Redistribution of Global Precipitation Observed in the El Niño Events by Using Multi-temporal Remote Sensing

According to model predictions, the most significant manifestation of climate change would be an acceleration of the global water cycle, leading to increased global precipitation. Knowledge of global precipitation is needed in order to investigate the existence of significant global trends in the rate of the water cycle. Quantitative measurement of the time and space distribution of precipitation is the next highest climate research priority after atmospheric temperature and moisture. Satellite remote sensing is the only means to acquire global rainfall data. The multi-satellite one degree daily global precipitation data spanning the years 1996-2004 has been used to meet challenges associated with regularity and perturbations in global precipitation. Wavelet is a tool used to study regularity. The most notable features are periodicity in an amount of precipitation and the total rainy area. They are independent variables. We introduce the global daily precipitation mass flow rate. The striking manifestations of El Niño are clear examples of the linkage between large-scale anomaly and changes in global weather process. Analysis of the time series of global precipitation that twice underwent perturbations during the El Niño events revealed new properties of the mass flow rate behaviour. To what extent are variations in precipitation related to global change remains to be learned.