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This study investigates the contribution of external forcings on global and regional ocean wave height change during 1961–2020. Historical significant wave height (Hs) produced for different CMIP6 external forcings and preindustrial control conditions following the Detection and Attribution Model Intercomparison Project (DAMIP) are employed. The internal variability ranges are compared with different external forcing scenario. Statistically significant linear trends in Hs computed over regional ocean basins are found to be mostly associated with anthropogenic forcings: greenhouse gas‐only (GHG) and aerosol‐only (AER) forcing. For Hs, GHG signals are robustly detected and dominant for most of the global ocean, except over North pacific and South Atlantic, where AER signals are dominant. These results are supported by multi‐model analysis for wind speed. The remarkable increase in Hs over the Arctic (22.3%) and Southern (8.2%) Ocean can be attributed to GHG induced sea‐ice depletion and larger effective fetch along with wind speed increase. Plain Language Summary: We quantify the influence of anthropogenic forcings (greenhouse gas‐only and aerosol‐only forcing) and natural forcing to the significant wave height trends during 1961–2020 using CMIP6 individual forcing experiments. It is shown that anthropogenic influence is majorly responsible for the significant wave height changes and natural (solar and volcanic activities) forcings show limited influence. The human‐induced greenhouse gas increases are found to be the dominating factor for most of the global ocean, whereas anthropogenic aerosols are the dominating forcing for a few ocean basins, such as North Pacific and South Atlantic. The multimodel analysis for wind speed corroborates the relative dominance of signals in wave height change. In the polar ocean (Arctic and Southern Ocean), we see exceptional wave height increase compared to other regions. Sea‐ice decline associated with greenhouse gas forcing provides larger fetch for the waves to grow in polar region. Moreover, the contrasting influence of greenhouse gas and aerosol forcing to sea‐ice area and wind speed changes are shown to drive the total wave height changes. Key Points: CMIP6/DAMIP simulations show that anthropogenic signals are robustly detected for the significant wave height (Hs) trends during 1961–2020Greenhouse gases are the major contributor for Hs trends over the global ocean, but aerosols dominance is seen for a few regional basinsHigh increase in Hs over the Polar oceans is due to greenhouse gas induced sea‐ice decline, fetch enlargement and wind speed increase [ABSTRACT FROM AUTHOR]

Satellite observations of significant wave height (Hs) have recently reached 30 years of continuous record. Is this length sufficient to detect the effect of anthropogenically forced climate change on wave height trends? Wave height decadal variability is influenced by a combination of internal variability and forced variability caused by both anthropogenic and natural forcing. Using a statistical model to derive Hs from sea level pressure field and exploiting ERA‐5 reanalysis data as well as 80 members of the Community Earth System Model v2 large ensemble, we show that, over the North Atlantic (NA), altimetry‐based Hs trends are mostly caused by internal variability. This suggests that Hs changes computed over the satellite era are not yet controlled by anthropogenic climate change. Starting from 1993, the date of emergence, defined as the date when the forced signal becomes dominant over the internal variability, is later than 2050 for Hs in the NA. Plain Language Summary: Satellite observations of significant wave height will soon reach 30 years of continuous record. Changes in significant wave height over this period can either be attributed to both anthropogenic or "natural" climate forcing or to the intrinsic variability of the climate system. In this article, we show that the intrinsic variability effect largely dominates the significant wave height changes in the North Atlantic (NA) over the 30 years of satellite observations. We further estimate that the significant wave height changes associated with anthropogenically forced climate change will become dominant over those due to the intrinsic variability after 2050 in most of the NA region. Key Points: Altimeter based significant wave height trends in the North Atlantic (NA) are largely dominated by internal variabilityForced significant wave height changes in the NA will only be detectable in altimeter data after 2050 [ABSTRACT FROM AUTHOR]

Numerical wave models are generally less accurate in the coastal ocean than offshore. It is generally suspected that a number of factors specific to coastal environments can be blamed for these larger model errors: complex shoreline and topography, relatively short fetches, combination of remote swells and local wind seas, less accurate wind fields, presence of strong currents, bottom friction, etc. These factors generally have strong local variations, making it all the more difficult to adapt a particular model setup from one area to another. Here we investigate a wide range of modeling choices including forcing fields, spectral resolution, and parameterizations of physical processes in a regional model that covers most of the Atlantic and North Sea coasts. The effects of these choices on the model results are analyzed with buoy spectral data and wave parameter time series. Additionally, satellite altimeter data are employed to provide a more complete performance assessment of the modeled wave heights as a function of the distance to the coast and to identify areas where wave propagation is influenced by bottom friction. We show that the accurate propagation of waves from offshore is probably the most important factor on exposed shorelines, while other specific effects can be important locally, including winds, currents, and bottom friction. [ABSTRACT FROM AUTHOR]

Ocean wave measurements are of major importance for a number of applications including climate studies, ship routing, marine engineering, safety at sea, and coastal risk management. Depending on the scales and regions of interest, a variety of data sources may be considered (e.g., in situ data, Voluntary Observing Ship observations, altimeter records, numerical wave models), each one with its own characteristics in terms of sampling frequency, spatial coverage, accuracy, and cost. To combine multiple source of wave information (e.g., for data assimilation scheme in numerical weather prediction models), the error characteristics of each measurement system need to be defined. In this study, we use the triple collocation technique to estimate the random error variance of significant wave heights from a comprehensive collection of collocated in situ, altimeter, and model data. The in situ dataset is a selection of 122 platforms provided by the Copernicus Marine Service In Situ Thematic Center. The altimeter dataset is the ESA Sea State CCI version1 L2P product. The model dataset is the WW3-LOPS hindcast forced with bias-corrected ERA5 winds and an adjusted T475 parameterization of wave generation and dissipation. Compared to previous similar analyses, the extensive (∼250 000 entries) triple collocation dataset generated for this study provides some new insights on the error variability associated to differences in in situ platforms, satellite missions, sea state conditions, and seasonal variability. [ABSTRACT FROM AUTHOR]

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 ,), a daily merged multi mission along-track L3 product (http://dx.doi.org/10.5285/3ef6a5a66e9947d39b356251909dc12b ,) and a multi-mission monthly gridded L4 product (http://dx.doi.org/10.5285/47140d618dcc40309e1edbca7e773478 ,). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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Longshore sediment transport (LST) is a major driver of coastal evolution. However, despite the recognition that it presents an unsteady behavior at the seasonal scale, the variability at longer term scales (interannual and decadal) is still far from being properly acknowledged. The present work contributes to the understanding of the seasonal to decadal variability of the LST, benefiting from recent developments in wave hindcast modeling. This work was developed for the northwest coast of Portugal, which is fully exposed to the highly energetic wave regime generated in the Northeast Atlantic Ocean that induces unusually large LST rates. Hindcast offshore waves, between 1953 and 2010, were used as offshore forcing to deduce LST estimates. The mean annual LST, between 1953 and 2010, shows an irregular and noncyclic pattern. Computed mean annual LST, for this coastal stretch, is around 1 million cubic meters directed to the south, with yearly averages ranging from 108,000 to 2.24 million m3 year−1 always directed to the south. The maximum observed annual LST magnitude exceeds the mean magnitude by more than 100%. The variability in LST magnitude was found to be mainly related to the LST magnitudes of autumn/winter months in response to the wave regime seasonality. Results show that to estimate the long-term LST within an error of about 20%, a period of about 10 years of data/observations is required. Interannual variability in the magnitude of the LST was found to be correlated () with the annual North Atlantic Oscillation (NAO) index. In the years where the NAO index was higher, the mean annual LST was generally greater than the long-term average, while negative NAO index corresponds to lower than average LST estimates. [ABSTRACT FROM AUTHOR]

Long-term changes of wind-generated ocean waves have important consequences for marine engineering, coastal management, ship routing, and marine spatial planning. It is well-known that the multi-annual variability of wave parameters in the North Atlantic is tightly linked to natural fluctuations of the atmospheric circulation, such as the North Atlantic Oscillation. However, anthropogenic climate change is also expected to influence sea states over the long-term through the modification of atmospheric and ocean circulation and melting of sea ice. Due to the relatively short duration of historical sea state observations and the significant multi-decadal variability in the sea state signal, disentangling the anthropogenic signal from the natural variability is a challenging task. In this article, the literature on inter-annual to multi-decadal variability of sea states in the North Atlantic is reviewed using data from both observations and model reanalysis. [ABSTRACT FROM AUTHOR]

Error in Figures Corrections Section 4.4: Comparison against Wave Model Figure 9 depicts the comparison statistics against the ERA5-h model for the retracked Jason-3 (J3) datasets. Text Correction Corrections Section 4.6: Selection and Decision Process of ESA SeaState cci Consortium The update of the comparison against wave model analysis statistics results in a slight change of the ranking. WHALES-SAR and DeDop-Waver now share the second place among the Delay-Doppler altimetry (DDA) retracking algorithms, as each of them wins one out of the two scoring schemes weighted metric scores and weighted metrics results. [Extracted from the article]

Radar altimeters have been measuring ocean significant wave height for more than three decades, with their data used to record the severity of storms, the mixing of surface waters and the potential threats to offshore structures and low-lying land, and to improve operational wave forecasting. Understanding climate change and long-term planning for enhanced storm and flooding hazards are imposing more stringent requirements on the robustness, precision, and accuracy of the estimates than have hitherto been needed. Taking advantage of novel retracking algorithms, particularly developed for the coastal zone, the present work aims at establishing an objective baseline processing chain for wave height retrieval that can be adapted to all satellite missions. In order to determine the best performing retracking algorithm for both Low Resolution Mode and Delay-Doppler altimetry, an objective assessment is conducted in the framework of the European Space Agency Sea State Climate Change Initiative project. All algorithms process the same Level-1 input dataset covering a time-period of up to two years. As a reference for validation, an ERA5-based hindcast wave model as well as an in-situ buoy dataset from the Copernicus Marine Environment Monitoring Service In Situ Thematic Centre database are used. Five different metrics are evaluated: percentage and types of outliers, level of measurement noise, wave spectral variability, comparison against wave models, and comparison against in-situ data. The metrics are evaluated as a function of the distance to the nearest coast and the sea state. The results of the assessment show that all novel retracking algorithms perform better in the majority of the metrics than the baseline algorithms currently used for operational generation of the products. Nevertheless, the performance of the retrackers strongly differ depending on the coastal proximity and the sea state. Some retrackers show high correlations with the wave models and in-situ data but significantly under- or overestimate large-scale spectral variability. We propose a weighting scheme to select the most suitable retrackers for the Sea State Climate Change Initiative programme. [ABSTRACT FROM AUTHOR]

Abstract: Like other similar coastal systems, the Albufeira lagoon is artificially opened every year to promote water renewal and closes naturally within a few months. The evolution of the Albufeira Lagoon Inlet from its opening in April 2010 to its closure 8 months later is qualitatively and quantitatively analyzed through a combination of monthly field surveys and the application of a process-based morphodynamic model. Field data alone would not cover the whole space–time domain of the morphology of the inlet during its life time, whereas the morphodynamic model alone cannot reliably simulate the morphological development. Using a nudging technique introduced herein, this problem is overcome and a reliable and complete data set is generated for describing the morphological development of the tidal inlet. The new technique is shown to be a good alternative to extensive model calibration, as it can drastically improve the model performance. Results reveal that the lagoon imported sediments during its life span. However, the whole system (lagoon plus littoral barrier) actually lost sediments to the sea. This behavior is partly attributed to the modulation of tidal asymmetry by the spring–neap cycle, which reduces flood dominance on spring tides. Results also allowed the assessment of the relationship between the spring tidal prism and the cross-section of tidal inlets (the PA relationship). While this relationship is well established from empirical, theoretical and numerical evidences, its validity in inlets that are small or away from equilibrium was unclear. Results for the Albufeira lagoon reveal an excellent match between the new data and the empirical PA relationship derived for larger inlets and equilibrium conditions, supporting the validity of the relationship beyond its original scope. [Copyright &y& Elsevier]

Abstract: Tidal inlets are extremely dynamic, as a result of an often delicate balance between the effects of tides, waves and other forcings. Since the morphology of these inlets can affect navigation, water quality and ecosystem dynamics, there is a clear need to anticipate their evolution in order to promote adequate management decisions. Over decadal time scales, the position and size of tidal inlets are expected to evolve with the conditions that affect them, for instance as a result of climate change. A process-based morphodynamic modeling system is validated and used to analyze the effects of sea level rise, an expected shift in the wave direction and the reduction of the upper lagoon surface area by sedimentation on a small tidal inlet (Óbidos lagoon, Portugal). A new approach to define yearly wave regimes is first developed, which includes a seasonal behavior, random inter-annual variability and the possibility to extrapolate trends. Once validated, this approach is used to produce yearly time series of wave spectra for the present and for the end of the 21st century, considering the local rotation trends computed using hindcast results for the past 57 years. Predictions of the mean sea level for 2100 are based on previous studies, while the bathymetry of the upper lagoon for the same year is obtained by extrapolation of past trends. Results show, and data confirm, that the Óbidos lagoon inlet has three stable configurations, largely determined by the inter-annual variations in the wave characteristics. Both sea level rise and the reduction of the lagoon surface area will promote the accretion of the inlet. In contrast, the predicted rotation of the wave regime, within foreseeable limits, will have a negligible impact on the inlet morphology. [Copyright &y& Elsevier]