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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.

Versions across snapshots

VersionRepositoryFileSize
0.1.4 rolling linux/jammy R-4.5 WQM_0.1.4.tar.gz 1.1 MiB
0.1.4 rolling linux/noble R-4.5 WQM_0.1.4.tar.gz 1.1 MiB
0.1.4 rolling source/ R- WQM_0.1.4.tar.gz 893.6 KiB
0.1.4 latest linux/jammy R-4.5 WQM_0.1.4.tar.gz 1.1 MiB
0.1.4 latest linux/noble R-4.5 WQM_0.1.4.tar.gz 1.1 MiB
0.1.4 latest source/ R- WQM_0.1.4.tar.gz 893.6 KiB
0.1.4 2026-04-26 source/ R- WQM_0.1.4.tar.gz 893.6 KiB
0.1.4 2026-04-23 source/ R- WQM_0.1.4.tar.gz 893.6 KiB
0.1.4 2026-04-09 windows/windows R-4.5 WQM_0.1.4.zip 1.1 MiB
0.1.4 2025-04-20 source/ R- WQM_0.1.4.tar.gz 893.6 KiB

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