MCQM

Three multivariate copula quantile mappings (MCQMs) and one-dimensional quantile mapping (QM) are used to predict bias-corrected values at unvisited locations. The MCQM_script.R in the scripts folder shows how to use the functions and implement MCQM using the example data.

The example_data.RData contains mean air temperature at one day obtained from weather stations and ERA-Interim data.

The packages sp, gstat, VineCopula, and copula are available on CRAN whereas the package spcopula on R-Forge.

New to copulas?

Please take a look at the post "Environmental processes are linked, but how?" An introduction to copulas.

References:

• Alidoost F., Stein A., Su Z, Sharifi, A. 2019. Multivariate copula quantile mapping for bias correction of reanalysis air temperature data. Journal of Spatial Science, https://doi.org/10.1080/14498596.2019.1601138.

• Alidoost, F., (2019), Copulas for integrating weather and land information in space and time (Doctoral), University of Twente.

How to contribute:

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If you would like to add your contributions, you can submit a pull request. Each pull request is reviewed at least by one reviewer.