Improved understanding of how our coasts will evolve over a range of time scales (years-decades) is critical for effective and sustainable management of coastal infrastructure. Globally, sea-level rise will result in increased erosion, with more frequent and intense coastal flooding. Understanding of current and future coastal evolution requires robust knowledge of the wave climate. This includes spatial, directional and temporal variability, with recent research highlighting the importance of wave climate directionality on coastal morphological response, for example in UK, Australia and California. However, the variability of the inshore directional wave climate has received little attention, and an improved understanding could drive development of skillful seasonal or decadal forecasts of coastal response. We examine inshore wave climate at 63 locations throughout the United Kingdom and Ireland (1980–2017) and show that 73% are directionally bimodal. We find that winter-averaged expressions of six leading atmospheric indices are strongly correlated with both total and directional winter wave power (peak spectral wave direction) at all studied sites. Coastal classification through hierarchical cluster analysis and stepwise multi-linear regression of directional wave correlations with atmospheric indices defined four spatially coherent regions. We show that combinations of indices have significant skill in predicting directional wave climates (r= 0.45–0.8; p<0.05). We demonstrate for the first time the significant explanatory power of leading winter-averaged atmospheric indices for directional wave climates, and show that leading seasonal forecasts of the NAO skillfully predict wave climate in some regions.

Embayed beaches separated by irregular rocky headlands represent 50% of global shorelines. Quantification of inputs and outflows via headland bypassing is necessary for evaluating long-term coastal change. Bypassing rates are predictable for idealised headland morphologies; however, it remains to test the predictability for realistic morphologies, and to quantify the influence of variable morphology, sediment availability, tides and waves-tide interactions. Here we show that headland bypassing rates can be predicted for wave-dominated conditions, and depend upon headland cross-shore length normalised by surf zone width, headland toe depth and spatial sediment coverage. Numerically modelled bypassing rates are quantified for 29 headlands under variable wave, tide and sediment conditions along 75km of macrotidal, embayed coast. Bypassing is predominantly wave-driven and nearly ubiquitous under energetic waves. Tidal elevations modulate bypassing rates, with greatest impact at lower wave energies. Tidal currents mainly influence bypassing through wave-current interactions, which can dominate bypassing in median wave conditions. Limited sand availability off the headland apex can reduce bypassing by an order of magnitude. Bypassing rates are minimal when cross-shore length > 5 surf zone widths. Headland toe depth is an important secondary control, moderating wave impacts off the headland apex. Parameterisations were tested against modelled bypassing rates, and new terms are proposed to include headland toe depth and sand coverage. Wave-forced bypassing rates are predicted with mean absolute error of a factor 4.4. This work demonstrates wave-dominated headland bypassing is amenable to parameterisation and highlights the extent to which headland bypassing occurs with implications for embayed coasts worldwide.