Spectral Ocean Wave Climate Variability Based on Atmospheric Circulation Patterns
Traditional approaches for assessing wave climate variability have been broadly focused on aggregated or statistical parameters such as significant wave height, wave energy flux, or mean wave direction. These studies, although revealing the major general modes of wave climate variability and trends,...
Published in: | Journal of Physical Oceanography |
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Main Authors: | , , , |
Other Authors: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
American Meteorological Society
2014
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Subjects: | |
Online Access: | http://hdl.handle.net/10902/10284 https://doi.org/10.1175/JPO-D-13-0276.1 |
Summary: | Traditional approaches for assessing wave climate variability have been broadly focused on aggregated or statistical parameters such as significant wave height, wave energy flux, or mean wave direction. These studies, although revealing the major general modes of wave climate variability and trends, do not take into consideration the complexity of the wind-wave fields. Because ocean waves are the response to both local and remote winds, analyzing the directional full spectra can shed light on atmospheric circulation not only over the immediate ocean region, but also over a broad basin scale. In this work, the authors use a pattern classification approach to explore wave climate variability in the frequency–direction domain. This approach identifies atmospheric circulation patterns of the sea level pressure from the 31-yr long Climate Forecast System Reanalysis (CFSR) and wave spectral patterns of two selected buoys in the North Atlantic, finding one-to-one relations between each synoptic pattern (circulation type) and each spectral wave energy distribution (spectral type). Even in the absence of long-wave records, this method allows for the reconstruction of longterm wave spectra to cover variability at several temporal scales: daily, monthly, seasonal, interannual, decadal, long-term trends, and future climate change projections. The authors are grateful to Puertos del Estado (Spanish Ministry of Public Works and Infrastructures) for providing us the instrumental buoy data. This work was partially funded by the project IMAR21 (CT M2010-15009) from the Spanish Government. |
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