MarineTools.temporal: A Python package to simulate Earth and environmental time series. (April 2022)

• Record Type: Journal Article
• Authors: Cobos, M.; Otiñar, P.; Magaña, P.; Lira-Loarca, A.; Baquerizo, A.
• Is Part Of: Environmental modelling & software. Volume 150(2022)
• Publication Date: 2022-04
• Subjects: Time expansion of parameters -- Non-stationary probability models -- Stochastic characterization -- Environmental modelling; 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.2022.105359
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The assessment of the uncertainty about the evolution of complex processes usually requires different realizations consisting of multivariate temporal signals of environmental data. However, it is common to have only one observational set. MarineTools.temporal is an open-source Python package for the non-stationary parametric statistical analysis of vector random processes suitable for environmental and Earth modelling. It takes a single timeseries of observations and allows the simulation of many time series with the same probabilistic behavior. The software generalizes the use of piecewise and compound distributions with any number of arbitrary continuous distributions. The code contains, among others, multi-model negative log-likely functions, wrapped-normal distributions, and generalized Fourier timeseries expansion. Its programming philosophy significantly improves the computing time and makes it compatible with future extensions of scipy.stats. We apply it to the analysis of freshwater river discharge, water currents, and the simulation of ensemble projections of sea waves, to show its capabilities. Highlights: Scripts for compound and piecewise non-stationary probability models are coded into MarineTools.temporal . The tool provides application examples for precipitation, fresh-water discharge, water currents, wind field, number of sunspots and sea waves, among others. Statistically equivalent multivariate time series can be obtained for several climate, Earth or environmental processes.