Cross-evaluation of ground-based, multi-satellite and reanalysis precipitation products: Applicability of the Triple Collocation method across Mainland China

• DOI: 10.1016/j.jhydrol.2018.04.039
• Publication Date: 2018-04-21T17:11:02Z
• Authors: Changming Li; Guoqiang Tang; Yang Hong
• Keywords: 13. Climate action; 01 natural sciences; 0105 earth and related environmental sciences

Abstract Evaluating the reliability of satellite and reanalysis precipitation products is critical but challenging over ungauged or poorly gauged regions. The Triple Collocation (TC) method is a reliable approach to estimate the accuracy of any three independent inputs in the absence of truth values. This study assesses the uncertainty of three types of independent precipitation products, i.e., satellite-based, ground-based and model reanalysis over Mainland China using the TC method. The ground-based data set is Gauge Based Daily Precipitation Analysis (CGDPA). The reanalysis data set is European Reanalysis Agency Reanalysis Product (ERA-interim). The satellite-based products include five mainstream satellite products. The comparison and evaluation are conducted at 0.25° and daily resolutions from 2013 to 2015. First, the effectiveness of the TC method is evaluated in South China with dense gauge network. The results demonstrate that the TC method is reliable because the correlation coefficient (CC) and root mean square error (RMSE) derived from TC are close to those derived from ground observations, with only 9% and 7% mean relative differences, respectively. Then, the TC method is applied in Mainland China, with special attention paid to the Tibetan Plateau (TP) known as the Earth’s third pole with few ground stations. Results indicate that (1) The overall performance of IMERG is better than the other satellite products over Mainland China, followed by 3B42V7, CMORPH-CRT and PERSIANN-CDR. (2) In the TP, CGDPA shows the best overall performance over gauged grid cells, however, over ungauged regions, IMERG and ERA-interim slightly outperform CGDPA with similar RMSE but higher mean CC (0.63, 0.61, and 0.58, respectively). It highlights the strengths and potentiality of remote sensing and reanalysis data over the TP and reconfirms the cons of the inherent uncertainty of CGDPA due to interpolation from sparsely gauged data. The study concludes that the TC method provides not only reliable cross-validation results over Mainland China but also a new perspective for comparatively assessing multi-source precipitation products, particularly over poorly gauged regions such as the TP.