A tool to create hydroclimate scenarios, stress test systems and visualize system performance in scenario-neutral climate change impact assessments. Scenario-neutral approaches 'stress-test' the performance of a modelled system by applying a wide range of plausible hydroclimate conditions (see Brown & Wilby (2012) <doi:10.1029/2012EO410001> and Prudhomme et al. (2010) <doi:10.1016/j.jhydrol.2010.06.043>). These approaches allow the identification of hydroclimatic variables that affect the vulnerability of a system to hydroclimate variation and change. This tool enables the generation of perturbed time series using a range of approaches including simple scaling of observed time series (e.g. Culley et al. (2016) <doi:10.1002/2015WR018253>) and stochastic simulation of perturbed time series via an inverse approach (see Guo et al. (2018) <doi:10.1016/j.jhydrol.2016.03.025>). It incorporates 'Richardson-type' weather generator model configurations documented in Richardson (1981) <doi:10.1029/WR017i001p00182>, Richardson and Wright (1984), as well as latent variable type model configurations documented in Bennett et al. (2018) <doi:10.1016/j.jhydrol.2016.12.043>, Rasmussen (2013) <doi:10.1002/wrcr.20164>, Bennett et al. (2019) <doi:10.5194/hess-23-4783-2019> to generate hydroclimate variables on a daily basis (e.g. precipitation, temperature, potential evapotranspiration) and allows a variety of different hydroclimate variable properties, herein called attributes, to be perturbed. Options are included for the easy integration of existing system models both internally in R and externally for seamless 'stress-testing'. A suite of visualization options for the results of a scenario-neutral analysis (e.g. plotting performance spaces and overlaying climate projection information) are also included. Version 1.0 of this package is described in Bennett et al. (2021) <doi:10.1016/j.envsoft.2021.104999>. As further developments in scenario-neutral approaches occur the tool will be updated to incorporate these advances.
Version: 1.2.0 Depends: R (≥ 3.5.0), GA (≥ 3.0.2) Imports: ggplot2 (≥ 3.3.0), directlabels, cowplot, stats, graphics, grDevices, utils, moments, jsonlite, progress, rcorpora, scales, viridisLite, fields, rlang, lattice, mvtnorm, Matrix, SoilHyP, cmaes, dfoptim, RGN LinkingTo: Rcpp Suggests: knitr (≥ 1.8), rmarkdown (≥ 1.18), testthat, evd Published: 2023-10-19 DOI: 10.32614/CRAN.package.foreSIGHT Author: Bree Bennett [aut], Sam Culley [aut], Anjana Devanand [aut], David McInerney [aut, cre], Seth Westra [aut], Danlu Guo [ctb], Holger Maier [ths] Maintainer: David McInerney <david.mcinerney at adelaide.edu.au> BugReports: https://github.com/ClimateAnalytics/foreSIGHT/issues License: GPL-3 NeedsCompilation: yes Materials: NEWS CRAN checks: foreSIGHT results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=foreSIGHT to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4