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The Caspian Sea. Main parts of the Caspian Sea: 1 -the North Caspian; 2 -the Middle Caspian; 3 -the South Caspian; 4 -the Kara-Bogaz-Gol Bay. Isobaths are shown in m.
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Oscillations of the Caspian Sea level is the result of interrelated hydrometeorological processes and climate change not only in the catchment area of the sea but also far beyond it. The change in the tendency of the mean sea level variations in the middle 1970s, when the long-term sea level fall was replaced by its rapid and significant rise, is a...
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Context 1
... 2016, the mean Caspian Sea level was −27.43 m (in the Baltic altitude system) measured against the world ocean level. The sea area is 392,600 km 2 , mean and maximum depths are 208 m and 1,025 m, respectively (Figure 1). The Caspian Sea longitudinal extent three times exceeds its size in latitudinal direction (1,000 km vs. 200-400 km), which results in strong climatic variability over the sea. ...
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... analysis of interannual variability of vorticity of the geostrophic velocity field shows that in different parts of the Caspian Sea and in the entire sea it does not have a pronounced seasonal pattern, though at the same time considerable interannual differences are observed (Figure 10). Between the North and Middle Caspian Sea as well as in seasonal variability, a reversed phase in vorticity is observed. ...
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... the Southern Caspian Sea, there were no similar local maxima in the period of 1993-2012. The average climatic values of vorticity in this part of Figure 10. The interannual variability of vorticity of monthly geostrophic current velocity field base on altimetric measurements of T/P and the J1/2 satellite since September 1992 to December 2012. ...
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... the whole sea, vorticity is 0.51 10 -7 . Figure 10 shows that after 2008, vorticity in almost all parts of the sea, with the exception of the northern part, increased in the range of 1.5-3 10 -7 . According to the analysis of the monthly average current velocity (Figure 9), in the same time period there was a decline in velocity in all parts of the sea. ...
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... analysis of variation of the average velocity and vorticity shows that they are inversely proportional to each other ( Figure 11). From 1993 to 2007, the vorticity was decreasing at the rate of −0.17 ± 0.02 10 -7 per year, and the velocity was increasing at the rate of +0.11 ± 0.06 cm per year. ...
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Citations
... In 2016, the average level of the Caspian Sea was measured to be -27.43m against the surface of the Atlantic Ocean (Lebedev, 2018). The Caspian Sea has a longitudinal geometry (1000 km long and 200 to 300 km wide) and has three northern, middle, and southern basins ( Figure 1a). ...
... In this study, after running the POM from 2009 to 2019, the electrical conductivity phenomenon was studied based on the changes in temperature, salinity and flow rate of the where, T is the temperature, S is the salinity, and is the electrical conductivity. (Lebedev, 2018), and (b) sea currents of the Caspian Sea (Ibrayev et al., 2010) ...
... (a) Depth topography(Lebedev, 2018), and (b) sea currents of theCasp et al., 2010) ...
The electrical conductivity of sea refers to the conductivity of seawater, which affects the electrodynamics and electromagnetic processes observed in the ocean. This study investigates temporal and spatial variations of electrical conductivity across the Caspian basin using Princeton Ocean Model (POM). The POM is an oceanic model with a vertical sigma array, a right-angled curved horizontal grid, free surface boundary conditions and sub-turbulence and wave models. To implement the deep data model from GEBCO, temperature and salinity data obtained from WOA database, as well as meteorological data and atmospheric fluxes achieved from ECMWF daily database with a spatial resolution of 7.5 minutes. The model was run from 2009 to 2019. Temperature, salinity, and flow rate data from the model were used to calculate and simulate the electrical conductivity in the Caspian Sea. The obtained results showed that the maximum electrical conductivity occurred in the southern basin with a value of 2.3s/m in summer and the minimum electrical conductivity occurred in the northern Caspian basin with a range of 0.8s/m in winter and autumn. The vertical profile of the electrical conductivity at the three geographical locations indicated that temperature is the dominant factor in the electrical conductivity.
... In 2016, the average level of the Caspian Sea was measured to be -27.43 m against the surface of the Atlantic Ocean [36]. The Caspian Sea has a longitudinal geometry (1000 km long and 200 to 300 km wide) and has three northern, middle, and southern basins ( Figure 1). ...
In this study, changes in the magnetic field and electrical conductivity across the Caspian Sea Basins were investigated using the Princeton Ocean Model (POM). In this model, bathymetry, temperature and salinity and atmospheric flux data were collected from GEBCO08, WOA and ECMWF databases, respectively. This model was implemented for ten years (2009-2019), and temperature, salinity and current velocity were extracted from the model output to calculate the electrical conductivity and simulate the magnetic field anomalies of the Caspian Sea. The calculated electrical conductivity indicates that the dominant factor in electrical conductivity was temperature. In the study area, the highest and lowest electrical conductivity were in the southern Caspian basin (SCB) with a value of 2.3 S/m in summer and in the northern Caspian basin (NCB) about 0.8 S/m in autumn. Also, the results show the highest and lowest magnetic fields in the SCB were 16 nT in March and 12 nT in November, respectively. The distribution of magnetic field anomalies with different values in the middle Caspian basin (MCB) can also be observed for all months. According to the results, the dominant factor in the magnetic field anomalies is the current velocity, which has the most effect on the magnetic field in the western part of the Caspian Sea.
... The northern part of the basin is a part of the Scythian plate, and the southern one is associated with the Alpine-Mediterranean Cenozoic fold belt region. The sea basin within the present Caspian Sea appeared in Paleozoic, its shoreline has changed many times since then as a result of repeating transgressions and regressions which continue to this day due to climate changes [18]. Five main crustal blocks are defined within this region [19]: The North Caspian Basin (that is a part of the Pre-Caspian depression), the Middle Caspian Basin, the Apsheron Sill (separating the northern and middle Caspian basins), the Mangyshlak Sill (separating the middle and south Caspian basins) and the South Caspian Basin. ...
Modern satellite gravity missions and ground gravimetry provide operational data models that can be used in various studies in geology, tectonics, and climatology, etc. In the present study, sedimentary basins in the southern part of the East European Platform and adjoining areas including the Caucasus are studied by employing the approach based on decompensative gravity anomalies. The new model of sediments, implying their thickness and density, demonstrates several important features of the sedimentary cover, which were not or differently imaged by previous studies. We found a significant redistribution of the low-dense sediments in the Black Sea. Another principal feature is the increased thickness of relatively low-dense sediments in the Eastern Greater Caucasus. The deepest part of the South Caspian basin is shifted to the north, close to the Apsheron Trough. In its present position, it is almost joined with the Terek–Caspian depression, which depth is also increased. The thickness of sediments is significantly decreased in the eastern Pre-Caspian basin. Therefore, the new sedimentary cover model gives a more detailed description of its thickness and density, reveals new features and helps in better understanding of the evolution of the basins, providing a background for further detailed studies of the region.
... Regular measurements of current velocities in situ are very expensive and in certain cases even impossible because water area belongs to five littoral states. The experience of using remote sensing data, in particular satellite altimetry, to analyze the circulation of the Caspian Sea is well known [3,4,[7][8][9]. For this reason, it is proposed to use satellite altimetry data to study the seasonal and interannual variability of water exchange between different parts of the Caspian Sea. ...
... At the same time, the accuracy of measuring sea level is about 4 cm, which is sufficient for this research. The orbit repetition period (about 10 days) allows us to analyze the interannual and seasonal variability of sea level and currents [3,4,[7][8][9]. The spatial resolution of sea level measurements by these satellites is better than the typical Rossby radius of deformation for the Caspian Sea (7.5-10 km) [4,7]. The calculation of the sea level anomalies (SLA) was carried out relative to the model of mean sea surface heights (MSS) of the Caspian Sea (named as CS_MSS_GCRAS19), developed at the Geophysical Center of the Russian Academy of Sciences, which takes into account interannual variability of the Caspian Sea level [11,13]. ...
... The orbit repetition period (about 10 days) allows us to analyze the interannual and seasonal variability of sea level and currents [3,4,[7][8][9]. The spatial resolution of sea level measurements by these satellites is better than the typical Rossby radius of deformation for the Caspian Sea (7.5-10 km) [4,7]. The calculation of the sea level anomalies (SLA) was carried out relative to the model of mean sea surface heights (MSS) of the Caspian Sea (named as CS_MSS_GCRAS19), developed at the Geophysical Center of the Russian Academy of Sciences, which takes into account interannual variability of the Caspian Sea level [11,13]. ...
Seasonal and interannual variability of water exchange between the Northern and Middle (133 track), and Middle and Southern (209 track) Caspian Sea was calculated based on satellite altimetry data of TOPEX/Poseidon and Jason-1, -2, -3 satellites for 1992–2018. The climatic value of water exchange through the 133 track was +0.41 Sv, and through the 209 track +0.37 Sv. The difference can be explained by the evaporation of water and the recirculation in the Middle Caspian cyclonic gyre. The maximum negative water exchange anomaly of –0.147 Sv occurs on average in August while the maximum positive water exchange anomaly of +0.112 Sv occurs in February. Since 2005 anomalies of water exchange through the Middle Caspian fluctuates from +0,013 Sv (2006) to –0,017 Sv (2008), i. e. the amplitude of interannualvariability of water exchange became five times less than in 1992–2005. This is an interesting observation which means that after 2005 in the course of the continuous sea level drop water exchange through the Middle Caspian from year to year became much more stable.
... Regular in-situ measurements of current velocities are very expensive and difficult to do because of the Caspian Sea division between five countries. The experience of using remote sensing data, in particular, satellite altimetry to analyze the circulation of the Caspian Sea is well established (Lebedev, Kostianoy 2005;Lebedev, Kostianoy, 2008;Kouraev et al., 2011;Lebedev, 2015;Lebedev, Kostianoy, 2016;Lebedev, 2018). ...
... Accuracy of sea level measurements is about 4 cm, which is an adequate value for studies of water circulation. The orbital repeat period of about 10 days along the tracks and 5 days in crossover points enables analysis of interannual and seasonal variability of the sea level and currents (Lebedev, Kostianoy 2005;Lebedev, Kostianoy 2008;Kouraev et al., 2011;Lebedev, 2015;Lebedev, Kostianoy, 2016;Lebedev, 2018). Spatial resolution of T/P, J1/2/3 sea level measurements is better than the typical Rossby radius of deformation for the Caspian Sea (7.5-10 km) (Baidin, Kosarev, 1986). ...
... Isobaths are shown in meters. The coastline corresponds to year 1934, when the sea level was -26.46 m relative to the World Ocean level(Lebedev, 2018). ...
The paper presents the results of estimation of interannual and seasonal variability of water exchange between the Northern, Middle and Southern Caspian Sea based on the TOPEX/Poseidon and Jason-1/2/3 satellite altimetry data. The boundaries between the Caspian Sea sub-basins were taken along the 133 and 209 tracks of the satellites. Temporal variability of surface geostrophic velocities directed perpendicular to the tracks showed that positive values correspond to the southeast direction of the currents, negative values correspond to the northwest direction. It is clearly seen that the main water exchange associated with the Volga River runoff is concentrated along the western coast of the Caspian Sea. In this area, anomalies of geostrophic velocities exceed 20 cm/s. Total water exchange anomalies through the 133 and 209 tracks show seasonal variability with an amplitude up to ±18x10 5 m 3 /s for track 133 (a line between the Northern and Middle Caspian) and ±11x10 5 m 3 /s for track 209 (a line between the Middle and Southern Caspian). The maximum values of water exchange anomalies were observed in 1993, 1994 and 2012 through 133 track (±16-18x10 5 m 3 /s) and in 1993, 1996 and 1997 (±11x10 5 m 3 /s) through 209 track.
... The general circulation in the CS is mostly cyclonic based on both indirect estimates of currents (floats and dynamical methods), and diagnostic simulations by numerical hydrodynamic models (Bondarenko, 1993;Ibrayev, Özsoy et al., 2010;Gunduz, Özsoy, 2014;Lebedev, 2018) although sometimes anticyclonic circulation is observed in some regions of CS. The currents in deep layers (below 20-50 m) have a stable cyclonic character during the whole year (Zyryanov, 2015). ...
The Caspian Sea (CS) is the largest enclosed basin in the world, located inside the Eurasian continent in the Northern Hemisphere. Although there have been few studies of the dynamics of the coastal zone in the CS, observations show that oscillations with periods from 2–3 days to 1–3 weeks dominate. These oscillations are presumed to be related to the synoptic variability of direct wind impact and to coastally-trapped waves (CTW). Here, we describe and interpret current meter observations on the continental margins of the southern CS from 2012 to 2014 to identify and characterize CTW there. Time series analysis provides evidence for both remote and locally wind-forced eastward traveling signals with time lags consistent with CTW theory. A wind-forced model with two CTW modes is able to reproduce the structure, amplitudes, and phases of observed alongshore current fluctuations, explaining half of the variance at frequencies less than 1 cpd. Remote forcing effects are present at all times, but are most striking when the local winds are weak, as in summer. The CTW calculations also suggest that the source region for the remote forcing may extend farther north along the west coast of the CS.
... The general circulation in the CS is mostly cyclonic based on both indirect estimates of currents (floats and dynamical methods), and diagnostic simulations by numerical hydrodynamic models (Bondarenko, 1993;Ibrayev, Özsoy et al., 2010;Gunduz, Özsoy, 2014;Lebedev, 2018) although sometimes anticyclonic circulation is observed in some regions of CS. The currents in deep layers (below 20-50 m) have a stable cyclonic character during the whole year (Zyryanov, 2015). ...
The Caspian Sea, as the largest island water body on the Earth has a unique marine environment and is of great importance for the world and the lateral countries around it. The continental shelf is one of the important marine areas. The continental shelf as a boundary between land and sea is one of the most important and most diverse ecosystems. Continental shelf has vast oil, coal, sulfur, metals sources, so this region is economically very important. Currents are the important factors to distribute pollution. One of the basic requirements for environmental, biological or any other marine related studies is the understandings about circulation and characteristics of the currents. Currents which due to coastal trapped are one of the most important currents on the continental shelf. Therefore, studying about currents and waves on the continental shelf is very important. The shelf in the study area covers a band of coastal waters with the length of 24 km and width of 12 km. The shelf in the study area has a width of about 10 km. The depth gradually increases to about 45 m near the shelf break, after that the depth sharply increases to 400 m at about 18 km from the coastline. This study attempts to introduce trapped waves and the probability of occurrence each of these waves.
This study introduces a technique to uncover concealed patterns in satellite altimetry data, reflecting sea level variations in inland water bodies. We applied the methodology to the Caspian Sea, using altimetry data from four satellite missions over 27 years (1993-2020): TOPEX/Poseidon, Jason1, Jason2, and Jason3. The approach involves two steps: estimating sea level trends and identifying breakpoints that indicate trend shifts; and leveraging time lags between breakpoints at various locations to classify water drainage areas according to their degree of influence on each period. By revealing concealed patterns in the altimetry data, this technique can provide insights to understand the impacts of global warming and local climate changes on sea level fluctuations in the Caspian Sea. We hope that our study can facilitate subsequent interdisciplinary research on the intricate interplay between climate change and hydrological processes in inland water bodies.
Satellite observation of sea surface height (SSH) may soon have sufficient accuracy and resolution to map geostrophic currents in Lake Superior. A dynamic atmosphere correction will be needed to remove SSH variance due to basin-wide seiching. Here, the dynamics of rotating barotropic gravity modes are examined using numerical models and lake-level gauges. Gravity modes explain 94% of SSH variance in a general circulation model, and evolve as forced, damped oscillators. These modes have significant SSH, but negligible kinetic energy (2 J m ⁻² ) and dissipation rates (0.01 W m ⁻² ) relative to other motions in Lake Superior. Removing gravity modes from instantaneous SSH allows geostrophic currents to be accurately computed. Complex empirical orthogonal functions (CEOFs) from 50 years of data at 8 lake-level gauges show patterns consistent with the first two gravity modes. The frequency spectra of these CEOFs are consistent with forced, damped oscillators with natural frequencies of 3.05 and 4.91 cycles per day and decay time scales of 4.5 and 1.0 days. Modal amplitudes from the general circulation model and lake-level gauges are 80% coherent at 1 cpd, but only 50% coherent at 3 cpd, indicating that the atmospheric reanalysis used to force the general circulation model is not accurate at the high natural frequencies of the gravity modes. The results indicate that a dynamic atmosphere correction should combine modeled gravity modes below 1 cpd and observed mode-1 and 2 amplitudes (from lake-level gauges) at higher frequencies. An inverted barometer correction is also recommended to account for low-frequency atmospheric pressure gradients that do not project onto gravity modes.
Changes in near surface air temperature (SAT) and vorticity of the wind speed field of the White Sea and the territory of the Murmansk and Arkhangelsk regions and the Republic of Karelia are investigated. We analyzed the monthly average NCEP/ NCAR reanalysis data for the period 1950–2020. The average surface air temperature growth estimated using a linear trend was +0.24 ⁰ C/10 years. Against the background of this linear growth, significant interdecadal changes in surface air temperature are observed. The following periods are highlighted: the strengthening of the continentality of the climate (1950–1976), a more maritime climate (1977–1998), and the rapid growth of surface air temperature (1999–2020). The transition from a period of increasing continentality of the climate to a period of a more maritime climate is associated with an increase in the influence of the North Atlantic on the region under study. A hypothesis has been put forward that the period of rapid growth of surface air temperature is caused by the transition of the climatic system of the western part of the Russian Arctic into a new phase state. The observed warming in the Arctic has caused a reduction in sea ice, which has led to an increase in solar energy absorption by the surface of the Barents and White Seas.
