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James B. Elsner

Abstract

In a 2008 paper, using satellite-derived wind speed estimates from tropical cyclones over the 25-yr period 1981–2006, we showed the strongest tropical cyclones getting stronger. We related the increasing intensity to rising ocean temperatures consistent with theory. Oceans have continued to warm since that paper was published, so the intensity of the strongest cyclones should have continued upward as well. Here I show that this is the case, with increases in the upper-quantile intensities of global tropical cyclones amounting to between 3.5% and 4.5% in the period 2007–19 relative to the earlier base period (1981–2006). All basins individually show upward intensity trends for at least one upper quantile considered, with the North Atlantic and western North Pacific basins showing the steepest and most consistent trends across the quantiles.

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James B. Elsner
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James B. Elsner

There is widespread concern about the recent increase in North Atlantic hurricane activity. Results here suggest that fledgling storms tracking east to west at low latitudes are more likely to reach hurricane intensity than those traveling on a more northerly trajectory. The annual occurrence of these straight-moving hurricanes (east to west at low latitudes) is statistically linked to the El Niño-Southern Oscillation (ENSO) and to the North Atlantic Oscillation (NAO) using a Poisson regression. Because the occurrence of U.S. hurricanes south of about 35°N is positively correlated with the abundance of straight-moving hurricanes, an accurate prediction of ENSO together with observations of the NAO could be used to forecast seasonal hurricane probabilities along the southeast U.S. coast. It is stressed that in order to understand the range of mechanisms associated with hurricane activity, it is important to consider factors that influence tracks. In this regard, the NAO is a leading candidate.

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James B. Elsner
and
Zoe Schroder

Abstract

Empirical studies have led to improvements in evaluating and quantifying the tornado threat. However, more work is needed to put the research onto a solid statistical foundation. Here the authors begin to build this foundation by introducing and then demonstrating a statistical model to estimate damage rating (enhanced Fujita scale) probabilities. A goal is to alert researchers to available statistical technology for improving severe weather warnings. The model is cumulative logistic regression and the parameters are determined using Bayesian inference. The model is demonstrated by estimating damage rating probabilities from values of known environmental factors on days with many tornadoes in the United States. Controlling for distance to nearest town/city, which serves as a proxy variable for damage target density, the model quantifies the chance that a particular tornado will be assigned any damage rating given specific environmental conditions. Under otherwise average conditions, the model estimates a 65% chance that a tornado occurring in a city or town will be rated EF0 when bulk shear (1000–500-hPa layer) is weak (10 m s−1). This probability drops to 38% when the bulk shear is strong (40 m s−1). The model quantifies the corresponding increases in the chance of the same tornado receiving higher damage ratings. Quantifying changes to the probability distribution on the ordered damage rating categories is a natural application of cumulative logistic regression.

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Zoe Schroder
and
James B. Elsner

Abstract

Environmental variables are routinely used in estimating when and where tornadoes are likely to occur, but more work is needed to understand how tornado and casualty counts of severe weather outbreak vary with the larger-scale environmental factors. Here the authors demonstrate a method to quantify “outbreak”-level tornado and casualty counts with respect to variations in large-scale environmental factors. They do this by fitting negative binomial regression models to cluster-level environmental data to estimate the number of tornadoes and the number of casualties on days with at least 10 tornadoes. Results show that a 1000 J kg−1 increase in CAPE corresponds to a 5% increase in the number of tornadoes and a 28% increase in the number of casualties, conditional on at least 10 tornadoes and holding the other variables constant. Further, results show that a 10 m s−1 increase in deep-layer bulk shear corresponds to a 13% increase in tornadoes and a 98% increase in casualties, conditional on at least 10 tornadoes and holding the other variables constant. The casualty-count model quantifies the decline in the number of casualties per year and indicates that outbreaks have a larger impact in the Southeast than elsewhere after controlling for population and geographic area.

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Todd B. Kimberlain
and
James B. Elsner

Abstract

Hurricane activity over the North Atlantic basin during 1995 and 1996 is compared to the combined hurricane activity over the previous four years (1991–94). The earlier period produced a total of 15 hurricanes compared to a total of 20 hurricanes over the latter period. Despite this similarity in numbers, the hurricanes of 1995 and 1996 were generally of the tropical-only variety, which marks a substantial departure from activity during the early 1990s. The return of tropical-only hurricanes to the Atlantic basin is likely the result of several global and local factors, including cool SST conditions in the equatorial central and eastern Pacific and warm SSTs in the tropical Atlantic. The hurricane activity of 1995 and 1996 is more reminiscent of activity of some seasons during the early and mid-1950s.

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James B. Elsner
and
Thomas H. Jagger

Abstract

Advances in hurricane climate science allow forecasts of seasonal landfall activity to be made. The authors begin with a review of the forecast methods available in the literature. They then reformulate the methods using a Bayesian probabilistic approach. This allows a direct comparison to be made while focusing on a single hindcast of the 2004 season over Florida. The models, including climatology, are estimated using Gibbs sampling. Diagnostic checks verify convergence and efficient mixing of the samples from each of the models. A below average sea level pressure gradient over the eastern North Atlantic Ocean during May and June in combination with an above average tropospheric-averaged wind index associated, in part, with a strengthening of the Bermuda high pressure during July resulted in an above average probability of at least one Florida hurricane. The relatively high hindcast probabilities for 2004 were in marked contrast to the most recent 50-yr empirical probabilities for Florida, but fell short in anticipating the unprecedented level of activity that ensued. Similar results are obtained from hindcasts of total U.S. hurricane activity for 2004.

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Thomas H. Jagger
and
James B. Elsner

Abstract

Models that predict annual U.S. hurricane activity assume a Poisson distribution for the counts. Here the authors show that this assumption applied to Florida hurricanes leads to a forecast that underpredicts both the number of years without hurricanes and the number of years with three or more hurricanes. The underdispersion in forecast counts arises from a tendency for hurricanes to arrive in groups along this part of the coastline. The authors then develop an extension to their earlier statistical model that assumes that the rate of hurricane clusters follows a Poisson distribution with cluster size capped at two hurricanes. Hindcasts from the cluster model better fit the distribution of Florida hurricanes conditional on the climate covariates including the North Atlantic Oscillation and Southern Oscillation index. Results are similar to models that parameterize the extra-Poisson variation in the observed counts, including the negative binomial and the Poisson inverse Gaussian models. The authors argue, however, that the cluster model is physically consistent with the way Florida hurricanes tend to arrive in groups.

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Nam-Young Kang
and
James B. Elsner

Abstract

Violent typhoons continue to have catastrophic impacts on economies and welfare, but how they are responding to global warming has yet to be fully understood. Here, an empirical framework is used to explain physically why observations support a tight connection between increasing ocean warmth and the increasing intensity of supertyphoons in the western North Pacific. It is shown that the energy needed for deep convection is on the rise with greater heat and moisture in the lower tropical troposphere but that this energy remains untapped when air pressure is high. Accordingly, tropical cyclone formation is becoming less common, but those that do form are likely to reach extreme intensities from the discharge of stored energy. These thermodynamic changes to the environment most significantly influence the upper portion of extreme typhoon intensities, indicating that supertyphoons are likely to be stronger at the expense of overall tropical cyclone occurrences in the western North Pacific.

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Nam-Young Kang
and
James B. Elsner

Abstract

Research on trends in western North Pacific tropical cyclone (TC) activity is limited by problems associated with different wind speed conversions used by the various meteorological agencies. This paper uses a quantile method to effectively overcome this conversion problem. Following the assumption that the intensity ranks of TCs are the same among agencies, quantiles at the same probability level in different data sources are regarded as having the same wind speed level. Tropical cyclone data from the Joint Typhoon Warning Center (JTWC) and Japan Meteorological Agency (JMA) are chosen for research and comparison. Trends are diagnosed for the upper 45% of the strongest TCs annually. The 27-yr period beginning with 1984, when the JMA began using the technique, is determined to be the most reliable for achieving consensus among the two agencies regarding these trends. The start year is a compromise between including as many years in the data as possible, but not so many that the period includes observations that result in inconsistent trend estimates. The consensus of TC trends between the two agencies over the period is interpreted as fewer but stronger events since 1984, even with the lower power dissipation index (PDI) in the western North Pacific in recent years.

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