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

Abstract

Novel climate reanalysis products like ERA5(-Land) provide more accurate environmental information at higher temporal resolution than traditional climate data products used in ecological applications. Furthermore, they provide uncertainty metrics useful for assessing data quality. The KrigR R-package reduces barriers for users to (a) download ERA5(-Land) data (b) aggregate these data to desired temporal resolutions and metrics, (c) acquire topographical co-variates, and (d) statistically downscale spatial data using co-variates via kriging which allows for integration of data uncertainty with interpolation uncertainty for improved data reliability indicators. The KrigR workflow allows highly flexible data product creation for unparalleled aligning of data set specifications with research objectives. Climate products obtained through KrigR offer great potential for quantification of exposure to extreme events due to their combinations of high spatial and temporal resolutions. Lastly, KrigR can incorporate third-party data which enables generation of high-resolution, bias-corrected climate projection data allowing for ecological forecasting at high-resolution.

Date
Jun 6, 2022 11:00
Event
Climate Science for Ecological Forecasting (Clim4Ecol)
Location
Conference
Erik Kusch
Erik Kusch
PhD Student

In my research, I focus on statistical approaches to understanding complex processes and patterns in biology using a variety of data banks.