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James P. Kossin

Abstract

Temperatures in the upper troposphere of the atmosphere, near the tropopause, play a key role in the evolution of tropical cyclones (TC) by controlling their potential intensity (PI), which describes the thermodynamically based maximum TC intensity that the environment will support. Accurately identifying past trends in PI is critical for understanding the causes of observed changes in TC intensity, but calculations of PI trends using different atmospheric reanalysis products can give very different results, largely due to differences in their representation of upper-tropospheric temperatures. Without a means to verify the fidelity of the upper-tropospheric temperatures, PI trends calculated from these products are very uncertain.

Here, a method is introduced to validate the upper-tropospheric temperatures in the reanalysis products by using the TCs themselves as thermometers. Using a 30-yr global dataset of TC cloud-top temperatures and three widely utilized atmospheric reanalysis products—Modern-Era Retrospective Analysis for Research and Applications (MERRA), ECMWF interim reanalysis (ERA-Interim), and NCEP–NCAR Global Reanalysis 1—it is shown that storm-local upper-level temperatures in the MERRA and ERA-Interim data vary similarly to the TC cloud-top temperatures on both interannual and decadal time scales, but the NCEP–NCAR data have substantial biases that introduce an increasing trend in storm-local PI not found in the other two products. The lack of global storm-local PI trends is due to a balance between temporal increases in the mean state and the poleward migration of TCs into lower climatological PI, and it has significant implications for the detection and attribution of mean TC intensity trends.

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James P. Kossin

Abstract

The relationship between minimum central surface pressure and the maximum sustained surface wind in tropical cyclones has been studied for many years, motivated by the fact that minimum pressure is generally easier to measure, but maximum wind is a much more relevant metric when considering tropical cyclone risk and potential impacts. It is well understood that tropical cyclone wind is closely related to the radial gradient of pressure through gradient or cyclostrophic balance assumptions, and not to a single point value of the minimum pressure near the storm center. But it is often the case that the maximum wind must be inferred from this single value. To accomplish this, a number of statistical relationships have been documented, such as those used in the Dvorak technique for estimating tropical cyclone intensity from satellite imagery. Here, the relationship between tropical cyclone maximum wind and minimum pressure is explored during eyewall replacement cycles (ERCs) that have been observed in North Atlantic hurricanes. It is shown that the wind–pressure relationship (WPR) can vary substantially during an ERC and generally moves away from the statistically fitted WPR used by the Dvorak technique in that basin. The changes in WPR during an ERC can be quite different depending on the intensity of the hurricane at the start of the ERC.

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James P. Kossin

Abstract

Using the National Environmental Satellite, Data, and Information Service–Cooperative Institute for Research in the Atmosphere (NESDIS–CIRA) tropical cyclone infrared (IR) imagery archive, combined with best track storm center fix information, a coherent depiction of the temporal and azimuthally averaged spatial structure of hurricane cloudiness is demonstrated. The diurnal oscillation of areal extent of the hurricane cirrus canopy, as documented in a number of previous studies, is clearly identified but often found to vanish near the convective region of the hurricane eyewall. While a significant diurnal oscillation is generally absent near the storm center, a powerful and highly significant semidiurnal oscillation is sometimes revealed in that region. This result intimates that convection near the center of tropical storms and hurricanes may not be diurnally forced, but might, at times, be semidiurnally forced. A highly significant semidiurnal oscillation is also often found in the near environment beyond the edge of the hurricane cirrus canopy. The phase of the semidiurnal oscillations in both the central convective region and the region beyond the canopy remains relatively fixed during the lifetime of each storm and is not found to vary much between individual storms. This fixed phase near the central convective region insinuates a mechanistic link between hurricane central convection and the semidiurnal atmospheric thermal tide S 2.

Two hypotheses are constructed. The first is offered to explain the diurnal oscillation of the canopy in the absence of a diurnal oscillation of the convective regions. The hypothesized mechanism is based on the radial variation of nighttime net radiational cooling and subsidence. The second hypothesis is offered to explain the semidiurnal oscillation near the central convective region, and is based on the possible presence of a semidiurnal oscillation of local lapse rates associated with S 2.

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James P. Kossin and Matthew Sitkowski

Abstract

Eyewall replacement cycles are commonly observed in tropical cyclones and are well known to cause fluctuations in intensity and wind structure. These fluctuations are often large and rapid and pose a significant additional challenge to intensity forecasting, yet there is presently no objective operational guidance available to forecasters that targets, quantifies, and predicts these fluctuations. Here the authors introduce new statistical models that are based on a recently documented climatology of intensity and structure changes associated with eyewall replacement cycles in Atlantic Ocean hurricanes. The model input comprises environmental features and satellite-derived features that contain information on storm cloud structure. The models predict the amplitude and timing of the intensity fluctuations, as well as the fluctuations of the wind structure, and can provide real-time operational objective guidance to forecasters.

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James P. Kossin and Matthew Sitkowski

Abstract

Hurricanes, and particularly major hurricanes, will often organize a secondary eyewall at some distance around the primary eyewall. These events have been associated with marked changes in the intensity and structure of the inner core, such as large and rapid deviations of the maximum wind and significant broadening of the surface wind field. While the consequences of rapidly fluctuating peak wind speeds are of great importance, the broadening of the overall wind field also has particularly dangerous consequences in terms of increased storm surge and wind damage extent during landfall events. Despite the importance of secondary eyewall formation in hurricane forecasting, there is presently no objective guidance to diagnose or forecast these events. Here a new empirical model is introduced that will provide forecasters with a probability of imminent secondary eyewall formation. The model is based on environmental and geostationary satellite features applied to a naïve Bayes probabilistic model and classification scheme. In independent testing, the algorithm performs skillfully against a defined climatology.

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James P. Kossin and Mark DeMaria

Abstract

Eyewall replacement cycles (ERCs) are fairly common events in tropical cyclones (TCs) of hurricane intensity or greater and typically cause large and sometimes rapid changes in the intensity evolution of the TC. Although the details of the intensity evolution associated with ERCs appear to have some dependence on the ambient environmental conditions that the TCs move through, these dependencies can also be quite different than those of TCs that are not undergoing an ERC. For example, the Statistical Hurricane Prediction Scheme (SHIPS), which is used in National Hurricane Center operations and provides intensity forecast skill that is, on average, equal to or greater than deterministic numerical model skill, typically identifies an environment that is not indicative of weakening during the onset and subsequent evolution of an ERC. Contrarily, a period of substantial weakening does typically begin near the onset of an ERC, and this disparity can cause large SHIPS intensity forecast errors. Here, a simple model based on a climatology of ERC intensity change is introduced and tested against SHIPS. It is found that the application of the model can reduce intensity forecast error substantially when applied at, or shortly after, the onset of ERC weakening.

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James P. Kossin and Wayne H. Schubert
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Christopher M. Rozoff and James P. Kossin

Abstract

The National Hurricane Center currently employs a skillful probabilistic rapid intensification index (RII) based on linear discriminant analysis of the environmental and satellite-derived features from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) dataset. Probabilistic prediction of rapid intensity change in tropical cyclones is revisited here using two additional models: one based on logistic regression and the other on a naïve Bayesian framework. Each model incorporates data from the SHIPS dataset over both the North Atlantic and eastern North Pacific Ocean basins to provide the probability of exceeding the standard rapid intensification thresholds [25, 30, and 35 kt (24 h)−1] for 24 h into the future. The optimal SHIPS and satellite-based predictors of rapid intensification differ slightly between each probabilistic model and ocean basin, but each set of optimal predictors incorporates thermodynamic and dynamic aspects of the tropical cyclone’s environment (such as vertical wind shear) and its structure (such as departure from convective axisymmetry). Cross validation shows that both the logistic regression and Bayesian probabilistic models are skillful relative to climatology. Dependent testing indicates both models exhibit forecast skill that generally exceeds the skill of the present operational SHIPS-RII and a simple average of the probabilities provided by the logistic regression, Bayesian, and SHIPS-RII models provides greater skill than any individual model. For the rapid intensification threshold of 25 kt (24 h)−1, the three-member ensemble mean improves the Brier skill scores of the current operational SHIPS-RII by 33% in the North Atlantic and 52% in the eastern North Pacific.

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James P. Kossin and Wayne H. Schubert

Abstract

The present work considers the two-dimensional barotropic evolution of thin annular rings of enhanced vorticity embedded in nearly irrotational flow. Such initial conditions imitate the observed flows in intensifying hurricanes. Using a pseudospectral numerical model, it is found that these highly unstable annuli rapidly break down into a number of mesovortices. The mesovortices undergo merger processes with their neighbors and, depending on initial conditions, they can relax to a monopole or an asymmetric quasi-steady state. In the latter case, the mesovortices form a lattice rotating approximately as a solid body. The flows associated with such vorticity configurations consist of straight line segments that form a variety of persistent polygonal shapes.

Associated with each mesovortex is a local pressure perturbation, or mesolow. The magnitudes of the pressure perturbations can be large when the magnitude of the vorticity in the initial annulus is large. In cases where the mesovortices merge to form a monopole, dramatic central pressure falls are possible.

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James P. Kossin and Daniel J. Vimont

Atlantic hurricane variability on decadal and interannual time scales is reconsidered in a framework based on a leading mode of coupled ocean-atmosphere variability known as the Atlantic meridional mode (AMM). It is shown that a large part of the variability of overall “hurricane activity,” which depends on the number of storms in a season, their duration, and their intensity, can be explained by systematic shifts in the cyclogenesis regions. These shifts are strongly correlated with the AMM on interannual as well as multidecadal time scales. It is suggested that the AMM serves to unify a number of previously documented relationships between hurricanes and Atlantic regional climate variability.

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