The main objective of the VALUE COST action is the validation and integration of downscaling methods for climate change research. To this aim, a number of indices and diagnostics have been identified in order to validate different aspects regarding the performance of the downscaling methods. These indices have been implemented in R by the VALUE cross-cutting group and are collected in this public package for further collaboration and extension with other initiatives, as well as research reproducibility.
The package includes R functions used to read the observational datasets (and output downscaled predictions) in VALUE data format as well as the auxiliary (and wrapper) functions used by the VALUE validation portal to compute these indices. The data structures are integrated with other climate data access and analysis tools namely loadeR, for local and remote data access (for instance to the Santander MetGroup User Data Gateway, UDG) and downscaleR, a R package for bias correction and statistical downscaling.
Gutiérrez, J.M., Maraun, D., Widmann, M. et al., 2018. An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment. International Journal of Climatology. https://doi.org/10.1002/joc.5462
A direct method for installing the most recent stable release requires the package devtools. Within R, just type:
devtools::install_github("SantanderMetGroup/VALUE")Alternatively, you can download the sources from the releases tab
Once installed, for a quick overview:
library(VALUE)
help(package="VALUE")For creating tickets please refer to these posting guidelines