The Study of the State of the World Ocean Areas Based on Modern Technologies for Processing and Analysing Data

Abstract

This paper is devoted to the processing of hydrophysical data on the state of marine areas utilizing modern data processing technologies. Author uses Python programming language to process marine data. The results on the processing of the remote sensing data on the Baltic and the Black Seas surface temperature are presented in the study. Daily satellite data for the years 1982–2018 were processed using Python scripts for both water areas. The analysis of the obtained information was conducted with R programming language. This language supports a wide range of statistical and numerical methods and is convenient to use to determine the statistical characteristics of the studied quantities. Data analysis reveals statistically significant positive trend in the sea surface temperature (SST) values in the both studied water areas over the past decades. The paper has also analyzed the spatial variability of the surface temperature within considered areas. The analysis illustrates the temperature variability in certain areas of the sea and identifies areas with the highest rate of temperature increase. Conclusions are made on the usability of the programming languages for various data processing tasks.