Variability of currents over the southern slope of the Gulf of Finland

In our intraseasonal variability studies of currents in the coastal sea of the Gulf of Finland northeast of Pakri Peninsula, we compared the observation data from a bottom-mounted ADCP (March–June of 2009, 50 m depth) with the simulation data from High Resolution Operational Model of the Baltic (HIROMB). The structure of the current pattern appeared strongly dependent on the stratification conditions. The flow was quasi-barotropic during the periods of weak inverse thermal stratification at the end of winter season and at transition from the inverse thermal stratification to summer type stratification when the sea was thermally unstratified, but mostly two-layered (baroclinic) when the summer type thermal stratification had developed. The alternation of strong westward (eastward) currents (up to 30 cm s−1) in the upper layer is explained in terms of coastal upwelling (downwelling) due to favourable background winds. The measured and the modelled upper layers along isobath currents showed a noticeable correlation with the correlation coefficient of 0.52 and 0.82 during the periods of winter type and summer type stratifications, respectively, and the absence of a significant correlation during the transition period. The eastward (upwind) current episodes with speeds reaching 18 cm s−1 below the seasonal thermocline are likely to reflect the specific circulation response in the elongated basin caused by the easterly wind. The long-term mean (over 3.5 months) current vector (−2.0 cm s−1, −2.9 cm s−1) was westward in the upper sea and eastward, nearly along isobaths (1.1 cm s−1, −0.3 cm s−1) in the deeper layers

The impact of surface currents and sea level on the wave field evolution during St. Jude storm in the eastern Baltic Sea

A third generation numerical wave model SWAN (Simulating WAves Nearshore) was applied to study the spatio-temporal effect of surface currents and sea level height on significant wave height; and to describe the mechanisms responsible for wave–current interaction in the eastern Baltic Sea. Simulation results were validated by comparison with in situ wave measurements in deep and shallow water, carried out using the directional wave buoy and RDCP respectively, and with TerraSAR-X imagery. A hindcast period from 23 to 31 October 2013 included both a period of calm to moderate weather conditions and a severe North-European windstorm called St. Jude. The prevailing wind directions were southerly to westerly. Four simulations with SWAN were made: a control run with dynamical forcing by wind only; and simulations with additional inputs of surface currents and sea level, both separately and combined. A clear effect of surface currents and sea level on the wave field evolution was found. It manifested itself as an increase or decrease of significant wave height of up to 20%. The strength of the interaction was influenced by the propagation directions of waves and surface currents and the severity of weather conditions. An increase in the wave height was mostly seen in shallower waters and in areas where waves and surface currents were propagating in opposite directions. In deeper parts of the eastern Baltic Sea and in case of waves and surface currents propagating in the same direction a decrease occurred

Veetaseme seire, üleujutuste kaardistamine ja märgalae niiskusrežiim

Projekti RITA1 KAUGSEIRE käigus töötati välja kaugseire andmete töötlemise metoodid/prototüübid, mis võimaldavad parandada mitmeid järgmisi seirerakendusi ja riiklike teenuseid: (1) üleujutuste seire satelliitpiltidel sisemaal ja rannikul; (2) veetaseme seire kasutades altimeetria andmeid; (3) veetaseme prognoosi täpsustamine satelliitaltimeetria andmetega; (4) veekogu ökoloogilise klassi korrektsioon vastavalt veetaseme sesoonsele muutusele; (5) soode niiskus režiimi jälgimine kaugseire meetodiga; (6) maardlate (s.h. turbamaardlate) seire satelliitpiltidelt

Nemo-Nordic 2.0 : operational marine forecast model for the Baltic Sea

This paper describes Nemo-Nordic 2.0, an operational marine model for the Baltic Sea. The model is used for both near-real-time forecasts and hindcast purposes. It provides estimates of sea surface height, water temperature, salinity, and velocity, as well as sea ice concentration and thickness. The model is based on the NEMO (Nucleus for European Modelling of the Ocean) circulation model and the previous Nemo-Nordic 1.0 configuration by Hordoir et al. (2019). The most notable updates include the switch from NEMO version 3.6 to 4.0, updated model bathymetry, and revised bottom friction formulation. The model domain covers the Baltic Sea and the North Sea with approximately 1 nmi resolution. Vertical grid resolution has been increased from 3 to 1 m in the surface layer. In addition, the numerical solver configuration has been revised to reduce artificial mixing to improve the representation of inflow events. Sea ice is modeled with the SI3 model instead of LIM3. The model is validated against sea level, water temperature, and salinity observations, as well as Baltic Sea ice chart data for a 2-year hindcast simulation (October 2014 to September 2016). Sea level root mean square deviation (RMSD) is typically within 10 cm throughout the Baltic basin. Seasonal sea surface temperature variation is well captured, although the model exhibits a negative bias of approximately −0.5 ∘C. Salinity RMSD is typically below 1.5 g kg−1. The model captures the 2014 major Baltic inflow event and its propagation to the Gotland Deep. The model assessment demonstrates that Nemo-Nordic 2.0 can reproduce the hydrographic features of the Baltic Sea.</p

Recent Progress in Performance Evaluations and Near Real-Time Assessment of Operational Ocean Products

Operational ocean forecast systems provide routine marine products to an ever-widening community of users and stakeholders. The majority of users need information about the quality and reliability of the products to exploit them fully. Hence, forecast centres have been developing improved methods for evaluating and communicating the quality of their products. Global Ocean Data Assimilation Experiment (GODAE) OceanView, along with the Copernicus European Marine Core Service and other national and international programmes, has facilitated the development of coordinated validation activities among these centres. New metrics, assessing a wider range of ocean parameters, have been defined and implemented in real-time. An overview of recent progress and emerging international standards is presented here

Copernicus marine service ocean state report

The oceans regulate our weather and climate from global to regional scales. They absorb over 90% of accumulated heat in the climate system (IPCC Citation2013) and over a quarter of the anthropogenic carbon dioxide (Le Quéré et al. Citation2016). They provide nearly half of the world’s oxygen. Most of our rain and drinking water is ultimately regulated by the sea. The oceans provide food and energy and are an important source of the planet's biodiversity and ecosystem services. They are vital conduits for trade and transportation and many economic activities depend on them (OECD Citation2016). Our oceans are, however, under threat due to climate change and other human induced activities and it is vital to develop much better, sustainable and science-based reporting and management approaches (UN Citation2017). Better management of our oceans requires long-term, continuous and state-of-the art monitoring of the oceans from physics to ecosystems and global to local scales. The Copernicus Marine Environment Monitoring Service (CMEMS) has been set up to address these challenges at European level. Mercator Ocean was tasked in 2014 by the European Union under a delegation agreement to implement the operational phase of the service from 2015 to 2021 (CMEMS Citation2014). The CMEMS now provides regular and systematic reference information on the physical state, variability and dynamics of the ocean, ice and marine ecosystems for the global ocean and the European regional seas (Figure 0.1; CMEMS Citation2016). This capacity encompasses the description of the current situation (analysis), the prediction of the situation 10 days ahead (forecast), and the provision of consistent retrospective data records for recent years (reprocessing and reanalysis). CMEMS provides a sustainable response to European user needs in four areas of benefits: (i) maritime safety, (ii) marine resources, (iii) coastal and marine environment and (iv) weather, seasonal forecast and climate. Figure 0.1. CMEMS geographical areas on the map are for: 1 – Global Ocean; 2 – Arctic Ocean from 62°N to North Pole; 3 – Baltic Sea, which includes the whole Baltic Sea including Kattegat at 57.5°N from 10.5°E to 12.0°E; 4 – European North-West Shelf Sea, which includes part of the North East Atlantic Ocean from 48°N to 62°N and from 20°W to 13°E. The border with the Baltic Sea is situated in the Kattegat Strait at 57.5°N from 10.5°E.to 12.0°E; 5 – Iberia-Biscay-Ireland Regional Seas, which includes part of the North East Atlantic Ocean from 26 to 48°N and 20°W to the coast. The border with the Mediterranean Sea is situated in the Gibraltar Strait at 5.61°W; 6 – Mediterranean Sea, which includes the whole Mediterranean Sea until the Gibraltar Strait at 5.61°W and the Dardanelles Strait; 7 – Black Sea, which includes the whole Black Sea until the Bosporus Strait