A pioneering and replicable method based on a 66‐year numerical weather and wave hindcast is developed to optimize a climate index based on the sea level pressure (SLP) that best explains winter wave height variability along the coast of western Europe, from Portugal to UK (36–52°N). The resulting so‐called Western Europe Pressure Anomaly (WEPA) is based on the sea level pressure gradient between the stations Valentia (Ireland) and Santa Cruz de Tenerife (Canary Islands). The WEPA positive phase reflects an intensified and southward shifted SLP difference between the Icelandic low and the Azores high, driving severe storms that funnel high‐energy waves toward western Europe southward of 52°N. WEPA outscores by 25–150% the other leading atmospheric modes in explaining winter‐averaged significant wave height, and even by a largest amount the winter‐averaged extreme wave heights. WEPA is also the only index capturing the 2013/2014 extreme winter that caused widespread coastal erosion and flooding in western Europe.

Long‐term changes in ocean surface waves are relevant to society and climate research. Significant wave height climatologies and trends over 1992–2017 are intercompared in four recent high‐quality global datasets using a consistent methodology. For two products based on satellite altimetry, including one from the European Space Agency Climate Change Initiative for Sea State, regional differences in mean climatology are linked to low and high sea states. Trends from the altimetry products, and two reanalysis and hindcast datasets, show general similarity in spatial variation and magnitude but with major differences in equatorial regions and the Indian Ocean. Discrepancies between altimetry products likely arise from differences in calibration and quality control. However, multidecadal observations at two buoy stations also highlight issues with wave buoy data, raising questions about their unqualified use, and more fundamentally about uncertainty in all products.

Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent, and sea state data users still mostly rely on numerical wave models for research and engineering applications. Facing the urgent need for a sea state climate data record, the Global Climate Observing System has listed “Sea State” as an Essential Climate Variable (ECV), fostering the launch in 2018 of the Sea State Climate Change Initiative (CCI). The CCI is a programme of the European Space Agency, whose objective is to realise the full potential of global Earth observation archives established by ESA and its member states in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset, the implementation and benefits of a high-level denoising method, its validation against in situ measurements and numerical model outputs, and the future developments considered within the Sea State CCI project. The Sea State CCI dataset v1 is freely available on the ESA CCI website (http://cci.esa.int/data, last access: 25 August 2020) at ftp://anon-ftp.ceda.ac.uk/neodc/esacci/sea_state/data/v1.1_release/ (last access: 25 August 2020). Three products are available: a multi-mission along-track L2P product (http://dx.doi.org/10.5285/f91cd3ee7b6243d5b7d41b9beaf397e1, Piollé et al., 2020a), a daily merged multi mission along-track L3 product (http://dx.doi.org/10.5285/3ef6a5a66e9947d39b356251909dc12b, Piollé et al., 2020b) and a multi-mission monthly gridded L4 product (http://dx.doi.org/10.5285/47140d618dcc40309e1edbca7e773478, Piollé et al., 2020c).

A 69‐year (1948–2017) numerical weather and wave hindcast is used to investigate the interannual variability and trend of winter wave height along the west coast of Europe. Results show that the winter‐mean wave height, variability, and periodicity all increased significantly in the northeast Atlantic over the last seven decades which primarily correlate with changes in the climate indices North Atlantic Oscillation (NAO) and West Europe Pressure Anomaly (WEPA) affecting atmospheric circulation in the North Atlantic. NAO and WEPA primarily explain the increase in winter‐mean wave height and periodicity, respectively, while both WEPA and NAO explain the increase in interannual variability. This increase in trend, variability, and periodicity resulted in more frequent high‐energy winters with high NAO and/or WEPA over the last decades. The ability of climate models to predict the winter NAO and WEPA indices a few months ahead will be crucial to anticipate coastal hazards in this region.

The storm sequence of the 2013–14 winter left many beaches along the Atlantic coast of Europe in their most eroded state for decades. Understanding how beaches recover from such extreme events is essential for coastal managers, especially in light of potential regional increases in storminess due to climate change. Here we analyse a unique dataset of decadal beach morphological changes along the west coast of Europe to investigate the post‐2013–14 winter recovery. We show that the recovery signature is site specific and multi‐annual, with one studied beach fully recovered after 2 years, and the others only partially recovered after 4 years. During the recovery phase, winter waves primarily control the timescales of beach recovery, as energetic winter conditions stall the recovery process whereas moderate winter conditions accelerate it. This inter‐annual variability is well correlated with climate indices. On exposed beaches, an equilibrium model showed significant skill in reproducing the post‐storm recovery and thus can be used to investigate the recovery process in more detail. © 2018 John Wiley & Sons, Ltd.