Error correction for IMERG precipitation estimates based on climatological adjustment combining the dry–wet season division and weight allocation

作者：Fuwan Gan, Xiang Diao, Kongrong Tan, Xinjing Li, Guangxu Cao, Xianci Zhong, Yang Gao · 发表于：Journal of Hydrology · 年份：2023 · DOI：10.1016/j.jhydrol.2023.129890 · 被引用次数：8 · 研究领域：Precipitation Measurement and Analysis、Climate variability and models、Meteorological Phenomena and Simulations

Error correction to obtain more accurate gridded precipitation estimates enhances the application prospects of the integrated multi-satellite retrievals for global precipitation measurement (IMERG). This study developed a climatological adjustment approach combining dry–wet season division and weight allocation (i.e., the DW approach) to achieve IMERG estimate correction without the need for contemporaneous gauge data. By learning the characteristics of an 18-year bias series from June 1, 2000 to December 31, 2017, through empirical probability calculation (the probability distribution function of every bias value in the dry and wet seasons), the bias field can be obtained without mathematical distribution assumptions for the biases. After recognizing the bias field at each of the 687 gauges in mainland China, the error adjustment can be tailored for every gauge to lower the current bias magnitude. The bias adjustment can be obtained as the product of two components, namely, the adjustment amount (AA) and the scaling factor (SF). The SF was discussed under different value intervals of the IMERG estimates to decide whether the original IMERG estimates should subtract or add the AA to generate the adjusted IMERG estimates. The quantile mapping (QM) approach was designed to be the standard method to examine the DW approach proposed. During the validation period from January 1, 2018, to December 31, 2019, the capability of two error adjustment approaches to the value reduction of...