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This study uses the WRF ARW to investigate how different atmospheric temperature environments impact the size and structure development of a simulated tropical cyclone (TC). In each simulation, the entire vertical virtual temperature profile is either warmed or cooled in 1°C increments from an initial specified state while the initial relative humidity profile and sea surface temperature are held constant. This alters the initial amount of convective available potential energy (CAPE), specific humidity, and air-sea temperature difference such that, when the simulated atmosphere is cooled (warmed), the initial specific humidity and CAPE decrease (increase), but the surface energy fluxes from the ocean increase (decrease). It is found that the TCs that form in an initially cooler environment develop larger wind and precipitation fields with more active outer-core rainband formation. Consistent with previous studies, outer-core rainband formation is associated with high surface energy fluxes, which leads to increases in the outer-core wind field. A larger convective field develops despite initializing in a low CAPE environment, and the dynamics are linked to a wider field of surface radial inflow. As the TC matures and radial inflow expands, large imports of relative angular momentum in the boundary layer continue to drive expansion of the TC's overall size. [ABSTRACT FROM AUTHOR]

Statistical, dynamical, and statistical-dynamical hybrid models have been developed in past decades for the seasonal prediction of North Atlantic hurricane numbers. These models' prediction skills show considerable decadal variability, with particularly poor performance in the past few years. Here, environmental factors that affect hurricane activities are reevaluated to develop a new statistical model for seasonal prediction by 1 June of each year. The predictors include the April-May multivariate ENSO index (MEI) conditioned upon the Atlantic multidecadal oscillation (AMO) index, the power of the average zonal pseudo-wind stress across the North Atlantic in May, and the average March-May tropical Atlantic sea surface temperature. When compared to the actual number of hurricanes each year from 1950 to 2013, this model has a root-mean-square error (RMSE) of 1.91 with a correlation coefficient of 0.71. It shows a 39% improvement in RMSE over a no-skill metric (based on the 5-yr running mean of seasonal hurricane counts) for the period 2001-13. It also outperforms three statistical-dynamical hybrid models [CPC, Colorado State University (CSU), and Tropical Storm Risk (TSR)] by more than 25% for the same period. Furthermore, two approaches are developed to provide the uncertainty ranges around the predicted (deterministic) hurricane number per season that better encompass the range of uncertainty than does the standard method of adding/subtracting a standard deviation of the errors. [ABSTRACT FROM AUTHOR]

A 42-yr study of eastern North Pacific tropical cyclones (TCs) undergoing extratropical transition (ET) is presented using the Japanese 55-yr Reanalysis dataset. By using cyclone phase space (CPS) to differentiate those TCs that undergo ET from those that do not, it is found that only 9% of eastern North Pacific TCs that developed from 1971 to 2012 complete ET, compared with 40% in the North Atlantic. Using a combination of CPS, empirical orthogonal function (EOF) analysis, and composite analysis, it is found that the evolution of ET in this basin differs from that observed in the North Atlantic and western North Pacific, possibly as a result of the rapidly decreasing sea surface temperatures north of the main genesis region. The presence of a strong, deep subtropical ridge extending westward from North America into the eastern North Pacific is a major factor inhibiting ET in this basin. Similar to other basins, eastern North Pacific ET generally occurs in conjunction with an approaching midlatitude trough, which helps to weaken the ridge and allow northward passage of the TC. The frequency of ET appears to increase during developing El Niño events but is not significantly affected by the Pacific decadal oscillation. [ABSTRACT FROM AUTHOR]

The deviation-angle variance technique (DAV-T), which was introduced in the North Atlantic basin for tropical cyclone (TC) intensity estimation, is adapted for use in the North Pacific Ocean using the 'best-track center' application of the DAV. The adaptations include changes in preprocessing for different data sources [Geostationary Operational Environmental Satellite-East (GOES-E) in the Atlantic, stitched GOES-E-Geostationary Operational Environmental Satellite-West (GOES-W) in the eastern North Pacific, and the Multifunctional Transport Satellite (MTSAT) in the western North Pacific], and retraining the algorithm parameters for different basins. Over the 2007-11 period, DAV-T intensity estimation in the western North Pacific results in a root-mean-square intensity error (RMSE, as measured by the maximum sustained surface winds) of 14.3 kt (1 kt ≈ 0.51 m s−1) when compared to the Joint Typhoon Warning Center best track, utilizing all TCs to train and test the algorithm. The RMSE obtained when testing on an individual year and training with the remaining set lies between 12.9 and 15.1 kt. In the eastern North Pacific the DAV-T produces an RMSE of 13.4 kt utilizing all TCs in 2005-11 when compared with the National Hurricane Center best track. The RMSE for individual years lies between 9.4 and 16.9 kt. The complex environment in the western North Pacific led to an extension to the DAV-T that includes two different radii of computation, producing a parametric surface that relates TC axisymmetry to intensity. The overall RMSE is reduced by an average of 1.3 kt in the western North Pacific and 0.8 kt in the eastern North Pacific. These results for the North Pacific are comparable with previously reported results using the DAV for the North Atlantic basin. [ABSTRACT FROM AUTHOR]

This paper describes results from an improvement to the objective deviation angle variance technique to estimate the intensity of tropical cyclones from satellite infrared imagery in the North Atlantic basin. The technique quantifies the level of organization of the infrared cloud signature of a tropical cyclone as an indirect measurement of its maximum wind speed. The major change described here is to use the National Hurricane Center's best-track database to constrain the technique. Results are shown for the 2004-10 North Atlantic hurricane seasons and include an overall root-mean-square intensity error of 12.9 kt (6.6 m s−1, where 1 kt = 0.514 m s−1) and annual root-mean-square intensity errors ranging from 10.3 to 14.1 kt. A direct comparison between the previous version and the one reported here shows root-mean-square intensity error improvements in all years with a best improvement in 2009 from 17.9 to 10.6 kt and an overall improvement from 14.8 to 12.9 kt. In addition, samples from the 7-yr period are binned based on level of intensity and on the strength of environmental vertical wind shear as extracted from Statistical Hurricane Intensity Prediction Scheme (SHIPS) data. Preliminary results suggest that the deviation angle variance technique performs best at the weakest intensity categories of tropical storm through hurricane category 3, representing 90% of the samples, and then degrades in performance for hurricane categories 4 and 5. For environmental vertical wind shear, there is far less spread in the results with the technique performing better with increasing vertical wind shear. [ABSTRACT FROM AUTHOR]