Precipitation in the Pearl River basin, South China: scaling, regional patterns, and influence of large-scale climate anomalies

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Abstract

This study examines the temporal patterns of precipitation and the influence of large-scale climate anomalies in the Pearl River basin (South China), with particular focus on sub-basin scale. Three popular data analysis techniques are employed: (1) wavelet analysis; (2) principal component analysis (PCA); and (3) rank correlation method. With due consideration to hydrologic factors, water resources activities, and large-scale climate data, the entire basin is divided into ten sub-basins and the analysis is performed on monthly data. The wavelet analysis reveals discernible differences in temporal scales of fluctuation embedded in the monthly precipitation anomalies over the basin. The PCA delineates three coherent regions exhibiting similar distribution of variability across scales. Analysis of linkages between precipitation and teleconnection patterns using cross-wavelet transform and wavelet coherence reveals that the dominant variabilities of precipitation are essentially depicted by the Indian Ocean Dipole (IOD), especially for the central and eastern part of the Pearl River basin. On the influence of El Niño-Southern Oscillation (ENSO) signal on precipitation, more significant correlation is detected for the eastern part of the basin, long-term relationships (within 4–8 years band) are found for the western part of the basin, while the central part seems to be acting as a transition zone. Rank correlations of scale-averaged wavelet power between regional precipitation and climate indices for the dominant low-frequency variability band (0.84–8.40 years) provide further support to the different precipitation-climate relationships for different regions over the basin. The present results provide valuable information towards: (1) improving predictions of extreme hydroclimatic events in the Pearl River basin, based on their relationships with IOD or ENSO; and (2) devising better adaptation and mitigation strategies under a future changing climate.