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Early summer southern China rainfall variability and its oceanic drivers

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Rainfall in southern China reaches its annual peak in early summer (May–June) with strong interannual variability. Using a combination of observational analysis and numerical modeling, the present study investigates the… Click to show full abstract

Rainfall in southern China reaches its annual peak in early summer (May–June) with strong interannual variability. Using a combination of observational analysis and numerical modeling, the present study investigates the leading modes of this variability and its dynamic drivers. A zonal dipole pattern termed the southern China Dipole (SCD) is found to be the dominant feature in early summer during 1979–2014, and is closely related to a low-level anomalous anticyclone over the Philippine Sea (PSAC) and a Eurasian wave-train pattern over the mid–high latitudes. Linear regressions based on observations and numerical experiments using the CAM5 model suggest that the associated atmospheric circulation anomalies in early summer are linked to decaying El Niño-Southern Oscillation-like sea surface temperature (SST) anomalies in the tropical Pacific, basin-scale SST anomalies in the tropical Indian Ocean, and meridional tripole-like SST anomalies in the North Atlantic in the previous winter to early summer. The tropical Pacific and Indian Ocean SST anomalies primarily exert an impact on the SCD through changing the polarity of the PSAC, while the North Atlantic tripole-like SST anomalies mainly exert a downstream impact on the SCD by inducing a Eurasian wave-train pattern. The North Atlantic tripole-like SST anomalies also make a relatively weak contribution to the variations of the PSAC and SCD through a subtropical teleconnection. Modeling results indicate that the three-basin combined forcing has a greater impact on the SCD and associated circulation anomalies than the individual influence from any single oceanic basin.

Keywords: early summer; southern china; sst anomalies; summer; rainfall

Journal Title: Climate Dynamics
Year Published: 2017

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