Articles | Volume 20, issue 11
Nat. Hazards Earth Syst. Sci., 20, 3057–3082, 2020
https://doi.org/10.5194/nhess-20-3057-2020

Special issue: Recent advances in drought and water scarcity monitoring,...

Nat. Hazards Earth Syst. Sci., 20, 3057–3082, 2020
https://doi.org/10.5194/nhess-20-3057-2020

Research article 14 Nov 2020

Research article | 14 Nov 2020

Evaluation of EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment for the Euro-Mediterranean area) historical simulations by high-quality observational datasets in southern Italy: insights on drought assessment

David J. Peres et al.

Related authors

Brief Communication: Key papers of 20 years in Natural Hazards and Earth System Sciences
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-321,https://doi.org/10.5194/nhess-2021-321, 2021
Preprint under review for NHESS
Short summary
Brief communication: Rainfall thresholds based on Artificial neural networks can improve landslide early warning
Pierpaolo Distefano, David J. Peres, Pietro Scandura, and Antonino Cancelliere
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-206,https://doi.org/10.5194/nhess-2021-206, 2021
Revised manuscript under review for NHESS
Short summary
Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds
David J. Peres, Antonino Cancelliere, Roberto Greco, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 18, 633–646, https://doi.org/10.5194/nhess-18-633-2018,https://doi.org/10.5194/nhess-18-633-2018, 2018
Short summary
Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach
D. J. Peres and A. Cancelliere
Hydrol. Earth Syst. Sci., 18, 4913–4931, https://doi.org/10.5194/hess-18-4913-2014,https://doi.org/10.5194/hess-18-4913-2014, 2014
Short summary

Related subject area

Hydrological Hazards
Modeling of a compound flood induced by the levee breach at Qianbujing Creek, Shanghai, during Typhoon Fitow
Yuhan Yang, Jie Yin, Weiguo Zhang, Yan Zhang, Yi Lu, Yufan Liu, Aoyue Xiao, Yunxiao Wang, and Wenming Song
Nat. Hazards Earth Syst. Sci., 21, 3563–3572, https://doi.org/10.5194/nhess-21-3563-2021,https://doi.org/10.5194/nhess-21-3563-2021, 2021
Short summary
Improving flood damage assessments in data-scarce areas by retrieval of building characteristics through UAV image segmentation and machine learning – a case study of the 2019 floods in southern Malawi
Lucas Wouters, Anaïs Couasnon, Marleen C. de Ruiter, Marc J. C. van den Homberg, Aklilu Teklesadik, and Hans de Moel
Nat. Hazards Earth Syst. Sci., 21, 3199–3218, https://doi.org/10.5194/nhess-21-3199-2021,https://doi.org/10.5194/nhess-21-3199-2021, 2021
Short summary
Assessment of direct economic losses of flood disasters based on spatial valuation of land use and quantification of vulnerabilities: a case study on the 2014 flood in Lishui city of China
Haixia Zhang, Weihua Fang, Hua Zhang, and Lu Yu
Nat. Hazards Earth Syst. Sci., 21, 3161–3174, https://doi.org/10.5194/nhess-21-3161-2021,https://doi.org/10.5194/nhess-21-3161-2021, 2021
Short summary
Evaluating integrated water management strategies to inform hydrological drought mitigation
Doris E. Wendt, John P. Bloomfield, Anne F. Van Loon, Margaret Garcia, Benedikt Heudorfer, Joshua Larsen, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 21, 3113–3139, https://doi.org/10.5194/nhess-21-3113-2021,https://doi.org/10.5194/nhess-21-3113-2021, 2021
Short summary
Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps?
Sara Lindersson, Luigia Brandimarte, Johanna Mård, and Giuliano Di Baldassarre
Nat. Hazards Earth Syst. Sci., 21, 2921–2948, https://doi.org/10.5194/nhess-21-2921-2021,https://doi.org/10.5194/nhess-21-2921-2021, 2021
Short summary

Cited articles

Adeniyi, M. O. and Dilau, K. A.: Assessing the link between Atlantic Niño 1 and drought over West Africa using CORDEX regional climate models, Theor. Appl. Climatol., 131, 937–949, https://doi.org/10.1007/s00704-016-2018-0, 2018. 
Arnell, N., Liu, C., Compagnucci, R., da Cunha, L., Hanaki, K., Howe, C., Mailu, G., Shiklomanov, I., Stakhiv, E., and Doll, P.: Hydrology and Water Resources, in: Climate Change2001: Impacts, Adaptation, and Vulnerability, edited by: McCarthy, J. J., Canziani, O. F., Leary, N. A., Dokken, D. J., and White, K. S., Cambridge University Press, Cambridge, UK, 192–234, 2001. 
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., Reinhardt, T., Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011. 
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013. 
Bonaccorso, B., Cancelliere, A., and Rossi, G.: An analytical formulation of return period of drought severity, Stoch. Environ. Res. Risk Assess., 17, 157–174, https://doi.org/10.1007/s00477-003-0127-7, 2003. 
Download
Short summary
Regional climate models (RCMs) are commonly used for high-resolution assessment of climate change impacts. This research assesses the reliability of several RCMs in a Mediterranean area (southern Italy), comparing historic climate and drought characteristics with high-density and high-quality ground-based observational datasets. We propose a general methodology and identify the more skilful models able to reproduce precipitation and temperature variability as well as drought characteristics.
Altmetrics
Final-revised paper
Preprint