Downscaling wind and wavefields for 21st century coastal flood hazard projections in a region of complex terrain
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Abstract
While global climate models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling. Statistically downscaled GCM projections from Multivariate Adaptive Constructed Analogues provide daily averaged near-surface winds at an appropriate spatial resolution for wave modeling within the orographically complex region of San Francisco Bay, but greater resolution in time is needed to capture the peak of storm events. Short-duration high wind speeds, on the order of hours, are usually excluded in statistically downscaled climate models and are of key importance in wave and subsequent coastal flood modeling. Here we present a temporal downscaling approach, similar to constructed analogues, for near-surface winds suitable for use in local wave models and evaluate changes in wind and wave conditions for the 21st century. Reconstructed hindcast winds (1975–2004) recreate important extreme wind values within San Francisco Bay. A computationally efficient method for simulating wave heights over long time periods was used to screen for extreme events. Wave hindcasts show resultant maximum wave heights of 2.2 m possible within the Bay. Changes in extreme over-water wind speeds suggest contrasting trends within the different regions of San Francisco Bay, but 21th century projections show little change in the overall magnitude of extreme winds and locally generated waves.
Study Area
Publication type | Article |
---|---|
Publication Subtype | Journal Article |
Title | Downscaling wind and wavefields for 21st century coastal flood hazard projections in a region of complex terrain |
Series title | Earth and Space Science |
DOI | 10.1002/2016EA000193 |
Volume | 4 |
Issue | 5 |
Year Published | 2017 |
Language | English |
Publisher | AGU |
Contributing office(s) | Pacific Coastal and Marine Science Center |
Description | 21 p. |
First page | 314 |
Last page | 334 |
Country | United States |
State | California |
Other Geospatial | San Francisco Bay |
Google Analytic Metrics | Metrics page |