No abstract

In its first 2 years of operation, the ground-based Terrestrial gamma ray flash and Energetic Thunderstorm Rooftop Array (TETRA)-II array of gamma ray detectors has recorded 22 bursts of gamma rays of millisecond-scale duration associated with lightning. In this study, we present the TETRA-II observations detected at the three TETRA-II ground-level sites in Louisiana, Puerto Rico, and Panama together with the simultaneous radio frequency signals from the lightning data sets VAISALA Global Lightning Dataset, VAISALA National Lightning Detection Network, Earth Networks Total Lightning Network, and World Wide Lightning Location Network. The relative timing between the gamma ray events and the lightning activity is a key parameter for understanding the production mechanism(s) of the bursts. The gamma ray time profiles and their correlation with radio sferics suggest that the gamma ray events are initiated by lightning leader activity and are produced near the last stage of lightning leader channel development prior to the lightning return stroke.

[1] The strongest hurricanes are getting stronger as the oceans heat up especially over the North Atlantic. Sensitivity of hurricane intensity to ocean heating is an important variable for understanding what hurricanes might be like in the future, but reliable estimates are not possible with short time-series records. Studies using paired values of intensity and sea-surface temperature (SST) are also limited because most pairs represent hurricanes in an environment less than thermodynamically optimal. Here we overcome these limitations using spatial grids and a model for the limiting hurricane intensity by region and estimate the sensitivity to be 7.9 AE 1.19 m s À K À1 (s.e.) for hurricanes over seas hotter than 25 C across the North Atlantic. Results indicate the potential for stronger hurricanes during the 21st century as oceans continue to warm over this part of the world.

High winds and storm surges associated with torrential rain from tropical cyclones (TCs) cause massive destruction to property and cost the lives of many people. The coastline of the Bay of Bengal (BoB) ranks as one of the most susceptible to storm surges in the world due to low-lying elevation and a high frequency of TC occurrence. This study uses data from 1885 to 2011 and a bivariate statistical copula to describe the relationship and dependency between empirical TC storm surge and reported wind speed before landfall at the BoB. Among the copulas and their families, an Archimedean, Gumbel copula with margins defined by the empirical distributions is specified as the most appropriate choice for the BoB. The model provides return periods for pairs of TC storm surge and 12-hr pre-landfall wind along the BoB coastline. On the shortest timescale, the BoB can expect a TC with 12-hr pre-landfall winds of at least 24 m/s and surge heights of at least 4.0 m, on average, once every 3.9 years. On the other hand, the long-term, worst case scenario suggests the BoB can expect 12-hr pre-landfall winds of 62 m/s and surge heights of at least 8.0 m, on average, once every 311.8 years. Using a copula to model the combined frequency of cyclone wind speeds along with storm surges along the BoB coastline increases the understanding of the dangerous TC characteristics in this region, which can reduce fatalities and monetary losses.

Tropical cyclones, with their nearshore high wind speeds and deep storm surges, frequently strike the United States Gulf of Mexico coastline influencing millions of people and disrupting offshore economic activities. The combined risk of occurrence of tropical cyclone nearshore wind speeds and storm surges is assessed at 22 coastal cities throughout the United States Gulf of Mexico. The models used are extreme value copulas fitted with margins defined by the generalized Pareto distribution or combinations of Weibull, gamma, lognormal, or normal distributions. The statistical relationships between the nearshore wind speed and storm surge are provided for each coastal city prior to the copula model runs using Spearman's rank correlations. The strongest significant relationship between the nearshore wind speed and storm surge exists at Shell Beach, LA (ρ = 0.67), followed by South Padre Island, TX (ρ = 0.64). The extreme value Archimedean copula models for each city then provide return periods for specific nearshore wind speed and storm surge pairs. Of the 22 cities considered, Bay St. Louis, MS, has the shortest return period for a tropical cyclone with at least a 50 ms−1 nearshore wind speed and a 3 m surge (19.5 years, 17.1‐23.5). The 90% confidence intervals are created by recalculating the return periods for a fixed set of wind speeds and surge levels using 100 samples of the model parameters. The results of this study can be utilized by policy managers and government officials concerned with coastal populations and economic activity in the Gulf of Mexico.