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Abstract Genesis potential indices (GPIs) are widely used to understand the climatology of tropical cyclones (TCs). However, the sign of projected future changes depends on how they incorporate environmental moisture. Recent theory combines potential intensity and midtropospheric moisture into a single quantity called the ventilated potential intensity, which removes this ambiguity. This work proposes a new GPI (GPI_υ) that is proportional to the product of the ventilated potential intensity and the absolute vorticity raised to a power. This power is estimated to be approximately 5 by fitting observed tropical cyclone best track and ECMWF Reanalysis v5 (ERA5) data. Fitting the model with separate exponents yields nearly identical values, indicating that their product likely constitutes a single joint parameter. Likewise, results are nearly identical for a Poisson model as for the power law. GPI_υperforms comparably well to existing indices in reproducing the climatological distribution of tropical cyclone genesis and its covariability with El Niño–Southern Oscillation, while only requiring a single fitting exponent. When applied to phase 6 of the Coupled Model Intercomparison Project (CMIP6) projections, GPI_υpredicts that environments globally will become gradually more favorable for TC genesis with warming, consistent with prior work based on the normalized entropy deficit, though significant changes emerge only at higher latitudes under relatively strong warming. The GPI_υhelps resolve the debate over the treatment of the moisture term and its implication for changes in TC genesis favorability with warming, and its clearer physical interpretation may offer a step forward toward a theory for genesis across climate states. Significance StatementTropical cyclones cause significant human impacts globally, yet we currently do not understand what controls the number of storms that form each year. Tropical cyclone formation depends on fine-scale processes that our climate models cannot capture. Thus, it is common to use parameters from the background environment to represent regions favorable for cyclone formation. However, there are a variety of formulations because the link between environment and cyclone formation is complicated. This work proposes a new method that unifies a few common formulations, which helps resolve a divergence in current explanations of how tropical cyclone formation may change under climate change. 

Abstract This paper presents a proof of concept for a new analogue-based framework for the detection and attribution of hurricane-related hazards. This framework addresses two important limitations of existing analogue-based methodologies: the lack of observed similar events, and the unsuitability of the distance metrics for hurricanes. To do so, we use a track-based metric, and we make use of synthetic tracks catalogues. We show that our method allows for selecting a sufficient number of suitable analogues, and we apply it to nine hurricane cases. Our analysis does not reveal any robust changes in wind hazards, translation speed, seasonality, or frequency over recent decades, consistent with current literature. This framework provides a reliable alternative to traditional analogue-based methods in the case of hurricanes, complementing and potentially enhancing efforts in addressing extreme weather event attribution. 

Abstract The El Niño—Southern Oscillation (ENSO) is an important mode of tropical Pacific atmosphere‐ocean variability that drives teleconnections with weather and climate globally. However, prior studies using state‐of‐the‐art climate models lack consensus regarding future ENSO projections and are often impacted by tropical Pacific sea‐surface temperature (SST) biases. We used 173 simulations from 29 climate models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) to analyze model biases and future ENSO projections. We analyzed two ENSO indices, namely the ENSO Longitude Index (ELI), which measures zonal shifts in tropical Pacific deep convection and accounts for changes in background SST, and the Niño 3.4 index, which measures SST anomalies in the central‐eastern equatorial Pacific. We found that the warm eastern tropical‐subtropical Pacific SST bias typical of previous generations of climate models persists into many of the CMIP6 models. Future projections of ENSO shift toward more El Niño‐like conditions based on ELI in 48% of simulations and 55% of models, in association with a future weakening of the zonal equatorial Pacific SST gradient. On the other hand, none of the models project a significant shift toward La Niña‐like conditions. The standard deviation of the Niño 3.4 index indicates a lack of consensus on whether an increase or decrease in ENSO variability is expected in the future. Finally, we found a possible relationship between historical SST and low‐level cloud cover biases in the ENSO region and future changes in ELI; however, this result may be impacted by limitations in data availability. 

Poleward migration is an interesting phenomenon regarding the shift of Tropical Cyclones (TCs) towards higher latitudes. As climate warms, TCs’ intensification is promoted, and yet over certain oceans, TCs may also migrate poleward into colder waters. To what extent this poleward shift can impact future TC’s intensification is unclear, and a quantitative understanding of these competing processes is lacking. Through investigating one of the most likely TC basins to experience poleward migration, the western North Pacific (WNP), here we explore the issue. Potential Intensity (PI, TC’s intensification upper bound) along TC’s intensification locations (from genesis to the lifetime maximum intensity location) are analysed. We find that poleward migration can partially cancel global warming’s positive impact on future WNP TC’s intensification. With poleward migration, the PI increasing trend slope is gentler. We estimate that poleward migration can reduce the increasing trend slope of the proportion of Category-5 PI by 42% (22%) under a strong (moderate) emission pathway; and 68% (30%) increasing trend slope reduction for the average PI.