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Every year the Caribbean Sea faces the passage of several tropical cyclones that generate coastal extreme sea levels with potential strong and hazardous impacts. In this work we simulate the storm surges and wind waves induced by a set of 1000 tropical cyclones over the Caribbean Sea that are representative of the present-day climate. These events have been extracted from a global database of synthetic tropical cyclones spanning a 10 000-year period. The atmospheric forcing fields, associated with the set of tropical cyclones, are used to feed a coupled hydrodynamic–wave model with high resolution (∼ 2 km) along the continental and island coasts. Given the large number of events modelled, our results allow detailed statistical analyses of the magnitude and mechanisms of coastal extreme sea levels, as well as the identification of one of the most exposed areas to both storm surges and extreme wind waves. [ABSTRACT FROM AUTHOR]

The ocean component and coastal impacts of Storm Gloria, which hit the western Mediterranean between 20 and 23 January 2020, are investigated with a numerical simulation of the storm surges and wind waves. Storm Gloria caused severe damages and beat several historical records, such as significant wave height or 24 h accumulated precipitation. The storm surge that developed along the eastern coasts of the Iberian Peninsula, reaching values of up to 1 m, was accompanied by wind waves with a significant wave height of up to 8 m. Along the coasts of the Balearic Islands, the storm footprint was characterised by a negligible storm surge and the impacts were caused by large waves. The comparison to historical records reveals that Storm Gloria is one of the most intense among the events in the region during the last decades and that the waves' direction was particularly unusual. Our simulation permits quantification of the role of the different forcings in generating the storm surge. Also, the high spatial grid resolution down to 30 m over the Ebro Delta allows determination of the extent of the flooding caused by the storm surge. We also simulate the overtopping caused by high wind waves that affected a rocky coast of high cliffs (∼15 m) on the eastern coast of Mallorca. [ABSTRACT FROM AUTHOR]

The ocean component and coastal impacts of Storm Gloria, that hit the Western Mediterranean between January 20th and 23rd 2020 are investigated with a numerical simulation of the storm surges and wind- waves. Storm Gloria caused severe damages and beat several historical records such as significant wave height or 24-h accumulated precipitation. The storm surge developed along the eastern coasts of the Iberian Peninsula reached values up to 1 m, and were accompanied by wind-waves with significant wave height up to 8 m. Along the coasts of the Balearic Islands, the storm footprint was characterised by a negligible storm surge and the impacts were caused by large waves. The comparison to historical records reveals that Storm Gloria is one of the most intense among the events in the region during the last decades and that the waves direction was particularly unusual. Our simulation permits quantifying the role of the different forcings in generating the storm surge. Also, the high spatial grid resolution down to 30 m over the Ebro Delta, allows determining the extent of the flooding caused by the storm surge. We also simulate the overtopping caused by high wind waves that affected a rocky coast of high cliffs (~ 15 m) in the eastern coast of Mallorca Island. [ABSTRACT FROM AUTHOR]

Remotely generated swell waves are the dominant contributor of the coastal wind-wave climate along most of the world coastlines. In this work we describe the characteristics of swells from a coastal perspective. We identify the main regions of formation of swell waves at present and during the late twenty-first century under the RCP8.5 emissions/climate change scenario. We have applied an algorithm that allows one to unequivocally differentiate the swell component from the local wind-waves for a global wave hindcast and for eight CMIP5 state-of-the-art wave model climate projections. We have identified four different regions of swell formation, two in each hemisphere, with the Southern Ocean being by far the main region of swell generation. By the end of this century, the number of swell events generated in the Northern Hemisphere is expected to decrease while the opposite is projected to occur in the Southern Hemisphere. The increase in the Southern Hemisphere is directly associated with a poleward movement and intensification of the wind belts projected by atmospheric climate models. [ABSTRACT FROM AUTHOR]

The dependence between extreme storm surges and wind waves is assessed statistically along the global coasts using the outputs of two numerical models consistently forced with the same atmospheric fields. We show that 55% of the world coastlines face compound storm surge wave extremes. Hence, for a given level of probability, neglecting these dependencies leads to underestimating extreme coastal water levels. Dependencies are dominant in midlatitudes and are likely underestimated in the tropics due to limited representation of tropical cyclones. Furthermore, we show that in half of the areas with dependence, the estimated probability of occurrence of coastal extreme water levels increases significantly when it is accounted for. Translated in terms of return periods, this means that along 30% of global coastlines, extreme water levels expected at most once in a century without considering dependence between storm surges and waves become a 1 in 50‐year event. Plain Language Summary: Coastal flooding is caused by a combination of factors, among which storm surges and wind waves are of major relevance due to their potentially large contributions to coastal extreme sea levels and their widespread effects. Based on global scale numerical simulations of these two components, we have investigated the relationship between extreme storm surges and waves along the world coastlines. We find that in more than half of the coastal regions, storm surges tend to be accompanied by large wind waves, thus increasing the potential coastal flooding. Measures for coastal protection often rely on the probability of occurrence of exceedance events (return periods for prescribed water heights), which in turn is determined by the dependence between the contributors to extreme sea levels. The dependency between surges and waves implies that the likelihood of co‐occurrence of extremes is higher than assuming these two variables as unrelated. More specifically, the probability of facing a 1 in 100‐year event is more than doubled in 30% of the global coastlines when accounting for the dependence between storm surges and waves. Considering these dependencies has a strong impact on return period estimates of extreme high waters and is therefore relevant for the design of coastal defenses. Key Points: Extreme storm surges and wind waves tend to occur in concurrence along 55% of the world coastlinesReturn periods of extreme sea levels are underestimated (by a factor of 2 or higher) in 30% of the coasts, if dependence is neglected [ABSTRACT FROM AUTHOR]

This study analyses the distribution of ocean wind waves in response to extratropical cyclones over the western Mediterranean Sea. To this end we use an ERA40‐based database of atmospheric cyclones and a 3‐hourly wind wave hindcast with high horizontal resolution (1/6°) based on an ERA40 downscaled forcing for the region of study. The imprint of winds on surface waves is evaluated through composites of modelled significant wave height, surface wind and wave peak period collocated under the storms. Results highlight an asymmetric pattern that depends on the translational speed and size of the cyclonic perturbations. Uncertainties of the composites are at most 10% at 95% confidence interval, with an average maximum perturbation of significant wave height near 2 m for those cyclones moving faster than 10 m/s. The local imprint of atmospheric cyclones on wind–wave patterns has been statistically analysed in the western Mediterranean Sea on the basis of the outputs of numerical simulations of cyclones and waves. An asymmetry perpendicular to the storm direction appears on the wave field depending on the storm translation speed, wind intensity and storm size. The spatial location and the amplitude of the highest waves may be consistently predicted through parameterizing the storm features. [ABSTRACT FROM AUTHOR]

A dynamical wind-wave climate simulation covering the North Atlantic Ocean and spanning the whole 21st century under the A1B scenario has been compared with a set of statistical projections using atmospheric variables or large scale climate indices as predictors. As a first step, the performance of all statistical models has been evaluated for the present-day climate; namely they have been compared with a dynamical wind-wave hindcast in terms of winter Significant Wave Height (SWH) trends and variance as well as with altimetry data. For the projections, it has been found that statistical models that use wind speed as independent variable predictor are able to capture a larger fraction of the winter SWH inter-annual variability (68% on average) and of the long term changes projected by the dynamical simulation. Conversely, regression models using climate indices, sea level pressure and/or pressure gradient as predictors, account for a smaller SWH variance (from 2.8% to 33%) and do not reproduce the dynamically projected long term trends over the North Atlantic. Investigating the wind-sea and swell components separately, we have found that the combination of two regression models, one for wind-sea waves and another one for the swell component, can improve significantly the wave field projections obtained from single regression models over the North Atlantic. [ABSTRACT FROM AUTHOR]

ABSTRACT This study investigates the relationship between the wind wave climate and the main climate modes of atmospheric variability in the North Atlantic Ocean. The modes considered are the North Atlantic Oscillation ( NAO), the East Atlantic ( EA) pattern, the East Atlantic Western Russian ( EA/ WR) pattern and the Scandinavian ( SCAN) pattern. The wave dataset consists of buoys records, remote sensing altimetry observations and a numerical hindcast providing significant wave height ( SWH), mean wave period ( MWP) and mean wave direction ( MWD) for the period 1989-2009. After evaluating the reliability of the hindcast, we focus on the impact of each mode on seasonal wave parameters and on the relative importance of wind-sea and swell components. Results demonstrate that the NAO and EA patterns are the most relevant, whereas EA/ WR and SCAN patterns have a weaker impact on the North Atlantic wave climate variability. During their positive phases, both NAO and EA patterns are related to winter SWH at a rate that reaches 1 m per unit index along the Scottish coast ( NAO) and Iberian coast ( EA) patterns. In terms of winter MWD, the two modes induce a counterclockwise shift of up to 65° per negative NAO (positive EA) unit over west European coasts. They also increase the winter MWP in the North Sea and in the Bay of Biscay (up to 1 s per unit NAO) and along the western coasts of Europe and North Africa (1 s per unit EA). The impact of winter EA pattern on all wave parameters is mostly caused through the swell wave component. [ABSTRACT FROM AUTHOR]

Abstract: Wave climate in the Western Mediterranean is presented through the calibration of an update wind wave hindcast spanning the period 1958–2008. The hindcast was obtained with the WAM model (spatial resolution of 1/6°) forced with wind fields from the atmospheric model ARPERA. Significant wave heights (SWH) provided by the hindcast were calibrated using buoy observations with the aim of improving the characterization of the wave climate over the region. The methodology is based on a spatial calibration of the statistical distribution of SWH performed through a non-linear transformation of the Empirical Orthogonal Functions of the modeled data that minimizes the differences with observations. This allows the calibration to be implemented not only at buoy locations, but also all over the model domain. The resulting fields were validated against satellite altimetry observations, showing an average reduction of about 76% in the bias and of about 10% in the root mean squared differences with respect to observations. [Copyright &y& Elsevier]