Sparse signal models are in the focus of recent developments in narrowband DOA estimation. Applying these methods to localizing audio sources, however, is challenging due to the wideband nature of the signals. The common approach of processing all frequency bands separately and fusing the results is costly and can introduce errors in the solution. We show how these problems can be overcome by decomposing the wavefield of a circular microphone array and using circular harmonic coefficients instead of time-frequency data for sparse DOA estimation. As a result, we present the super-resolution localization method WASCHL (Wideband Audio Sparse Circular Harmonics Localizer) that is inherently frequency-coherent and highly efficient from a computational point of view.