Wavelet-Based Quantile Mapping for Postprocessing Numerical Weather Predictions R package WQM version 0.1.4 The wavelet-based quantile mapping (WQM) technique is designed to correct biases in spatio-temporal precipitation forecasts across multiple time scales. The WQM method effectively enhances forecast accuracy by generating an ensemble of precipitation forecasts that account for uncertainties in the prediction process. For a comprehensive overview of the methodologies employed in this package, please refer to Jiang, Z., and Johnson, F. (2023) <doi:10.1029/2022EF003350>. The package relies on two packages for continuous wavelet transforms: 'WaveletComp', which can be installed automatically, and 'wmtsa', which is optional and available from the CRAN archive <https://cran.r-project.org/src/contrib/Archive/wmtsa/>. Users need to manually install 'wmtsa' from this archive if they prefer to use 'wmtsa' based decomposition. Software Depends: R (>= 3.5.0) Imports: MBC, WaveletComp, matrixStats, ggplot2 Suggests: stats, tidyr, dplyr, wmtsa, scales, data.table, graphics, testthat (>= 3.0.0), knitr, rmarkdown, bookdown Ze Jiang <ze.jiang@unsw.edu.au> Comprehensive R Archive Network (CRAN) Ze Jiang [aut, cre] (ORCID: <https://orcid.org/0000-0002-3472-0829>), Fiona Johnson [aut] (ORCID: <https://orcid.org/0000-0001-5708-1807>) GPL (>= 3) 2024-10-11 application/tgz https://CRAN.R-project.org/package=WQM doi:10.32614/CRAN.package.WQM