Spatio–Temporal Variation of Extreme Climates and Its Relationship with Teleconnection Patterns in Beijing–Tianjin–Hebei from 1980 to 2019 - Jinjie Wang; Anzhou Zhao (Atmosphere, 2022)
Extreme climate events have a significant impact both on the ecological environment and human society, and it is crucial to analyze the spatial–temporal evolutionary trends of extreme climate. Based on the RClimDex model, this study used trend analysis, probability density function, and wavelet coherence analysis to analyze the spatiotemporal variation characteristics of extreme climate indices and their response mechanisms to teleconnection patterns. The results of the study show that: (1) All the extreme precipitation indices, except max 1-day precipitation amount, max 5-day precipitation amount, and extremely wet days increased, with no significant abrupt changes. The extreme warm indices increased and extreme cold indices decreased. The years with abrupt changes were mainly distributed between 1988 and 1997. (2) Spatially, the extreme precipitation indices of most meteorological stations decreased, except for the simple daily intensity index and the number of very heavy precipitation days. The extreme warm indices of most meteorological stations increased, and the extreme cold indices decreased. (3) Except for consecutive dry days, the frequency of extreme precipitation indices increased significantly, the severity and frequency of high-temperature events increased, while the frequency of low-temperature events increased, but the severity decreased. The results of rescaled range (R/S) analysis indicated that the climate in the Beijing–Tianjin–Hebei region will further tend to be warm and humid in the future. (4) The Polar/Eurasia Pattern, the East Atlantic Pattern, the Arctic Oscillation, and the East Atlantic/West Russian Pattern were most closely associated with extreme climate events in the Beijing–Tianjin–Hebei region. The multi-factor combination greatly enhanced the explanatory power of the teleconnection pattern for extreme climates.