A series of typhoons and tropical storms have produced extreme precipitation events in Vietnam during the first part of the 2020 monsoon season: events of this magnitude pose significant. challenges to remote sensing Quantitative Precipitation Estimation (QPE) techniques. The weathermonitoring

needs of modern human activities require that these challenges be overcome. In order to address this issue, in this work, seven precipitation products were validated with high spatial and temporal detail against over 1200 rain gauges in Vietnam during six case studies tailored around the most intense events of 2020. The data sources included the Vietnamese weather radar network, IMERG Early run and Final run, the South Korean GEO-KOMPSAT-2A and Chinese FengYun-4A geostationary satellites, DPR on board the GPM-Core Observatory, and European ERA5-Land reanalysis.

All products were resampled to a standardized 0.02? grid and compared at hourly scale with ground stations measurements. The results indicated that the radars product was the most capable of reproducing the information collected by the rain gauges during the selected extreme events, with a correlation coefficient of 0.70 and a coefficient of variation of 1.38. However, it exhibited some underestimation, approximately 30%, in both occurrence and intensity. Conversely, geostationary products tended to overestimatemoderate rain rates (FY-4A) and areas with low precipitation (GK-2A).

More complex products such as ERA5-Land and IMERG failed to capture the highest intensities typical of extreme events, while GPM-DPR showed promising results in detecting the highest rain rates, but its capability to observe isolated events was limited by its intermittent coverage.



Keywords: Vietnam; precipitation; satellite; rain gauge; AWS; weather radar; QPE validation; IMERG; GEO-KOMPSAT-2A; FengYun-4A