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Christopher M. Rozoff, Christopher S. Velden, John Kaplan, James P. Kossin, and Anthony J. Wimmers

Abstract

The probabilistic prediction of tropical cyclone (TC) rapid intensification (RI) in the Atlantic and eastern Pacific Ocean basins is examined here using a series of logistic regression models trained on environmental and infrared satellite-derived features. The environmental predictors are based on averaged values over a 24-h period following the forecast time. These models are compared against equivalent models enhanced with additional TC predictors created from passive satellite microwave imagery (MI). Leave-one-year-out cross validation on the developmental dataset shows that the inclusion of MI-based predictors yields more skillful RI models for a variety of RI and intensity thresholds. Compared with the baseline forecast skill of the non-MI-based RI models, the relative skill improvements from including MI-based predictors range from 10.6% to 44.9%. Using archived real-time data during the period 2004–13, evaluation of simulated real-time models is also carried out. Unlike in the model development stage, the simulated real-time setting involves using Global Forecast System forecasts for the non-satellite-based predictors instead of “perfect” observational-based predictors in the developmental data. In this case, the MI-based RI models still generate superior skill to the baseline RI models lacking MI-based predictors. The relative improvements gained in adding MI-based predictors are most notable in the Atlantic, where the non-MI versions of the models suffer acutely from the use of imperfect real-time data. In the Atlantic, relative skill improvements provided from the inclusion of MI-based predictors range from 53.5% to 103.0%. The eastern Pacific relative improvements are less impressive but are still uniformly positive.

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Kenneth R. Knapp, Jessica L. Matthews, James P. Kossin, and Christopher C. Hennon

Abstract

The Cyclone Center project maintains a website that allows visitors to answer questions based on tropical cyclone satellite imagery. The goal is to provide a reanalysis of satellite-derived tropical cyclone characteristics from a homogeneous historical database composed of satellite imagery with a common spatial resolution for use in long-term, global analyses. The determination of the cyclone “type” (curved band, eye, shear, etc.) is a starting point for this process. This analysis shows how multiple classifications of a single image are combined to provide probabilities of a particular image’s type using an expectation–maximization (EM) algorithm. Analysis suggests that the project needs about 10 classifications of an image to adequately determine the storm type. The algorithm is capable of characterizing classifiers with varying levels of expertise, though the project needs about 200 classifications to quantify an individual’s precision. The EM classifications are compared with an objective algorithm, satellite fix data, and the classifications of a known classifier. The EM classifications compare well, with best agreement for eye and embedded center storm types and less agreement for shear and when convection is too weak (termed no-storm images). Both the EM algorithm and the known classifier showed similar tendencies when compared against an objective algorithm. The EM algorithm also fared well when compared to tropical cyclone fix datasets, having higher agreement with embedded centers and less agreement for eye images. The results were used to show the distribution of storm types versus wind speed during a storm’s lifetime.

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Kimberly J. Mueller, Mark DeMaria, John Knaff, James P. Kossin, and Thomas H. Vonder Haar

Abstract

Geostationary infrared (IR) satellite data are used to provide estimates of the symmetric and total low-level wind fields in tropical cyclones, constructed from estimations of an azimuthally averaged radius of maximum wind (RMAX), a symmetric tangential wind speed at a radius of 182 km (V182), a storm motion vector, and the maximum intensity (VMAX). The algorithm is derived using geostationary IR data from 405 cases from 87 tropical systems in the Atlantic and east Pacific Ocean basins during the 1995–2003 hurricane seasons that had corresponding aircraft data available. The algorithm is tested on 50 cases from seven tropical storms and hurricanes during the 2004 season. Aircraft-reconnaissance-measured RMAX and V182 are used as dependent variables in a multiple linear regression technique, and VMAX and the storm motion vector are estimated using conventional methods. Estimates of RMAX and V182 exhibit mean absolute errors (MAEs) of 27.3 km and 6.5 kt, respectively, for the dependent samples. A modified combined Rankine vortex model is used to estimate the one-dimensional symmetric tangential wind field from VMAX, RMAX, and V182. Next, the storm motion vector is added to the symmetric wind to produce estimates of the total wind field. The MAE of the IR total wind retrievals is 10.4 kt, and the variance explained is 53%, when compared with the two-dimensional wind fields from the aircraft data for the independent cases.

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Eric A. Hendricks, Wayne H. Schubert, Richard K. Taft, Huiqun Wang, and James P. Kossin

Abstract

The asymmetric dynamics of potential vorticity mixing in the hurricane inner core are further advanced by examining the end states that result from the unforced evolution of hurricane-like vorticity rings in a nondivergent barotropic model. The results from a sequence of 170 numerical simulations are summarized. The sequence covers a two-dimensional parameter space, with the first parameter defining the hollowness of the vortex (i.e., the ratio of eye to inner-core relative vorticity) and the second parameter defining the thickness of the ring (i.e., the ratio of the inner and outer radii of the ring). In approximately one-half of the cases, the ring becomes barotropically unstable, and there ensues a vigorous vorticity mixing episode between the eye and eyewall. The output of the barotropic model is used to (i) verify that the nonlinear model approximately replicates the linear theory of the fastest-growing azimuthal mode in the early phase of the evolution, and (ii) characterize the end states (defined at t = 48 h) that result from the nonlinear chaotic vorticity advection and mixing. It is found that the linear stability theory is a good guide to the fastest-growing exponential mode in the numerical model. Two additional features are observed in the numerical model results. The first is an azimuthal wavenumber-2 deformation of the vorticity ring that occurs for moderately thick, nearly filled rings. The second is an algebraically growing wavenumber-1 instability (not present in the linear theory because of the assumed solution) that is observed as a wobbling eye (or the trochoidal oscillation for a moving vortex) for thick rings that are stable to all exponentially growing instabilities. Most end states are found to be monopoles. For very hollow and thin rings, persistent mesovortices may exist for more than 15 h before merging to a monopole. For thicker rings, the relaxation to a monopole takes longer (between 48 and 72 h). For moderately thick rings with nearly filled cores, the most likely end state is an elliptical eyewall. In this nondivergent barotropic context, both the minimum central pressure and maximum tangential velocity simultaneously decrease over 48 h during all vorticity mixing events.

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John A. Knaff, Thomas A. Cram, Andrea B. Schumacher, James P. Kossin, and Mark DeMaria

Abstract

Annular hurricanes are a subset of intense tropical cyclones that have been shown in previous work to be significantly stronger, to maintain their peak intensities longer, and to weaken more slowly than average tropical cyclones. Because of these characteristics, they represent a significant forecasting challenge. This paper updates the list of annular hurricanes to encompass the years 1995–2006 in both the North Atlantic and eastern–central North Pacific tropical cyclone basins. Because annular hurricanes have a unique appearance in infrared satellite imagery, and form in a specific set of environmental conditions, an objective real-time method of identifying these hurricanes is developed. However, since the occurrence of annular hurricanes is rare (∼4% of all hurricanes), a special algorithm to detect annular hurricanes is developed that employs two steps to identify the candidates: 1) prescreening the data and 2) applying a linear discriminant analysis. This algorithm is trained using a dependent dataset (1995–2003) that includes 11 annular hurricanes. The resulting algorithm is then independently tested using datasets from the years 2004–06, which contained an additional three annular hurricanes. Results indicate that the algorithm is able to discriminate annular hurricanes from tropical cyclones with intensities greater than 84 kt (43.2 m s−1). The probability of detection or hit rate produced by this scheme is shown to be ∼96% with a false alarm rate of ∼6%, based on 1363 six-hour time periods with a tropical cyclone with an intensity greater than 84 kt (1995–2006).

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Christopher M. Rozoff, Wayne H. Schubert, Brian D. McNoldy, and James P. Kossin

Abstract

Intense tropical cyclones often possess relatively little convection around their cores. In radar composites, this surrounding region is usually echo-free or contains light stratiform precipitation. While subsidence is typically quite pronounced in this region, it is not the only mechanism suppressing convection. Another possible mechanism leading to weak-echo moats is presented in this paper. The basic idea is that the strain-dominated flow surrounding an intense vortex core creates an unfavorable environment for sustained deep, moist convection. Strain-dominated regions of a tropical cyclone can be distinguished from rotation-dominated regions by the sign of S 2 1 + S 2 2ζ 2, where S 1 = uxυy and S 2 = υx + uy are the rates of strain and ζ = υxuy is the relative vorticity. Within the radius of maximum tangential wind, the flow tends to be rotation-dominated (ζ 2 > S 2 1 + S 2 2), so that coherent structures, such as mesovortices, can survive for long periods of time. Outside the radius of maximum tangential wind, the flow tends to be strain-dominated (S 2 1 + S 2 2 > ζ 2), resulting in filaments of anomalous vorticity. In the regions of strain-dominated flow the filamentation time is defined as τ fil = 2(S 2 1 + S 2 2ζ 2)−1/2. In a tropical cyclone, an approximately 30-km-wide annular region can exist just outside the radius of maximum tangential wind, where τ fil is less than 30 min and even as small as 5 min. This region is defined as the rapid filamentation zone. Since the time scale for deep moist convective overturning is approximately 30 min, deep convection can be significantly distorted and even suppressed in the rapid filamentation zone. A nondivergent barotropic model illustrates the effects of rapid filamentation zones in category 1–5 hurricanes and demonstrates the evolution of such zones during binary vortex interaction and mesovortex formation from a thin annular ring of enhanced vorticity.

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Christopher M. Rozoff, David S. Nolan, James P. Kossin, Fuqing Zhang, and Juan Fang

Abstract

The Weather and Research and Forecasting Model (WRF) is used to simulate secondary eyewall formation (SEF) in a tropical cyclone (TC) on the β plane. The simulated SEF process is accompanied by an outward expansion of kinetic energy and the TC warm core. An absolute angular momentum budget demonstrates that this outward expansion is predominantly a symmetric response to the azimuthal-mean and wavenumber-1 components of the transverse circulation. As the kinetic energy expands outward, the kinetic energy efficiency in which latent heating can be retained as local kinetic energy increases near the developing outer eyewall.

The kinetic energy efficiency associated with SEF is examined further using a symmetric linearized, nonhydrostatic vortex model that is configured as a balanced vortex model. Given the symmetric tangential wind and temperature structure from WRF, which is close to a state of thermal wind balance above the boundary layer, the idealized model provides the transverse circulation associated with the symmetric latent heating and friction prescribed from WRF. In a number of ways, this vortex response matches the azimuthal-mean secondary circulation in WRF. These calculations suggest that sustained azimuthal-mean latent heating outside of the primary eyewall will eventually lead to SEF. Sensitivity experiments with the balanced vortex model show that, for a fixed amount of heating, SEF is facilitated by a broadening TC wind field.

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Christopher M. Rozoff, James P. Kossin, Wayne H. Schubert, and Pedro J. Mulero

Abstract

In hurricane eyewalls, the vertical stretching effect tends to produce an annular ring of high vorticity. Idealized, unforced nondivergent barotropic model results have suggested such rings of vorticity are often barotropically unstable, leading to strong asymmetric mixing events where vorticity is mixed inward into a more stable configuration. Such mixing events most often result in weakened maximum winds. The manner in which forcing modifies these unforced simulations remains an open question.

In the current study, a forced, two-dimensional barotropic model is used to systematically study the sensitivity of vorticity rings to ring geometry and spatially and temporally varying forcing. The simulations reveal an internal mechanism that interrupts the intensification process resulting from vorticity generation in the hurricane eyewall. This internal control mechanism is due to vorticity mixing in the region of the eye and eyewall and can manifest itself in two antithetical forms—as a transient “intensification brake” during symmetric intensification or as an enhancer of intensification through efficient transport of vorticity from the eyewall, where it is generated, to the eye.

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James P. Kossin, Thomas R. Karl, Thomas R. Knutson, Kerry A. Emanuel, Kenneth E. Kunkel, and James J. O’Brien
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Stephanie C. Herring, Andrew Hoell, Martin P. Hoerling, James P. Kossin, Carl J. Schreck III, and Peter A. Stott
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