Seasonal Prediction of Climate Extremes: Mechanisms, Models, and Societal Applications

Background Climate extremes, including heatwaves, droughts, heavy precipitation, tropical and extratropical storms, atmospheric rivers, wildfires, marine heatwaves, and compound events, pose growing risks to human health, infrastructure, agriculture, water resources, energy systems, and ecosystems. Anticipating these extremes weeks to months in advance is one of the most consequential challenges in climate science, yet predictive skill remains uneven across regions, seasons, and hazard types. This Research Topic focuses on the seasonal timescale (roughly one to six months ahead), a window that sits at the heart of operational climate services, disaster preparedness, and resource planning. Despite two decades of progress driven by improved coupled Earth system models, ensemble forecasting, and data assimilation, the physical mechanisms governing seasonal predictability of extremes remain incompletely understood, and translating forecast skill into actionable societal guidance remains an open challenge. ScopeThis Research Topic is organized around two interlinked questions: what drives the seasonal predictability of climate extremes, and how can that predictability be more effectively modeled, communicated, and applied? Key sources of predictability under investigation include ENSO and its diverse flavors, Indian Ocean variability, the Pacific Meridional Mode (PMM), Atlantic multidecadal variability, the NAO, PNA, and PDO, land-atmosphere coupling, sea ice variability, and large-scale teleconnections. The collection gives particular emphasis to hazard types that warrant deeper treatment at seasonal lead times: compound extremes, marine heatwaves, wildfire-conducive conditions, and renewable energy resources (wind and solar). The Topic particularly encourages interdisciplinary studies linking seasonal predictability to societal impacts and decision-making. Potential topics include, but are not limited to: o Seasonal prediction and predictability of climate extremes, including heatwaves, cold extremes, droughts, floods, atmospheric rivers, and wildfireso Seasonal prediction of compound climate extremeso Seasonal prediction of marine heatwaves and ocean-atmosphere coupled extremeso Physical mechanisms and large-scale teleconnections governing seasonal predictability (ENSO, PMM, IOD, NAO, PNA, PDO, AMV, and related modes)o Seasonal predictability of tropical cyclones, extratropical cyclones, storm tracks, and atmospheric blockingo Seasonal prediction of renewable energy resources (wind, solar)o Climate prediction for energy demand, agriculture, water resources, and disaster risk reductiono AI and machine learning applications in seasonal forecastingo Hybrid dynamical-statistical prediction systemso Ensemble design, forecast calibration, and verification of seasonal forecast systemso Predictability diagnostics, hindcast analysis, and attribution studieso Operationally relevant seasonal outlooks and climate serviceso Stratosphere-troposphere interactions Topic editors: Xiaosong Yang, Wei Zhang, Yushi Morioka, Marisol Osman Source: https://www.frontiersin.org/research-topics/82120/seasonal-prediction-of-climate-extremes-mechanisms-models-and-societal-applications