Climate projections of a multivariate heat stress index: the role of downscaling and bias correction

Casanueva, Ana; Kotlarski, Sven; Herrera, Sixto; Fischer, Andreas M.; Kjellstrom, Tord; Schwierz, Cornelia

doi:https://doi.org/10.5194/gmd-12-3419-2019

Articles | Volume 12, issue 8

https://doi.org/10.5194/gmd-12-3419-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-12-3419-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 8

Model evaluation paper

|

05 Aug 2019

Model evaluation paper |

| 05 Aug 2019

Climate projections of a multivariate heat stress index: the role of downscaling and bias correction

Ana Casanueva, Sven Kotlarski, Sixto Herrera, Andreas M. Fischer, Tord Kjellstrom, and Cornelia Schwierz

Supplement

https://doi.org/10.5194/gmd-12-3419-2019-supplement

Model code and software

HeatStress A. Casanueva https://doi.org/10.5281/zenodo.3264930

plotFun A. Casanueva https://doi.org/10.5281/zenodo.3265025

qmCH2018 S. Kotlarski, J. Rajczak, and I. Feigenwinter https://doi.org/10.5281/zenodo.3275571

climate4R M. Iturbide, J. Bedia, S. Herrera, J. Baño-Medina, J. Fernández, M. D. Frías, R. Manzanas, D. San-Martín, E. Cimadevilla, A. S. Cofiño, and J. M. Gutiérrez https://doi.org/10.1016/j.envsoft.2018.09.009

Short summary

Given the large number of available data sets and products currently produced for climate impact studies, it is challenging to distil the most accurate and useful information for climate services. This work presents a comparison of methods widely used to generate climate projections, from different sources and at different spatial resolutions, in order to assess the role of downscaling and statistical post-processing (bias correction).