We describe an innovative approach to estimate global changes in extreme wave conditions by 2100, as a result of projected climate change. We generate a synthetic dataset from an ensemble of wave models forced by independent climate simulation winds, enhancing statistical confidence associated with projected changes in extreme wave conditions. Under two IPCC representative greenhouse gas emission scenarios (RCP4.5 and RCP8.5), we find that the magnitude of a 1 in 100-year significant wave height (H_s) event increases by 5 to 15% over the Southern Ocean by the end of the 21st century, compared to the 1979–2005 period. The North Atlantic shows a decrease at low to mid latitudes (≈5 to 15%) and an increase at high latitudes (≈10%). The extreme significant wave height in the North Pacific increases at high latitudes by 5 to 10%. The ensemble approach used here allows statistical confidence in projected changes of extremes.

A holistic review is given of the Southern Ocean dynamic system, in the context of the crucial role it plays in the global climate and the profound changes it is experiencing. The review focuses on connections between different components of the Southern Ocean dynamic system, drawing together contemporary perspectives from different research communities, with the objective of closing loops in our understanding of the complex network of feedbacks in the overall system. The review is targeted at researchers in Southern Ocean physical science with the ambition of broadening their knowledge beyond their specific field, and aims at facilitating better‐informed interdisciplinary collaborations. For the purposes of this review, the Southern Ocean dynamic system is divided into four main components: large‐scale circulation; cryosphere; turbulence; and gravity waves. Overviews are given of the key dynamical phenomena for each component, before describing the linkages between the components. The reviews are complemented by an overview of observed Southern Ocean trends and future climate projections. Priority research areas are identified to close remaining loops in our understanding of the Southern Ocean system.

We present four 140-yr wind-wave climate simulations (1961–2100) forced with surface wind speed and sea ice concentration from two CMIP6 GCMs under two different climate scenarios: SSP1–2.6 and SSP5–8.5. A global three-grid system is implemented in WAVEWATCH III to simulate the wave–ice interactions in the Arctic and Antarctic regions. The models perform well in comparison with global satellite altimeter and in situ buoys climatology. The comparison with traditional trend analyses demonstrates the present GCM-forced wave models’ ability to reproduce the main historical climate signals. The long-term datasets allow a comprehensive description of the twentieth- and twenty-first-century wave climate and yield statistically robust trends. Analysis of the latest IPCC ocean climatic regions highlights four regions where changes in wave climate are projected to be most significant: the Arctic, the North Pacific, the North Atlantic, and the Southern Ocean. The main driver of offshore wave climate change is the wind, except for the Arctic where the significant sea ice retreat causes a sharp increase in the projected wave heights. Distinct changes in the wave period and the wave direction are found in the Southern Hemisphere, where the poleward shift of the Southern Ocean westerlies causes an increase in the wave period of up to 5% and a counterclockwise change in wave direction of up to 5°. The new CMIP6 forced wave models improve in performance compared to previous CMIP5 forced wave models, and will ultimately contribute to a new CMIP6 wind-wave climate model ensemble, crucial for coastal adaptation strategies and the design of future marine offshore structures and operations. Significance Statement: The purpose of this study is to advance the understanding of ocean wind-wave climate evolution over the twentieth and twenty-first centuries and to effectively communicate the long-term impacts of climate change in diverse wind-wave climatic regions across the globe. The 140-yr continuous model results produced in this work are crucial to studying changes in extreme sea states and investigating the relationship between interdecadal periodic oscillations and long-term climate trends. The dataset produced can be used to gain further insight into the substantial long-term changes of the polar wind-wave climate caused by the rapid decrease of sea ice coverage, and the evolution of the directional changes in the sea states triggered by climate change.

The trends in marine 10-m wind speed U₁₀ and significant wave height H_s found in two century-long reanalyses are compared against a model-only integration. Reanalyses show spurious trends due to the assimilation of an increasing number of observations over time. The comparisons between model and reanalyses show that the areas where the discrepancies in U₁₀ and H_s trends are greatest are also the areas where there is a marked increase in assimilated observations. Large differences in the yearly averages call into question the quality of the observations assimilated by the reanalyses, resulting in unreliable U₁₀ and H_s trends before the 1950s. Four main regions of the world’s oceans are identified where the trends between model and reanalyses deviate strongly. These are the North Atlantic, the North Pacific, the Tasman Sea, and the western South Atlantic. The trends at +24-h lead time are markedly weaker and less correlated with the observation count. A 1985–2010 comparison with an extensive dataset of calibrated satellite altimeters shows contrasting results in H_s trends but similar U₁₀ spatial trend distributions, with general agreement between model, reanalyses, and satellite altimeters on a broad increase in wind speed over the Southern Hemisphere.

The present work develops an innovative approach to wind speed and significant wave height extreme value analysis. The approach is based on global atmosphere–wave model ensembles, the members of which are propagated in time from the best estimate of the initial state, with slight perturbations to the initial conditions, to estimate the uncertainties connected to model representations of reality. The low correlation of individual ensemble member forecasts at advanced lead times guarantees their independence and allows us to perform inference statistics. The advantage of ensemble probabilistic forecasts is that it is possible to synthesize an equivalent dataset of duration far longer than the simulation period. This allows the use of direct inference statistics to obtain extreme value estimates. A short time series of six years (from 2010 to 2016) of ensemble forecasts is selected to avoid major changes to the model physics and resolution and thus ensure stationarity. This time series is used to undertake extreme value analysis. The study estimates global wind speed and wave height return periods by selecting peaks from ensemble forecasts from +216- to +240-h lead time from the operational ensemble forecast dataset of the European Centre for Medium-Range Weather Forecasts (ECMWF). The results are compared with extreme value analyses performed on a commonly used reanalysis dataset, ERA-Interim, and buoy data. The comparison with traditional methods demonstrates the potential of this novel approach for statistical analysis of significant wave height and wind speed ocean extremes at the global scale.