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) .


rSQM

The goal of rSQM is to 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) "Climate Change Impacts on Agricultural Drought with Consideration of Uncertainty in CMIP5 Scenarios".

Example

Run function 'rSQMSampleProject()' and see what happens. And reading vignette is also recommanded.

News

rSQM 1.3.13

fixed some minor bugs, enriched vignette

Reference manual

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install.packages("rSQM")

1.3.14 by Wonil Cho, a year ago


Browse source code at https://github.com/cran/rSQM


Authors: Jaepil Cho [aut] , Wonil Cho [aut, cre] , Imgook Jung [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports ncdf4, zoo, stringr, EcoHydRology, dplyr, gsubfn, yaml, mise, reshape2, qmap, ggplot2

Suggests knitr, rmarkdown, testthat


See at CRAN