A New Method for Hour-by-Hour Bias Adjustment of Satellite Precipitation Estimates over Mainland China

Highly accurate near-real-time satellite precipitation estimates (SPEs) are important for hydrological forecasting and disaster warning. The near-real quantitative (REGC) of the recently developed Chinese geostationary meteorological Fengyun 4A (FY4A) have advantage high spatial temporal resolution, but there errors uncertainties to some extent. In this paper, a self-adaptive ill-posed least squares scheme based on sequential processing (SISP) is proposed practiced in mainland China correct real-time biases REGC hour by hour. Specifically, adaptively acquires sample data setting windows constructs an error-correction model method from perspectives climate regions, topography, rainfall intensity. adopts idea update within time hour-by-hour basis can using dynamically changing parameters, fully taking into account influence variability. Only short-term historical needed accurately rate parameters. results show that SISP algorithm significantly reduce original REGC, which values relative bias (RB) reduced 11.2% 3.3%, root mean square error (RMSE) also about 17%. has better correction humid semi-humid regions than arid semi-arid effective reducing negative each region. terms rain intensity, improve overestimation low intensity (0.2–1 mm/h), (>1 mm/h) needs further improvement. component analysis shows effectively hit bias. This study serves as valuable reference accumulated data.