Abstract
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 long-term wave spectra to cover variability at several temporal scales: daily, monthly, seasonal, interannual, decadal, long-term trends, and future climate change projections.
Long-term variability and trends in the Caspian Sea – Hindu Kush Index: Influence on atmospheric circulation patterns, temperature and rainfall over the Middle East and Southwest Asia
