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By using the one-month‑lead predictions from the Climate Forecast System version 2 (CFSv2), this study evaluates the predictability of the unprecedented heatwaves hitting the Yangtze River Valley (YRV) and Tibetan Plateau (TP) in 2022 late summer. CFSv2 successfully reproduces the central China heatwaves, but shows distinct performances between the YRV and TP. Specifically, CFSv2 exhibits stronger ability to capture TP heatwaves that is close to the highest historical prediction record, whereas the predicted extremity of the YRV heatwaves is underestimated compared to the observations. The accurate simulation of the intense upper-level circumglobal teleconnection (CGT) pattern, particularly for the East Asia CGT center (CGT EA), is essential for the success predictions of high temperature anomalies, due to the strong and accurate linkage between CGT EA and YRV/TP heatwaves in CFSv2. The intense CGT pattern is associated with a stronger model response to developing La Niña in CFSv2, quite different from the observed leading contribution from the unprecedented Pakistan rainfall. The impacts of developing La Niña and Pakistan rainfall on the intense CGT pattern are significantly overestimated and underestimated by CFSv2, respectively. Additionally, the La Niña-forced enhancement of lower-level western Pacific subtropical high (WPSH) plays another important role in YRV heatwaves, but the reproduction of WPSH intensity is unable to reflect YRV heatwaves in CFSv2 due to the southeastward shift of the predicted WPSH location, which should be responsible for the underestimated YRV heatwaves. The model improvements in aspect of the Pakistan rainfall, El Niño-Southern Oscillation–CGT linkage and lower-level WPSH location should help effectively predict the central China heatwaves in the future. • CFSv2 successfully predicts the central China heatwaves in 2022 late summer. • The accurately predicted CGT is essential for the reproduction of heatwaves. • La Niña leads to the intense CGT in CFSv2 rather than Pakistan rainfall in observation. [ABSTRACT FROM AUTHOR]