Abstract. In this study, the quality of wave data provided by the new Sentinel-3A satellite is evaluated and the sensitivity of the wave model to wind forcing is tested. We focus on coastal areas, where altimeter data are of lower quality and wave modelling is more complex than for the open ocean. In the first part of the study, 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, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis and short-range forecasts, German Weather Service (DWD) forecasts and regional atmospheric model simulations (coastDat). Numerical simulations show that 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. In the second part of the study, the satellite data of Sentinel-3A, Jason-2 and CryoSat-2 are assessed in comparison with in situ measurements and spectral wave model (WAM) simulations. 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 7 to 26 cm. The quality of all satellite data near the coastal area decreases; however, within 10 km 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.
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.
Ensemble simulations are performed to quantify the internal variability of both regional atmospheric models and wave-atmosphere coupled model systems. Studies have shown that the internal variability in atmospheric models (e.g., wind or pressure fields) is increased during extreme events, such as storms. Comparing the magnitude of the internal variability of the atmospheric model with the internal variability of the coupled model system reveals that the internal variability can be reduced by coupling a wave model to the atmospheric model. While this effect is most evident during extreme events, it is still present in a general assessment of the mean internal variability during the whole study period. Furthermore, the role of this wave-atmosphere coupling can be distinguished from that of the internal variability of the atmospheric model since the impact of the wave-atmosphere interaction is larger than the internal variability. This is shown to be robust to different boundary conditions. One method to reduce the internal variability of the atmospheric model is to apply spectral nudging, the role of which in both the stand-alone atmospheric model and the coupled wave-atmosphere system is evaluated. Our analyses show that spectral nudging in both coupled and stand-alone ensemble simulations keeps the internal variability low, while the impact of the wave-atmosphere interaction remains approximately the same as in simulations without spectral nudging, especially for the wind speed and significant wave height. This study shows that in operational and climate research systems, the internal variability of the atmospheric model is reduced when the ocean waves and atmosphere are coupled. Clear influences of the wave-atmosphere interaction on both of these earth system components can be detected and differentiated from the internal model variability. Furthermore, the wave-atmosphere coupling has a positive effect on the agreement of the model results with both satellite and in situ observations.
Recent advances in numerical modeling, satellite data, and coastal processes, together with the rapid evolution of CMEMS products and the increasing pressures on coastal zones, suggest the timeliness of extending such products toward the coast. The CEASELESS EU H2020 project combines Sentinel and in-situ data with high-resolution models to predict coastal hydrodynamics at a variety of scales, according to stakeholder requirements. These predictions explicitly introduce land discharges into coastal oceanography, addressing local conditioning, assimilation memory and anisotropic error metrics taking into account the limited size of coastal domains. This article presents and discusses the advances achieved by CEASELESS in exploring the performance of coastal models, considering model resolution and domain scales, and assessing error generation and propagation. The project has also evaluated how underlying model uncertainties can be treated to comply with stakeholder requirements for a variety of applications, from storm-induced risks to aquaculture, from renewable energy to water quality. This has led to the refinement of a set of demonstrative applications, supported by a software environment able to provide met-ocean data on demand. The article ends with some remarks on the scientific, technical and application limits for CMEMS-based coastal products and how these products may be used to drive the extension of CMEMS toward the coast, promoting a wider uptake of CMEMS-based predictions.
Abstract. 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 7 cm to 26 cm. The quality of all satellite data near the coastal area decreases; however, within 10 km 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.
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