Moving-Window Regression Downscaling of Raster Data R package topocast version 0.0.5 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>. Software Depends: R (>= 4.1.0) Imports: Rcpp (>= 1.0.0), terra (>= 1.7.0) LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, raster, rmarkdown, sf, stars, svglite, testthat (>= 3.0.0) Gilles Colling <gilles.colling051@gmail.com> Comprehensive R Archive Network (CRAN) Gilles Colling [aut, cre, cph] (ORCID: <https://orcid.org/0000-0003-3070-6066>) MIT + file LICENSE (https://CRAN.R-project.org/package=topocast/LICENSE) 2026-08-07 application/tgz https://CRAN.R-project.org/package=topocast doi:10.32614/CRAN.package.topocast en-US