Open AccessModelling of the evolution of the multi-behavioural dynamics from the regulatory climate theory
Author(s) -
Yury Kolokolov,
Anna Monovskaya
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2001/1/012018
Subject(s) - attractor , phase portrait , dynamics (music) , adaptation (eye) , computer science , nonlinear system , basis (linear algebra) , statistical physics , synchronization (alternating current) , ecology , mathematics , physics , biology , mathematical analysis , geometry , quantum mechanics , acoustics , optics , bifurcation , computer network , channel (broadcasting)
The regulatory ability in the local climate dynamics to evolve in accordance with the environmental changes is modeled in the paper. The specialized software provides the following research program: to calculate the solutions of the nonlinear nonstationary multi-behavioural model of the dynamical system with variable structure; to determine the nonlinear dynamics regularities on the basis of these solutions; to reconstruct these regularities by processing the meteorological observations; to solve the inverse problem of building the multi-behavioural portraits of local climate dynamics by use of the reconstructed regularities. Thus factually realized and potential evolutional vacancies of the local dynamics are visualized in the form of the multiple attractors. The physical basis of the research originates from the regulatory climate theory, in accordance with which the local climate dynamics is conceptually considered as the dynamics of the solar energy converter under the astronomically forced hysteresis control with double synchronization. Here landscape and ecological relations are taken into account via the adaptation unit, and the recent dynamics is compared with the one observed as far as possible distant in time. So, structural modifications within the multi-behavioural portrait of local climate dynamics are revealed and crucial evolutionary tendencies are demonstrated.