Annual and seasonal precipitation trends and their attributions in the Qinling Mountains, a climate transitional zone in China

• Published in: Theoretical and Applied Climatology
• Main Authors: Meng, Q., Bai, H., Sarukkalige, Ranjan, Fu, G., Jia, W., Zhang, C.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: 2021
• Subjects: Soi; North Atlantic; North Atlantic oscillation
• Online Access: https://hdl.handle.net/20.500.11937/84085; https://doi.org/10.1007/s00704-020-03482-z

In this study, annual and seasonal precipitation trends and their connection with large-scale climate indices in the Qinling Mountains (QMs) were investigated using the innovative trend analysis (ITA), based on observed monthly precipitation data between 1959 and 2016 from 32 meteorological stations. The results indicated a declining trend in annual precipitation in the QMs. Seasonally, a decreasing trend was also observed in spring and autumn, while increasing trends were observed in summer and winter. Spring and autumn precipitations significantly contributed to this observed decline in annual precipitation. More importantly, both low and high values indicated a declining trend, which would have a significant influence on ecology and livelihood in the QMs. Additionally, the results of wavelet coherence showed that annual precipitation is strongly associated with the East Asian Summer Monsoon Index (EASMI), Southern Oscillation Index (SOI), South Asian Summer Monsoon Index (SASMI), South China Sea Summer Monsoon Index (SCSMI), and Southwest Australian Circulation Index (SWACI). However, its relationship with the North Atlantic Oscillation (NAO) and West African Summer Monsoon Index (WASMI) was insignificant, and seasonally, EASMI had negative effects on the precipitation in each season. It was also observed that spring and autumn precipitations were more sensitive to SOI than SWACI, while SASMI had a strong positive relationship with winter precipitation, and SCSMI was more negatively related to autumn and winter precipitation. This study will provide scientific basis for precipitation forecast, prevention, and mitigation of flood in the future.