Classification of climate of the Northern hemisphere using phases of temperature signals
This paper presents the results of structuring surface temperatures in the Northern hemisphere for the period of modern climate changes. Main idea of the proposed classification is the geographic conditionality of the phase modulation of the temperature signal. The criterion is the consistency, namely, phasing of the temperature oscillations in certain geographic areas. We believe that changes in the synchronization modes of climatic processes during changing climate lead to transformations of the spatial structure of the temperature field because of transition of the system to the new state. The temperature series are represented as phase-modulated oscillations. External and internal disturbances, having influenced on the climate system, form a complicated modulation of the phase, and it is partly corresponded to these ones. Initial temperature space of 818 series is structured into 17 regional clusters, where the temperature changes occur synchronously. Properties of the resulting clusters and their compliance with the known climatic classifications are discussed. The classifying algorithm affords ground for the researchers to choose the degree of differentiation of the investigated field depending on the task. The phase modulation indices were evaluated, to identify manifestations of the external forcing in the surface temperature. Inconsistency of the indices to those in the case of the harmonic phase modulation allows quantifying the role of the regional climate-factors for each class. Modulation, which is the closest to the harmonic one, was found in the area of the North Atlantic thermohaline conveyor. During the study of the climate change, the proposed approach can be used as an analytical framework on any spatial scale, only by data on the surface temperature, and with predetermined level of detalisation. Searching synchronization in nonlinear chaotic systems may become one of the perspective ways to optimize the predictive models.