There is a crucial societal need to develop an integrated capability to understand, attribute, and predict annual to decadal changes in the Earth’s climate system, including capabilities for early warning of potential high-impact events and changes. To meet this need, the climate science community needs to provide actionable scientific information that meets the evolving needs of societies all over the world. This goal is shared by the World Climate Research Programme (WCRP) Lighthouse Activity on Explaining and Predicting Earth System Change (EPESC) and by the WCRP’s core project Atmospheric Processes and their Role in Climate (APARC) Large Ensembles for Attribution of Dynamically-driven ExtRemes (LEADER) activity.

In pursuit of this goal, this special issue welcomes research that addresses prediction, projection, and attribution of phenomena and events acting on annual to decadal timescales. This includes evaluating existing and developing new methodologies to attribute and predict changes and extremes driven by the atmospheric or oceanic circulation. We also seek advances that can lead to more reliable quantitative attribution statements to support the Global Annual to Decadal Climate Update and State of the Climate reports issued by the World Meteorological Organization and to improved projections.

While early warnings of changes in the Earth system are now potentially possible through, e.g., operational decadal predictions, there are several challenges: there is a lack of understanding of the dynamical mechanisms that enable such projections, and there is evidence that global models underestimate some predictable signals and that there are systematic discrepancies between simulated and observed trends. The special issue seeks research that highlights these challenges and improves our understanding of the causes of regional climate changes, needed both to attribute recent events and to gain further confidence in forecasts.

A particular focus of this special issue is papers that analyze output from the Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP; Smith et al., 2022), as these coordinated model experiments will enable the impacts of different external drivers to be isolated that otherwise would be buried under internal variability while also offering a testbed for methods to extract predictable signals with the correct amplitude.

Review process: This inter-journal special issue co-lists papers of different journals. Thereby, each paper was submitted to 1 particular journal and underwent the regular interactive peer-review process of that journal. The peer review was handled by regular members of the editorial board.