Abstract
Quantifying rainfall from remotely sensed data is crucial for regions where meteorological stations are scarce. This might be one of the only options for analysing rainfall patterns at different temporal and spatial scales in data-scarce environments, particularly in developing countries. The Tropical Rainfall Measuring Mission (TRMM) provides rainfall estimation over the tropics. Rainfall estimates from the TRMM satellite exhibit inaccuracies over topographically complex regions, thus warranting suitable corrections. Multi-resolution analysis (MRA) was applied to improve TRMM 3B42 daily rainfall estimation at 19 meteorological stations located over the Andean Plateau. The detailed signal from each meteorological station was added to the trend signal of each TRMM data cell. Comparing raw and corrected TRMM with gauged rainfall revealed that wavelet-based correction of TRMM 3B42 on average improved several metrics: entropy difference (15.45−1.32), determination coefficient (0.07−0.92), bias (0.68−1.01) and relative mean absolute error (RMAE, 0.86−0.59). The entropy difference of corrected TRMM and gauged rainfall was less than 5%, even when TRMM correction was performed with noise from a station located up to 565 km away from the TRMM cell. This entropy difference corresponded to an average bias of less than 10% in the rainfall estimation.
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