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

Abstract

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 study region; (2) the magnitude of precipitation is influenced mainly by the Arctic Oscillation, the North Pacific Oscillation, and the Pacific Decadal Oscillation (PDO). The El Niño / 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.

Keywords

China / ENSO regimes / GAMLSS model / Nonstationarity / Probabilistic precipitation forecasting

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