climate4R is a bundle of R packages for transparent climate data access, post processing (including bias correction and downscaling) and visualization. Predictia has been involved in its development since an early stage, in collaboration with researchers from the Santander Meteorology Group (University of Cantabria-CSIC). climate4R builds on two main data structures (grid and station, including metadata) to deal with gridded and point data from observations, reanalysis, seasonal forecasts and climate projections. It considers ensemble members as a basic dimension of the data structures. Compatibility with some external packages has been achieved by wrapping packages, thus enhancing climate4R with new functionalities: extreme climate indices, etc. A number of datasets (observations, reanalysis, seasonal predictions and climate change projections) are used to provide worked-out illustrative examples. Moreover, climate4R is transparently (and remotely) connected to the User Data Gateway, UDG (a service from the Santander Climate Data Service), offering several state-of-the-art datasets for climate analysis.
A paper describing this R bundle is now available in the journal Environmental Modelling & Software.
Iturbide, M., Bedia, J., Herrera, S., Baño-Medina, J., Fernández, J., Frías, M.D., Manzanas, R., San-Martín, D., Cimadevilla, E., Cofiño, A.S., Gutiérrez, J.M., 2018. An R-based open framework for reproducible climate data access and post-processing. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2018.09.009