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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.
Package details |
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| Author | Ze Jiang [aut, cre] (<https://orcid.org/0000-0002-3472-0829>), Fiona Johnson [aut] (<https://orcid.org/0000-0001-5708-1807>) |
| Maintainer | Ze Jiang <ze.jiang@unsw.edu.au> |
| License | GPL (>= 3) |
| Version | 0.1.4 |
| Package repository | View on CRAN |
| Installation |
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