  Advances in climate science have rendered obsolete gridded observation data
sets commonly used in macroecological analyses. Novel climate reanalysis
products outperform legacy data products in accuracy, temporal resolution, and
provision of uncertainty metrics. Consequently, there is an urgent need to
develop a workflow through which to integrate these improved data into
analyses. The ERA5 product family are the latest and most advanced global
reanalysis products created by the ECMWF. These data products offer up to 83
essential climate variables at hourly intervals for the time-period of 1981 to
today with preliminary back-extensions being available for 1950-1981. Spatial
resolutions range from 30km (ERA5) to 11km (ERA5-Land) and can be statistically
downscaled to study-requirements at finer spatial resolutions. Kriging is one
such method to interpolate data to finer resolutions and has the advantages
that one can leverage additional covariate information and obtain the
uncertainty associated with the downscaling. The KrigR R Package enables users
to (1) download ERA5(-Land) climate reanalysis data for a user-specified
region, and time-period, (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. This R package provides a workflow for
implementation of state-of-the-art climate data into biological analyses while
avoiding issues of storage limitations at high temporal and spatial resolutions
by providing data according to user-needs rather than in global data sets.
Consequently, KrigR provides a toolbox to obtain a wide range of tailored
climate data at unprecedented combinations of high temporal and spatial
resolutions thus enabling the use of world-leading climate data in the
R-environment.
