The R-based climate4R open framework for reproducible climate data access and post-processing. (January 2019)

• Record Type: Journal Article
• Authors: 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.
• Is Part Of: Environmental modelling & software. Volume 111(2019)
• Page Start: 42
• Page End: 54
• Publication Date: 2019-01
• Subjects: Open science -- Climate indices -- CMIP5 -- Downscaling -- Climatic change -- NetCDF-java; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.09.009
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Climate-driven sectoral applications commonly require different types of climate data (e.g. observations, reanalysis, climate change projections) from different providers. Data access, harmonization and post-processing (e.g. bias correction) are time-consuming error-prone tasks requiring different specialized software tools at each stage of the data workflow, thus hindering reproducibility. Here we introduce climate4R, an R-based climate services oriented framework tailored to the needs of the vulnerability and impact assessment community that integrates in the same computing environment harmonized data access, post-processing, visualization and a provenance metadata model for traceability and reproducibility of results. climate4R allows accessing local and remote (OPeNDAP) data sources, such as the Santander User Data Gateway (UDG), a THREDDS-based service including a wide catalogue of popular datasets (e.g. ERA-Interim, CORDEX, etc.). This provides a unique comprehensive open framework for end-to-end sectoral reproducible applications. All the packages, data and documentation for reproducing the experiments in this paper are available from http://www.meteo.unican.es/climate4R . Highlights: climate4R is an R-based framework for accessing and post-processing climate data. Allows for advanced post-processing: bias correction and statistical downscaling. Envisaged as a data access layer for the User Data Gateway (UDG). Provides harmonized access to widely used public datasets (e.g. CORDEX) via UDG. climate4R favours end-to-end reproducibility of sectoral impact studies.