitation is influenced mainly by the Arctic Oscillation, the North Pacific Oscillation, and the Pacific Decadal Oscillation(PDO). The El Nin? o/Southern Oscillation(ENSO) also has a considerable effect on the variability of precipitation regimes across the East River basin;(3) taking the seasonal precipitation changes of the entire study period as a whole, the climate oscillations influence precipitation magnitude, and this is particularly clear for the PDO and the ENSO. The latter also impacts the dispersion of precipitation changes; and(4) the seasonal model is appropriate for modeling spring precipitation, but the global model performs better for summer, autumn, and winter precipitation.
出处 《International Journal of Disaster Risk Science》 SCIE CSCD 2018年第1期100-115,共16页 国际灾害风险科学学报(英文版)
基金 financially supported by the Fund for Creative Research Groups of the National Natural Science Foundation of China(Grant No.41621061) the National Science Foundation for Distinguished Young Scholars of China(Grant No.51425903) the National Science Foundation of China(Grant Nos.41601023 41401052)
关键词 China ENSO regimes GAMLSS model Nonstationarity Probabilistic precipitation forecasting China ENSO regimes GAMLSS model Nonstationarity Probabilistic precipitation forecasting
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