Multiple Coordinate Translations to Forecast Local Seasonal Changes with Daily Details

The paper demonstrates novel abilities of computer aided processing of meteorological temperature observations to analyze seasonal changes in local climate dynamics. These abilities are connected with the following two missions: to escape traditional losses of the existing information due to the consecutive averaging and to get more necessary information at the expense of restored evolutionary and regulatory constituents in the dynamics. The restoration passes through multiple coordinate translations from weather terms to the climate ones and vice versa, where nonlinear nonstationary features of temperature time series are taken into the consideration but not ignored. Physical meaning of these translations originates from conceptual models of the regulatory theory of local climate dynamics. Then it seems to be promising to direct IT power towards the following problem statement of sustainable development: to determine geographical locations, where seasonally-dependent productions could be best developed with natural conditions in middle-term outlook.