ALBERT

Description: The future Stokes drift climate is investigated using a global wave climate projection (2071–2100) forced with EC-EARTH winds under the RCP8.5 scenario. The future climate run is compared against a historical run (1976–2005). The Stokes drift climate is analyzed in terms of Stokes transport and surface Stokes drift. The impact on Stokes drift from changes to the wind, wind sea, and swell climate is identified. The consequences for upper-ocean mixing and circulation are studied by investigating the turbulent Langmuir number and the Stokes depth. The historical climate run is also compared to a hindcast with ERA-Interim forcing. Systematic discrepancies due to differences in resolution and model physics are identified, but no fundamental weaknesses are uncovered that should adversely affect the future run. As the surface Stokes drift is largely dictated by high-frequency waves, it is to a great degree controlled by changes to the local wind field, whereas the Stokes transport is more sensitive to swell. Both are expected to increase in the Southern Ocean by about 15%, while the North Atlantic sees a decrease of about 10%. The Stokes depth and the turbulent Langmuir number are set to change by about ±20% and ±10%, respectively. The changes to the Stokes depth suggest a deeper impact of the Coriolis–Stokes force in the Southern Ocean and a decrease in the northern extratropics. Changes to the KPP Langmuir-enhancement factor suggests potentially increased mixing in the Southern Ocean and a reduction in the North Atlantic and the North Pacific.

Description: The coupling of models is a commonly used approach when addressing the complex interactions between different components of earth systems. We demonstrate that this approach can result in a reduction of errors in wave forecasting, especially in dynamically complicated coastal ocean areas, such as the southern part of the North Sea – the German Bight. Here, we study the effects of coupling of an atmospheric model (COSMO) and a wind wave model (WAM), which is enabled by implementing wave-induced drag in the atmospheric model. The numerical simulations use a regional North Sea coupled wave–atmosphere model as well as a nested-grid high-resolution German Bight wave model. Using one atmospheric and two wind wave models simultaneously allows for study of the individual and combined effects of two-way coupling and grid resolution. This approach proved to be particularly important under severe storm conditions as the German Bight is a very shallow and dynamically complex coastal area exposed to storm floods. The two-way coupling leads to a reduction of both surface wind speeds and simulated wave heights. In this study, the sensitivity of atmospheric parameters, such as wind speed and atmospheric pressure, to the wave-induced drag, in particular under storm conditions, and the impact of two-way coupling on the wave model performance, is quantified. Comparisons between data from in situ and satellite altimeter observations indicate that two-way coupling improves the simulation of wind and wave parameters of the model and justify its implementation for both operational and climate simulations.

Description: The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the German Bight in the North Sea as a prime example of a heavily used coastal area, and Svalbard as an example of an Arctic coast that is under strong pressure due to global change.The COSYNA automated observing and modelling system is designed to monitor real-time conditions and provide short-term forecasts, data, and data products to help assess the impact of anthropogenically induced change. Observations are carried out by combining satellite and radar remote sensing with various in situ platforms. Novel sensors, instruments, and algorithms are developed to further improve the understanding of the interdisciplinary interactions between physics, biogeochemistry, and the ecology of coastal seas. New modelling and data assimilation techniques are used to integrate observations and models in a quasi-operational system providing descriptions and forecasts of key hydrographic variables. Data and data products are publicly available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public.

Description: In this study, the quality of wind and wave data provided by the new Sentinel-3A satellite is evaluated. We focus on coastal areas, where altimeter data are of lower quality than those for the open ocean. The satellite data of Sentinel-3A, Jason-2 and CryoSat-2 are assessed in a comparison with in situ measurements and spectral wave model (WAM) simulations. The sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, such as ERA-Interim and ERA5 reanalyses, ECMWF operational analysis and short-range forecasts, German Weather Service (DWD) forecasts and regional atmospheric model simulations -coastDat. Numerical simulations show that both the wave model forced using the ERA5 reanalyses and that forced using the ECMWF operational analysis/forecast demonstrate the best capability over the whole study period, as well as during extreme events. To further estimate the variance of the significant wave height of ensemble members for different wind forcings, especially during extreme events, an empirical orthogonal function (EOF) analysis is performed. Intercomparisons between remote sensing and in situ observations demonstrate that the overall quality of the former is good over the North Sea and Baltic Sea throughout the study period, although the significant wave heights estimated based on satellite data tend to be greater than the in situ measurements by 7cm to 26cm. The quality of all satellite data near the coastal area decreases; however, within 10km off the coast, Sentinel-3A performs better than the other two satellites. Analyses in which data from satellite tracks are separated in terms of onshore and offshore flights have been carried out. No substantial differences are found when comparing the statistics for onshore and offshore flights. Moreover, no substantial differences are found between satellite tracks under various metocean conditions. Furthermore, the satellite data quality does not depend on the wind direction relative to the flight direction. Thus, the quality of the data obtained by the new Sentinel-3A satellite over coastal areas is improved compared to that of older satellites.

Description: Operational ocean forecasts are typically produced by modelling systems run using a forced mode approach. The evolution of the ocean state is not directly influenced by surface waves, and the ocean dynamics are driven by an external source of meteorological data which is independent of the ocean state. Model coupling provides one approach to increase the extent to which ocean forecast systems can represent the interactions and feedbacks between ocean, waves and the atmosphere seen in nature. This paper demonstrates the impact of improving how the effect of waves on the momentum exchange across the ocean-atmosphere interface is represented through ocean-wave coupling on the performance of an operational regional ocean prediction system. This study focuses on the eddy-resolving (1.5 km resolution) Atlantic Margin Model (AMM15) ocean model configuration for the North-West European Shelf (NWS) region. A series of two-year duration forecast trials of the Copernicus Marine Environment Monitoring Service (CMEMS) North-West Shelf regional ocean prediction system are analysed. The impact of including ocean-wave feedbacks via dynamic coupling on the simulated ocean is discussed. The main interactions included are the modification of surface stress by wave growth and dissipation, Stokes–Coriolis forcing and wave height dependent ocean surface roughness. Given the relevance to operational forecasting, trials with and without ocean data assimilation are considered. Summary forecast metrics demonstrate that the ocean-wave coupled system is a viable evolution for future operational implementation. When results are considered in more depth, wave coupling was found to result in an annual cycle of relatively warmer winter and cooler summer sea surface temperatures for seasonally stratified regions of the NWS. This is driven by enhanced mixing due to waves, and a deepening of the ocean mixed layer during summer. The impact of wave coupling is shown to be reduced within the mixed layer with assimilation of ocean observations. Evaluation of salinity and ocean currents against profile measurements in the German Bight demonstrates improved simulation with wave coupling relative to control simulations. Further, evidence is provided of improvement to simulation of extremes of sea surface height anomalies relative to coastal tide gauges.

Description: In many coastal areas there is an increasing number and variety of observation data available, which are often very heterogeneous in their temporal and spatial sampling characteristics. With the advent of new systems, like the radar altimeter onboard the SENTINEL-3a satellite, a lot of questions arise concerning the accuracy and added value of different instruments and numerical models. Quantification of errors is a key factor for applications, like data assimilation and forecast improvement. In the past, the triple collocation method to estimate systematic and stochastic errors of measurements and numerical models was successfully applied to different data sets. This method relies on the assumption, that three independent data sets provide estimates of the same quantity. In coastal areas with strong gradients even small distances between measurements can lead to larger differences and this assumption can become critical. In this study the triple collocation method is extended in different ways with the specific problems of the coast in mind. In addition to nearest neighbor approximations considered so far, the presented method allows to use a large variety of interpolation approaches to take spatial variations in the observed area into account. Observation and numerical model errors can therefore be estimated, even if the distance between the different data sources is too big to assume, that they measure the same quantity. If the number of observations is sufficient, the method can also be used to estimate error correlations between certain data source components. As a second novelty, an estimator for the uncertainty of the derived observation errors is derived as a function of the covariance matrices of the input data and the number of available samples. In the first step, the method is assessed using synthetic observations and Monte Carlo simulations. The technique is then applied to a data set of SENTINEL-3a altimeter measurements, insitu wave observation, and numerical wave model data with a focus on the North Sea. Stochastic observation errors for the significant wave height, as well as bias and calibration errors are derived for the model and the altimeter. The analysis indicates a slight overestimation of altimeter wave heights, which becomes more pronounced at higher sea states. The smallest stochastic errors are found for the insitu measurements. Different observation geometries of insitu data and altimeter tracks are furthermore analysed, considering 1D and 2D interpolation approaches. For example, the geometry of an altimeter track passing between two insitu wave instruments is considered with model data being available at the insitu locations. It is shown, that for a sufficiently large sample, the errors of all data sources, as well as the error correlations of the model, can be estimated with the new method.

Description: A Coupled Model Intercomparison Project Phase 5 (CMIP5)-derived single-forcing, single-model, and single-scenario dynamic wind-wave climate ensemble is presented, and its historic period (1979–2005) performance in representing the present wave climate is evaluated. A single global climate model (GCM)-forcing wave climate ensemble was produced with the goal of reducing the inter GCM variability inherent in using a multi-forcing approach for the same wave model. Seven CMIP5 EC-Earth ensemble runs were used to force seven WAM wave model realizations, while future wave climate simulations, not analyzed here, were produced using a high-emission representative concentration pathway 8.5 (RCP8.5) set-up. The wave climate ensemble’s historic period was extensively compared against a set of 72 in situ wave-height observations, as well as to ERA-Interim reanalysis and Climate Forecast System Reanalysis (CFSR) hindcast. The agreement between the wave climate ensemble and the in situ measurements and reanalysis of mean and extreme wave heights, mean wave periods, and mean wave directions was good, in line with previous studies or even better in some areas of the global ocean, namely in the extratropical latitudes. These results give a good degree of confidence in the ability of the ensemble to simulate a realistic climate change signal.

Description: The effects of coupling between the atmospheric model of the Consortium for Small-Scale Modelling-Climate Limited-area Modelling (CCLM) and the wind wave model (WAM) on the lower atmosphere within the North Sea area are studied. Due to the two-way coupling between the models, the influences of wind waves and the atmosphere on each other can be determined. This two-way coupling between these models is enabled through the introduction of wave-induced drag into CCLM and updated winds into WAM. As a result of wave-induced drag, different atmospheric parameters are either directly or indirectly influenced by the wave conditions. The largest differences between the coupled and reference model simulation are found during storm events as well as in areas of steep gradients in the mean sea level pressure, wind speed or temperature. In the two-way coupled simulation, the position and strength of these gradients vary, compared to the reference simulation, leading to differences that spread throughout the entire planetary boundary layer and outside the coupled model area, thereby influencing the atmosphere over land and ocean, although not coupled to the wave model. Ultimately, the results of both model simulations are assessed against in situ and satellite measurements, with a better general performance of the two-way coupled simulation with respect to the observations.

Description: Wave climate change by the end of the 21st century (2075–2100) was investigated using a regional wave climate projection under the RCP 8.5 scenario. The performance of the historical run (1980–2005) in representing the present wave climate was assessed when compared with in situ (e.g., GTS) and remote sensing (i.e., Jason-1) observations and wave hindcasts (e.g., ERA5-hindcast). Compared with significant wave height observations in different subdomains, errors on the order of 20–30% were observed. A Principal Component (PC) analysis showed that the temporal leading modes obtained from in situ data were well correlated (0.9) with those from the historical run. Despite systematic differences (10%), the general features of the present wave climate were captured by the historical run. In the future climate projection, with respect to the historical run, similar wave climate change patterns were observed when considering both the mean and severe wave conditions, which were generally larger during summer. The range of variation in the projected extremes (±10%) was consistent with those observed in previous studies both at the global and regional spatial scales. The most interesting feature was the projected increase in extreme wind speed, surface Stokes drift speed and significant wave height in the Northeast Atlantic. On the other hand, a decrease was observed in the North Sea and the southern part of the Baltic Sea basin, while increased extreme values occurred in the Gulf of Bothnia during winter.