In this paper, we describe a novel manifold-based interpolation method for sensed environmental data. Furthermore, we present initial results for applying the proposed method to estimate wind speed and direction around Lake Michigan. The proposed method is showing promising results based on the hypothesis that an environmental dataset (including longitude, latitude time, and measured parameters) can be mapped onto an underlying differential manifold. Our preliminary results show that the proposed manifold-based approach outperforms state-of-the-art interpolation and estimation methods.