Modeling turbine wakes is critical to maximizing wind farm energy production but is also challenging due to the complicated phenomena that must be accounted for, including wind shear, veer, atmospheric stratification, and overlapping wakes. Our work introduces a new, efficient method of modeling wakes which naturally captures these complex wake behaviors. We show that our wake modeling approach is as accurate as higher-fidelity methods, but with much less computational cost.