Abstract. Accurately assessing cloud feedback on global warming is essential for producing reliable climate projections. Linear regression analysis is a widely used method for this purpose, offering a straightforward approach for examining the relationship between cloud radiative effects and global-mean surface temperature. However, the El Niño–Southern Oscillation (ENSO) can significantly contribute to these estimates, which is often overlooked due to ENSO's relatively short periodicity (2–7 years). Using 72 years of reanalysis data and 150 years of simulations by 11 global climate models, this study demonstrates that, over a large portion of the low- to mid-latitude oceans, ENSO can contribute up to a few W m−2 K−1 to the regression-based cloud feedback estimates over decades and even centuries. Through a detailed spatial and temporal analysis, our findings underscore the importance of accounting for and removing ENSO's influence to improve the accuracy of cloud feedback assessments in the context of global warming.
Liu et al. (Thu,) studied this question.