Evaluating the precision of monthly IMERG precipitation products in Guangxi of China

Accurate monitoring and assessment of precipitation distribution can be vital to effectively manage water resources and disaster preparedness for high productivity in modern agriculture against global climate change. Among them, Guangxi in southern China is in a monsoonal climate. A great challenge remains on the notable temporal and spatial fluctuations in precipitation, particularly for agricultural productivity and ecological integrity. The purpose of this study is to assess the suitability and precision of the monthly IMERG (V06) precipitation dataset in the Guangxi region. A scientific foundation was then established to manage the local water resources and disaster preparedness. The study area was characterized by low rainfall (≤1300 mm/a), moderate rainfall (>1300-1700 mm/a), and high rainfall (>1700 mm/a). The performance of the IMERG Early, Late, and Final products was also elucidated across the different zones. The baseline data of monthly precipitation was collected from 91 meteorological stations in the period from 2001 to 2020. Three quantitative indexes were employed, including the metrics-correlation coefficient (CC), root mean square error (RMSE), and relative error (RE). A comprehensive analysis was conducted on the precision of IMERG products at the various spatial and temporal scales, as well as precipitation intervals. Results indicate that: 1) Both Early and Late products exhibited similar precision to underestimate the overall precipitation, whereas the Final product tended to overestimate the precipitation. 2) The increase in precipitation caused a decrease in the CC and RE for all products, while an increase in RMSE. The deviation thresholds after monthly precipitation estimation were 271, 272, and 351 mm for the Early, Late, and Final products, respectively. Once the actual monthly precipitation fell below these thresholds, an overestimation occurred and vice versa. 3) Spatially, the IMERG products demonstrated that there was a stronger correlation and greater variability in the areas with the higher precipitation, with the overestimation in the regions under low or moderate rainfall, and the underestimation under high rainfall. 4) Temporally, the precision of products was higher in the dry season during drought years. The Early and Late products performed adequately in autumn, indicating noticeable underestimations. The final product excelled in winter. 5) A decreasing trend was found in the precision of the Final product over the whole years, whereas, an ever-growing overestimation was in the Early and Late products. In conclusion, the precision of the monthly-scale IMERG product was notably influenced by the precipitation, indicating considerable discrepancies in the various regions and temporal scopes. Hence, it is recommended to conduct customized evaluations of product precision for the specific regions and time frames in practical applications. This finding can serve as a significant reference to monitor and manage the water resources for beneficial insights into the climate zones.