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

Abstract

A collection of images depicting various swirling patterns within low-level cloud decks in hurricane eyes is presented and described. A possible causal mechanism for the presence of these cloud patterns is suggested by comparison of the observed cloud patterns with the evolution of passive tracers in a simple 2D barotropic model. The model is initialized with a barotropically unstable flow field that imitates the observed flows in hurricanes, and numerical integration of this field simulates vigorous mixing between eye and eyewall. During the mixing process, passive tracers initially embedded in the flow form swirling patterns in the eye that are strikingly similar to cloud patterns often observed in the eyes of hurricanes.

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James P. Kossin, Suzana J. Camargo, and Matthew Sitkowski

Abstract

The variability of North Atlantic tropical storm and hurricane tracks, and its relationship to climate variability, is explored. Tracks from the North Atlantic hurricane database for the period 1950–2007 are objectively separated into four groups using a cluster technique that has been previously applied to tropical cyclones in other ocean basins. The four clusters form zonal and meridional separations of the tracks. The meridional separation largely captures the separation between tropical and more baroclinic systems, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. General climatologies of the seasonality, intensity, landfall probability, and historical destructiveness of each cluster are documented, and relationships between cluster membership and climate variability across a broad spectrum of time scales are identified.

Composites, with respect to cluster membership, of sea surface temperature and other environmental fields show that regional and remote modes of climate variability modulate the cluster members in substantially differing ways and further demonstrate that factors such as El Niño–Southern Oscillation (ENSO), Atlantic meridional mode (AMM), North Atlantic Oscillation (NAO), and Madden–Julian oscillation (MJO) have varying intrabasin influences on North Atlantic tropical storms and hurricanes. Relationships with African easterly waves are also considered. The AMM and ENSO are found to most strongly modulate the deep tropical systems, while the MJO most strongly modulates Gulf of Mexico storms and the NAO most strongly modulates storms that form to the north and west of their Cape Verde counterparts and closer to the NAO centers of action.

Different clusters also contribute differently to the observed trends in North Atlantic storm frequency and may be related to intrabasin differences in sea surface temperature trends. Frequency trends are dominated by the deep tropical systems, which account for most of the major hurricanes and overall power dissipation. Contrarily, there are no discernable trends in the frequency of Gulf of Mexico storms, which account for the majority of landfalling storms. When the proportion that each cluster contributes to overall frequency is considered, there are clear shifts between the deep tropical systems and the more baroclinic systems. A shift toward proportionally more deep tropical systems began in the early to mid-1980s more than 10 years before the 1995 North Atlantic hurricane season, which is generally used to mark the beginning of the present period of heightened activity.

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Carl J. Schreck III, Kenneth R. Knapp, and James P. Kossin

Abstract

Using the International Best Track Archive for Climate Stewardship (IBTrACS), the climatology of tropical cyclones is compared between two global best track datasets: 1) the World Meteorological Organization (WMO) subset of IBTrACS (IBTrACS-WMO) and 2) a combination of data from the National Hurricane Center and the Joint Typhoon Warning Center (NHC+JTWC). Comparing the climatologies between IBTrACS-WMO and NHC+JTWC highlights some of the heterogeneities inherent in these datasets for the period of global satellite coverage 1981–2010. The results demonstrate the sensitivity of these climatologies to the choice of best track dataset. Previous studies have examined best track heterogeneities in individual regions, usually the North Atlantic and west Pacific. This study puts those regional issues into their global context. The differences between NHC+JTWC and IBTrACS-WMO are greatest in the west Pacific, where the strongest storms are substantially weaker in IBTrACS-WMO. These disparities strongly affect the global measures of tropical cyclone activity because 30% of the world’s tropical cyclones form in the west Pacific. Because JTWC employs similar procedures throughout most of the globe, the comparisons in this study highlight differences between WMO agencies. For example, NHC+JTWC has more 96-kt (~49 m s−1) storms than IBTrACS-WMO in the west Pacific but fewer in the Australian region. This discrepancy probably points to differing operational procedures between the WMO agencies in the two regions. Without better documentation of historical analysis procedures, the only way to remedy these heterogeneities will be through systematic reanalysis.

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Jason C. Knievel, David S. Nolan, and James P. Kossin

Abstract

The authors examine the degree of hydrostatic and gradient balances in a mesoscale convective vortex (MCV) in the stratiform region of a mesoscale convective system (MCS) that crossed Oklahoma on 1 August 1996. Results indicate that the MCV was partially unbalanced because the cool layer at the base of its core was too cool and too shallow to balance the tangential winds about the MCV's axis. The apparent imbalance may have been due to strong, unsteady forcing on the vortex; insufficient or unrepresentative data; approximations used in the analysis; or reasons that are unknown.

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Stephanie C. Herring, Martin P. Hoerling, James P. Kossin, Thomas C. Peterson, and Peter A. Stott

Editors note: For easy download the posted pdf of the Explaining Extreme Events of 2014 is a very low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download.

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Stephanie C. Herring, Martin P. Hoerling, James P. Kossin, Thomas C. Peterson, and Peter A. Stott
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Stephanie C. Herring, Martin P. Hoerling, James P. Kossin, Thomas C. Peterson, and Peter A. Stott
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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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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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Carl J. Schreck III, Lei Shi, James P. Kossin, and John J. Bates

Abstract

The Madden–Julian oscillation (MJO) and convectively coupled equatorial waves are the dominant modes of synoptic-to-subseasonal variability in the tropics. These systems have frequently been examined with proxies for convection such as outgoing longwave radiation (OLR). However, upper-tropospheric water vapor (UTWV) gives a more complete picture of tropical circulations because it is more sensitive to the drying and warming associated with subsidence. Previous studies examined tropical variability using relatively short (3–7 yr) UTWV datasets. Intersatellite calibration of data from the High Resolution Infrared Radiation Sounder (HIRS) has recently produced a homogeneous 32-yr climate data record of UTWV for 200–500 hPa. This study explores the utility of HIRS UTWV for identifying the MJO and equatorial waves.

Spectral analysis shows that the MJO and equatorial waves stand out above the low-frequency background in UTWV, similar to previous findings with OLR. The fraction of variance associated with the MJO and equatorial Rossby waves is actually greater in UTWV than in OLR. Kelvin waves, on the other hand, are overshadowed in UTWV by horizontal advection from extratropical Rossby waves.

For the MJO, UTWV identifies subsidence drying in the subtropics, poleward of the convection. These dry anomalies are associated with the MJO’s subtropical Rossby gyres. MJO events with dry anomalies over the central North Pacific Ocean also amplify the 200-hPa flow pattern over North America 7 days later. These events cannot be identified using equatorial OLR alone, which demonstrates that UTWV is a useful supplement for identifying the MJO, equatorial waves.

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