The 2022 record-breaking high temperature in China: Sub-seasonal stepwise enhanced characteristics, possible causes and its predictability

Abstract

In the summer of 2022, an unprecedented and long-lasting high temperature swept central-eastern China, causing significant societal effects. However, the sub-seasonal characteristics, causes and predictability of this extreme high temperature event are not well explored. Based on the locations, intensities and causes of the high temperature, we divided it into three stages: early (13 June–3 July), sustained (4–28 July), and enhancement (29 July–30 August) stages. The high temperature during the early stage mainly occurred in north-central China with an anomaly of 2.5 °C compared with climatology (1981–2010), while the last two stages occurred in the middle and lower Yangtze River Basin with anomalies of 2.8 and 3.8 °C respectively. The high temperature during the three stages were all regulated by the strengthening and westward extension of the western Pacific subtropical high (WPSH) but involved different physical process. In the early stage, it was mainly caused by the anticyclones over the Mongolia and Northwest Pacific and enhanced by the minor impact of WPSH. In the sustained stage it was influenced by relatively more stronger WPSH and South Asia high (SAH) and the relatively minor impact of the anticyclone over the north-western South Asia. In the enhancement stage, the high temperature was mainly caused by a combination of the record-breaking WPSH and SAH and the strong European blocking high. Inside, the exceptionally powerful WPSH was well correlated with the sea surface temperature gradient induced by the developing La Niña. The ECMWF and NCEP models reasonably predicted the location and intensity of the high temperature in the early stage, but poorly predicted that in the sustained and enhancement stages partly because of the failure prediction of the WPSH's enhancement and westward extension. The ECMWF model's more accurate prediction of the WPSH may contribute to its better forecasting of the heatwaves.