Space, Earth and supercomputing: conjugate problems of ecology, climate, monitoring and remote sensing of earth, hyper-spectral approach and nanodiagnostics of natural environments dedicated to the 65th anniversary of the Keldysh Institute of Applied Mathematics of Russian Academy of Sciences)

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The most complex problems of evolution, climate, ecology, global monitoring and remote sensing of the Earth (ERS) with hyperspectral approaches and nanodiagnostics of the natural environment and objects are proposed to be considered as conjugate for the first time. Electromagnetic radiation is a single physical field that combines the radiation field of the Earth with radiation-active components. For example, the volcanic eruptions and transboundary transport of pollution that affect the ecology and the state of the environment can be detected by remote sensing, and then through the transfer of radiation energy dependent on environmental pollutants can affect the climate, and ultimately, the trend of the evolution of the Earth as a planet. The insurmountable difficulty of the problem lies in the fact that the natural experiments are not allowed for the study of the planet, and only monitoring and observation by different means are possible, on the one hand, and on the other hand, at the time of the radiation measurements it is impossible to restore the entire set of optical-geophysical and optical-meteorological parameters of the “atmosphere-land-ocean” system, on which the radiation depends, and it is not possible to repeat the conditions of observations, since the environment is constantly changing and never repeats. And only mathematical modeling of “big” direct and inverse problems of the radiation transfer theory with parallel supercomputing allows to conduct the theoretical and computational research of such complex problems and to obtain qualitative and quantitative estimates for analysis and forecasts, as well as for different thematic applications based on “scenarios”.

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Conjugate problems, radiation field of the earth, remote sensing, climate, ecology, supercomputing

Короткий адрес: https://sciup.org/147233184

IDR: 147233184   |   DOI: 10.14529/cmse180401

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