Articles | Volume 10, issue 1
https://doi.org/10.5194/esd-10-31-2019
https://doi.org/10.5194/esd-10-31-2019
Research article
 | 
07 Jan 2019
Research article |  | 07 Jan 2019

The effect of univariate bias adjustment on multivariate hazard estimates

Jakob Zscheischler, Erich M. Fischer, and Stefan Lange

Related authors

The perfect storm? Co-occurring climate extremes in East Africa
Derrick Muheki, Axel A. J. Deijns, Emanuele Bevacqua, Gabriele Messori, Jakob Zscheischler, and Wim Thiery
Earth Syst. Dynam., 15, 429–466, https://doi.org/10.5194/esd-15-429-2024,https://doi.org/10.5194/esd-15-429-2024, 2024
Short summary
Technical Note: The Divide and Measure Nonconformity
Daniel Klotz, Martin Gauch, Frederik Kratzert, Grey Nearing, and Jakob Zscheischler
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-59,https://doi.org/10.5194/hess-2024-59, 2024
Preprint under review for HESS
Short summary
An increase in the spatial extent of European floods over the last 70 years
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
EGUsphere, https://doi.org/10.5194/egusphere-2023-2890,https://doi.org/10.5194/egusphere-2023-2890, 2024
Short summary
River flooding mechanisms and their changes in Europe revealed by explainable machine learning
Shijie Jiang, Emanuele Bevacqua, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 26, 6339–6359, https://doi.org/10.5194/hess-26-6339-2022,https://doi.org/10.5194/hess-26-6339-2022, 2022
Short summary
Hotspots and drivers of compound marine heatwaves and low net primary production extremes
Natacha Le Grix, Jakob Zscheischler, Keith B. Rodgers, Ryohei Yamaguchi, and Thomas L. Frölicher
Biogeosciences, 19, 5807–5835, https://doi.org/10.5194/bg-19-5807-2022,https://doi.org/10.5194/bg-19-5807-2022, 2022
Short summary

Related subject area

Dynamics of the Earth system: models
Stable stadial and interstadial states of the last glacial's climate identified in a combined stable water isotope and dust record from Greenland
Keno Riechers, Leonardo Rydin Gorjão, Forough Hassanibesheli, Pedro G. Lind, Dirk Witthaut, and Niklas Boers
Earth Syst. Dynam., 14, 593–607, https://doi.org/10.5194/esd-14-593-2023,https://doi.org/10.5194/esd-14-593-2023, 2023
Short summary
The modelled climatic response to the 18.6-year lunar nodal cycle and its role in decadal temperature trends
Manoj Joshi, Robert A. Hall, David P. Stevens, and Ed Hawkins
Earth Syst. Dynam., 14, 443–455, https://doi.org/10.5194/esd-14-443-2023,https://doi.org/10.5194/esd-14-443-2023, 2023
Short summary
The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences
Nicola Maher, Robert C. Jnglin Wills, Pedro DiNezio, Jeremy Klavans, Sebastian Milinski, Sara C. Sanchez, Samantha Stevenson, Malte F. Stuecker, and Xian Wu
Earth Syst. Dynam., 14, 413–431, https://doi.org/10.5194/esd-14-413-2023,https://doi.org/10.5194/esd-14-413-2023, 2023
Short summary
Regime-oriented causal model evaluation of Atlantic–Pacific teleconnections in CMIP6
Soufiane Karmouche, Evgenia Galytska, Jakob Runge, Gerald A. Meehl, Adam S. Phillips, Katja Weigel, and Veronika Eyring
Earth Syst. Dynam., 14, 309–344, https://doi.org/10.5194/esd-14-309-2023,https://doi.org/10.5194/esd-14-309-2023, 2023
Short summary
Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System
Elias C. Massoud, Lauren Andrews, Rolf Reichle, Andrea Molod, Jongmin Park, Sophie Ruehr, and Manuela Girotto
Earth Syst. Dynam., 14, 147–171, https://doi.org/10.5194/esd-14-147-2023,https://doi.org/10.5194/esd-14-147-2023, 2023
Short summary

Cited articles

Addor, N. and Fischer, E. M.: The influence of natural variability and interpolation errors on bias characterization in RCM simulations, J. Geophys. Res.-Atmos., 120, 10180–10195, https://doi.org/10.1002/2014JD022824, 2015. a, b, c
Bosshard, T., Carambia, M., Goergen, K., Kotlarski, S., Krahe, P., Zappa, M., and Schär, C.: Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections, Water Resour. Res., 49, 1523–1536, https://doi.org/10.1029/2011WR011533, 2013. a
Brando, P. M., Balch, J. K., Nepstad, D. C., Morton, D. C., Putz, F. E., Coe, M. T., Silvério, D., Macedo, M. N., Davidson, E. A., Nóbrega, C. C., Alencar, A., and Soares-Filho, B. S.: Abrupt increases in Amazonian tree mortality due to drought–fire interactions, P. Natl. Acad. Sci. USA, 111, 6347–6352, 2014. a
Bröde, P., Blazejczyk, K., Fiala, D., Havenith, G., Holmér, I., Jendritzky, G., Kuklane, K., and Kampmann, B.: The Universal Thermal Climate Index UTCI Compared to Ergonomics Standards for Assessing the Thermal Environment, Ind. Health, 51, 16–24, https://doi.org/10.2486/indhealth.2012-0098, 2013. a
Cannon, A. J.: Multivariate Bias Correction of Climate Model Output: Matching Marginal Distributions and Intervariable Dependence Structure, J. Climate, 29, 7045–7064, https://doi.org/10.1175/jcli-d-15-0679.1, 2016. a
Download
Short summary
Many climate models have biases in different variables throughout the world. Adjusting these biases is necessary for estimating climate impacts. Here we demonstrate that widely used univariate bias adjustment methods do not work well for multivariate impacts. We illustrate this problem using fire risk and heat stress as impact indicators. Using an approach that adjusts not only biases in the individual climate variables but also biases in the correlation between them can resolve these problems.
Altmetrics
Final-revised paper
Preprint