The High-Resolution Gridded Observations System generates high-resolution gridded observations using the MetPy interpolate_to_grid Python tool. Gridded observations are used as ground truth for evaluating high-resolution Numerical Weather Prediction model forecasts in a spatial framework that enables assessment of the true value of high-resolution forecasts. The tool, as received from MetPy, uses five different interpolation techniques that take meteorological observations from irregularly spaced point locations and produces a uniformgrid that contains the interpolated values of the observations. The gridded observations are then plotted on a map. The tool was modified to generate observations on grids with sub-kilometer grid spacing. In addition, the tool was modified (1) to read an input text file different from the default text file and (2) to output the gridded observations using a different map projection and array type to ensure compatibility with model assessment software. The tool, which is run in a Python script, can be edited to specify which interpolation technique(s) willbe used as well as various parameters that control the interpolation. The output gridded observations are plotted on the original map and can be passed to the Model Evaluation Tools (MET) and METplus Wrappers, which compute numerous spatial skill scores and error statistics for input model forecasts.