Global Wave Climate Research Articles

An 8-model ensemble of CMIP6-derived ocean surface wave climate

We present a global wind wave climate model ensemble composed of eight spectral wave model simulations forced by 3-hourly surface wind speed and daily sea ice concentration from eight different CMIP6 GCMs. The spectral wave model uses ST6 physics parametrizations and a global three-grid structure for efficient Arctic and Antarctic wave modeling. The ensemble performance is evaluated against a reference global multi-mission satellite altimeter database and the recent ECMWF IFS Cy46r1 ERA5 wave hindcast, ERA5H. For each ensemble member three 30-year slices, one historical, and two future emission scenarios (SSP1-2.6 and SSP5-8.5) are available, and cover two distinct periods: 1985–2014 and 2071–2100. Two models extend to 140 years (1961–2100) of continuous wind wave climate simulations. The present ensemble outperforms a previous CMIP5-forced wind wave climate ensemble, showing improved performance across all ocean regions. This dataset is a valuable resource for future wind wave climate research and can find practical applications in offshore and coastal engineering projects, providing crucial insights into the uncertainties connected to wind wave climate future projections.

On the assessment of the wave modeling uncertainty in wave climate projections

Abstract This study investigates the epistemic uncertainty associated with the wave propagation modeling in wave climate projections. A single-forcing, single-scenario, seven-member global wave climate projection ensemble is used, developed using three wave models with a consistent numerical domain. The uncertainty is assessed through projected changes in wave height, wave period, and wave direction. The relative importance of the wave model used and its internal parameterization are examined. The former is the dominant source of uncertainty in approximately two-thirds of the global ocean. The study reveals divergences in projected changes from runs of different models and runs of the same model with different parameterizations over 75% of the ensemble mean change in several ocean regions. Projected changes in the wave period shows the most significant uncertainties, particularly in the Pacific Ocean basin, while the wave height shows the least. Over 30% of global coastlines exhibit significant uncertainties in at least two out of the three wave climate variables analyzed. The coasts of western North America, the Maritime Continent and the Arabian Sea show the most significant wave modeling uncertainties.

Performance evaluation of a global CMIP6 single forcing, multi wave model ensemble of wave climate simulations

A performance evaluation is conducted for a state-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6)-derived ensemble of global wave climate simulations. A single-model (forcing), single-scenario approach is considered to build the ensemble, where the differentiating factor between each member is the wave model or physics parameterization used to simulate waves. The 7-member ensemble is evaluated for the 1995-2014 historical period, highlighting the impact of the multiple source terms on its robustness. The ensemble’s ability to accurately represent the present wave climate is assessed through an extensive comparison with long-term ERA5 reanalysis and in-situ observational data. Relevant aspects such as the depiction of extremes and natural wave climate variability are analyzed, and inter-member uncertainties are quantified. Overall, the results indicate that the ensemble is able to accurately simulate the global wave climate, regarding the significant wave height (HS), mean and peak wave periods (Tm and Tp, respectively) and mean wave direction (MWD). However, we show that using multiple wave models and parameterizations should be cautiously considered when building ensembles, even under the same forcing conditions. Model-parameterization-induced ensemble spreads during the historical period are found to be high, compromising the robustness of projected changes in wave parameters towards the end of the 21st century across several areas of the global ocean.

Global Climatology of Extratropical Cyclones From a New Tracking Approach and Associated Wave Heights From Satellite Radar Altimeter

AbstractExtratropical cyclones (ECs) produce comparable wave heights and hazardous sea states to those under hurricanes. With strong wind speeds and considerably larger diameters, the impact of ECs on the global wave climate is substantial. Because ECs occur more frequently, move more quickly, and exist in a large variety of sizes and shapes, these storms are not as well documented. Here, we present findings from a global EC tracking algorithm aimed at creating an EC database of wave producing storms. We focus on the major ocean basins of extratropical cyclone activity: The North Atlantic, North Pacific, and Southern Oceans. Our tracking algorithm uses mean sea level pressure fields from the European Centre for Medium‐Range Weather Forecasts (ECMWF) high resolution, advanced data assimilating, ERA5 reanalysis over the years 1979–2020. The 42 year‐long data set of thousands of cyclone tracks allows seasonal patterns and longer‐term trends of EC activity to be analyzed in these ocean regions. In addition, we employ 36 years of satellite radar altimeter‐derived significant wave height (Hs) data from 14 inter‐calibrated satellite missions to study the wave climate induced by the identified ECs in each basin. The resulting wave climatology compares well with previous results in the mid to high latitudes. We then analyze average wave heights under different EC characteristics, including cyclone translational speed and maximum winds, which have strong effects on wave height variability. Finally, a brief analysis of EC and wave climate under positive and negative phases of the North Atlantic Oscillation is presented.

Global Wind and Wave Climate Based on Two Reanalysis Databases: ECMWF ERA5 and NCEP CFSR

In the present work, the global wind and wave climate is studied on the basis of two well-known reanalysis products, namely ERA5 and CFSR-W (WW3 hereafter). Several statistical features of the datasets are assessed, such as seasonal variability, quantiles of the probability distribution, monthly, annual and inter-annual variability, and several error metrics. The time span covers a period of 31 years (1979–2009), a fact that assures that most of the long-scale features are equally present in both datasets. The analysis performed is depicted both on a global and regional scale. The results are also assessed by means of a global satellite altimeter dataset.

Natural Variability and Warming Signals in Global Ocean Wave Climates

AbstractThis paper presents a multivariate classification of the global wave climate into types driven by atmospheric circulation patterns. The primary source of the net long‐term variability is evaluated based on historical wave simulations. Results show that the monsoon, extratropical, subtropical, and polar wave climate types of the Pacific and North Atlantic Oceans are dominated by natural variability, whereas the extratropical and subtropical wave climate types in the Indian Ocean, and the tropical wave climate types of the Atlantic and Pacific Oceans exhibit a global warming signal. In the Pacific sector of the Southern Ocean, strong natural variability may mask a global warming signal that is yet to emerge as being statistically significant. In addition, wave climate teleconnections were found across the world that can provide a framework for joint strategies to achieve the goals of climate adaption for resilient coastal communities and environments.

LONG-TERM PREDICTION OF LONGSHORE SEDIMENT TRANSPORT IN THE CONTEXT OF CLIMATE CHANGE

Due to climate change impacts on atmospheric circulation, global and regional wave climate in many coastal regions around the world might change. Any changes in wave parameters could result in significant changes in wave energy flux, the patterns of coastal sediment transport, and coastal evolution. Although some studies have tried to address the potential impacts of climate change on longshore sediment transport (LST) patterns, they did not sufficiently consider the uncertainties arising from different sources in the projections. In this study, the uncertainty associated with the choice of model used for the estimation of LST is examined. The models were applied to a short stretch of coastline located in Northern Gold Coast, Australia, where a huge volume of sediment is transported along the coast annually. The ensemble of results shows that the future mean annual and monthly LST rate might decrease by about 11 percent, compared to the baseline period. The results also show that uncertainty associated with LST estimation is significant. Hence, it is proposed that this uncertainty, in addition to that from other sources, should be considered to quantify the contribution of each source in total uncertainty. In this way, a probabilistic-based framework can be developed to provide more meaningful output applicable to long-term coastal planningRecorded Presentation from the vICCE (YouTube Link): https://youtu.be/3CGU9RcGYjE

El Niño‐Southern Oscillation Impacts on Global Wave Climate and Potential Coastal Hazards

AbstractWave direction and wave power are the main climate‐related drivers of large‐scale coastal morphological hazards on open sandy coastlines. El Niño‐Southern Oscillation (ENSO) is the main climate driver affecting global wave climates on interannual timescales. Hence, a quantification of wave climate variability with ENSO would aid the characterization of coastal risk as a first‐pass assessment tool. However, no such data are available on the global scale at present. To address this, this work (1) quantifies ENSO impacts on global mean wave direction and wave power, and (2) classifies the global coast according to the ENSO wave climate hazard. The correlation coefficient (R) of the Multivariate ENSO Index between wave power and mean wave direction was calculated. Then, employing a multivariate technique, the resulting R values were used to classify the global coastlines. The results show that ENSO has distinct latitudinal impacts around the world. El Niño increases the wave power of swells generated in the extra‐tropics which propagate toward the tropics, a phenomenon which is particularly notable in the Pacific Basin, while the most significant rotations in wave direction with ENSO occur at tropical and subtropical latitudes. Based on this new information, the global coastline was classified into five distinct types, depending on the directional wave climate response to ENSO.

Bias-Corrected CMIP5-Derived Single-Forcing Future Wind-Wave Climate Projections toward the End of the Twenty-First Century

AbstractA quantile-based bias-correction method is applied to a seven-member dynamic ensemble of global wave climate simulations with the aim of reducing the significant wave heightHS, mean wave periodTm, and mean wave direction (MWD) biases, in comparison with the ERA5 reanalysis. The corresponding projected changes toward the end of the twenty-first century are assessed. Seven CMIP5 EC-EARTH runs (single forcing) were used to force seven wave model (WAM) realizations (single model), following the RCP8.5 scenario (single scenario). The biases for the 1979–2005 reference period (present climate) are corrected using the empirical Gumbel quantile mapping and empirical quantile mapping methods. The same bias-correction parameters are applied to theHS,Tm(and wave energy fluxPw), and MWD future climate projections for the 2081–2100 period. The bias-corrected projected changes show increases in the annual meanHS(14%),Tm(6.5%), andPw(30%) in the Southern Hemisphere and decreases in the Northern Hemisphere (mainly in the North Atlantic Ocean) that are more pronounced during local winter. For the upper quantiles, the bias-corrected projected changes are more striking during local summer, up to 120%, forPw. After bias correction, the magnitude of theHS,Tm, andPworiginal projected changes has generally increased. These results, albeit consistent with recent studies, show the relevance of a quantile-based bias-correction method in the estimation of the future projected changes in swave climate that is able to deal with the misrepresentation of extreme phenomena, especially along the tropical and subtropical latitudes.

The imprint of the ENSO activities on the South China Sea wave climate

Global warming is changing the global wave climate, making waves stronger. In this study, we find that the wave climate in the South China Sea (SCS) undergoes an intensifying trend under global warming background, by examining the ERA-5 wave reanalysis data over 1979–2018. Results show a significant increase in most of the SCS, of 0.2% per year in significant wave height (SWH) and 0.15% per year in wave period (WP), but there is no significant change in surface wind speed (WS), which may correspond to the weakening of the Asian monsoon. The increase of the swell is the main characteristic of wave climate change in the SCS. We further examined the possible factors to cause the increasing of SWH, and found that the frequency of gale events occurring in the SCS and its adjacent regions increased over study period. The more frequent gale events can explain the significant increasing tendency of the SWH in the SCS by causing the occurrence of swell. The increasing appearance of gale events is closely related to the intensification of El Nino/Southern Oscillation (ENSO). ENSO activities also can regulate the interannual variability of wave climate in the SCS through the surface wind. Therefore, ENSO activities play an important role in the change of wave climate in the SCS.

Climate drivers of directional wave power on the Mexican coast

Ocean waves are the main driver of sediment transport on open sandy coastlines, and inter-annual to multi-decadal variability in the wave climate significantly impacts year-on-year coastal risk. As such, the integration of large-scale climatic variability into local-scale coastal management studies is pertinent but seldom implemented in practice, mainly due to the lack of knowledge in this subject as is the case of Mexico. This knowledge gap is addressed here by quantifying the seasonal to long-term variability of the wave climate along the coasts of Mexico. The influence of large-scale climate drivers on this variability is also characterized. To do this, we identify monthly-averaged directional wave power signatures of the Mexican coast at a 0.5° resolution pertaining to a range of climate indices, using a newly available climate reanalysis product (ERA5) and a statistical-based global wave climate classification method. The wave climate of the Mexican Pacific coast is strongly bi-directional with considerable seasonal variability and high sensitivity to pan-hemispheric climate variability in the Pacific. Conversely, the wave climate of the Mexican Caribbean coast is more homogenous year-round, having its origins in the tropical Atlantic. Results show that El Nino effects break down the bi-directionality of the Mexican Pacific wave climate, leading to a more uni-directional, shore-normal, and more energetic nearshore wave power climate, compared with ENSO-neutral periods. Additionally, the wave power response to individual ENSO events can be either amplified or dampened depending on the underlying phase of the multi-decadal PDO.

A global view on bimodal wave spectra and crossing seas from ERA-interim

The paper aims at providing a global view of the wave climate, with specific focus on separation of the wave components and the analysis of crossing seas. The knowledge about complex sea-states may, in fact, have a great influence in the prediction of ship responses. The occurrence of bimodal wave spectra is assessed by analysing the ERA-interim wave database and in particular the parameters describing the different spectral components for wind-sea and swell. A brief description of the global wave climate is provided, with a discussion on the significance of the average conditions as representative for the actual scenarios that can be expected, and the consistency of the results with previous studies is verified. The contribution of the two regimes in different areas is then investigated, as well as the probability of crossing seas, separating the stormy conditions by the highly swell dominated periods, highlighting those regions where a traditional single peak representation could lead to inaccuracies in the representation of the actual sea-state. A qualitative analysis is then supported by some examples in which two different spectral models are compared in a number selected locations.

A global ensemble of ocean wave climate projections from CMIP5-driven models

This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, represents the first coordinated multivariate ensemble of 21st Century global wind-wave climate projections available (henceforth COWCLIP2.0). COWCLIP2.0 comprises general and extreme statistics of significant wave height (HS), mean wave period (Tm), and mean wave direction (θm) computed over time-slices 1979–2004 and 2081–2100, at different frequency resolutions (monthly, seasonally and annually). The full ensemble comprising 155 global wave climate simulations is obtained from ten CMIP5-based state-of-the-art wave climate studies and provides data derived from alternative wind-wave downscaling methods, and different climate-model forcing and future emissions scenarios. The data has been produced, and processed, under a specific framework for consistency and quality, and follows CMIP5 Data Reference Syntax, Directory structures, and Metadata requirements. Technical comparison of model skill against 26 years of global satellite measurements of significant wave height has been undertaken at global and regional scales. This new dataset provides support for future broad scale coastal hazard and vulnerability assessments and climate adaptation studies in many offshore and coastal engineering applications.

Wave Climate Patterns from Spatial Tracking of Global Long-Term Ocean Wave Spectra

AbstractLong-term wave spectral statistics can provide a better description of wave climate than integrated wave parameters because several wave climate systems (WCSs) generated by different wind climate systems can coexist at the same location. In this study, global wave climate patterns are presented by spatially tracking point-wise long-term wave spectra (probability density distributions of wave spectral partitions) from a WAVEWATCH III hindcast, providing new insights into global wave climate. Tens of well-defined WCSs, which are generated in different source regions by different wind systems, including prevailing westerlies, polar easterlies, trade winds, and monsoons, were identified. These WCSs are independent of each other because wave systems from different origins travel independently. The spatial distributions of these WCSs can illustrate the entire life cycle of ocean waves, from being generated as dominant wind-seas to becoming less dominant swells in far fields, from a climatic point of view. The mean wave directions in WCS patterns, especially those in westerlies-generated WCSs, are generally in agreement with the great circles on Earth’s surface, which display the propagation routes of ocean swells.

Impacts of the Cryosphere and Atmosphere on Observed Microseisms Generated in the Southern Ocean

The Southern Ocean (in the region 60–180° E) south of the Indian Ocean, Australia, and the West Pacific is noted for the frequent occurrence and severity of its storms. These storms give rise to high‐amplitude secondary microseisms from sources, including the deep ocean regions, and primary microseisms where the swells impinge on submarine topographic features. A better understanding of the varying microseism wavefield enables improvements to seismic imaging and development of proxy observables to complement sparse in situ wave observations and hindcast models of the global ocean wave climate. We analyze 12–26 years of seismic data from 11 seismic stations either on the East Antarctic coast or sited in the Indian Ocean, Australia, and New Zealand. The power spectral density of the seismic wavefield is calculated to explore how the time‐changing microseism intensity varies with (i) sea ice coverage surrounding Antarctica and (ii) the Southern Annular Mode (SAM) climate index. Variations in sea ice extent are found to be the dominant control on the microseism intensity at Antarctic stations, which exhibit a seasonal pattern phase‐shifted by 4–5 months compared to stations in other continents. Peaks in extremal intensity at East Antarctic stations occur in March–April, with the highest peaks for secondary microseisms occurring during negative SAM events. This relationship between microseism intensity and the SAM index is opposite to that observed on the Antarctic Peninsula. This work informs the complexity of microseism amplitudes in the Southern Hemisphere and assists ongoing interdisciplinary investigations of interannual variability and long‐term trends.

A classification system for global wave energy resources based on multivariate clustering

Better understanding of the global wave climate is required to inform wave energy device design and large-scale deployment. Spatial variability in the global wave climate is analysed here to provide a range of characteristic design wave climates. K-means clustering was used to split the global wave resource into 6 classes in a device agnostic, data-driven method using data from the ECMWF ERA5 reanalysis product. Classification using two sets of input data were considered: a simple set (based on significant wave height and peak wave period) and a comprehensive set including a wide range of relevant wave climate parameters. Both classifications gave resource classes with similar characteristics; 55% of tested locations were assigned to the same class. Two classes were low energy, found in enclosed seas and sheltered regions. Two classes were moderate wave energy classes; one swell dominated and the other in areas with wave action often generated by more local storms. Of the two higher energy classes; one was more often found in the northern hemisphere and the other, most energetic, predominantly on the tips of continents in the southern hemisphere. These classes match existing regional understanding of resource. Consideration of publicly available device power matrices showed good performance was primarily realised for the two highest energy resource classes (25–30% of potential deployment locations); it is suggested that effort should focus on optimising devices for additional resource classes. The authors hypothesise that the low-risk, low variability, swell dominated moderate wave energy class would be most suitable for future exploitation.

On the need of bias correction methods for wave climate projections

Abstract This study focuses on the assessment of systematic biases in wave climate simulations, exploring different bias correction methods commonly used for climate impact variables (e.g. precipitation, temperature), and on the analysis of bias corrected wave climate projections. Four different bias correction methods are analyzed, two of which are applied to an 8-member dynamic multi-forcing global wave climate ensemble, to mitigate the significant wave height (HS) bias. The GOW2 (Global Ocean Waves 2) global wave hindcast is used as reference data for the calibration. Assuming that the statistical properties of the present climate biases are maintained in the future, these biases can be corrected by applying a bias correction model based on the reference data. Thus, the impact of climate change in the bias corrected future HS climate, is also investigated. A bias corrected 8-member ensemble is analyzed for the 2081–2100 period, under the RCP8.5 scenario. The results indicate the relevance of bias correction in both the estimation of ensemble mean HS projected changes towards the end of the 21st century, and in the ensemble spread magnitude. Outcomes support the need for a quantile based bias correction, able to deal with extreme events, which have a disproportionate impact in coastal processes.

Robustness and uncertainties in global multivariate wind-wave climate projections

Understanding climate-driven impacts on the multivariate global wind-wave climate is paramount to effective offshore/coastal climate adaptation planning. However, the use of single-method ensembles and variations arising from different methodologies has resulted in unquantified uncertainty amongst existing global wave climate projections. Here, assessing the first coherent, community-driven, multi-method ensemble of global wave climate projections, we demonstrate widespread ocean regions with robust changes in annual mean significant wave height and mean wave period of 5–15% and shifts in mean wave direction of 5–15°, under a high-emission scenario. Approximately 50% of the world’s coastline is at risk from wave climate change, with ~40% revealing robust changes in at least two variables. Furthermore, we find that uncertainty in current projections is dominated by climate model-driven uncertainty, and that single-method modelling studies are unable to capture up to ~50% of the total associated uncertainty.

Seasonal Variability of the Global Spectral Wind Wave Climate

AbstractOur understanding of the seasonal variability in the global wind wave field is revisited here using a novel analysis that resolves the directional wave spectra. Empirical orthogonal function analysis was applied to modeled wave spectral data from a WAVEWATCH III hindcast across a sparse global grid to identify the main patterns of the climatological wave spectral variability at each grid point. Prior methods have focused on the variability of two modes of the wave field—locally generated sea and the primary swell component. Our results also consider additional wave modes at each location, enabling us to track the passage of the less dominant swell modes. Consistent with existing climatological knowledge, the main modes of wave spectral variability at high latitudes are related to eastward propagating waves that disperse equatorward as swell following great circle paths. However, despite being the less energetic mode, the Northern Hemisphere generated swell is found to propagate into the Southern Hemisphere further than the more energetic Southern Hemisphere swell which propagates northward. In the equatorial zone, a complex multimodal wave climate is found, with the spectra variability modulated by remotely generated swell and higher‐frequency waves associated with the prevailing winds. The evolution of these patterns throughout the year is clearly depicted. Overall, our approach captures a more complete picture of the seasonal variability of the global wave field, by accounting for all the wave modes observed in the spectra at each location together with their temporal variability.

Teleconnections and Extreme Ocean States in the Northeast Atlantic Ocean

Abstract. The Northeast Atlantic possesses an energetic and variable wind and wave climate which has a large potential for renewable energy extraction; for example along the western seaboards off Ireland. The role of surface winds in the generation of ocean waves means that global atmospheric circulation patterns and wave climate characteristics are inherently connected. In quantifying how the wave and wind climate of this region may change towards the end of the century due to climate change, it is useful to investigate the influence of large scale atmospheric oscillations using indices such as the North Atlantic Oscillation (NAO), the East Atlantic pattern (EA) and the Scandinavian pattern (SCAND). In this study a statistical analysis of these teleconnections was carried out using an ensemble of EC-Earth global climate simulations run under the RCP4.5 and RCP8.5 forcing scenarios, where EC-Earth is a European-developed atmosphere ocean sea-ice coupled climate model. In addition, EC-Earth model fields were used to drive the WAVEWATCH III wave model over the North Atlantic basin to create the highest resolution wave projection dataset currently available for Ireland. Using this dataset we analysed the correlations between teleconnections and significant wave heights (Hs) with a particular focus on extreme ocean states using a range of statistical methods. The strongest, statistically significant correlations exist between the 95th percentile of significant wave height and the NAO. Correlations between extreme Hs and the EA and SCAND are weaker and not statistically significant over parts of the North Atlantic. When the NAO is in its positive phase (NAO+) and the EA and SCAND are in a negative phase (EA−, SCAND−) the strongest effects are seen on 20-year return levels of extreme ocean waves. Under RCP8.5 there are large areas around Ireland where the 20-year return level of Hs increases by the end of the century, despite an overall decreasing trend in mean wind speeds and hence mean Hs.