Recent occurrences of marine heatwaves (MHWs) in coastal China seas have caused serious impacts on marine ecosystem services and socio-economics. Nevertheless, the underlying physical process, including local drivers and remote associations, remains poorly understood, thereby hindering accurate predictability. In this study, we reported an extreme MHW event in the East China Seas (ECSs, including the Bohai, Yellow, and East China Sea), lasting for 75 d with a maximum intensity of 1.96 °C relative to 1982–2011 during the summer 2022. This ECSs MHW event was triggered by a combination of anomalous atmospheric and oceanic conditions, including enhanced insolation, weakened surface wind speed, suppressed latent heat loss from ocean, a shallower mixed layer, and upper ocean current anomaly. Mixed-layer temperature budget diagnosis suggested that changes in the ECSs temperature were dominated by the surface net heat flux, largely due to strong shortwave radiation flux, during the development and decay of the MHW event. Oceanic advection also created favorable conditions for the maintenance of the MHW. These physical drivers were further regulated by the westward expanded and intensified western Pacific subtropical high (WPSH), potentially linked to the negative phase of Indian Ocean Dipole (IOD). Despite the three years (2020–2022) consecutive La Niña events, the ECSs summer MHWs appeared to be more closely linked to negative IOD events, with a lagging period of 1–3 mon. The seasonal precursor signals of the negative IOD have the potential to affect local physical drivers of ECSs MHWs through regulating the strength and position of WPSH, thus serving as a promising predictor for the ECSs MHWs. The future likelihood and intensity of the ECSs MHWs are projected to increase substantially in the coming decades, largely due to broad-scale warming attributed to anthropogenic climate change. Consequently, there is an urgent need to develop MHW forecasting and early warning systems, and robust approaches to address climate change.