This study introduces an original methodology combining ensemble boosting and conditional probability theory to estimate return periods of rare climate extremes without relying on long climate simulations. The method is rigorously developed, validated on a red-noise process, and applied to CESM2 simulations, including an analysis of the 2021 Pacific Northwest heatwave. Importantly, this framework enables linking probability estimates to specific climate storylines, allowing an assessment of the odds that an extreme event like the one examined will occur in the future.

The occurrence and predictability of extreme events is often modulated by regional dynamical drivers, but their identification is not straightforward. This paper by Fiona Spuler et al. presents an innovate approach to dimensionality reduction targeted on regionally occurring phenomena. Their approach is based on a machine-learning method demonstrating, in a broad sense, that these method can identify physically interpretable drivers of targeted phenomena. The authors discuss the tradeoff between regime informativeness of local precipitation extremes and predictability of the regimes at subseasonal lead times. The novel machine-learning-based approach may find useful application beyond atmospheric and climate science.

This study provides a unifying framework for extratropical low-pressure systems with tropical characteristics like nearly axisymmetric inner cores, eyes, and spiral bands. These characteristics can be found, e.g., in subtropical cyclones, polar lows, and medicanes. The authors propose to call these cyclones CYCLOPs, which refers to "cyclones from locally originating potential intensity". The paper presents several case studies to explain and illustrate the new concept, and therefore the paper is also of particular educational value.

How precipitation over ocean regions changes with global warming is grounded in a well accepted theory, but there is so far no such theory to describe precipitation changes over land. This paper provides important theoretical, numerical and observational evidence for the sensitivity of orographically-induced precipitation in the tropics to background wind changes. The result that tropical orographic rainfall increases with cross-slope winds at a rate of 20-30% (which is more than twice the rate expected from simple "upslope flow” theory) has important implications for constraining future climate change, providing an avenue for reliable projections of continental precipitation without the need for climate models that explicitly resolve convection.

This study provides a novel Lagrangian perspective on cyclogenesis grounded in atmospheric energetics. While the energetics framework is commonly used to understand the planetary scale circulation, its application to synoptic scales is less explored. The authors establish a close connection between extratropical baroclinic zones and local available potential energy, and further analyze air parcel trajectories to link conversions between potential and kinetic energy to specific features of the developing cyclones. The results of this study offer insights into the local, synoptic and large scale contributions to cyclogenesis that are relevant for diverse disciplines in atmospheric and climate sciences.

High-impact medicanes, like Ianos September 2020, are occasionally poorly predicted by operational numerical weather prediction models, and it is therefore very important to understand the factors that limit their predictability and to eventually improve predictions. The well-written study by Pantillon et al. investigates simulations of medicane Ianos performed with 10 model setups, using different models, horizontal grid spacings, and representations of moist convection. Their results highlight the critical importance of a high-resolution representation of moist convection, and the coupling of convective and baroclinic processes in the cyclogenesis phase of the medicane. These results from the major modelling undertaking in this study have important ramifications also for practical forecasting.

Observations and climate models consistently indicate that, during the past decades in the tropics and subtropics, land surfaces at higher altitudes have been warming faster than lower-elevated ones, a phenomenon denoted as elevation-dependent warming (EDW). In this study, Byrne and co-authors quantify the magnitude of this effect, attribute it to greenhouse gas forcing, and provide a very thorough and comprehensive analysis of the underlying mechanisms. They identify Planck and surface albedo feedback as well as atmospheric energy transport as most important drivers of EDW, while water vapor and cloud feedback oppose EDW. In this way, the authors substantially improve our understanding of a fundamental aspect of current climate warming.

Understanding the specific dynamical processes leading to extreme floods is an important but challenging task. Ruff and Pfahl used an innovative approach that allowed them to go beyond single case studies. They used operational ensemble forecasts from the ECMWF during the period 2003-2019 and focused on five major river catchments in Central Europe. Comparing extreme events (with a return period of 100 years) with more moderate events revealed important differences between the catchments. For some catchments the main factors that distinguish 100-year events were the intensity of the upper-level cutoff and surface cyclone, whereas in other catchments the main factor was an increased low-tropospheric moisture supply. The original results clearly illustrate that regional variability is substantial and no single atmospheric process can be claimed responsible for the distinction between extreme and moderate flood events.

Numerical weather prediction depends essentially on high-quality upper-air wind observations to constrain the initial conditions. This study by Martin et al. investigates the impact of spaceborne Doppler wind lidar measurements from the Aeolus mission on forecast quality of the operational global forecasting system with ICON at Deutscher Wetterdienst. An observing system experiment shows an overall beneficial impact, and the authors go one important step further and present illustrative examples how events with strong forecast quality improvements can be related to specific dynamical phenomena such as ENSO and the extratropical transition of tropical cyclones.

This paper analyses the extensive scientific debate around the potential influence of Arctic warming and sea ice loss on recent cooling trends over the Eurasian continent. It provides a novel, holistic perspective on this debate that goes beyond a simple yes or no answer to the question whether a causal link exists between these two phenomena. As such, it has the potential to bring together seemingly diverging portrayals existing in the literature.

The paper by Tim Woollings et al. provides first a theoretical summary of the role of Rossby wave dynamics for polar variability, regarding the large-scale polar flow conceptually as a superposition of geostrophic turbulence and Rossby wave propagation, emphasising the key role of isolated vortices at high latitudes. In a second part, the paper addresses how comparatively weak Rossby waves can be triggered from high latitudes in the presence of a relative vorticity gradient as a direct response to sea ice loss, which often manifests as a heat low. The paper provides a well written and much needed foundation for an active area of research.