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Warren Blier
,
Stanley Keefe
,
Wilson A. Shaffer
, and
Sung C. Kim

Abstract

Within the period of the historical record there have been several occurrences of extensive damage from storm-surge-related coastal flooding in the region of Nome, Alaska. The most recent of these events, although by no means the most destructive, occurred in association with the storm of 5–6 October 1992. Despite the small population of Nome (approximately 4000 people), total damage costs exceeded $6 million.

The research into the nature and causes of such flooding events has focused on this October 1992 case. The authors have, however, also examined a weaker, shorter-duration event that occurred on 20 August 1993 and, for contrast, a case in September 1993 where a sustained offshore wind transported water out of Norton Sound. Tide gauge data from Nome were used to quantitatively assess the associated changes in water level, and meteorological analyses were utilized to examine the associated synoptic-scale circulations and their evolution.

In addition, numerical modeling experiments were conducted using an extratropical storm surge model. (A version of this model is operational for the east coast of the United States.) Hindcasts of phase and amplitude for the October 1992 and September 1993 events agreed well with observations. Simulations of the shorter-duration August 1993 event were in poorer agreement with observations and indicate several possibilities for future improvement of the performance of the surge model: enhancement of the horizontal and temporal resolution of the model domain; more accurate input sea level pressure and wind data; and improvements to the surge model itself (e.g., inclusion of sea ice). Overall, however, results indicate that recent operational implementation of the model should be of significant benefit to coastal forecasters.

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Samuel H. Houston
,
Wilson A. Shaffer
,
Mark D. Powell
, and
Jye Chen

Abstract

Surface wind observations analyzed by the Hurricane Research Division (HRD) were compared to those computed by the parametric wind model used in the National Weather Service Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model’s storm surge computations for seven cases in five recent hurricanes. In six cases, the differences between the SLOSH and HRD surface peak wind speeds were 6% or less, but in one case (Hurricane Emily of 1993) the SLOSH computed peak wind speeds were 15% less than the HRD. In all seven cases, statistics for the modeled and analyzed wind fields showed that for the region of strongest winds, the mean SLOSH wind speed was 14% greater than that of the HRD and the mean inflow angle for SLOSH was 19° less than that of the HRD. The radii beyond the region of strongest winds in the seven cases had mean wind speed and inflow angle differences that were very small. The SLOSH computed peak storm surges usually compared closely to the observed values of storm surge in the region of the maximum wind speeds, except Hurricane Emily where SLOSH underestimated the peak surge. HRD’s observation-based wind fields were input to SLOSH for storm surge hindcasts of Hurricanes Emily and Opal (1995). In Opal, the HRD input produced nearly the same computed storm surges as those computed from the SLOSH parametric wind model, and the calculated surge was insensitive to perturbations in the HRD wind field. For Emily, observation-based winds produced a computed storm surge that was closer to the peak observed surge, confirming that the computed surge in Pamlico Sound was sensitive to atmospheric forcing. Using real-time, observation-based winds in SLOSH would likely improve storm surge computations in landfalling hurricanes affected by synoptic and mesoscale factors that are not accounted for in parametric models (e.g., a strongly sheared environment, convective asymmetries, and stably stratified boundary layers). An accurate diagnosis of storm surge flooding, based on the actual track and wind fields could be supplied to emergency management agencies, government officials, and utilities to help with damage assessment and recovery efforts.

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