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Abstract Tropical cyclone (TC) hazards coupled with dense urban development along the coastline have resulted in trillions in US damages over the past several decades, with an increasing trend in losses in recent years. So far, this trend has been driven by increasing coastal development. However, as the climate continues to warm, changing TC climatology may also cause large changes in coastal damages in the future. Approaches to quantifying regional TC risk typically focus on total storm damage. However, it is crucial to understand the spatial footprint of TC damage and ultimately the spatial distribution of TC risk. Here, we quantify the magnitude and spatial pattern of TC risk (in expected annual damage) across the US from wind, storm surge, and rainfall using synthetic TCs, physics-based hazard models, and a county-level statistical damage model trained on historical TC data. We then combine end-of-century TC hazard simulations with US population growth and wealth increase scenarios (under the SSP2 4.5 emission scenario) to investigate the sensitivity of changes in TC risk across the US Atlantic and Gulf coasts. We find that not directly accounting for the effects of rainfall and storm surge results in much lower risk estimates and smaller future increases in risk. TC climatology change and socioeconomic change drive similar magnitude increases in total expected annual damage across the US (roughly 160%), and that their combined effect (633% increase) is much higher. 

Abstract Severe convective storms and tornadoes rank among nature’s most hazardous phenomena, inflicting significant property damage and casualties. Near-surface weather conditions are closely governed by large-scale synoptic patterns. It is crucial to delve into the involved multiscale associations to understand tornado potential in response to climate change. Using clustering analysis, this study unveils that leading synoptic patterns driving tornadic storms and associated spatial trends are distinguishable across geographic regions in the U.S. Synoptic patterns with intense forcing featured by intense upper-level eddy kinetic energy and a dense distribution of Z500 fields dominate the increasing trend in tornado frequency in the southeast U.S., generating more tornadoes per event. Conversely, the decreasing trend noted in certain regions of the central Great Plains is associated with weak upper-level synoptic forcing. These findings offer an explanation of observational changes in tornado occurrences, suggesting that the physical mechanisms driving those changes differ across regions. 

Abstract Despite its high tropical cyclone (TC) density, the Eastern North Pacific (ENP) basin has received relatively little research attention on landfall variability. This study investigates the climatological seasonal cycle and interannual variability of TC landfalls in the ENP. We find that the basin is characterized by a bimodal distribution of landfalls, with peaks in June and September–October. Using a composite analysis of high and low landfall years, we show that this distribution is primarily driven by landfall probability rather than genesis. The absence of landfalls during July is due to enhanced easterlies from the Caribbean Low‐Level Jet entering the ENP through gaps in the Americas Cordillera. High landfall years feature enhanced easterly wind reversals from a northward‐shifted Intertropical Convergence Zone. These additional steering winds drive hurricanes ashore in the vulnerable region of southwest Mexico. This study provides valuable insights for improving TC landfall forecasts and preparedness in the region. 

Abstract The effect of warming on severe convective storm potential is commonly explained in terms of changes in vertically integrated (“bulk”) environmental parameters, such as CAPE and 0–6-km shear. However, such events are known to depend on the details of the vertical structure of the thermodynamic and kinematic environment that can change independently of these bulk parameters. This work examines how warming may affect the complete vertical structure of these environments for fixed ranges of values of high CAPE and bulk shear, using data over the central Great Plains from two high-performing climate models (CNRM and MPI). To first order, projected changes in the vertical sounding structure are consistent between the two models: the environment warms approximately uniformly with height at constant relative humidity, and the shear profile remains relatively constant. The boundary layer becomes slightly drier (−2% to 6% relative humidity) while the free troposphere becomes slightly moister (+1% to 3%), with a slight increase in moist static energy deficit aloft with stronger magnitude in CNRM. CNRM indicates enhanced low-level shear and storm-relative helicity associated with stronger hodograph curvature in the lowest 2 km, whereas MPI shows near-zero change. Both models strongly underestimate shear below 1 km compared to ERA5, indicating large uncertainty in projecting subtle changes in the low-level flow structure in climate models. The evaluation of the net effect of these modest thermodynamic and kinematic changes on severe convective storm outcomes cannot be ascertained here but could be explored in simulation experiments. Significance StatementSevere thunderstorms and tornadoes cause substantial damage and loss of life each year, which raise concerns about how they may change as the world warms. We typically use a small number of common atmospheric parameters to understand how these localized events may change with climate change. However, climate change may alter the weather patterns that produce these events in ways not captured by these parameters. This work examines how climate change may alter the complete vertical structure of temperature, moisture, and wind and discusses the potential implications of these changes for future severe thunderstorms and tornadoes. 

Abstract Are the results of aerosol invigoration studies that neglect entrainment valid for diluted deep convective clouds? We address this question by applying an entraining parcel model to soundings from tropical and midlatitude convective environments, wherein pollution is assumed to increase parcel condensate retention. Invigoration of 5%–10% and <2% is possible in undiluted tropical and midlatitude parcels respectively when freezing is rapid. This occurs because the positive buoyancy contribution from freezing is larger than the negative buoyancy contribution from condensate loading, leading to positive net condensate contribution to buoyancy. However, aerosol‐induced weakening is more likely when realistic entrainment rates occur because water losses from entrainment more substantially reduce the latent heating relative to the loading contribution. This leads to larger net negative buoyancy contribution from condensates in polluted than in clean entraining parcels. Our results demonstrate that accounting for entrainment is critical in conceptual models of aerosol indirect effects in deep convection. 

Abstract It is often assumed in parcel theory calculations, numerical models, and cumulus parameterizations that moist static energy (MSE) is adiabatically conserved. However, the adiabatic conservation of MSE is only approximate because of the assumption of hydrostatic balance. Two alternative variables are evaluated here: MSE − IB and MSE + KE, wherein IB is the path integral of buoyancy (B) and KE is kinetic energy. Both of these variables relax the hydrostatic assumption and are more precisely conserved than MSE. This article quantifies the errors that result from assuming that the aforementioned variables are conserved in large-eddy simulations (LES) of both disorganized and organized deep convection. Results show that both MSE − IB and MSE + KE better predict quantities along trajectories than MSE alone. MSE − IB is better conserved in isolated deep convection, whereas MSE − IB and MSE + KE perform comparably in squall-line simulations. These results are explained by differences between the pressure perturbation behavior of squall lines and isolated convection. Errors in updraftBdiagnoses are universally minimized when MSE − IB is assumed to be adiabatically conserved, but only when moisture dependencies of heat capacity and temperature dependency of latent heating are accounted for. When less accurate latent heat and heat capacity formulae were used, MSE − IB yielded poorerBpredictions than MSE due to compensating errors. Our results suggest that various applications would benefit from using either MSE − IB or MSE + KE instead of MSE with properly formulated heat capacities and latent heats. 

Abstract The damage potential of a hurricane is widely considered to depend more strongly on an integrated measure of the hurricane wind field, such as integrated kinetic energy (IKE), than a point‐based wind measure, such as maximum sustained wind speed (V_max). Recent work has demonstrated that minimum sea level pressure (MSLP) is also an integrated measure of the wind field. This study investigates how well historical continental US hurricane damage is predicted by MSLP compared to bothV_maxand IKE for continental United States hurricane landfalls for the period 1988–2021. We first show for the entire North Atlantic basin that MSLP is much better correlated with IKE (r_rank = 0.50) thanV_max(r_rank = 0.26). We then show that continental US hurricane normalized damage is better predicted by MSLP (r_rank = 0.83) than eitherV_max(r_rank = 0.67) or IKE (r_rank = 0.65). For Georgia to Maine hurricane landfalls specifically, MSLP and IKE show similar levels of skill at predicting damage, whereasV_maxprovides effectively no predictive power. Conclusions for IKE extend to power dissipation as well, as the two quantities are highly correlated because wind radii closely follow a Modified Rankine vortex. The physical relationship of MSLP to IKE and power dissipation is discussed. In addition to better representing damage, MSLP is also much easier to measure via aircraft or surface observations than eitherV_maxor IKE, and it is already routinely estimated operationally. We conclude that MSLP is an ideal metric for characterizing hurricane damage risk.