%0 Journal Article
%T Electron Orbital Theory for an Alternative Interpretation of Low-pressure Hurricane Systems
%J Marine Science
%@ 2163-243X
%D 2012
%I 
%R 10.5923/j.ms.20120205.03
%X Hurricanes, cyclones and typhoons are weather phenomena which induce damages for billions of dollars yearly and pose significant risks to communities worldwide. The need for better meteorological prediction methods is therefore more important than ever, particularly with the emergence of ¡°extreme weather¡± conditions. Super-computer methods are key tools for storm-analysis and prediction, and are used frequently to predict the direction of large low-pressure systems such as Hurricanes heading yearly for American continent, cyclones in Australia and typhoons in Japan. The dynamical behaviour of these vast low-pressure systems is not fully understood, and the directions of these weather phenomena are often resolved too late for evacuation procedures to be fully effective. In order to increase the understanding of low-pressure systems and meteorological prediction, a hybrid view on the behaviour of hurricane systems based on a blend of quantum mechanics and classical physics is introduced in this brief note. The aims are to introduce a mathematical contemplation to bring to the attention of meteorological modelers a putative behaviour of the storm systems analogue with electron orbital density functional theory, and to use electron orbital theory to improve the resolution and predictive power of storm modeling. The mathematical discussion presented herein shows that a low-pressure system can be subdivided into N-layers, with physical and energetical qualities. Such qualities comprise angular momenta and individual energies of high-density regions which can be used to predict the direction of the low-pressure system. The results and mathematical discussion presented herein serve as a foundation for Hurricane theory improvement.
%K Prediction
%K Atmospheric Systems
%K Low Pressure
%K Modeling
%K Density Functional
%K Electron Orbital
%K Mathematics
%K Computational Sciences
%U http://article.sapub.org/10.5923.j.ms.20120205.03.html