MOSCOW, March 1. /TASS/ Researchers from the Department of Physics of Higher School of Economics (HSE) and Landau Institute of Theoretical Physics, Igor Kolobkov and Vladimir Lebedev, have formulated an analytical theory that helps people get a better grasp of the reasons behind coherent vortices, which include such atmospheric events as cyclones, anticyclones, and hurricanes, the HSE press service reported. According to the scientists, their theory illustrates how order arises from chaos, for example, from air masses. The results of the study were published in the Journal of Fluid Mechanics.

"This refers to the birth of order from chaos," Vladimir Lebedev elaborated. "We pinpointed the analytical relationship, which illustrates the results of the numerical and laboratory experiments on the formation of coherent vortices [stable whirling motions] by linking the vortex’s characteristics with the statistical properties of chaotic flow fluctuations."

The theory interprets the results of the laboratory experiment and numerical modeling of two-dimensional turbulence where the coherent vortices were previously observed. The impact of the analytical results lies in both their predictive power and establishing insights in the natural phenomena.

According to the scientists, all large-scale atmospheric events such as cyclones, anti-cyclones, and hurricanes, belong to coherent structures generated from chaos. Researchers believe that their study will cultivate a better understanding of how atmospheric vortices appear from "nothing" and eventually down the line how they could be potentially controlled.

The research article titled: "Velocity statistics inside coherent vortices generated by the inverse cascade of 2-D turbulence," presents a consistent analytical theory describing the intensive middle flow of vortices and fluctuations from the mean-value which can be rationalized as temporally and spatially chaotic changes in the flow’s speed. Scientists demonstrated that vortices possess a general structure implying the interval where the azimuth rate does not depend on the distance to the center and the statistical properties of fluctuations are well-defined. The knowledge of these properties enables, for instance, the analysis of processes as the displacement of intermixing of various admixtures.