Tropical cyclones (TCs) routinely cause coastal flooding that results in economic disruption and loss of life. The primary driving force behind TC flooding arises from (shear) stresses at the ocean surface due to winds, which are estimated by a drag formulation that is a function of the surface-level (10-m) winds. In turn, these winds are typically estimated by simple parametric TC wind models, which provide the so-called gradient balanced winds that occur well above the surface-level winds, thereby requiring an adjustment based on an empirical surface wind reduction factor (SWRF). In practice, the SWRF is typically taken as a fixed constant value; however, previous studies have noted that ``The use of a universal constant for surface wind reduction is thus shown by both the linear and numerical models to be incorrect'' and that, more specifically, ``The factor for reducing upper winds to a near-surface equivalent, which is frequently used in operational work, is shown to have a substantial spatial variability''. Therefore, using surface-level wind speed data retrieved from NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission from 2018 to the present day, a radial-dependent SWRF function is derived and implemented into an existing discontinuous Galerkin shallow water equation model (DG-SWEM), with the goal of obtaining improved results over the ``standard'' technique of using a fixed value of the SWRF. Our proposed approach for estimating the SWRF is evaluated for a number of historical storms making landfall in the US.