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This study analyzed the past wave climate of the Black Sea region for the period from 1988 to 2021. The wave field has been simulated using the state-of-the-art, third-generation wave model WAVEWATCH III forced by the ECMWF reanalysis ERA5 winds, with the model resolution being the highest ever applied to the region in a basin-scale climate study. The surface currents provided by the Copernicus Marine Service have been included in the wave model to evaluate wave--current interactions. The wave model results have been validated with respect to satellite and buoy observations, showing that the simulation accurately reproduces the past evolution of the wave field, exceeding 0.9 correlation with respect to satellite data. The inclusion of wave--current interaction has been positively evaluated. Four statistics (significant wave height 5th and 95th percentiles, mean, and maxima) have been used to describe the wave field at seasonal timescale, showing a clear distinction between the Western (rougher sea conditions) and Eastern (calmer sea conditions) sub-basins. Furthermore, the intra-annual wave climate variability has been investigated using a Principal Component Analysis (PCA) and the Mann--Kendall test on significant wave height (SWH). This study represents the first time the PCA is applied to the region, identifying two main modes that highlight distinct features and seasonal trends in the Western and Eastern subbasins. Throughout most seasons, the SWH trend is positive for the Eastern basin and negative for the Western basin. The PCA shows a regime shift with increasing eastward waves and decreasing north and north-eastward waves. Finally, SWH correlation (r) with four Teleconnection indexes (East Atlantic Pattern, Scandinavian Pattern, North Atlantic Oscillation, and East Atlantic/West Russia Pattern) revealed that the strongest r is observed with the Eastern--Atlantic--Western Russia teleconnection, with a peculiar spatial pattern of correlation, and is positive for the northwestern and negative for the southeastern sub-basin. [ABSTRACT FROM AUTHOR]

Accurate prediction of surface waves in the Baltic Sea is crucial for enhancing the safety and efficiency of maritime transport. Over the years, the accuracy of wave forecasts in this area has seen considerable improvement and has proven reliable for forecast windows of 2 to 3 days. However, the issuance of warnings for marine operations often requires longer forecast ranges. This study investigated the forecasting accuracy over a longer time frame of 4 to 6 days and assessed its effectiveness in issuing warnings for moderate and severe wave conditions. To achieve this, we have evaluated the high-resolution wave forecasts for the Baltic Sea available at the Copernicus Marine Services Monitoring Forecasting Centre (BAL MFC) against buoy and altimeter data. Our analysis demonstrates strong agreement between the model predictions and the observed data for shorter forecast ranges. Nevertheless, starting from the third day of the forecast, there is a growing bias in the values of significant wave height. The underestimation becomes more pronounced on the last day of the forecast, with significant wave heights underestimated by approximately 10% compared to buoy data and 20% compared to altimeter data. Part of this underestimation was addressed to the forecast system setup that used the combination of Harmonie and ECMWF winds. As the wind-wave coupling was tuned to Harmonie winds, which without tuning lead to overestimation of significant wave height, it affected negatively the longer forecasts using ECMWF wind forcing. To access the forecast ability to predict high-sea wave events, a 4-meter threshold was employed, aligning with Finnish Meteorological Institute wave warning. The results of two cases show that forecasts 84, 96, and 120 hours in advance provide valuable insights for effective warning issuance. [ABSTRACT FROM AUTHOR]

Understanding and monitoring the ecological quality of coastal waters is crucial for preserving marine ecosystems. Eutrophication is one of the major problems affecting the ecological state of coastal marine waters. For this reason, the control of the trophic conditions of aquatic ecosystems is needed for the evaluation of their ecological quality. This study leverages space-based Sentinel-3 Ocean and Land Color Instrument imagery (OLCI) to assess the ecological quality of Mediterranean coastal waters using the Trophic Index (TRIX) key indicator. In particular, we explore the feasibility of coupling remote sensing and machine learning techniques to estimate the TRIX levels in the Ligurian, Tyrrhenian, and Ionian coastal regions of Italy. Our research reveals distinct geographical patterns in TRIX values across the study area, with some regions exhibiting eutrophic conditions near estuaries and others showing oligotrophic characteristics. We employ the Random Forest Regression algorithm, optimizing calibration parameters to predict TRIX levels. Feature importance analysis highlights the significance of latitude, longitude, and specific spectral bands in TRIX prediction. A final statistical assessment validates our model's performance, demonstrating a moderate level of error (MAE of 0.51) and explanatory power (R2 of 0.37). These results highlight the potential of Sentinel-3 OLCI imagery in assessing ecological quality, contributing to our understanding of coastal water ecology. They also underscore the importance of merging remote sensing and machine learning in environmental monitoring and management. Future research should refine methodologies and expand datasets to enhance TRIX monitoring capabilities from space. [ABSTRACT FROM AUTHOR]

European coasts are regularly exposed to severe storms that trigger extreme water-level conditions, leading to coastal flooding and erosion. Early Warning Systems (EWS) are important tools for the increased preparedness and response against coastal flood events, hence greatly reducing associated risks. With this objective, a proof-of-concept for a European Coastal Flood Awareness System (ECFAS) was developed in the framework of the H2020 ECFAS project, which capitalizes on the Copernicus products. In this context, this manuscript evaluates for the first time the capability of the current Copernicus Marine operational ocean models to forecast extreme coastal water levels and hence to feed coastal flood awareness applications at European scale. A methodology is developed to focus the assessment on storm-driven extreme sea level events (EEs) from tide-gauge records. For the detected EEs, the event peak representation is validated, and the impact of forecast lead time is evaluated. Results show satisfactory performance but a general underprediction of peak magnitudes of 10% for water levels and 18% for surges across the detected EEs. In average, the models are capable of independently flagging 76% of the observed EEs. Forecasts show limited lead time impact up to a 4-day lead time, demonstrating the suitability of the systems for early warning applications. Finally, by separating the surge and tidal contributions to the extremes, the potential sources of the prediction misfits are discussed and consequent recommendations for the evolution of the Copernicus Marine Service forecasting models towards coastal flooding applications are provided.

GLORYS12 is a global eddy-resolving physical ocean and sea ice reanalysis at 1/12° horizontal resolution covering the 1993-present altimetry period, designed and implemented in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). The model component is the NEMO platform driven at the surface by atmospheric conditions from the ECMWF ERA-Interim reanalysis. Ocean observations are assimilated by means of a reduced-order Kalman filter. Along track altimeter sea level anomaly, satellite sea surface temperature and sea ice concentration, as well as in situ temperature and salinity vertical profiles are jointly assimilated. A 3D-VAR scheme provides an additional correction for the slowly-evolving large-scale biases in temperature and salinity. The performance of the reanalysis shows a clear dependency on the time-dependent in situ observation system. The general assessment of GLORYS12 highlights a level of performance at the state-of-the-art and the capacity of the system to capture the main expected climatic interannual variability signals for ocean and sea ice, the general circulation and the inter-basins exchanges. In terms of trends, GLORYS12 shows a higher than observed warming trend together with a slightly lower than observed global mean sea level rise. Comparisons made with an experiment carried out on the same platform without assimilation show the benefit of data assimilation in controlling water mass properties and sea ice cover and their low frequency variability. Moreover, GLORYS12 represents particularly well the small-scale variability of surface dynamics and compares well with independent (non-assimilated) data. Comparisons made with a twin experiment carried out at 1/4° resolution allows characterizing and quantifying the strengthened contribution of the 1/12° resolution onto the downscaled dynamics. GLORYS12 provides a reliable physical ocean state for climate variability and supports applications such as seasonal forecasts. In addition, this reanalysis has strong assets to serve regional applications and provide relevant physical conditions for applications such as marine biogeochemistry. In the near future, GLORYS12 will be maintained to be as close as possible to real time and could therefore provide relevant and continuous reference past ocean states for many operational applications.

The Training workshop Copernicus Marine Service 2019 BLACK SEA organized in Constanta, Romania, falls within the programme of activities of the Copernicus Marine Service, namely to create training opportunities which will strengthen the existing of all maritime regions in their activities ranging from harbour management, aquaculture to water quality monitoring in the frame of national and European policies. The Training was hosted by the National Institute for Marine Research and Development "Grigore Antipa" (NIMRD) Constanta, Romania (26-27 of June 2019). The planning of the training workshop was done jointly by Mercator Ocean International and CMEMS. The overall scientific objectives of Copernicus Marine Service 2019 Black Sea Training Workshop were to increase the knowledge of users about the EU Copernicus Programme and the CMEMS capacity (products portfolio releases, new services, opportunities), facilitate the acquisition and improvement of skills and competencies of users and potential users linked by a common region, by common needs or common domain of interests and to design an effective and innovative research governance framework based on sound scientific knowledge. The training covered the main issues focused on: Black Sea Model Products (ocean currents, sea level, waves, chloropyll-a); Satellite Ocean Color products; Satellite Wave Products; Satellite Sea Level Products; In Situ Products. [ABSTRACT FROM AUTHOR]

We present a study on the potential of the Copernicus Imaging Microwave Radiometer (CIMR) mission for the global monitoring of Sea-Surface Salinity (SSS) using Level-4 (gap-free) analysis processing. Space-based SSS are currently provided by the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellites. However, there are no planned missions to guarantee continuity in the remote SSS measurements for the near future. The CIMR mission is in a preparatory phase with an expected launch in 2026. CIMR is focused on the provision of global coverage, high resolution sea-surface temperature (SST), SSS and sea-ice concentration observations. In this paper, we evaluate the mission impact within the Copernicus Marine Environment Monitoring Service (CMEMS) SSS processing chain. The CMEMS SSS operational products are based on a combination of in situ and satellite (SMOS) SSS and high-resolution SST information through a multivariate optimal interpolation. We demonstrate the potential of CIMR within the CMEMS SSS operational production after the SMOS era. For this purpose, we implemented an Observing System Simulation Experiment (OSSE) based on the CMEMS MERCATOR global operational model. The MERCATOR SSSs were used to generate synthetic in situ and CIMR SSS and, at the same time, they provided a reference gap-free SSS field. Using the optimal interpolation algorithm, we demonstrated that the combined use of in situ and CIMR observations improves the global SSS retrieval compared to a processing where only in situ observations are ingested. The improvements are observed in the 60% and 70% of the global ocean surface for the reconstruction of the SSS and of the SSS spatial gradients, respectively. Moreover, the study highlights the CIMR-based salinity patterns are more accurate both in the open ocean and in coastal areas. We conclude that CIMR can guarantee continuity for accurate monitoring of the ocean surface salinity from space.

We present a study on the potential of the Copernicus Imaging Microwave Radiometer (CIMR) mission for the global monitoring of Sea-Surface Salinity (SSS) using Level-4 (gap-free) analysis processing. Space-based SSS are currently provided by the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellites. However, there are no planned missions to guarantee continuity in the remote SSS measurements for the near future. The CIMR mission is in a preparatory phase with an expected launch in 2026. CIMR is focused on the provision of global coverage, high resolution sea-surface temperature (SST), SSS and sea-ice concentration observations. In this paper, we evaluate the mission impact within the Copernicus Marine Environment Monitoring Service (CMEMS) SSS processing chain. The CMEMS SSS operational products are based on a combination of in situ and satellite (SMOS) SSS and high-resolution SST information through a multivariate optimal interpolation. We demonstrate the potential of CIMR within the CMEMS SSS operational production after the SMOS era. For this purpose, we implemented an Observing System Simulation Experiment (OSSE) based on the CMEMS MERCATOR global operational model. The MERCATOR SSSs were used to generate synthetic in situ and CIMR SSS and, at the same time, they provided a reference gap-free SSS field. Using the optimal interpolation algorithm, we demonstrated that the combined use of in situ and CIMR observations improves the global SSS retrieval compared to a processing where only in situ observations are ingested. The improvements are observed in the 60% and 70% of the global ocean surface for the reconstruction of the SSS and of the SSS spatial gradients, respectively. Moreover, the study highlights the CIMR-based salinity patterns are more accurate both in the open ocean and in coastal areas. We conclude that CIMR can guarantee continuity for accurate monitoring of the ocean surface salinity from space. [ABSTRACT FROM AUTHOR]