WQM: Wavelet-Based Quantile Mapping for Postprocessing Numerical Weather Predictions

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.

Version:	0.1.4
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
Published:	2024-10-11
DOI:	10.32614/CRAN.package.WQM
Author:	Ze Jiang [aut, cre], Fiona Johnson [aut]
Maintainer:	Ze Jiang <ze.jiang at unsw.edu.au>
License:	GPL (≥ 3)
NeedsCompilation:	no
Materials:	README
CRAN checks:	WQM results

Documentation:

Reference manual:	WQM.pdf
Vignettes:	WQM (source, R code)

Downloads:

Package source:	WQM_0.1.4.tar.gz
Windows binaries:	r-devel: WQM_0.1.4.zip, r-release: WQM_0.1.4.zip, r-oldrel: WQM_0.1.4.zip
macOS binaries:	r-release (arm64): WQM_0.1.4.tgz, r-oldrel (arm64): WQM_0.1.4.tgz, r-release (x86_64): WQM_0.1.4.tgz, r-oldrel (x86_64): WQM_0.1.4.tgz

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