Moving-Window Regression Downscaling of Raster Data // Downscales coarse-resolution raster data to a finer grid by fitting local linear regressions of a response, such as a climate variable, on one or more fine-resolution predictors, such as elevation and other terrain indices, within a moving window. Regression coefficients are estimated for every cell using summed-area tables, so the cost is independent of the window size, then resampled to the target resolution and applied to the fine- resolution predictors. Multiplicative and additive anomaly application downscale time series relative to a baseline climatology, following the regression-on-elevation approach used for high-resolution climate surfaces described in Karger et al. (2017) doi:10.1038/sdata.2017.122.