Articles | Volume 23, issue 3
https://doi.org/10.5194/hess-23-1741-2019
https://doi.org/10.5194/hess-23-1741-2019
Technical note
 | 
27 Mar 2019
Technical note |  | 27 Mar 2019

Technical note: Changes in cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers

Jan Hnilica, Martin Hanel, and Vladimír Puš

Related authors

Technical note: Changes of cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers
Jan Hnilica, Martin Hanel, and Vladimír Puš
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-7,https://doi.org/10.5194/hess-2018-7, 2018
Manuscript not accepted for further review
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024,https://doi.org/10.5194/hess-28-3777-2024, 2024
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
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024,https://doi.org/10.5194/hess-28-3755-2024, 2024
Short summary
140-year daily ensemble streamflow reconstructions over 661 catchments in France
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024,https://doi.org/10.5194/hess-28-3457-2024, 2024
Short summary
The agricultural expansion in South America's Dry Chaco: regional hydroclimate effects
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024,https://doi.org/10.5194/hess-28-3281-2024, 2024
Short summary
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024,https://doi.org/10.5194/hess-28-3305-2024, 2024
Short summary

Cited articles

Bárdossy, A. and Pegram, G.: Multiscale spatial recorrelation of RCM precipitation to produce unbiased climate change scenarios over large areas and small, Water Resour. Res., 48, W09502, https://doi.org/10.1029/2011WR011524, 2012. 
Chen, J., Brissette, F. P., and Lucas-Picher, P.: Assessing the limits of bias-correcting climate model outputs for climate change impact studies, J. Geophys. Res.-Atmos., 120, 1123–1136, https://doi.org/10.1002/2014JD022635, 2015. 
Davison, A. C. and Hinkley, D. V.: Bootstrap methods and their application, Cambridge University Press, Cambridge, United Kingdom, 1997. 
Déqué, M.: Frequency of precipitation and temperature extremes over France in an anthropogenic scenario: Model results and statistical correction according to observed values, Global Planet. Change, 57, 16–26, https://doi.org/10.1016/j.gloplacha.2006.11.030, 2007. 
Ehret, U., Zehe, E., Wulfmeyer, V., Warrach-Sagi, K., and Liebert, J.: HESS Opinions “Should we apply bias correction to global and regional climate model data?”, Hydrol. Earth Syst. Sci., 16, 3391–3404, https://doi.org/10.5194/hess-16-3391-2012, 2012. 
Download
Short summary
A statistical significance of changes in correlations of daily precipitation in six RCM simulations is assessed. The effect of outliers is explored and a concept of dependence outliers is presented. We show that correlation estimates can be strongly affected by a few outliers; therefore any statistical correction relying on sample correlation can provide misleading results. An exploratory procedure is proposed to detect and evaluate the dependence outliers in multivariate data.