North Atlantic wind and wave climate: Observed extremes, hindcast performance, and extratropical recurrence intervals

Abstract

An investigation of the extreme offshore wind and wave climate in the mid-Atlantic region has been conducted for the U.S. Bureau of Safety and Environmental Enforcement (BSEE). The overall objective of the project is to assist with the development of Metocean standards for offshore wind farm design, and establish a 100-yr extratropical wind speed and wave height climatology for the specific regions of interest. Specific accomplishments include evaluating and selecting a climatological data base to use for the study, establish a technique for performing the extremal analysis, and generating maps of 100-yr return period wind speeds and wave heights. A total of four extremal analysis techniques were evaluated for assessment of extratropical wind and wave storm data. The Empirical Simulation Technique (EST) provided in [14] employs a life-cycle approach to extreme value analysis. In contrast, the Generalized Pareto Distribution (GPD) [2], Weibull [11], and Generalized Extreme Value (GEV) [22] methods are parametric extrapolations to the data. To evaluate these approaches in our area of interest, extratropical Storm populations were identified at five test stations by applying both Peak over Threshold (POT) and Annual Maximum Series (AMS) techniques (for use with the GEV) to the NCEP 30-yr hindcast which is the longest hindcast currently available. Tropical storms were removed by an automated process linked to the North Atlantic HurricaneDatabase (HURDAT). The four extremal techniques were applied to the storm populations and comparisons made at the 50-and 100-yr recurrence interval. The selection of a final methodology will be described and resulting maps of the 50-and 100-yr recurrence interval extratropical wind speeds and wave heights will be presented.

Recurrence Interval Analysis on Electricity Consumption of an Office Building in China

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The Recurrence Interval Difference of Power Load in Heavy/Light Industries of China

“…RIA has been widely used to analyze extreme events in many fields, for example, climate [44], earthquake activities [45,46], heartbeat monitoring [47,48] and financial volatility [49,50]. These events occur with a high magnitude and low probability.…”

Bayesian trend analysis of extreme wind using observed and hindcast series off Catalan coast, NW Mediterranean Sea

“…Bayesian methods (e.g. Gelman et al, 1995) are very useful in contexts where data are scarce, such as hazard assessment problems. Bayesian methods allow us to assess the uncertainty of the estimates of parameters, usually large in these situations.…”

“…Bayesian methods were introduced in the field of natural hazards two decades ago and they have succeeded as a flexible and consistent way of controlling uncertainty (Sánchez-Arcilla et al, 2008a;Coles and Tawn, 1996;Gelman et al, 1995). Simultaneously, the models for analysing extremal events have evolved.…”