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For centuries, soaring birds -- such as albatrosses and eagles -- have been mysterious and intriguing for biologists, physicists, aeronautical/control engineers, and applied mathematicians. These fascinating biological organisms have the ability to fly for long-duration while spending little to no energy. This flight technique/maneuver is called dynamic soaring (DS). For biologists and physicists, the DS phenomenon is nothing but a wonder of the very elegant ability of the bird's interaction with nature and using its physical ether in an optimal way for better survival and energy efficiency. For the engineering community, it is a source of inspiration and an unequivocal promising chance for bio-mimicking. In literature, significant work has been done on modeling and constructing control systems that allow the DS maneuver to be mimicked. However, mathematical characterization of the DS phenomenon in literature has been limited to optimal control configurations that utilized developments in numerical optimization algorithms along with control methods to identify the optimal DS trajectory taken (or to be taken) by the bird/mimicking system. In this paper, we provide a novel two-layered mathematical approach to characterize, model, mimic, and control DS in a simple and real-time implementation. The first layer will be a differential geometric control formulation and analysis of the DS problem. The second layer will be a linkage between the DS philosophy and a class of dynamical control systems known as extremum seeking systems. We believe our framework captures more of the biological behavior of soaring birds and opens the door for geometric control theory and extremum seeking systems to be utilized in systems biology and natural phenomena. Simulation results are provided along with comparisons with powerful optimal control solvers to illustrate the advantages of the introduced method.