Summer heatwaves over Europe, which can cause many deaths and severe damage, have become increasingly frequent over central and eastern Europe and western Russia in recent decades. In this paper, we estimate the contributions of the warming due to increased greenhouse gases (GHG) and nonlinear variations correlated with the Atlantic Multidecadal Oscillation (AMO) to the observed heatwave trend over Europe during 1980–2021, when the GHG‐induced warming over Europe exhibits a linear trend. It is found that GHG‐induced warming contributes to ∼57% of the European heatwave trend over 1980–2021, while the cold‐to‐warm phase shift of the AMO‐like variations accounts for ∼43% of the trend via the intensification of midlatitude North Atlantic jet. The recent trend of heatwaves over western and northern Europe is mainly due to GHG‐induced warming, while that over central and eastern Europe and western Russia is primarily related to the combined effect of the AMO‐like variations and GHG‐induced warming. To some extent, GHG‐induced warming is an amplifier of the increasing trend of recent AMO‐related European heatwaves. Moreover, European blocking (Ural blocking, UB) is shown to contribute to 55% (42%) of the AMO‐related heatwave trend via the influence of midlatitude North Atlantic jet. In the presence of a strong North Atlantic jet during the recent warm AMO phase, UB events concurrent with positive‐phase North Atlantic Oscillation can cause intense, persistent and widespread heatwaves over Europe such as that observed in the summer of 2022.

The North Pacific sea surface temperature (SST) has a profound climatic influence. The El Niño‐Southern Oscillation (ENSO) significantly impacts the North Pacific SST; however, the influence of the distinct phases of ENSO on SST predictability remains unclear. To overcome the model limitations, this study assessed SST predictability under diverse ENSO phases using reanalysis. The predictability limit of the North Pacific SST under La Niña (8.4 months) is longer than that under Neutral (5.9 months) and El Niño (5.5 months) conditions, which unveils asymmetry. This asymmetry mirrors contemporary multimodal prediction skills. Error growth dynamics reveal La Niña's robust signal strength with a slow error growth rate, in contrast to El Niño's weaker signal and faster error growth. There exhibits intermediate signal strength and elevated error growth in Neutral condition. Physically, predictability signal strength aligns with SST variability, whereas the error growth rate correlates with atmospheric‐ocean heating anomalies. La Niña, which induces positive heating anomalies, minimizes the impact of atmospheric noise, resulting in lower error growth. The result is beneficial for improving North Pacific SST predictions.