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The Caspian Sea is of particular interest. Against the background of long-term sea level changes, low-lying coastal areas in the northern part are subject to constant flooding as a result of storm surges. The elongation of the sea in the meridional direction allows the development of strong waves in the middle and southern parts. A comprehensive understanding of the characteristics of storm surges and storm waves is especially important in the context of ongoing climate change. This study is devoted to the analysis of storm surges for the time period from 1979 up to 2017 and wind waves from 1979 to 2020 in the Caspian Sea region. The circulation model ADCIRC and the wave model WAVEWATCH III with wind and pressure forcing from the NCEP/CFSR reanalysis were used. The modeling is performed on different unstructured grids with spacings of 500–900 m in the coastal zone. Mean and extreme values of surges, wave parameters and storm activity are provided in the research. The maximum significant wave height for the whole period was 8.2 m. The average long-term SWH did not exceed 1.1 m. No significant trends in the storm activity were found. The maximum surge height was 2.7 m. The analysis of the interannual variability of the surges' occurrence showed that 7–10 surges with a height of more than 1 meter were detected every year. The total duration of these surges was 20–30 days per year. Assessment of the risks of coastal flooding was carried out by calculating the extreme values of the sea for different return periods: 5, 10, 25, 50, and 100 years. The extreme sea level values in the northern part of the Caspian Sea for the 100-year return period are close to 3 m, and the areas with big surges are located along the eastern and western coasts. A forecast is made for the recurrence of storm wind waves in the 21st century based on climatic scenarios in CMIP5. A statistically significant increase in the recurrence of storm waves is to be expected in the near future, but that increase is not severe. Doi: 10.28991/CEJ-2022-08-11-01 Full Text: PDF

Short summary We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis. The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for the rapidly changing Arctic-boreal region. Air quality in China, together with the long-range transport of atmospheric pollutants, was also indicated as one of the most crucial topics of the research agenda. These two geographical regions, the northern Eurasian Arctic-boreal region and China, especially the megacities in China, were identified as a “PEEX region”. It is also important to recognize that the PEEX geographical region is an area where science-based policy actions would have significant impacts on the global climate. This paper summarizes results obtained during the last 5 years in the northern Eurasian region, together with recent observations of the air quality in the urban environments in China, in the context of the PEEX programme. The main regions of interest are the Russian Arctic, northern Eurasian boreal forests (Siberia) and peatlands, and the megacities in China. We frame our analysis against research themes introduced in the PEEX Science Plan in 2015. We summarize recent progress towards an enhanced holistic understanding of the land–atmosphere–ocean systems feedbacks. We conclude that although the scientific knowledge in these regions has increased, the new results are in many cases insufficient, and there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures, especially the lack of coordinated, continuous and comprehensive in situ observations of the study region as well as integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, especially “the enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate climate change” and the “socio-economic development to tackle air quality issues”.

Wind wave modeling (WAVEWATCH III model) is used to analyze the storm activity in the Kara Sea for the period from 1979 to 2019. The NCEP/CFSR/CFSv2 reanalysis data used as forcing. Simulations realized on the nonstructural grid with a resolution of 700 m to 10 km. The quality of wind wave simulation is assessed through a comparison with direct measurements and satellite data. The storm wave frequencies are analyzed separately for each year. It is found that storms with waves more than 3 m are observed on average about 30 times a year. The frequency of storms with waves more than 3–5 m increased twofold from 1979 to 2019. The increase in the storm frequency is due to a decrease in the sea ice cover extent. Analysis of the seasonal variations in storm activity shows that the largest amount of storms is observed from July to December. A strong positive trend in the frequency of storms is observed from October to December. Storms in January, February, and March have been observed since 2005 due to the absence of ice, which contributes significantly to the ultimate increase in the storm frequency.

This work is devoted to the wave energy in the Caspian Sea analysis for the period from 1979 to 2020. Wave energy calculations were performed using the WAVEWATCH III wave model on an irregular grid with a step of up to 900 m in the coastal zone. Results are obtained on the spatial variability of the wave energy flux and its seasonal variability. The maximum values of the energy flux are about 5 kW/m of the wave front and appear in the central part of the Caspian Sea. Availability of wave energy of 1 kW/m in the central part of the Caspian Sea is 50-55%, in the northern part – no more than 20%, and in the southern part – 30-45%. The seasonal variability of the energy flux analysis for three points located in different parts of the sea has been carried out. Seasonal changes in the energy flow are most pronounced in the central part of the sea: in the summer months, the energy flow is 2-5 kW/m, and in winter it increases to 7-10 kW/m. The maximum average monthly flow of wave energy was 18.5 kW/m of the wave front.

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This study is devoted to the analysis of the storm surges and wind waves in the Caspian Sea for the period from 1979 to 2017–2020. The models used are the circulation model ADCIRC and the wave model WAVEWATCH III with wind and pressure forcing from the NCEP/CFSR reanalysis. The modeling is performed on the unstructured grid with spacing to 300–700 m in the coastal zone. Mean and extreme values of surges, wave parameters, and storm activity are provided. The maximum significant wave height for the whole period amounts to 8.2 m. The average long-term SWH does not exceed 1.1 m. No significant trend in the storm activity was found. The maximum surges height amounts to 2.7 m. Analysis of the interannual variability of the surges occurrence showed that 7–10 surges with a height of more than 1 meter were obtained per year and the total duration of all these surges was 20–30 days per year. Assessment of the risk of coastal flooding was carried out by calculating the extreme values of the Sea for different return periods 5, 10, 25, 50, and 100 years. The extreme sea level values in the northern part of the Caspian Sea for the return period 100 years is close to 3 m and the areas with big surges are located along the eastern and western coasts. Based on climatic scenarios of CMIP5, a forecast is made for the recurrence of storm wind waves in the 21st century. A statistically significant increase of storm waves recurrence in the future was found, but it is not dramatically growing.

The article gives an analysis of a unique data of the thermistor chain, which installed on the D-6 oil platform in the coastal zone of the Baltic Sea. In total 10 temperature sensors were installed at different depths with a recording interval of 1 min, the depth at the installation site was 29 m. Based on satellite data, ship measurements and thermistor chain observation the characteristics and dynamics of the sharp decrease in water temperature which registered in the south-eastern Baltic Sea (Gdansk Bay area), during June 5-12, 2016 are analyzed. The temperature decreasing caused by the simultaneous action of at least two factors: wind-driven Ekman upwelling and advection of cold water. Scales of temporal and spatial variability of water temperature in a coastal zone of the south-eastern Baltic Sea near the coast of the Kaliningrad region are described. This event led to the considerable SST (sea sur face temperature) drop by more than 8 °C for two days. The rate of reduction of its temperature during certain upwelling periods can reach 0.3-0.4 o С per hour, but the maximum warming rate between phases varies from 0.25 to 0.28 o С per hour. This dramatically changed the conditions of the thermal balance of the sea sur face. The width of the upwelling, as seen in the SST data, was about 25 km. Satellite data were supplemented with data of a thermistor chain and C TD measurements. The high correlation between water temperature variability and changes in wind parameters: when the wind speed has decreased and its direction has changed, the response of the vertical thermal structure has occurred very quickly, sometimes within 1 hour. Thermistor chain data allow to evaluate the vertical temperature distribution and get more detailed analysis of temporal variability and short pulsations of upwelling.

The recurrence of extreme wind waves in the Kara Sea strongly influences the Arctic climate change. The period 2000–2010 is characterized by significant climate warming, a reduction of the sea ice in the Arctic. The main motivation of this research to assess the impact of climate change on storm activity over the past 39 years in the Kara Sea. The paper presents the analysis of wave climate and storm activity in the Kara Sea based on the results of numerical modeling. A wave model WAVEWATCH III is used to reconstruct wind wave fields for the period from 1979 to 2017. The maximum significant wave height (SWH) for the whole period amounts to 9.9 m. The average long-term SWH for the ice-free period does not exceed 1.3 m. A significant linear trend shows an increase in the storm wave frequency for the period from 1979 to 2017. It is shown that trends in the storm activity of the Kara Sea are primarily regulated by the ice. Analysis of the extreme storm events showed that the Pareto distribution is in the best agreement with the data. However, the extreme events with an SWH more than 6‒7 m deviate from the Pareto distribution.

This paper is devoted to the modeling of extreme wind wave parameters in the Gorky Reservoir. The third generation model SWAN version 41.10 is used. The parameters of wind waves calculated on a special unstructured triangulation grid with spatial resolution from 100 m near the coast and up to 700 m in the central part. The constant wind data for several directions with the speed of 15 m/s and duration of 23 h were used in wave modeling. As a result of modeling, significant wave height fields, the average period and the mean wavelength for each of the wind directions were obtained. The parameters of the waves were analyzed under the influence of the wind for 12 and 23 h.

Recurrence of extreme wind waves in the Kara Sea strongly influences the Arctic climate change. The paper presents the analysis of wave climate and storm activity in the Kara Sea based on the results of numerical modeling. A third-generation wave model WaveWatchIII is used to reconstruct wind wave fields on an unstructured grid with a spatial resolution of 15–20 km for the period from 1979 to 2017. The mean and maximum wave heights, wavelengths and periods are calculated. The maximum significant wave height (SWH) for the whole period amounts to 9.9 m. The average long-term SWH for the ice-free period does not exceed 1.3 m. The seasonal variability of the wave parameters is analyzed. The interannual variability of storm waves recurrence with different thresholds (from 3 to 7 m) was calculated. A significant linear trend shows an increase in the storm wave frequency for the period from 1979 to 2017. A double growth in the reccurence was observed for cases with an SWH more than 3–5 m from 1979 to 2017. The local maximum of the storm waves more than 3–4 m was observed in 1995, and the minimum in 1998. The maximum value (four cases) of the number of storms with an SWH threshold 7 m is registered in 2016. The frequency of wind speeds and ice conditions contributing to the storm waves formation were analyzed. It is shown that trends in the storm activity of the Kara Sea are primarily regulated by the ice. If the ice cover decreases in the southern part of the sea that leads to the increase of the number of events only with SWH threshold more than 3–4 m. If in the entire sea the ice cover decreases that leads already to increase of the extreme storms. The frequency of strong and long-term winds has high interannual variability and a weak positive trend. The analysis of distribution functions of the storm events with an SWH more than 3 m was carried out. Six different sectors of the Kara Sea were analyzed to reveal spatial differences. A comparison of the different distribution laws showed that the Pareto distribution is in the best agreement with the data. Up to 99 % of the points are described by this distribution. However, the extreme events with an SWH more than 6–7 m deviate from the distribution, and their probability is approximately twice as less as that predicted by the Pareto distribution. Presumably, this deviation is caused by the combined impact of rare wind speed frequencies and anomalies of the sea ice conditions.

The results of wind wave hindcast for the Caspian Sea for the period of 1979–2017 are presented. The WAVEWATCHIII wave model and wind forcing from the NCEP/CFSR reanalysis are used. The modeling is performed on the unstructured grid with the spacing to 1 km in the coastal zone. Mean and extreme values of wave height, length, and period are provided. It is shown that the maximum height of waves of 3% probability of exceedance is 11.7 m. The interannual variability of wave parameters is analyzed. No unambiguous trend towards increase or decrease in the storm activity was revealed over the hindcasting period.

According to earlier estimates, the Russian coasts have a high potential of wave and wind energy. At the same time, the use of several types of renewable energy sources (RES) allows us to overcome the inherent drawback–the inhomogeneity in time of the energy flow. Nowadays in Russia and abroad, the results of satellite observations, mathematical modeling and reanalysis data are widely used to assess the potential of wind and wave resources. The maps, the atlases, the databases and other information resources (both printed and electronic) are developed for use in the design, mathematical modeling of the power plants performance on the base of RES including hybrid ones. The paper presents the results of developing a Web Atlas of wave and wind energy for the coastal zone of the seas in the Russian Federation, demonstrates the methods for calculating wave and wind characteristics (SWAN spectral wave model), as well as data sources (wind speed reanalyses NCEP / CFSR and NCEP / CFSv2 for the periods 19792010 and 2011-2016). As the characteristics of the energy potential, mean annual values of the height of significant waves, length, period of waves, flux of wave energy, average specific power of the wind flow are calculated and analyzed. The tools for developing a Web Atlas prototype are discussed in detail. Web Atlas is based on the classical three-tier model which includes a storage subsystem (database server), a subsystem for analyzing and publishing data (directly a GIS server), and a Web application subsystem providing a user interface for interacting with data and mapping services (web server). The implementation of the Web Atlas has been carried out for the Black Sea waters. It is planned to further develop the atlas covering the coastal waters of all the seas of Russia.

This paper presents the variability of wind-driven upwelling based on results of the coastal upwelling criterion analysis for the Gelendzhik region of the Black Sea for 1979–2016 years. The calculations of the criterion are based on the wind data from reanalysis of NCEP-CFSR. The proposed method is used for the analysis of long-term upwelling variability in the Black Sea for the first time. This method allows detecting both full and incomplete upwelling in contrast to measurements of the sea-surface temperature (SST) on regular coastal weather stations or on satellites. Current study shows more than 100 cases of the upwelling (when upwelling criterion < - 1) for 37 years in total, and some of them were confirmed with a satellite images. Comparison of the SST from Gelendzhik meteostation and upwelling criterion revealed that 70% of the upwelling cases are related to decrease of the temperature on sea surface. It is shown that the highest probability of wind upwelling events is detected in the mid-summer period. Interannual variability of the coastal upwelling criterion is very high, there was 1 year (2010) when no upwelling cases were registered, and maximum 8 cases are registered for 1987 year. There are three cases of upwelling on average per year. The process of the coastal upwelling depends on wind impact, but also on direction and strength of the coastal current. Study of the upwelling and its variability is necessary to supplement knowledge about coastal dynamic processes that affect the ecosystem and the recreational potential of the region.

The purpose of this research is to estimate the energy potential of the Barents Sea based on numerical modeling of the wave energy over a long period of time from 1979 to 2010. Using the WaveWatchIII wave model, the wave energy flux in the open part and in the coastal zone of the Barents Sea has been calculated. The calculations are based on the data of the NCEP/CFSR reanalysis with spatial resolution of 0.3°. The calculations were performed on a unstructured grid, which has high spatial resolution at the shore (200–500 m). The long-term average annual significant wave height1 varies from 1.5–2.0 m for the open part of the Barents Sea to 1.0–1.5 m in the coastal zone of Murmansk oblast. The long-term average annual wave energy flux varies from 15–20 kW/m for the open part of the Barents Sea to 5–10 kW/m in the coastal zone of Murmansk region. The probability of exceedance of wave energy of more than 1 kW/m is 80–90% for the open part of the sea and 70–75% at the northeastern coast of the Rybachy Peninsula. To the east and west of the peninsula, this figure decreases significantly. Near the village of Teriberka, the probability of exceedance of the wave energy is 65–70%. The probability of exceedance of energy of more than 5 kW/m is 50–60% in the open sea and it does not exceed 35% in the coastal zone. The average probability of exceedance of the wave energy is subject to seasonal fluctuations. Thus, in the coastal zone, the probability of exceedance of energy of 1 kW/m is approximately 90% in the winter months and it does not exceed 50% in summer. The obtained results can be applied to designing a wave power station in the Barents Sea.

The numerical model simulations of storm activity in the White, Baltic andBarentsSeaswere analyzed for the period from 1979 to2015. Inthis paper the storm number of these seas was calculated. The connections of wind wave climate with indecies of large-scale atmospheric circulation such as NAO, AO and SCAND were estimated. Also, the future changes of wind wave climate were analysed.

This study presents the first spatial calibration of SWAN model physical parameters based on satellite observations for the Black and Azov Seas. Currently, the wind-wave model performance is unknown in several coastal and offshore areas due to the gap in wave buoy measurements. The development and increase of altimetry satellites allow collecting a large number of observations in a reasonable time, and thus to calibrate spatially wave models. Therefore, the present study aims to determine the best physical parameterization of the unstructured SWAN model based on satellite data for coarse domain over Black and Azov Seas and for local domain implementations. For this purpose, the significant wave height (SWH) was simulated using 44 physical settings for both ERA5 and CFSR winds. The spatial calibration is based on observations from seven altimetry satellites (Jason-3, Sentinel-3A, Sentinel-3B, Cryosat-2, SARAL/AltiKa, CFOSAT, and Hai Yang-2B). The spatial calibration and evaluation of the wind-wave model performance show an informative variation in the wave model performance, which can depend on several factors such as coastal morphology and the wind source accuracy and the physical setting of the wind-wave model. It raises several findings concerning the spatial sensitivity of the SWAN model to the used wind field, the wind and whitecapping source terms, whitecapping coefficient (Cds), and the windscaling tunable parameter, and the wind growth formulates using the ST6 package. Thus, this study allows observing the spatial response of the SWAN model as a function of physical parameterizations. The SWAN model calibration improved the simulation accuracy considerably overall Black and Azov Sea areas, using both CFSR and ERA5. The SWAN model using the ERA5 winds has provided a higher correlation and better accuracy in large part of the seas. It is highly recommended for the whole Black and Azov Seas to define the wind input term and whitecapping term based on ( Komen et al., 1984 ), with a Cds coefficient of 0.8E-5. Considering the spatial error statistics, the same finding was obtained when the model results were compared with Utrish wave buoy measurements in the northeastern part of the Black Sea. Therefore, for local nested model implementation, it is also recommended to define the optimal configuration based on the error statistics mapped in the present paper.

This paper presents the results of wind wave forecasts for the Black Sea. Three different versions utilized were utilized: the WAVEWATCH III model with GFS 0.25 forcing on a regular grid, the WAVEWATCH III model with COSMO-RU07 forcing on a regular grid, and the SWAN model with COSMO-RU07 forcing on an unstructured grid. AltiKa satellite altimeter data were used to assess the quality of wind and wave forecasts for the period from 1 April to 31 December 2017. Wave height and wind speed forecast data were obtained with a lead time of up to 72 h. The presented models provide an adequate forecast in terms of modern wave modeling (a correlation coefficient of 0.8–0.9 and an RMSE of 0.25–0.3 m) when all statistics were analyzed. A clear improvement in the wave forecast quality with the high-resolution wind forecast COSMO-RU07 was not registered. The bias error did not exceed 0.5 m in an SWH range from 0 to 3 m. However, the bias sharply increased to −2 or −3 m for an SWH range of 3–4 m. Wave forecast quality assessments were conducted for several storm cases.

Long series data of a thermistor chain in the Black Sea coastal zone near Gelendzhik were analyzed. A thermistor chain installed 1 km offshore and at a depth of 22 m. There are full and incomplete upwelling events observed. The study of upwelling genesis based on: wind speed data from the NCEP/CFSR reanalysis and Gelendzhik weather station, velocity and direction of coastal currents measured by ADCP profiler moored on the bottom near the thermistor chain. Over the whole observation period (warm seasons of 2013–2015), more than 40 events of upwelling were registered four of them were full upwellings, when presence of under-thermocline water was observed near the sea surface. For every upwelling event, conditions prior to the changes in thermic structure, were analyzed. It is found that full upwelling generally occur under synergistic wind and current forcing. Fairly strong forcing of one of these factors is sufficient for partial upwelling to occur.

This study is dedicated to the wind waves parameters distribution on the Black Sea with a focus on coastal areas. Wind waves were simulated using the SWAN model forced by the NCEP CFSR and NCEP CFSv2 reanalyses for the period 1979–2016. An unstructured computational grid with resolution varying between 15 km and 200 m was applied. Modelling results were validated against in situ and remote sensing data. For the entire sea, distributions of total and seasonal maxima of wave parameters are analyzed. Maximal significant wave heights exceed 8.5 m and are found in the southwestern areas of the sea. Maximal wave lengths (over 160 m) and periods (over 10.5 s) are located in the eastern part of the sea. Total and seasonal time series extracted for 12 locations along the coasts of the Black Sea were studied. Maximal values of significant wave heights (over 6 m) correspond to areas along the northeastern and southwestern coasts of the Black Sea and the southern coast of the Crimean Peninsula. Maximal values of wave lengths and wave periods (over 140 m and 10 s) are located along the northeastern and southern coasts of the Black sea.

The results ofnumerical simulation of storm waves near the northeastern coast ofthe Black Sea using different wind forcing (CFSR reanalysis, GFS forecast, and WRF reanalysis and forecast) are presented. The wave modeling is based on the SWAN spectral wave model and the high-resolution unstructured grid for the Tsemes Bay. The quality estimates of wave simulation results for various wind forcing are provided by comparing the model results with the instrumental data on wind waves in the Tsemes Bay. It is shown that the forecast of the maximum wave height for some storms using the WRF wind forcing is more accurate than that based on the GFS forcing.

We present the results of development and testing of a coastal X-band radar system for monitoring wind waves and currents at the Black Sea (near Gelendzhik) created on the basis of nautical radars. Radar measurements of wave heights were validated by data from a wave buoy and a moored acoustic Doppler current profiler (ADCP). The conditions for successful radar measurements of waves in the coastal environment have been determined. It was shown that a radar with an aperture 1° could successfully measure wave heights at a distance of 1.2 km from the radar, when waves arrive at an angle of ±31° to the main sensing direction. In this case, for wave height measurements, the correlation coefficient between the radar and independent data is 0.82 and the standard deviation is 0.26 m.

This paper presents the description of a monitoring system based on drifters equipped with GPSreceiver and cellular GSM. The system provides data about currents with a temporal and spatial resolution of 5–10 minutes and 100–200 m. The movement of the drifter can be observed in real time. Several experiments were conducted on the Black Sea shelf for identification of the advantages of the monitoring system. The results of experiments include a comparison of the drifter trajectories with bottom-tracked ADCP and towed ADCP data.

The Lena, Kolyma, and Indigirka rivers are among the largest rivers that inflow to the Arctic Ocean. Their discharges form a freshened surface water mass over a wide area in the Laptev and East-Siberian seas and govern many local physical, geochemical, and biological processes. In this study we report coastal upwelling events that are regularly manifested on satellite imagery by increased sea surface turbidity and decreased sea surface temperature at certain areas adjacent to the Lena Delta in the Laptev Sea and the Kolyma and Indigirka deltas in the East-Siberian Sea. These events are formed under strong easterly and southeasterly wind forcing and are estimated to occur during up to 10%–30% of ice-free periods at the study region. Coastal upwelling events induce intense mixing of the Lena, Kolyma, and Indigirka plumes with subjacent saline sea. These plumes are significantly transformed and diluted while spreading over the upwelling areas; therefore, their salinity and depths abruptly increase, while stratification abruptly decreases in the vicinity of their sources. This feature strongly affects the structure of the freshened surface layer during ice-free periods and, therefore, influences circulation, ice formation, and many other processes at the Laptev and East-Siberian seas.

Russian priority - the study of storm surges and wave climate in the Arctic seas due to the active development of offshore oil and gas. Researching the formation of storm surge and wave are necessary for the design and construction of facilities in the coastal zone, as well as for the safety of navigation. An inactive port ensues considerable economic losses. It is important to study the variability of storm surges, wave climate in the past and forecast the future. Consequently, this information would be used for planning the development of the Arctic in accordance with the development programme 2020. Mathematical modeling is used to analyze the characteristics of storm surges and wave climate formation from 1979 to 2010 in the White and Barents Seas. Calculation of storm surge heights in the seas is performed using model AdCirc on an unstructured grid with a 20 km pitch in the Barents Sea and 100 m in the White Sea. The model AdCirc used data of wind field reanalysis CFSv2. The simulation of storm surge was conducted with/without pressure, sea state, tides. A non-linear interaction of the surge and tide during the phase of destruction storm surge was detected. Calculation of the wave climate performed using SWAN spectral wave model on unstructured grids. Spatial resolution is 500 m-5 km for the White Sea and 10-20 km for the Barents Sea. NCEP/CFSR (~0.3°) input wind forcing was used. The storminess of the White Sea tends to increase from 1979 to 1991, and then decrease to minimum at 2000 and increase again till 2010.

This work presents the description and results of drifter experiments which were held in coastal zone of the Black Sea every summer and sometimes in autumn since 2013. Surface GSM/GPS drifters were used for observation coastal currents with spatial resolution 100–200 m and temporal variability from 5-10 minutes . Some parameters of sub-mesoscale eddies was described due to experiments. An optional battery pack allowed to extent autonomy to 19 days (one of the drifters covered a distance of ~ 300 km).The results of experiments include a comparison of the drifter trajectories with bottom-tracked ADCP and moored ADCP data. The speed and direction of current velocity from the ADCP data coincide with the data from drifters. We demonstrate that using drifter data for analysis of water dynamics gives a more comprehensive pattern of actual processes in comparison to using the ADCP data alone.

This study is focused on the alterations and typical features of the wind wave climate of the Black Sea’s coastal waters since 1979 till nowadays. Wind wave parameters were calculated by means of the 3rd-generation numerical spectral wind wave model SWAN, which is widely used on various spatial scales – both coastal waters and open seas. Data on wind speed and direction from the NCEP CFSR reanalysis were used as forcing. The computations were performed on an unstructured computational grid with cell size depending on the distance from the shoreline. Modeling results were applied to evaluate the main characteristics of the wind wave in various coastal areas of the sea.