Why was South China extremely wet during January–February 2022 despite La Niña? - Ma, Hedi; Wang, Ruili; Li, Xing; Lai, Anwei; Yang, Hao; Li, Xiao (Frontiers in Earth Science, 2022)
The boreal winter climate of 2022 was characterized by the occurrence of La Niña, which is one of the most predictable drivers of South China precipitation (SCP) deficit. However, surprisingly, the South China (SC) had received abnormally high precipitation in January-February (JF) 2022. Possible causes of the deviation of JF 2022 SCP from its historical response to La Niña are explored with observational and reanalysis data. Results suggest the La Niña event in winter 2022 features an eastern Pacific (EP) type, which corresponds to a weaker zonal sea surface temperature (SST) gradient between the equatorial central and western Pacific than those of the historical La Niña events, leading to a weaker western North Pacific (WNP) cyclone (WNPC) anomaly. Meanwhile, the SST warming over the tropical Indian Ocean (TIO) would also weaken the La Niña associated WNP circulation anomaly. Therefore, the flavor of La Niña and the TIO warming act in concert to dampen the La Niña-associated WNPC anomaly and the SCP deficit. But these tropical SST anomalies are still insufficient to explain the extremely high SCP. Further investigation identifies two extra-tropical circulation patterns over Eurasia that dominant the SCP anomalies in JF 2022. One is the wave train propagating along the south Asian jet that intensifies the India-Burma trough. It enhances the SCP through exciting anomalous strong moisture transport from Bay of Bengal and ascending motion. The other is the positive geopotential height anomaly over the eastern Siberia that prompts southward cold air intrusion and convergence over the SC region. These two dynamical drivers can account for approximately 75% of the observed SCP anomaly in JF 2022. However, they may be largely attributed to the atmospheric internal dynamical processes, which implies limited seasonal predictability of this extreme wet event.