In the northeastern United States, extratropical cyclones (ETCs) are associated with the majority of the largest storm surges, which significantly impact coastal regions. We characterize the synoptic evolution of the largest ETC-driven surge events in observations and a long record from a coupled climate model representing recent climate conditions. A k-means cluster analysis is applied to the top 100 observed surge-producing ETCs at select locations (Sewells Point, Virginia; The Battery, New York; and Boston, Massachusetts) to group similar circulation features. These distinct patterns suggest that the largest surges are generated when slowly propagating ETCs encounter a strong anticyclone, which produces a tighter pressure gradient and longer duration of onshore winds. Multiple clusters feature a slower-than-average storm and a strong anticyclone, indicating that various circulation scenarios with these features can produce a large surge. This favorable environment is influenced by El NiƱo conditions, and maximum surge occurs preferentially during the positive phase of PNA and the negative phases of AO/NAO.
Return periods of the largest ETC-driven surge events are difficult to estimate owing to the short duration of high-quality observational datasets, so a long simulation from a coupled model, GFDL FLOR, is employed. Distributions of meteorological quantities that influence surge height (i.e. central pressure and surface winds) indicate that the longer integration contains a greater number of extreme ETCs. An exceedance probability risk assessment of the strongest impacts demonstrates a consistent underestimation in historical-length records compared to return levels estimated from the full FLOR simulation. This indicates that if the underlying distributions of observed metrics are similar to those of the 1505-year record, the actual frequency of extreme events is being underestimated.
Comparisons of cyclone statistics between FLOR and a reanalysis product, CFSR, exhibit biases in quantitative measures of storm surge and intensity, but characteristics of the distributions of these quantities are representative of features of a climate constrained by observations. A k-means cluster analysis of the synoptic evolution of storm surge events estimated using a regression-based index displays similar circulation features to clusters of observed events. At The Battery and Sewells Point, clusters containing the majority of the largest estimated storm surges exhibit a strong anticyclone and a slow-moving cyclone. Discrepancies at Boston are related to approximations made by the regression index applied to identify and arrange clustered meteorological patterns.
Subject (authority = RUETD)
Topic
Atmospheric Science
Subject (authority = LCSH)
Topic
Cyclones--United States
Subject (authority = LCSH)
Topic
Storm surges--United States
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Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
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TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
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