Understanding wave systems (WS) dynamics in semi-enclosed tropical basins is challenging due to interactions between remote wave generation and regional climate variability. In the Gulf of Panama, prior studies mainly relied on single-site offshore analyses, limiting characterization of wave energy distribution and its atmospheric and oceanic drivers. This gap in knowledge is particularly consequential for coastal hazard assessments and for deciphering ocean–atmosphere interactions in regions influenced by both long-period swells and low-level wind jets. To address this limitation, we present a comprehensive multi-decadal analysis of the seasonal and long-term variability of significant wave height (Hs) and peak wave period (Tp), based on WS identified applying spectral statistical techniques using the GLOSWAC-5 atlas. To understand the variability and the modulating effect of the Gulf of Panama semi-enclosed morphology, three representative sites at its entrance were selected. Monthly patterns were analyzed by classifying wave trains according to relative orientation (i.e., following, crossing, and opposing) to determine the predominant direction and multimodal activity. Long-term trends were assessed over 17 to 18-year intervals (i.e. 1969–1987, 1988–2005, 2006–2023) using exploratory analysis and quantile regression, with results reported separately for the dry season (December–April) and the wet season (May–November). The analysis revealed five dominant WS, each associated with specific generation mechanisms and geographic origins: WS1, associated with Southern Ocean swells; WS5, originating from Northern Hemisphere swells; WS2, driven by southeasterly trade winds from the subtropical Pacific; and two regionally forced systems, WS3 and WS4, generated by the Panama and Chocó Low-Level Jets, respectively. WS1 shows increases in Hs of about 5–10 cm during 1969–1987 and 1988–2005, and up to ~ 15 cm in 2006–2023, with Tp rising by ~ 0.3–0.6 s over the same intervals. WS2 exhibits small variations, with Hs ranging from − 10 to + 17 cm and Tp fluctuations within ± 0.3 s across the three intervals. WS3 displays the strongest changes, with median Hs increases of 10–30 cm in the first two intervals and extreme values reaching 50–60 cm in 1988–2005 and 2006–2023, together with Tp increments of ~ 0.3–0.5 s. WS4 remains comparatively stable in all periods, with Hs variations within ± 10 cm and Tp changes < 0.4 s. WS5 intensifies mainly in 2006–2023, showing Hs increases of 8–15 cm and Tp rises of ~ 0.2–0.4 s. Monthly mean Hs anomalies (> 0.10 m) at the 50th percentile suggest a relationship with El Niño–Southern Oscillation (ENSO), but analyses using the 95th percentile reveal that only WS2, WS3, and WS4 exhibit a stronger association with ENSO phases.

Changing (wind) climate might influence the magnitude, direction, and frequency of wave systems (Lobeto et al., 2021). However, in coastal engineering applications, generalized wave parameters are commonly used in climate change assessments with the risk of, for example, misrepresenting the nearshore transformation of wind-driven wave climates (Hegermiller et al., 2017). In consequence, these uncertainties in the nearshore (wind) climate will affect, amongst others, ship navigation, the implementation of marine renewable energy farms, the feasibility of coastal infrastructure and defences, or the efficiency of sandy coastal maintenance, and thus the decision-making of long-term, multidecadal coastal strategies (Rijksoverheid, 2013), especially when they are designed accounting for the Building with Nature concept (de Vriend et al., 2015). This study analyses the importance and application of considering multiple coexisting wave trains on the Dutch shoreface.