rSQM: Statistical Downscaling Toolkit for Climate Change Scenario using Non Parametric Quantile Mapping

Conducts statistical downscaling of daily CMIP5 (Coupled Model Intercomparison Project 5) climate change scenario data at a station level using empirical quantile mapping method by Jaepil Cho et al. (2016) <doi:10.1002/ird.2035>.

Version: 1.3.14
Depends: R (≥ 3.3.0)
Imports: ncdf4, zoo, stringr, EcoHydRology, dplyr, gsubfn, yaml, mise, reshape2, qmap, ggplot2
Suggests: knitr, rmarkdown, testthat
Published: 2018-01-12
Author: Jaepil Cho [aut], Wonil Cho [aut, cre], Imgook Jung [aut]
Maintainer: Wonil Cho <climate.service at apcc21.org>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README NEWS
CRAN checks: rSQM results

Downloads:

Reference manual: rSQM.pdf
Vignettes: rSQM workflow
Package source: rSQM_1.3.14.tar.gz
Windows binaries: r-devel: rSQM_1.3.14.zip, r-release: rSQM_1.3.14.zip, r-oldrel: rSQM_1.3.14.zip
macOS binaries: r-release: rSQM_1.3.14.tgz, r-oldrel: rSQM_1.3.14.tgz
Old sources: rSQM archive

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