Climatological oceanographic data of the shelf zone of Sakhalin Island

Pishchalnik, V.M.; Arkhipkin, V.S.; Latkovskaya, E.M.; Myslenkov, S.A.; Bobkov, A.O.; Pishalnik, A.V.

Авторы: Pishchalnik V.M., Arkhipkin V.S., Latkovskaya E.M., Myslenkov S.A., Bobkov A.O., Pishalnik A.V.
Журнал: Regional Studies in Marine Science
Том: 89
Год издания: 2025
Номер статьи: 104389
DOI: 10.1016/j.rsma.2025.104389
Аннотация: A comprehensive catalogue of more than 44,800 deep-sea stations was compiled and documented in the shelf zone of Sakhalin Island, spanning from 1948 to 1994. This represents in excess of 95 % of all global estimates of the amount of data in the corresponding period in this water area. Utilizing 18,500 complex hydrological stations that were meticulously positioned at fixed coordinates and standard depths of up to 500 m, a database encompassing hydrological data from 1948 to 1994 and hydrochemical data from 1975 to 1994 was developed. Drawing on the initial data and applying a unique analytic approach, we calculated the average long-term values for all oceanographic parameters at each station across the specified standard depths, namely, water temperature, salinity, dissolved oxygen, pH, nutrients: dissolved mineral phosphorus (P-PO4), dissolved nitrite nitrogen (N- NO2) and dissolved inorganic silicon (Si-SiO3). The article provides quantitative data derived from nodes within regular grids across various spatial scales for five specific regions of the shelf zone. The resulting three-dimensional matrices facilitate the monitoring of long-term trends in oceanographic parameters, enabling the evaluation of marine area bioproductivity and carbon balance, as well as the analysis of dynamic phenomena such as storm surges, tsunamis, and seiches. Together with matrices, Supplementary 3, we also present seasonal maps and sections for the entire shelf zone, Supplementary 1, as well as vertical profiles and annual cycles for eight “mean” oceanological stations, Supplementary 2 (DOI:10.13140/RG.2.2.13923.26406). This assessment contributes significantly to understanding their effects on coastal ecosystems and infrastructure, thereby fostering the advancement of methodologies for monitoring and modelling dynamic and geoecological processes within coastal regions.
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