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Abstract A model for tropical cyclone (TC) potential size (PS), which is capable of predicting the equilibrium outer radius of a TC solely from environmental parameters, is proposed. The model combines an updated Carnot cycle model with a physical model for the wind profile, which serve as energetic and dynamic constraints, respectively, on the minimum pressure. Physically, the Carnot cycle model defines how much the surface pressure can be dropped energetically, and the wind profile model defines how large the steady-state storm needs to be to yield that pressure drop for a given maximum wind speed. The model yields an intrinsic length scale V Carnot / f , with f the Coriolis parameter, V Carnot similar to the potential intensity V p , but without a dependence on the surface exchange coefficients of enthalpy C k and momentum C d . Analytic tests with the theory varying outflow temperature, sea surface temperature (SST), and f demonstrate that the model predictions are qualitatively consistent with the V p / f scaling for outer size found in past work. The model also predicts a weak dependence of outer size on C d , C k , and horizontal mixing length l h of turbulence, consistent with numerical simulation results. Idealized numerical simulation experiments with varied tropopause temperature, SST, f , C d , C k , and l h show that the model performs well in predicting the simulated outer radius. The V Carnot / f scaling also better captures the dependence of simulated TC size on SST than V p / f . Overall, the model appears to capture the essential physics that determine equilibrium TC size on the f plane. 

Abstract Seasonal predictions of tropical cyclone (TC) landfalls are challenging because seasonal landfall count not only depends on the number and spatial distribution of TC genesis, but also whether those TCs are steered toward land or not. Past studies have separately examined genesis and landfall as a function of large-scale ocean and atmospheric environmental conditions. Here, we introduce a practical statistical framework for estimating the seasonal count of TC landfalls as the product of a Poisson model for seasonal TC genesis and a logistic model for landfall probability. We compute spatial variations in TC landfall and genesis by decomposing TC activity in the western North Pacific (WNP) basin into 10° × 10° bins, then identify coherent regions where El Niño–Southern Oscillation (ENSO) and the western extent of the Pacific subtropical high (WPSH) have significant influences on seasonal landfall count. Our framework shows that ENSO and the WPSH are weakly related to basinwide landfalls but strongly related to regional genesis and landfall probability. ENSO modulates the zonal distribution of TC genesis, consistent with past work, whereas the WPSH modulates the meridional distribution of landfall probability due to variations in steering flow associated with the Pacific subtropical high. These spatial patterns result in four coherent subregions of the WNP basin that define seasonal landfall variations: landfall count increases in the southwestern WNP during a positive WPSH and La Niña, the south-central WNP during a positive WPSH and El Niño, the eastern WNP during a negative WPSH and El Niño, and the northern WNP during a negative WPSH and La Niña. 

The impacts of a tropical cyclone after landfall depend not only on storm intensity but also on the size and structure of the wind field. Hence, a simple predictive model for the wind field after landfall has significant potential value. This work tests existing theory for wind structure and size over the ocean against idealized axisymmetric landfall experiments in which the surface beneath a mature storm is instantaneously dried and roughened individually or simultaneously. Structure theory captures the response of the low-level wind field to different types of idealized landfalls, given the intensity and size response. Storm size, modeled to follow the ratio of simulated time-dependent storm intensity to the Coriolis parameter, can generally predict the transient response of the storm gale wind radiir_34ktto inland surface forcings, particularly for at least moderate surface roughening regardless of the level of drying. Given knowledge of the intensity evolution, the above results combine to yield a theoretical model that can predict the full tangential wind field response to idealized landfalls.

A theoretical model that can predict the time-dependent wind field structure of landfalling tropical cyclones (TCs) with a small number of physical, observable input parameters is essential for mitigating hazards and allocating public resources. This work provides a first-order prediction of storm size and structure after landfall, which can be combined with existing intensity predictions to form a simple model describing the inland wind field evolution. Results show its potential utility for modeling idealized inland TC wind fields.

 

This article introduces an analytic formula for entraining convective available potential energy (ECAPE) with an entrainment rate that is determined directly from an environmental sounding, rather than prescribed by the formula user. Entrainment is connected to the background environment using an eddy diffusivity approximation for lateral mixing, updraft geometry assumptions, and mass continuity. These approximations result in a direct correspondence between the storm-relative flow and the updraft radius and an inverse scaling between the updraft radius squared and entrainment rate. The aforementioned concepts, combined with the assumption of adiabatic conservation of moist static energy, yield an explicit analytic equation for ECAPE that depends entirely on state variables in an atmospheric profile and a few constant parameters with values that are established in past literature. Using a simplified Bernoulli-like equation, the ECAPE formula is modified to account for updraft enhancement via kinetic energy extracted from the cloud’s background environment. CAPE and ECAPE can be viewed as predictors of the maximum vertical velocityw_maxin an updraft. Hence, these formulas are evaluated usingw_maxfrom past numerical modeling studies. Both of the new formulas improve predictions ofw_maxsubstantially over commonly used diagnostic parameters, including undiluted CAPE and ECAPE with a constant prescribed entrainment rate. The formula that incorporates environmental kinetic energy contribution to the updraft correctly predicts instances of exceedance ofbyw_max, and provides a conceptual explanation for why such exceedance is rare among past simulations. These formulas are potentially useful in nowcasting and forecasting thunderstorms and as thunderstorm proxies in climate change studies.

Substantial mixing occurs between the upward-moving air currents in thunderstorms (updrafts) and the surrounding comparatively dry environmental air, through a process called entrainment. Entrainment controls thunderstorm intensity via its diluting effect on the buoyancy of air within updrafts. A challenge to representing entrainment in forecasting and predictions of the intensity of updrafts in future climates is to determine how much entrainment will occur in a given thunderstorm environment without a computationally expensive high-resolution simulation. To address this gap, this article derives a new formula that computes entrainment from the properties of a single environmental profile. This formula is shown to predict updraft vertical velocity more accurately than past diagnostics, and can be used in forecasting and climate prediction to improve predictions of thunderstorm behavior and impacts.

 

This work evaluates how well Coupled Model Intercomparison Project 6 models reproduce the climatology of North American severe convective storm (SCS) environments in ERA5 reanalysis and examines what drives biases across models. Biases in spring SCS environments vary widely in magnitude and spatial pattern, though most models do well in reproducing the climatological pattern and a few (MPI and CNRM) also reproduce the overall magnitude. SCS biases are driven by biases in extreme convective available potential energy. These biases are ultimately found to be driven by biases in mean‐state near‐surface moist static energy, indicating that the SCS environments depend strongly on the near‐surface mean state. Results are similar for fall, but not summer or winter when free‐tropospheric biases are also important. Biases differ strongly across parent models but weakly across child models of the same parent. These outcomes help identify models well‐suited for studying climate effects on SCS environments.

 

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 Tropical cyclones cause significant inland hazards, including wind damage and freshwater flooding, which depend strongly on how storm intensity evolves after landfall. Existing theoretical predictions for storm intensification and equilibrium storm intensity have been tested over the open ocean but have not yet been applied to storms after landfall. Recent work examined the transient response of the tropical cyclone low-level wind field to instantaneous surface roughening or drying in idealized axisymmetric f -plane simulations. Here, experiments testing combined surface roughening and drying with varying magnitudes of each are used to test theoretical predictions for the intensity response. The transient response to combined surface forcings can be reproduced by the product of their individual responses, in line with traditional potential intensity theory. Existing intensification theory is generalized to weakening and found capable of reproducing the time-dependent inland intensity decay. The initial (0–10 min) rapid decay of near-surface wind caused by surface roughening is not captured by existing theory but can be reproduced by a simple frictional spindown model, where the decay rate is a function of surface drag coefficient. Finally, the theory is shown to compare well with the prevailing empirical decay model for real-world storms. Overall, results indicate the potential for existing theory to predict how tropical cyclone intensity evolves after landfall. 

Recent work found evidence using aquaplanet experiments that tropical cyclone (TC) size on Earth is limited by the Rhines scale, which depends on the planetary vorticity gradientβ. This study aims to examine how the Rhines scale limits the size of an individual TC. The traditional Rhines scale is first reexpressed as a Rhines speed to characterize how the effect ofβvaries with radius in a vortex whose wind profile is known. The framework is used to define the vortex Rhines scale, which is the transition radius that divides the vortex into a vortex-dominant region at smaller radii, where the axisymmetric circulation is steady, and a wave-dominant region at larger radii, where the circulation stimulates planetary Rossby waves and dissipates. Experiments are performed using a simple barotropic model on aβplane initialized with a TC-like axisymmetric vortex defined using a recently developed theoretical TC wind profile model. The gradientβand initial vortex size are each systematically varied to investigate the detailed responses of the TC-like vortex toβ. Results show that the vortex shrinks toward an equilibrium size that closely follows the vortex Rhines scale. A larger initial vortex relative to its vortex Rhines scale will shrink faster. The shrinking time scale is well described by the vortex Rhines time scale, which is defined as the overturning time scale of the circulation at the vortex Rhines scale and is shown to be directly related to the Rossby wave group velocity. The relationship between our idealized results and the real Earth is discussed. Results may generalize to other eddy circulations, such as the extratropical cyclone.

Tropical cyclones vary in size significantly on Earth, but how large a tropical cyclone could potentially be is still not understood. The variation of the Coriolis parameter with latitude is known to limit the size of turbulent circulations, but its effect on tropical cyclones has not been studied. This study derives a new parameter related to this concept called the “vortex Rhines scale” and shows in a simple model how and why storms will tend to shrink toward this size. These results help explain why tropical cyclone size tends to increase slowly with latitude on Earth and can help us understand what sets the size of tropical cyclones on Earth in general.

 

The radius of maximum wind (R_max) in a tropical cyclone governs the footprint of hazards, including damaging wind, surge, and rainfall. However,R_maxis an inconstant quantity that is difficult to observe directly and is poorly resolved in reanalyses and climate models. In contrast, outer wind radii are much less sensitive to such issues. Here we present a simple empirical model for predictingR_maxfrom the radius of 34-kt (1 kt ≈ 0.51 m s⁻¹) wind (R_17.5 ms). The model only requires as input quantities that are routinely estimated operationally: maximum wind speed,R_17.5 ms, and latitude. The form of the empirical model takes advantage of our physical understanding of tropical cyclone radial structure and is trained on the Extended Best Track database from the North Atlantic 2004–20. Results are similar for the TC-OBS database. The physics reduces the relationship between the two radii to a dependence on two physical parameters, while the observational data enables an optimal estimate of the quantitative dependence on those parameters. The model performs substantially better than existing operational methods for estimatingR_max. The model reproduces the observed statistical increase inR_maxwith latitude and demonstrates that this increase is driven by the increase inR_17.5 mswith latitude. Overall, the model offers a simple and fast first-order prediction ofR_maxthat can be used operationally and in risk models.

If we can better predict the area of strong winds in a tropical cyclone, we can better prepare for its potential impacts. This work develops a simple model to predict the radius where the strongest winds in a tropical cyclone are located. The model is simple and fast and more accurate than existing models, and it also helps us to understand what causes this radius to vary in time, from storm to storm, and at different latitudes. It can be used in both operational forecasting and models of tropical cyclone hazard risk.