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WQM  

Wavelet-Based Quantile Mapping for Postprocessing Numerical Weather Predictions
View on CRAN: Click here


Download and install WQM package within the R console
Install from CRAN:
install.packages("WQM")

Install from Github:
library("remotes")
install_github("cran/WQM")

Install by package version:
library("remotes")
install_version("WQM", "0.1.4")



Attach the package and use:
library("WQM")
Maintained by
Ze Jiang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-10-11
Latest Update: 2024-10-11
Description:
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.
How to cite:
Ze Jiang (2024). WQM: Wavelet-Based Quantile Mapping for Postprocessing Numerical Weather Predictions. R package version 0.1.4, https://cran.r-project.org/web/packages/WQM. Accessed 07 Mar. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited WQM R package
View WQM citation profile
Other R packages that WQM depends, imports, suggests or enhances
Complete documentation for WQM
Functions, R codes and Examples using the WQM R package
Full WQM package functions and examples
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