Paper
30 November 2017 Variability of chlorophyll-a concentration in the north-western part of the Black Sea based on satellite data analysis and modeling
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Proceedings Volume 10466, 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 104662H (2017) https://doi.org/10.1117/12.2284311
Event: XXIII International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, 2017, Irkutsk, Russian Federation
Abstract
The main objective of this research is to study the interannual variability of the Black Sea chlorophyll-a concentrations related to the forcing of physical factors (SST, wind, sea circulation) and/or influence of climate variability. The Self-Organization Map (SOM) analysis was applied to identify typical (recurrent) spatial patterns of chlorophyll-a concentrations and physical forcing data. The results of SOM analysis are compared with temporal variability of the climatic indices (NAO, EAWR). The propagation of desalinated water through Danube delta along the Western Black Sea coast and the hydrological structure of shelf water are studied. The dynamics, the coastal current, and formation of Danube plume and salinity front are studied on the basis of numerical modeling which was adapted to the conditions of the North-Western shelf. The results of numerical modeling of effects of plume and buoyancy current evolution, shelf water stratification and wind forcing for summer period conditions are discussed. As a result, the model gives qualitatively correct position of salinity front related with Danube discharge, plume and alongshore current evolution.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. V. Tsyganova and E. M. Lemeshko "Variability of chlorophyll-a concentration in the north-western part of the Black Sea based on satellite data analysis and modeling", Proc. SPIE 10466, 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 104662H (30 November 2017); https://doi.org/10.1117/12.2284311
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KEYWORDS
Data analysis

Data modeling

Satellites

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