Analysis of Monsoon Characteristics in China Based on Precipitable Water Vapor Derived From GNSS and ERA5 Over 2016–2020

Climate over China is mainly governed by monsoons, which bring frequent and intense convective precipitations. Adequate knowledge of monsoon characteristics is necessary for understanding the development of extreme weather events. Given that the monsoon is usually associated with distinct variations in water vapor between dry and wet seasons and rapid dry‐wet transitions, understanding the distribution and variability of water vapor can help characterize the monsoon. In this work, global navigation satellite system (GNSS) data from over 1,000 stations densely distributed in China were used to obtain zenith tropospheric delays (ZTDs). Combined with ERA5 meteorological data, precipitable water vapor (PWV) grid products were retrieved during the period 2016–2020 to characterize the Asian Summer Monsoon (ASM). To address the issue of data gaps in GNSS‐derived PWV, we employed a random forest machine learning method using ERA5‐derived PWV for data imputation ensuring the integrity of the products. We first utilized the bimodality of PWV statistical distribution and selected a suitable metric to quantify the monsoon impact across different regions. Subsequently, the normalized precipitable water indexes (NPWI) were constructed based on temporal variations in PWV to describe the monsoon movement characteristics. The average monsoon onset in China occurs from late May to mid‐June (Day of year (DOY) 150–170), whereas the monsoon retreat takes place in September (DOY 252–274). The interannual variability of the monsoon onset and retreat times is similar with a variation of around 10 days. Generally, the monsoon advances from southeast to northwest over China with an uneven speed.