Multivariate Bias Correction of Climate Model Outputs

Calibrate and apply multivariate bias correction algorithms for climate model simulations of multiple climate variables. Three methods described by Cannon (2016) and Cannon (2018) are implemented -- (i) MBC Pearson correlation (MBCp), (ii) MBC rank correlation (MBCr), and (iii) MBC N-dimensional PDF transform (MBCn) -- as is the Rank Resampling for Distributions and Dependences (R2D2) method. An additional multivariate rescaling method based on the linear Monge-Kantorovich map for Gaussian optimal transport of dependence structure is also included.


MBC

MBC is an R package for calibrating and applying univariate and multivariate bias correction algorithms for climate model simulations of multiple climate variables. This test build updates the package to version 0.10-8 and adds MRSmk(), a multivariate rescaling method based on the linear Monge--Kantorovich map for Gaussian optimal transport of dependence structure.

Reference manual

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install.packages("MBC")

0.10-8 by Alex J. Cannon, 4 months ago


Browse source code at https://github.com/cran/MBC


Authors: Alex J. Cannon [aut, cre] (ORCID:


Documentation:   PDF Manual  


GPL-2 license


Depends on Matrix, energy, FNN


Imported by WQM.


See at CRAN