In recent decades, inter-monthly variability of winter surface air temperature (SAT) in East Asia has become increasingly pronounced, often manifesting as sharp transitions between extreme cold and extreme warm events across different months or within different stages of winter. In China, SAT exhibits distinct month-to-month fluctuations, with some winters beginning anomalously warm and ending unusually cold, or vice versa. Previous studies have suggested that these fluctuations are influenced by atmospheric circulation anomalies and modulated by extratropical teleconnections in the mid-high latitudes. However, the specific teleconnection that exert dominant influence, as well as their relative roles, remain unclear.
This study investigates the spatial and temporal characteristics of inter-monthly SAT anomalies in China and investigates the impacts of Eurasian mid-high latitude teleconnection patterns on SAT variability during December-January-February (DJF) over the period 1979—2020. The leading empirical orthogonal function mode (EOF1) of monthly SAT anomalies reveals a pan-China variability pattern, characterized by two distinct types: 1) uniform anomalies of the same sign across DJF, and 2) anomalies of opposite sign between early winter (December) and late winter (next January-February). Together, these two types account for approximately 50% of the total EOF1 variance.
Analysis shows that the two types are associated with markedly different atmospheric circulation anomalies. Opposite-sign anomalies between early and late winter are primarily linked to the Polar-Eurasia (POL), East Atlantic (EA), and Eurasian (EU) patterns, while uniform anomalies across DJF are more strongly associated with the Arctic Oscillation (AO), POL, Scandinavian (SCA), western Pacific (WP), and EU patterns. These teleconnection anomalies alter the location and intensity of the Siberian high, thereby exerting significant control over inter-monthly SAT variability.
The results highlight the dominant role of anomalous teleconnection patterns on monthly timescales in shaping the leading mode (EOF1) of winter SAT variability in China. This study provides new insights into the mechanisms driving inter-monthly temperature fluctuations, with implications for seasonal climate prediction.