资源环境科技发展态势分析平台

The anomalous large-scale atmospheric circulation patterns concerned with surface air temperature and precipitation anomalies within East Asian Monsoon region for winter and summer months from 1979 to 2017 are analyzed by employing the self-organizing map (SOM) neural network. The asymmetric 3 x 4 SOM neural network is firstly constructed with the geopotential height anomalies at 500-hPa level as the only input variable. Then 12 characteristic anomalous large-scale atmospheric circulation patterns (nodes) are identified. The composites of temperature and precipitation anomalies as well as vertical wind anomalies at 500-hPa level assigned to each node are generated and visualized. The spatial distributions of anomalous geopotential height (anticyclones or cyclones) are highly consistent with that of surface air temperature anomalies in both winter and summer. Most precipitation extremes in winter are attributed to the joint effect of the horizontal and vertical atmospheric motions, while strong air convection is prone to inducing extreme precipitation events in summer. Based on the SOM classification, the differences of atmospheric circulations, temperature and precipitation anomalies have also been partly identified in strong and weak phases of East Asia Monsoon.