Diffusion?Based Smoothers for Spatial Filtering of Gridded Geophysical Data

We describe a new way to apply spatial filter gridded data from models or observations, focusing on low-pass filters. The method is analogous smoothing via diffusion, and its implementation requires only discrete Laplacian operator appropriate the data. can approximate arbitrary shapes, including Gaussian filters, be extended spatially varying anisotropic diffusion-based smoother's properties are illustrated with examples ocean model observational products. An open-source Python package implementing this algorithm, called gcm-filters, currently under development.