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COMPUTER TECHNOLOGY FOR WATER MASSES ANALYSIS USING IN SITU AND REMOTE SENSING DATA (PROGRAMMED IN PYTHON AND R)
Abstract
Computer technology for Arctic seas water masses analysis is presented. It facilitates data obtained both as remote sensing and in situ. Modern methods and software tools are described as parts of detailed technology in case of one spatial distribution assigned to particular time stamp map and time series of them. Open data from MODIS Aqua satellite project and expeditions listed in World Ocean Database are treated with open source programming tools (R/Python software stacks). Sea surface temperature analysis is combined with research in depth of water masses inflow defined through particular isohaline. Paper covers current state in field of water masses analysis based on temperature and salinity values measured on sea surface or in depth. Fronts and frontal zones are efficient terms to describe interaction and circulation processes of water masses having different origin with effects of complex bottom topography. These processes are registered from analysis of temperature and salinity gradients. Gradient magnitude fields are handled to get front map with contextual median filter, Sobel and other window operators for particular date sea surface temperature distribution. Averaged maps are also calculated. Front maps can be presented as content of interactive web application based on R software stack. Water inflow measure is determined as total area of the shapes bounded by the selected contour (isohaline), the bottom GEBCO profile and the surface. We tested presented computer technology in two case studies for the Barents Sea: (1) Polar front numerical detection and (2) Atlantic waters inflow evaluation.
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Aagaard K., Swift J. H., Carmack E. C., Thermohaline circulation in the Arctic Mediterranean Seas, Journal of Geophysical Research, vol. 90, pp. 4833–4846, 1985.
Mugo R. M., Saitoh S. I., Takahashi F., Nihira A., Evaluating the role of fronts in habitat overlaps between cold and warm water species in the western North Pacific: A proof of concept, Deep-Sea Research Part II, vol. 107, pp. 29-39, 2014.
Sagarminaga Y., Arrizabalaga H., Relationship of Northeast Atlantic albacore juveniles with surface thermal and chlorophyll-a fronts, Deep-Sea Research Part II, vol. 107, pp. 54-63, 2014.
Oziel L., Sirven J., Gascard J.-C., The Barents Sea Frontal Zones and Water Masses Variability (1980–2011), Ocean Science, vol. 12/issue 1, pp. 169-184, 2016.
Moiseev D. V., Zaporozhtsev I. F., Maximovskaya T. M., Dukhno G. N., Identification of frontal zones position on the surface of the Barents Sea according to in situ and remote sensing data (2008-2018), Arctic: Ecology and Economy, vol. 34/issue 2, pp. 48-63, 2019. (In Russian).
Zaporozhtsev I. F., Moiseev D. V., Calculation of Atlantic Waters Inflow and Polar Front Position in the Barents Sea with Long-Term Data on Kola Transect, Proceedings of 4th International Symposium on Geoinformatics, ISyG 2018, Indonesia, Malang, 10-12 Nov. 2018, pp. 45-49.
Belkin I. M., O'Reilly J. E., An algorithm for oceanic front detection in chlorophyll and SST satellite imagery, Journal of marine systems, vol. 78/issue 3, pp. 319-326, 2009.
Karimova S., Hydrological fronts seen in visible and infrared MODIS imagery of the Black Sea, International Journal of Remote Sensing, vol. 35/issue 16, pp. 6113- 6134, 2014.
Kirches G., Paperin M., Klein H., Brockmann C., Stelzer K., GRADHIST - A method for detection and analysis of oceanic fronts from remote sensing data, Remote Sensing Of Environment, vol. 181, pp. 264-280, 2016.
Ping B., Su F., Meng Y., Du Y., Fang S., Application of a sea surface temperature front composite algorithm in the Bohai, Yellow, and East China Seas, Chinese Journal of Oceanology and Limnology, vol. 34/issue 3, pp. 597-607, 2016.
Roa-Pascuali L., Demarcq H., Nieblas A.-E., Detection of mesoscale thermal fronts from 4 km data using smoothing techniques: Gradient-based fronts classification and basin scale application, Remote Sensing Of Environment, vol. 164, pp. 225- 237, 2015.
Oerder V., Bento J. P., Morales C. E., Hormazabal S., Pizarro O., Coastal Upwelling Front Detection off Central Chile (36.5-37°S) and Spatio-Temporal Variability of Frontal Characteristics”, Remote sensing, vol. 10/issue 5, pp. 440- 464, 2018.
Ozhigin V. K., Ivshin V. A., Trofimov A. G., Karsakov A. L., Anciferov M. Yu. The Barents Sea waters: structure, circulation, variability, Russia, PINRO, 2016, 260 p. (in Russian).
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