KrigR -- A tool for downloading and statistically downscaling climate reanalysis data

We present KrigR, an R package for acquiring and statistically downscaling state-of-the-art climate data using kriging. KrigR allows R-users to (1) download ERA5 and ERA5-Land climate reanalysis data for a user-specified region, and time-length, (2) aggregate these climate products to desired temporal resolutions and metrics, (3) acquire topographical co-variates, and (4) statistically downscale spatial data to a user-specified resolution using co-variate data via kriging. KrigR can execute all of these tasks in a single function call, thus enabling the user to obtain any of 83 (ERA5) / 50 (ERA5-Land) climate variables at high spatial and temporal resolution with a single R-command. Thereby, KrigR provides a toolbox to obtain a wide range of tailored climate data at unprecedented combinations of high temporal and spatial resolutions. Additionally, we demonstrate how KrigR is compartmentalised to enable use of any given climate dataset and third-party/user-provided co-variates for the kriging step and brings an advantage over other high-resolution datasets by providing downscaling uncertainties, which can explain the difference between several existing high-resolution climate products.