RankHist

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.

Ze Jiang

Wavelet-Based Quantile Mapping for Postprocessing Numerical
Weather Predictions

Fiona Johnson

RankHist function

<dl><dt>forecasts</dt>
<dd>A matrix of ensemble forecasts, in which the rows corresponds to locations and times and the columns correspond to the individual ensemble members.</dd>
<dt>observations</dt>
<dd>A vector of observations corresponding to the locations and times of the forecasts.</dd>
<dt>do.plot</dt>
<dd>Logical value of plot.</dd></dl>

Arguments

Verification Rank and Histogram — RankHist

<dl>

<dt>forecasts</dt>
<dd>A matrix of ensemble forecasts, in which the rows corresponds to locations and times and the columns correspond to the individual ensemble members.</dd>


<dt>observations</dt>
<dd>A vector of observations corresponding to the locations and times of the forecasts.</dd>


<dt>do.plot</dt>
<dd>Logical value of plot.</dd>

</dl>

RankHist: Verification Rank and Histogram

Description

Usage

Value

Arguments

References