scholarly journals Validation of Wind Speed Calculated on Satellite Altimetry Data by Measurements on Weather Stations Located Along the White Sea Coast

2019 ◽  
Vol 25 ◽  
pp. 36-43
Author(s):  
Sergey A. Lebedev ◽  
Alexander S. Sorokin ◽  
Pavel V. Kluev ◽  
Pavel N. Kravchenko
Keyword(s):  
Wind Speed ◽  
Barents Sea ◽  
White Sea ◽  
Altimeter Data ◽  
The White Sea ◽  
Satellite Altimeter ◽  
Weather Stations ◽  
Sea Coast ◽  
Satellite Altimetry Data

The White Sea is a southern inlet of the Barents Sea located in the northwest of European Russia. Winds are predominantly southwestern in winter with speeds of 4–8 m/s. Arctic anticyclones can change winds to the northeastern ones. The consistency between satellite altimeter derived wind speed and measurements on coastal stations of the White Sea was checked in the present study. For different parts of the coastal zone, satellites tracks were chosen to be located close to the weather station (within 10-20 km). Then, for every cycle of the selected satellite passes, corresponding values of satellite derived wind speed together with corresponding time (UT) were selected. In-situ wind speed data for the time nearest to the satellite pass were picked up from the databases collected at coastal weather stations. For the comparative analysis, five weather stations on the White Sea coast and tracks of TOPEX/Poseidon and Jason-1/2/3 satellites were selected. Improvement in correlation between meteo and altimeter data on wind speed can be obtained when using method of decomposition of the winds in four quadrants according to wind direction relative to local coastline orientation.

Epilithic lichens and their morphological adaptations to the conditions of the White and Barents Seas coast (Russian Arctic)

2012 ◽  
Vol 2 (2) ◽  
pp. 109-116 ◽  
Author(s):  
Anzhella V. Sonina
Keyword(s):  
Species Composition ◽  
Barents Sea ◽  
White Sea ◽  
Lichen Species ◽  
The White Sea ◽  
The Barents Sea ◽  
Lichen Cover ◽  
Functional Features ◽  
Epilithic Lichens ◽  
Sea Coast

The main aim of our work was to investigate the biodiversity of coastal lichens, conditions of lichen cover formation, and study the structural and functional adaptations of Lecanora intricata (Ach.) Ach. and L. polytropa (Ehrh. ex Hoffm.) Rabenh. The investigation was carried out during 2008-2012 on cliffs both along the Murmansk (the Barents Sea) coast and the southern and western shores of the White Sea. For the evaluation of species composition, and ecotopic coenotical features of epilithic lichen growing on cliffs, the geobotanical methods have been used. In addition, the anatomical, morphological and biochemical studies of Lecanora intricata and L. polytropa have been made. 91 species have been included in the total list of lichens on the White Sea coast. On the Murmask coast of the Barents Sea, 36 lichen species had revealed. On the coastal territory, the epilithic lichens inhabit the upper littoral and supralittoral zone. The lichen cover is formed by two interacting factors: the water factor (sea) and the terrestrial vegetation. Four lichen zones were distinguished in the all studying territories. They differed by the lichen species composition and effect of the sea. The first lichen’s zone is the intrazonal structure in the complex coastal lichen cover. In Lecanora polytropa and L. intricata, structural and functional features of lichens for adaptation to unstable coastal conditions were identified. The crustose biomorphs were better adapted to temperature and degree of hydration of thalli. Formation of the smallest ascospores is reproductive strategy of epilithic lichens in extreme habitats. High content of usnic acid in the studied lichen thalli allows them to exist in the open areas exposed to solar radiation and provides the biotic regulation that affects the structure of lichen cover. Optimal ratio of algal to fungal components in the thalli of these species is necessary to maintain their life in extreme environments.

scholarly journals The White Sea: Available Data and Numerical Models

Geosciences ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 463
Author(s):  
Ilya Chernov ◽  
Alexey Tolstikov
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Barents Sea ◽  
White Sea ◽  
Numerical Models ◽  
The White Sea ◽  
North West ◽  
Tidal Motion ◽  
The North

The White Sea is a small shallow semi-closed sea in the North-West of Russia. It is strongly affected by induced tides, so the tidal motion dominates in the sea. Sea ice is seasonal and the water salinity is less than in the neighbouring Barents sea due to strong river discharge. We review the sources of in-situ and satellite data that are available for the sea, and describe those few numerical models, together with the challenges that are faced. We focus on the large-scale circulation and thermohaline fields, but also cover sea ice, river runoff, and pelagic biogeochemical data.

scholarly journals Boulder pits of the White Sea Region

2021 ◽  
Vol 12 (4-2021) ◽  
pp. 104-125
Author(s):  
M. M. Shakhnovitch ◽  
Keyword(s):  
Coastal Zone ◽  
Russian Federation ◽  
Barents Sea ◽  
White Sea ◽  
The White Sea ◽  
Field Surveys ◽  
Finnish Lapland ◽  
The Barents Sea ◽  
The Russian Federation

The purpose of the article is to introduce into scientific circulation little-known and controversial objects made of stones discovered during our field surveys in 2019 on the Tersk Coast of the White Sea near the Khlebnaya River. The monument consists of 27 boulder structures of four types: ring-shaped layouts with a recess in the center –– boulder pits (24), “seid”, “pile”, a flat boulder with stones laid on it. Boulder pits within the borders of the Russian Federation are found in the coastal zone of the Western and Northern White Sea regions and the Barents Sea. The distribution of such objects is noted in Finnmark and Finnish Lapland and correlates with the area of historical settlement of local Sami groups. We tend to interpret the “boulder pits” as objects associated with non-Christian cult practices, possibly of a funerary nature.

scholarly journals Marine Wind and Wave Height Trends at Different ERA-Interim Forecast Ranges

2015 ◽  
Vol 28 (2) ◽  
pp. 819-837 ◽  
Author(s):  
Ole Johan Aarnes ◽  
Saleh Abdalla ◽  
Jean-Raymond Bidlot ◽  
Øyvind Breivik
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
North Atlantic ◽  
Wave Model ◽  
Altimeter Data ◽  
The North ◽  
The Impact ◽  
Global Reanalysis ◽  
Made In

Abstract Trends in marine wind speed and significant wave height are investigated using the global reanalysis ERA-Interim over the period 1979–2012, based on monthly-mean and monthly-maximum data. Besides the traditional reanalysis, the authors include trends obtained at different forecast range, available up to 10 days ahead. Any model biases that are corrected differently over time are likely to introduce spurious trends of variable magnitude. However, at increased forecast range the model tends to relax, being less affected by assimilation. Still, there is a trade-off between removing the impact of data assimilation at longer forecast range and getting a lower level of uncertainty in the predictions at shorter forecast range. Because of the sheer amount of assimilations made in ERA-Interim, directly and indirectly affecting the data, it is difficult, if not impossible, to distinguish effects imposed by all updates. Here, special emphasis is put on the introduction of wave altimeter data in August 1991, the only type of data directly affecting the wave field. From this, it is shown that areas of higher model bias introduce quite different trends depending on forecast range, most apparent in the North Atlantic and eastern tropical Pacific. Results are compared with 23 in situ measurements, Envisat altimeter winds, and two stand-alone ECMWF operational wave model (EC-WAM) runs with and without wave altimeter assimilation. Here, the 48-h forecast is suggested to be a better candidate for trend estimates of wave height, mainly due to the step change imposed by altimeter observations. Even though wind speed seems less affected by undesirable step changes, the authors believe that the 24–48-h forecast more effectively filters out any unwanted effects.

scholarly journals A new species of Incertella Sabrosky (Diptera: Chloropidae) from the White Sea coast, Russian Karelia

2009 ◽  
Vol 20 (1) ◽  
pp. 4-8 ◽  
Author(s):  
Emilia Nartshuk ◽  
Andrey Przhiboro
Keyword(s):  
New Species ◽  
White Sea ◽  
The White Sea ◽  
Diagnostic Characters ◽  
A New Species ◽  
Sea Coast ◽  
Russian Karelia

A new chloropid species, Incertella karteshensis sp. n. with darkened wings, is described from the White Sea coast (northern Karelia, Russia). The diagnostic characters of the new species are discussed

scholarly journals COMPARATIVE STUDY OF POLYPHENOLS OF BROWN ALGAE OF THE BARENTS SEA AND THE WHITE SEA, AS WELL AS THE WATERS OF THE NORTH ATLANTIC

2020 ◽  
pp. 129-137
Author(s):  
Ekaterina Dmitriyevna Obluchinskaya ◽  
Lubov Viktorovna Zakharova
Keyword(s):  
Brown Algae ◽  
Barents Sea ◽  
White Sea ◽  
Raw Materials ◽  
Dry Mass ◽  
Biologically Active ◽  
The White Sea ◽  
Polyphenol Content ◽  
Norwegian Sea ◽  
The Barents Sea

The polyphenol content in the brown algae of the Barents, White Seas, as well as the water areas of the Northwest Atlantic (the Norwegian Sea, the Faxflow bay of the Atlantic Ocean) located in Russia, Norway, Greenland, and Iceland are compared. Algae of the following species were used for this study: Fucus vesiculosus, Fucus spiralis, Fucus serratus, Ascophyllum nodosum, Fucus evanescens. It was found that the most productive raw materials for the extraction of polyphenolic compounds are brown algae F. vesiculosus, growing in Zavalishin Bay of the Barents Sea (Russia): the highest polyphenol content (14.4%) in the summer of 2019 was noted here. Polyphenols detected in F. vesiculosus in the summer from the White Sea on about. Great burnt (13.3%) (Russia), as well as in the Norwegian Sea, Cape Sydspissen (11.6%) (Norway). The minimum content of polyphenols was found in F. spiralis (0.7% dry mass) on the coast of Iceland (Faxflow bay), a low content of polyphenols was characteristic of all types of algae from this location (0.7–2.4%). Three-way analysis of variance (MANOVA) on the example of three types of algae (F. vesiculosus, F. spiralis, A. nodosum) showed that all the studied factors (place of collection, type of algae, fertile phase) are significant. The most significant factor affecting the accumulation of polyphenols by brown algae is the location of algae growth. The high content of polyphenols in the types of algae we studied from Russian water areas allows us to recommend their use as food and medicinal raw materials, as well as raw materials for biologically active additives.

MODELING STORM SURGES AND WAVE CLIMATE IN THE WHITE AND BARENTS SEAS

2017 ◽  
Author(s):  
Anastasia Korablina ◽  
Anastasia Korablina ◽  
Victor Arkhipkin ◽  
Victor Arkhipkin ◽  
Sergey Dobrolyubov ◽  
...  
Keyword(s):  
Storm Surge ◽  
Barents Sea ◽  
White Sea ◽  
Storm Surges ◽  
Wave Climate ◽  
The Arctic ◽  
Economic Losses ◽  
The White Sea ◽  
Linear Interaction ◽  
The Barents Sea

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.

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