SOM-based synoptic analysis of atmospheric circulation patterns and temperature anomalies in China

Abstract

Anomalous atmospheric circulation patterns in relation to surface air temperature anomalies during 1979–2017 within China are investigated using the self-organizing map neural network. The SOM-based synoptic analysis begins with classifying the normalized daily anomalies of 500-hPa geopotential height, zonal and meridional winds fields into 4 × 4 SOM arrays in winter and summer, respectively. The synoptic analysis shows that the spatial distributions of anomalous geopotential height (anticyclones or cyclones) are highly consistent with that of surface air temperature anomalies within China. The influences of two teleconnections, the El Niño-Southern Oscillation and the Arctic Oscillation, on anomalous atmospheric circulation patterns and surface air temperature anomalies are also visually investigated based on the above SOM classification. Changes of node frequencies in winter and summer for the two periods 1979–1998 and 1999–2017 are also observed indicting the changes of regional atmospheric circulations. Our analysis also shows that the decrease of cold extreme and the increase of warm extreme in the two periods are mainly caused by the thermodynamics factor within China, while change in atmospheric circulation sometimes contributes negatively to temperature extreme changes.