Articles | Volume 22, issue 6
https://doi.org/10.5194/nhess-22-2117-2022
https://doi.org/10.5194/nhess-22-2117-2022
Research article
 | 
23 Jun 2022
Research article |  | 23 Jun 2022

Quantification of meteorological conditions for rockfall triggers in Germany

Katrin M. Nissen, Stefan Rupp, Thomas M. Kreuzer, Björn Guse, Bodo Damm, and Uwe Ulbrich

Related authors

A non-stationary climate-informed weather generator for assessing future flood risks
Viet Dung Nguyen, Sergiy Vorogushyn, Katrin Nissen, Lukas Brunner, and Bruno Merz
Adv. Stat. Clim. Meteorol. Oceanogr., 10, 195–216, https://doi.org/10.5194/ascmo-10-195-2024,https://doi.org/10.5194/ascmo-10-195-2024, 2024
Short summary
Compound events in Germany in 2018: drivers and case studies
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim Pinto, Markus Augenstein, Ting-Chen Chen, Hendrik Feldmann, Petra Friederichs, Daniel Gliksman, Laura Goulier, Karsten Haustein, Jens Heinke, Lisa Jach, Florian Knutzen, Stefan Kollet, Jürg Luterbacher, Niklas Luther, Susanna Mohr, Christoph Mudersbach, Christoph Müller, Efi Rousi, Felix Simon, Laura Suarez-Gutierrez, Svenja Szemkus, Sara M. Vallejo-Bernal, Odysseas Vlachopoulos, and Frederik Wolf
EGUsphere, https://doi.org/10.5194/egusphere-2023-1460,https://doi.org/10.5194/egusphere-2023-1460, 2023
Short summary
A decrease in rockfall probability under climate change conditions in Germany
Katrin M. Nissen, Martina Wilde, Thomas M. Kreuzer, Annika Wohlers, Bodo Damm, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 23, 2737–2748, https://doi.org/10.5194/nhess-23-2737-2023,https://doi.org/10.5194/nhess-23-2737-2023, 2023
Short summary
More than heavy rain turning into fast-flowing water – a landscape perspective on the 2021 Eifel floods
Michael Dietze, Rainer Bell, Ugur Ozturk, Kristen L. Cook, Christoff Andermann, Alexander R. Beer, Bodo Damm, Ana Lucia, Felix S. Fauer, Katrin M. Nissen, Tobias Sieg, and Annegret H. Thieken
Nat. Hazards Earth Syst. Sci., 22, 1845–1856, https://doi.org/10.5194/nhess-22-1845-2022,https://doi.org/10.5194/nhess-22-1845-2022, 2022
Short summary
Increasing frequencies and changing characteristics of heavy precipitation events threatening infrastructure in Europe under climate change
Katrin M. Nissen and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 17, 1177–1190, https://doi.org/10.5194/nhess-17-1177-2017,https://doi.org/10.5194/nhess-17-1177-2017, 2017
Short summary

Related subject area

Landslides and Debris Flows Hazards
Optimizing rainfall-triggered landslide thresholds for daily landslide hazard warning in the Three Gorges Reservoir area
Bo Peng and Xueling Wu
Nat. Hazards Earth Syst. Sci., 24, 3991–4013, https://doi.org/10.5194/nhess-24-3991-2024,https://doi.org/10.5194/nhess-24-3991-2024, 2024
Short summary
Brief communication: Monitoring impending slope failure with very high-resolution spaceborne synthetic aperture radar
Andrea Manconi, Yves Bühler, Andreas Stoffel, Johan Gaume, Qiaoping Zhang, and Valentyn Tolpekin
Nat. Hazards Earth Syst. Sci., 24, 3833–3839, https://doi.org/10.5194/nhess-24-3833-2024,https://doi.org/10.5194/nhess-24-3833-2024, 2024
Short summary
Size scaling of large landslides from incomplete inventories
Oliver Korup, Lisa V. Luna, and Joaquin V. Ferrer
Nat. Hazards Earth Syst. Sci., 24, 3815–3832, https://doi.org/10.5194/nhess-24-3815-2024,https://doi.org/10.5194/nhess-24-3815-2024, 2024
Short summary
InSAR-informed in situ monitoring for deep-seated landslides: insights from El Forn (Andorra)
Rachael Lau, Carolina Seguí, Tyler Waterman, Nathaniel Chaney, and Manolis Veveakis
Nat. Hazards Earth Syst. Sci., 24, 3651–3661, https://doi.org/10.5194/nhess-24-3651-2024,https://doi.org/10.5194/nhess-24-3651-2024, 2024
Short summary
A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence
Zhen Lei Wei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia
Nat. Hazards Earth Syst. Sci., 24, 3357–3379, https://doi.org/10.5194/nhess-24-3357-2024,https://doi.org/10.5194/nhess-24-3357-2024, 2024
Short summary

Cited articles

Akaike, H.: A new look at the statistical model identification, IEEE T. Automat. Contr., 19, 716–723, https://doi.org/10.1109/TAC.1974.1100705, 1974. a
Bajni, G., Camera, C. A. S., and Apuani, T.: Deciphering meteorological influencing factors for Alpine rockfalls: a case study in Aosta Valley, Landslides, 18, 3279–3298, https://doi.org/10.1007/s10346-021-01697-3, 2021. a, b, c
Benedetti, R.: Scoring Rules for Forecast Verification, Mon. Weather Rev., 138, 203–2011, https://doi.org/10.1175/2009MWR2945.1, 2010. a, b
Copernicus Land Monitoring Service: EU-DEM v1.1, Copernicus Programme [data set], https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1 (last access: 13 August 2021), 2016. a
Cornes, R., van der Schrier, G., van den Besselaar, E. J. M., and Jones, P. D.: Ensemble Version of the E-OBS Temperature and Precipitation Datasets, J. Geophys. Res.-Atmos, 123, 9391–9409, https://doi.org/10.1029/2017JD028200, 2018. a
Download
Short summary
A statistical model is introduced which quantifies the influence of individual potential triggering factors and their interactions on rockfall probability in central Europe. The most important factor is daily precipitation, which is most effective if sub-surface moisture levels are high. Freeze–thaw cycles in the preceding days can further increase the rockfall hazard. The model can be applied to climate simulations in order to investigate the effect of climate change on rockfall probability.
Altmetrics
Final-revised paper
Preprint