Analyzing the Spatiotemporal Characteristics of Extreme Rainfall Using CAPE and GNSS-Derived ZTD Across China

The power-law relationship between precipitable water vapor (PWV)/convective available potential energy (CAPE) and extreme rainfall (ER) has been explored. However, the retrieval of PWV is reliant on the zenith total delay (ZTD) of the Global Navigation Satellite System (GNSS), and errors are introduced when converting ZTD to PWV. In this study, we propose the ZTD, CAPE, and ER (ZCER) model, a comprehensive analysis model that integrates ZCER, for investigating long-term variation in ER intensity and frequency, which expresses their close relationships in a novel approach and expands the application area of GNSS-derived ZTD. Daily ZTD, CAPE, and rainfall data were collected from 219 GNSS stations in China from 2011 to 2020 (ten years). Time- and frequency-domain information encapsulated in the three variables was extracted using wavelet coherence, proving that both ZTD and CAPE contributed to rainfall. The relationships between ZTD/loge(CAPE) and loge(ER) were investigated at the annual, seasonal, and monthly scales. The results revealed that the contribution of ZTD/CAPE to ER varied spatially and temporally. Furthermore, the synergistic contributions of ZTD and CAPE to ER were further investigated. Statistical results showed that CAPE and ZTD complemented each other not only on the geographical scales to ER in China, but also on the seasonal and monthly scales. Moreover, the qualitative relationships between the ZCER frequency were elucidated. Our findings validate the strong links between high ZCER intensity and frequency in China on geographical and temporal scales.