SynoptReg: An R package for computing a synoptic climate classification and a spatial regionalization of environmental data. (August 2019)

• Record Type: Journal Article
• Authors: Lemus-Canovas, Marc; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Royé, Dominic
• Is Part Of: Environmental modelling & software. Volume 118(2019)
• Page Start: 114
• Page End: 119
• Publication Date: 2019-08
• Subjects: Alps -- Environmental regionalization -- R package -- synoptReg -- Synoptic classification; 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.2019.04.006
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Spatial knowledge of the climatic or environmental variables associated with the most frequent circulation types is essential with regard to developing strategies to address the risk of avalanches, floods, soil erosion, air pollution or other natural hazards. In order to derive an environmental regionalization, we present an Open Source R package known as synoptReg, which combines the spatialization of environmental variables based on the atmospheric circulation types. The synoptReg package contains a set of functions which we will employ (1) to perform a PCA-based synoptic classification using an atmospheric variable; (2) to map the spatial distribution of the selected environmental variable based upon the circulation types; (3) to develop a spatial environmental regionalization based on the previous results. We illustrate the usefulness of the package for a case study in the Alps area. Highlights: We present an open source R package to regionalize environmental gridded data The package allows to compute a weather type classification An environmental variable is mapped based on the circulation types We conducted a spatial regionalization based on the previous environmental maps