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.
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.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
05 Aug 2019
Model evaluation paper |
| 05 Aug 2019
| 05 Aug 2019
Climate projections of a multivariate heat stress index: the role of downscaling and bias correction
Federal Office of Meteorology and Climatology MeteoSwiss, Zurich,
Switzerland
currently at: Meteorology Group, Dept. Applied Mathematics and
Computer Sciences, University of Cantabria, Santander, Spain
Sven Kotlarski
Federal Office of Meteorology and Climatology MeteoSwiss, Zurich,
Switzerland
Sixto Herrera
Meteorology Group, Dept. Applied Mathematics and Computer Sciences,
University of Cantabria, Santander, Spain
Andreas M. Fischer
Federal Office of Meteorology and Climatology MeteoSwiss, Zurich,
Switzerland
Tord Kjellstrom
Centre for Technological Research and Innovation (CETRI), Limmasol,
Cyprus
National Center for Epidemiology and Population Health, Australian National University, Canberra, Australia
Cornelia Schwierz
Federal Office of Meteorology and Climatology MeteoSwiss, Zurich,
Switzerland
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- Impact of climate change on potential evapotranspiration and crop water requirement in Upper Wabe Bridge watershed, Wabe Shebele River Basin, Ethiopia M. Gurara et al. 10.1016/j.jafrearsci.2021.104223
- Assessing future heat stress across China: combined effects of heat and relative humidity on mortality G. Zhang et al. 10.3389/fpubh.2023.1282497
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- High-Resolution Air Temperature Forecasts in Urban Areas: A Meteorological Perspective on Their Added Value S. Oswald et al. 10.3390/atmos15121544
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- Projections of future precipitation and air temperature over the Tibetan Plateau based on Coupled Model Intercomparison Project Phase 6 multimodel ensembles W. Zhang et al. 10.1002/joc.7865
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- Changes in the probability of temporally compound wet and dry events in a warmer world: case study in the Upper Jhelum Basin—South Asia R. Ansari et al. 10.1007/s10113-025-02367-z
- Avoidable heat-related mortality in China during the 21st century G. Zhang et al. 10.1038/s41612-023-00404-4
- A global high-resolution and bias-corrected dataset of CMIP6 projected heat stress metrics Q. Kong & M. Huber 10.1038/s41597-025-04527-6
- Underestimated increase and intensification of humid-heat extremes across southeast China due to humidity data inhomogeneity X. Li et al. 10.3389/fenvs.2022.1104039
- Spatiotemporal changes in population exposure to heat stress in South Asia A. Kyaw et al. 10.1016/j.scs.2023.104544
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Latest update: 31 Oct 2025
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).
Given the large number of available data sets and products currently produced for climate impact...
