Articles | Volume 12, issue 8
Geosci. Model Dev., 12, 3419–3438, 2019
https://doi.org/10.5194/gmd-12-3419-2019
Geosci. Model Dev., 12, 3419–3438, 2019
https://doi.org/10.5194/gmd-12-3419-2019

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 et al.

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

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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).