Mathematical methods for analyzing the shape of time series and their applications to remote sensing of the Earth and atmosphere

The work is devoted to methods of time series analysis based on the theory of morphological analysis and measuring and computing systems developed at the Department of Mathematical Modeling and Computer Science of the Faculty of Physics of Lomonosov Moscow State University. Modern relevant methods of time series analysis have been studied. A morphological filtering method is proposed to detect a trend in a time series. A computer experiment was conducted on real experimental data (temperature measurements in the city of Tver) using the above method. The results demonstrated the successful identification of the trend component of the time series. It is planned to develop new methods of time series analysis to solve a wider class of problems for a wider class of input data.