ensbiascoR: Ensemble Resampling Bias Correction

An R package to resample or constrain large model ensemble to preserve physical aspects of the model simulations.

Contents

Introduction

Resampling initial condition or multi-model climate ensemble simulations offers a complementary methodology to traditional bias correction by retaining physical aspects of the original model simulations. The R-package “ensbiascoR” offers tools and examples, including data, to do so.

Related papers:

Sippel, S., Otto, F. E. L., Forkel, M., Allen, M. R., Guillod, B. P., Heimann, M., Reichstein, M., Seneviratne, S. I., Thonicke, K. & Mahecha, M. D. (2016) A novel bias correction methodology for climate impact simulations. Earth System Dynamics, 7, 71-88. doi:10.5194/esd-7-71-2016.

Installation and Usage

To install the most recent version of ensbiascor in R:
install.packages(“ensbiascor”, repos=“http://R-Forge.R-project.org”)

If you use ensbiascor in scientific publications, please cite:
Sippel, S., Otto, F. E. L., Forkel, M., Allen, M. R., Guillod, B. P., Heimann, M., Reichstein, M., Seneviratne, S. I., Thonicke, K. & Mahecha, M. D. (2016) A novel bias correction methodology for climate impact simulations. Earth System Dynamics, 7, 71-88. doi:10.5194/esd-7-71-2016.

The package has been developed at the Max Planck Institute for Biogeochemistry, Jena, Germany.

Author details and further information:

Sebastian Sippel (ssippel@bgc-jena.mpg.de)
For news and further information check my personal page: here.