Influence of the Pacific‐South American Modes on the Global Spectral Wind‐Wave Climate

Abstract

In this study, we analyze the influence of the Pacific‐South American modes (PSA‐1 and PSA‐2) on the global wind‐wave climate using wave data derived from a WAVEWATCH III global wave hindcast. We apply an empirical orthogonal function analysis to daily‐averaged directional wave spectra to extract the two main patterns of interannual wave spectral variability. These are related to changes in the wave spectral density levels (variability in the wave heights) and to rotations of the wave signal (variability in wave direction). The PSA‐1 mode is positively correlated with the wave height variability in the southeast Pacific and negatively correlated in the Indian Ocean sector of the Southern Ocean. The PSA‐2 mode presents a strong negative correlation with wave heights in the central South Pacific. Moreover, the PSA modes are significantly correlated with changes in modeled wave direction in the South Pacific region. Composite maps of wind anomalies during positive stages of PSA‐1 and PSA‐2 provide a compelling explanation for the observed correlation patterns. The methodology applied in this study is also used to assess the influence of other climate modes on the global wind‐wave climate (namely, the Southern Annular Mode, Arctic Oscillation, North Atlantic Oscillation, El Niño/Southern Oscillation, and the Pacific North American mode). While our results are consistent with previous studies, we provide more clarity as to how different atmospheric modes influence the variability of specific components of the wave spectrum. Importantly, we assess how these climate modes would modulate the interannual variability of wave direction.

Natural Variability and Warming Signals in Global Ocean Wave Climates

“…The link between planetary winds, pressures systems, and WCTs, gives us a fuller understanding of the causal mechanisms between the climate patterns, global warming and wave climate, and provides a more accurate quantification of their impacts. Moreover, the findings regarding these WCTs are in agreement with previous studies on global wave variability (Echevarria et al, 2020;Hemer, Fan, et al, 2013;Reguero et al, 2019;Shimura et al, 2013;Stopa & Cheung, 2014) and swell wave generation (Alves, 2006;Li, 2016; Semedo et al, 2011). Indeed, some of the WCTs shown here exhibit the same spatial patterns as those obtained by other authors (Echevarria et al, 2019;Jiang, 2020).…”

Global wave hindcast with Australian and Pacific Island Focus: From past to present

“…The CAWCR wave hindcast has been extensively used to explore the climatology of wave climate, utilizing both the bulk wave parameters (Marshall et al, 2015(Marshall et al, , 2018(Marshall et al, , 2020Godoi et al, 2020) and spectral information (Echevarria et al, 2019(Echevarria et al, , 2020. The derivation of wave climatological information has applications in determining the efficacy of wave energy resources (Amiruddin et al, 2019) and leads to the calculation of energy potential from wave data (Morim et al, 2016;Hemer et al, 2017).…”

Projections of Directional Spectra Help to Unravel the Future Behavior of Wind Waves

“…Directional spectra provide additional information by characterizing how wave energy is spread along directional sectors, enabling us to undertake a more detailed analysis of the wave climatology in a particular location (Espejo et al, 2014;Shimura and Mori, 2019) and to identify the different wave systems reaching it (Portilla-Yandún et al, 2015). More recently, directional spectra have been utilized to develop studies at global scale, assessing the wave climate seasonality through the identification of wave modes and their variations throughout the year (Echevarria et al, 2019), as well as their relation with climate teleconnection patterns (Echevarria et al, 2020).…”