Articles | Volume 23, issue 1
https://doi.org/10.5194/nhess-23-21-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-21-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Jan 2023
Research article |
| 11 Jan 2023
| 11 Jan 2023
Time of emergence of compound events: contribution of univariate and dependence properties
Bastien François
CORRESPONDING AUTHOR
Laboratoire des Sciences du Climat et l’Environnement (LSCE-IPSL) CNRS/CEA/UVSQ, UMR8212, Université Paris-Saclay, Gif-sur-Yvette, France
Mathieu Vrac
Laboratoire des Sciences du Climat et l’Environnement (LSCE-IPSL) CNRS/CEA/UVSQ, UMR8212, Université Paris-Saclay, Gif-sur-Yvette, France
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EGUsphere, https://doi.org/10.5194/egusphere-2024-2079, https://doi.org/10.5194/egusphere-2024-2079, 2024
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Spatially compounding wind and precipitation (CWP) extremes can lead to severe impacts on society. We find that concurrent climate variability modes favor the occurrence of such wintertime spatially compounding events in the Northern Hemisphere, and can even amplify the number of regions and population exposed. Our analysis highlights the importance of considering the interplay between variability modes to improve risk management of such spatially compounding events.
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Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
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Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
Bastien François, Mathieu Vrac, Alex J. Cannon, Yoann Robin, and Denis Allard
Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, https://doi.org/10.5194/esd-11-537-2020, 2020
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Recently, multivariate bias correction (MBC) methods designed to adjust climate simulations have been proposed. However, they use different approaches, leading potentially to different results. Therefore, this study intends to intercompare four existing MBC methods to provide end users with aid in choosing such methods for their applications. To do so, a wide range of evaluation criteria have been used to assess the ability of MBC methods to correct statistical properties of climate models.
Bastien François, Khalil Teber, Lou Brett, Richard Leeding, Luis Gimeno-Sotelo, Daniela I. V. Domeisen, Laura Suarez-Gutierrez, and Emanuele Bevacqua
EGUsphere, https://doi.org/10.5194/egusphere-2024-2079, https://doi.org/10.5194/egusphere-2024-2079, 2024
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Spatially compounding wind and precipitation (CWP) extremes can lead to severe impacts on society. We find that concurrent climate variability modes favor the occurrence of such wintertime spatially compounding events in the Northern Hemisphere, and can even amplify the number of regions and population exposed. Our analysis highlights the importance of considering the interplay between variability modes to improve risk management of such spatially compounding events.
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, Gianmarco Mengaldo, and Robert Vautard
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We introduce ClimaMeter, a tool offering real-time insights into extreme-weather events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analysed two distinct events, showcasing ClimaMeter's global relevance.
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Earth Syst. Dynam., 15, 735–762, https://doi.org/10.5194/esd-15-735-2024, https://doi.org/10.5194/esd-15-735-2024, 2024
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We aim to combine multiple global climate models (GCMs) to enhance the robustness of future projections. We introduce a novel approach, called "α pooling", aggregating the cumulative distribution functions (CDFs) of the models into a CDF more aligned with historical data. The new CDFs allow us to perform bias adjustment of all the raw climate simulations at once. Experiments with European temperature and precipitation demonstrate the superiority of this approach over conventional techniques.
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Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
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Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
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Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022, https://doi.org/10.5194/hess-26-1481-2022, 2022
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Revised manuscript not accepted
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Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
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Claire Waelbroeck, Sylvain Pichat, Evelyn Böhm, Bryan C. Lougheed, Davide Faranda, Mathieu Vrac, Lise Missiaen, Natalia Vazquez Riveiros, Pierre Burckel, Jörg Lippold, Helge W. Arz, Trond Dokken, François Thil, and Arnaud Dapoigny
Clim. Past, 14, 1315–1330, https://doi.org/10.5194/cp-14-1315-2018, https://doi.org/10.5194/cp-14-1315-2018, 2018
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Guillaume Latombe, Ariane Burke, Mathieu Vrac, Guillaume Levavasseur, Christophe Dumas, Masa Kageyama, and Gilles Ramstein
Geosci. Model Dev., 11, 2563–2579, https://doi.org/10.5194/gmd-11-2563-2018, https://doi.org/10.5194/gmd-11-2563-2018, 2018
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Mathieu Vrac
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Adjoua Moise Famien, Serge Janicot, Abe Delfin Ochou, Mathieu Vrac, Dimitri Defrance, Benjamin Sultan, and Thomas Noël
Earth Syst. Dynam., 9, 313–338, https://doi.org/10.5194/esd-9-313-2018, https://doi.org/10.5194/esd-9-313-2018, 2018
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This study uses the cumulative distribution function transform (CDF-t) method to provide bias-corrected data over Africa using WFDEI as a reference dataset. It is shown that CDF-t is very effective in removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets, particularly for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields.
Emanuele Bevacqua, Douglas Maraun, Ingrid Hobæk Haff, Martin Widmann, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, https://doi.org/10.5194/hess-21-2701-2017, 2017
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We develop a conceptual model to quantify the risk of compound events (CEs), i.e. extreme impacts to society which are driven by statistically dependent climatic variables. Based on this model we study compound floods, i.e. joint storm surge and high river level, in Ravenna (Italy). The model includes meteorological predictors which (1) provide insight into the physical processes underlying CEs, as well as into the temporal variability, and (2) allow us to statistically downscale CEs.
Pascal Yiou, Aglaé Jézéquel, Philippe Naveau, Frederike E. L. Otto, Robert Vautard, and Mathieu Vrac
Adv. Stat. Clim. Meteorol. Oceanogr., 3, 17–31, https://doi.org/10.5194/ascmo-3-17-2017, https://doi.org/10.5194/ascmo-3-17-2017, 2017
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The attribution of classes of extreme events, such as heavy precipitation or heatwaves, relies on the estimate of small probabilities (with and without climate change). Such events are connected to the large-scale atmospheric circulation. This paper links such probabilities with properties of the atmospheric circulation by using a Bayesian decomposition. We test this decomposition on a case of extreme precipitation in the UK, in January 2014.
Claudia Volosciuk, Douglas Maraun, Mathieu Vrac, and Martin Widmann
Hydrol. Earth Syst. Sci., 21, 1693–1719, https://doi.org/10.5194/hess-21-1693-2017, https://doi.org/10.5194/hess-21-1693-2017, 2017
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For impact modeling, infrastructure design, or adaptation strategy planning, high-quality climate data on the point scale are often demanded. Due to the scale gap between gridbox and point scale and biases in climate models, we combine a statistical bias correction and a stochastic downscaling model and apply it to climate model-simulated precipitation. The method performs better in summer than in winter and in winter best for mild winter climate (Mediterranean) and worst for continental winter.
Jérôme Pernin, Mathieu Vrac, Cyril Crevoisier, and Alain Chédin
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 115–136, https://doi.org/10.5194/ascmo-2-115-2016, https://doi.org/10.5194/ascmo-2-115-2016, 2016
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Here, we propose a classification methodology of various space-time atmospheric datasets into discrete air mass groups homogeneous in temperature and humidity through a probabilistic point of view: both the classification process and the data are probabilistic. Unlike conventional classification algorithms, this methodology provides the probability of belonging to each class as well as the corresponding uncertainty, which can be used in various applications.
Benjamin Grouillet, Denis Ruelland, Pradeebane Vaittinada Ayar, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 20, 1031–1047, https://doi.org/10.5194/hess-20-1031-2016, https://doi.org/10.5194/hess-20-1031-2016, 2016
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This original paper provides a guideline to select statistical downscaling methods (SDMs) in climate change impact studies (CCIS) to minimize uncertainty from downscaling. Three SDMs were applied to NCEP reanalysis and 2 GCM data values. We then analyzed the sensitivity of the hydrological model to the various downscaled data via 5 hydrological indicators representing the main features of the hydrograph. Our results enable selection of the appropriate SDMs to be used to build climate scenarios.
P. Yiou, M. Boichu, R. Vautard, M. Vrac, S. Jourdain, E. Garnier, F. Fluteau, and L. Menut
Clim. Past, 10, 797–809, https://doi.org/10.5194/cp-10-797-2014, https://doi.org/10.5194/cp-10-797-2014, 2014
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The study presents an open-source model to determine the occurrence of hail damage to field crops and grapevines after hailstorms in Switzerland based on radar, agricultural land use data, and insurance damage reports. The model performs best at 8 km resolution for field crops and 1 km for grapevine and in the main production areas. Highlighting performance trade-offs and the relevance of user needs, the study is a first step towards the assessment of risk and damage for crops in Switzerland.
Dieter Roel Poelman, Hannes Kohlmann, and Wolfgang Schulz
Nat. Hazards Earth Syst. Sci., 24, 2511–2522, https://doi.org/10.5194/nhess-24-2511-2024, https://doi.org/10.5194/nhess-24-2511-2024, 2024
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EUCLID's lightning data unveil distinctive ground strike point (GSP) patterns in Europe. Over seas, GSPs per flash surpass inland, reaching a minimum in the Alps. Mountainous areas like the Alps and Pyrenees have the closest GSP separation, highlighting terrain elevation's impact. The daily peak current correlates with average GSPs per flash. These findings could significantly influence lightning protection measures, urging a focus on GSP density rather than flash density for risk assessment.
Nicola Loglisci, Giorgio Boni, Arianna Cauteruccio, Francesco Faccini, Massimo Milelli, Guido Paliaga, and Antonio Parodi
Nat. Hazards Earth Syst. Sci., 24, 2495–2510, https://doi.org/10.5194/nhess-24-2495-2024, https://doi.org/10.5194/nhess-24-2495-2024, 2024
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We analyse the meteo-hydrological features of the 27 and 28 August 2023 event that occurred in Genoa. Rainfall observations were made using rain gauge networks based on either official networks or citizen science networks. The merged analysis stresses the spatial variability in the precipitation, which cannot be captured by the current spatial density of authoritative stations. Results show that at minimal distances the variations in cumulated rainfall over a sub-hourly duration are significant.
Ellina Agayar, Franziska Aemisegger, Moshe Armon, Alexander Scherrmann, and Heini Wernli
Nat. Hazards Earth Syst. Sci., 24, 2441–2459, https://doi.org/10.5194/nhess-24-2441-2024, https://doi.org/10.5194/nhess-24-2441-2024, 2024
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This study presents the results of a climatological investigation of extreme precipitation events (EPEs) in Ukraine for the period 1979–2019. During all seasons EPEs are associated with pronounced upper-level potential vorticity (PV) anomalies. In addition, we find distinct seasonal and regional differences in moisture sources. Several extreme precipitation cases demonstrate the importance of these processes, complemented by a detailed synoptic analysis.
Antonio Giordani, Michael Kunz, Kristopher M. Bedka, Heinz Jürgen Punge, Tiziana Paccagnella, Valentina Pavan, Ines M. L. Cerenzia, and Silvana Di Sabatino
Nat. Hazards Earth Syst. Sci., 24, 2331–2357, https://doi.org/10.5194/nhess-24-2331-2024, https://doi.org/10.5194/nhess-24-2331-2024, 2024
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To improve the challenging representation of hazardous hailstorms, a proxy for hail frequency based on satellite detections, convective parameters from high-resolution reanalysis, and crowd-sourced reports is tested and presented. Hail likelihood peaks in mid-summer at 15:00 UTC over northern Italy and shows improved agreement with observations compared to previous estimates. By separating ambient signatures based on hail severity, enhanced appropriateness for large-hail occurrence is found.
Claire L. Ryder, Clément Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
Nat. Hazards Earth Syst. Sci., 24, 2263–2284, https://doi.org/10.5194/nhess-24-2263-2024, https://doi.org/10.5194/nhess-24-2263-2024, 2024
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Desert dust poses a hazard to aircraft via degradation of engine components. This has financial implications for the aviation industry and results in increased fuel burn with climate impacts. Here we quantify dust ingestion by aircraft engines at airports worldwide. We find Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. Dust ingestion can be reduced by changing take-off times and the altitude of holding patterns.
Khalil Ur Rahman, Songhao Shang, Khaled Saeed Balkhair, Hamza Farooq Gabriel, Khan Zaib Jadoon, and Kifayat Zaman
Nat. Hazards Earth Syst. Sci., 24, 2191–2214, https://doi.org/10.5194/nhess-24-2191-2024, https://doi.org/10.5194/nhess-24-2191-2024, 2024
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This paper assesses the impact of drought (meteorological drought) on the hydrological alterations in major rivers of the Indus Basin. Threshold regression and range of variability analysis are used to determine the drought severity and times where drought has caused low flows and extreme low flows (identified using indicators of hydrological alterations). Moreover, this study also examines the degree of alterations in river flows due to drought using the hydrological alteration factor.
Alexander Frank Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Nat. Hazards Earth Syst. Sci., 24, 2115–2132, https://doi.org/10.5194/nhess-24-2115-2024, https://doi.org/10.5194/nhess-24-2115-2024, 2024
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The risk posed to ships by Arctic cyclones has seldom been quantified due to the lack of publicly available historical Arctic ship track data. This study investigates historical Arctic ship tracks, cyclone tracks, and shipping incident reports to determine the number of shipping incidents caused by the passage of Arctic cyclones. Results suggest that Arctic cyclones have not been hazardous to ships and that ships are resilient to the rough sea conditions caused by Arctic cyclones.
Niklas Ebers, Kai Schröter, and Hannes Müller-Thomy
Nat. Hazards Earth Syst. Sci., 24, 2025–2043, https://doi.org/10.5194/nhess-24-2025-2024, https://doi.org/10.5194/nhess-24-2025-2024, 2024
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Future changes in sub-daily rainfall extreme values are essential in various hydrological fields, but climate scenarios typically offer only daily resolution. One solution is rainfall generation. With a temperature-dependent rainfall generator climate scenario data were disaggregated to 5 min rainfall time series for 45 locations across Germany. The analysis of the future 5 min rainfall time series showed an increase in the rainfall extremes values for rainfall durations of 5 min and 1 h.
Ran Zhu and Lei Chen
Nat. Hazards Earth Syst. Sci., 24, 1937–1950, https://doi.org/10.5194/nhess-24-1937-2024, https://doi.org/10.5194/nhess-24-1937-2024, 2024
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There is a positive correlation between the frequency of Jianghuai cyclone activity and precipitation during the Meiyu period. Its occurrence frequency has an obvious decadal variation, which corresponds well with the quasi-periodic and decadal variation in precipitation during the Meiyu period. This study provides a reference for the long-term and short-term forecasting of precipitation during the Meiyu period.
Andi Xhelaj and Massimiliano Burlando
Nat. Hazards Earth Syst. Sci., 24, 1657–1679, https://doi.org/10.5194/nhess-24-1657-2024, https://doi.org/10.5194/nhess-24-1657-2024, 2024
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The study provides an in-depth analysis of a severe downburst event in Sânnicolau Mare, Romania, utilizing an analytical model and optimization algorithm. The goal is to explore a multitude of generating solutions and to identify potential alternatives to the optimal solution. Advanced data analysis techniques help to discern three main distinct storm scenarios. For this particular event, the best overall solution from the optimization algorithm shows promise in reconstructing the downburst.
Luca G. Severino, Chahan M. Kropf, Hilla Afargan-Gerstman, Christopher Fairless, Andries Jan de Vries, Daniela I. V. Domeisen, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 1555–1578, https://doi.org/10.5194/nhess-24-1555-2024, https://doi.org/10.5194/nhess-24-1555-2024, 2024
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We combine climate projections from 30 climate models with a climate risk model to project winter windstorm damages in Europe under climate change. We study the uncertainty and sensitivity factors related to the modelling of hazard, exposure and vulnerability. We emphasize high uncertainties in the damage projections, with climate models primarily driving the uncertainty. We find climate change reshapes future European windstorm risk by altering damage locations and intensity.
Daniel Krieger, Sebastian Brune, Johanna Baehr, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 1539–1554, https://doi.org/10.5194/nhess-24-1539-2024, https://doi.org/10.5194/nhess-24-1539-2024, 2024
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Previous studies found that climate models can predict storm activity in the German Bight well for averages of 5–10 years but struggle in predicting the next winter season. Here, we improve winter storm activity predictions by linking them to physical phenomena that occur before the winter. We guess the winter storm activity from these phenomena and discard model solutions that stray too far from the guess. The remaining solutions then show much higher prediction skill for storm activity.
João P. A. Martins, Sara Caetano, Carlos Pereira, Emanuel Dutra, and Rita M. Cardoso
Nat. Hazards Earth Syst. Sci., 24, 1501–1520, https://doi.org/10.5194/nhess-24-1501-2024, https://doi.org/10.5194/nhess-24-1501-2024, 2024
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Over Europe, 2022 was truly exceptional in terms of extreme heat conditions, both in terms of temperature anomalies and their temporal and spatial extent. The satellite all-sky land surface temperature (LST) is used to provide a climatological context to extreme heat events. Where drought conditions prevail, LST anomalies are higher than 2 m air temperature anomalies. ERA5-Land does not represent this effect correctly due to a misrepresentation of vegetation anomalies.
Rudolf Brázdil, Kateřina Chromá, and Pavel Zahradníček
Nat. Hazards Earth Syst. Sci., 24, 1437–1457, https://doi.org/10.5194/nhess-24-1437-2024, https://doi.org/10.5194/nhess-24-1437-2024, 2024
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The official mortality data in the Czech Republic in 1919–2022 are used to show long-term fluctuations in the number of fatalities caused by excessive natural cold and heat, lightning, natural disasters, and falls on ice/snow, as well as the sex and age of the deceased, based on certain meteorological, historical, and socioeconomic factors that strongly influence changes in the number and structure of such fatalities. Knowledge obtained is usable in risk management for the preservation of lives.
Ben Maybee, Cathryn E. Birch, Steven J. Böing, Thomas Willis, Linda Speight, Aurore N. Porson, Charlie Pilling, Kay L. Shelton, and Mark A. Trigg
Nat. Hazards Earth Syst. Sci., 24, 1415–1436, https://doi.org/10.5194/nhess-24-1415-2024, https://doi.org/10.5194/nhess-24-1415-2024, 2024
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This paper presents the development and verification of FOREWARNS, a novel method for regional-scale forecasting of surface water flooding. We detail outcomes from a workshop held with UK forecast users, who indicated they valued the forecasts and would use them to complement national guidance. We use results of objective forecast tests against flood observations over northern England to show that this confidence is justified and that FOREWARNS meets the needs of UK flood responders.
Ashbin Jaison, Asgeir Sorteberg, Clio Michel, and Øyvind Breivik
Nat. Hazards Earth Syst. Sci., 24, 1341–1355, https://doi.org/10.5194/nhess-24-1341-2024, https://doi.org/10.5194/nhess-24-1341-2024, 2024
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The present study uses daily insurance losses and wind speeds to fit storm damage functions at the municipality level of Norway. The results show that the damage functions accurately estimate losses associated with extreme damaging events and can reconstruct their spatial patterns. However, there is no single damage function that performs better than another. A newly devised damage–no-damage classifier shows some skill in predicting extreme damaging events.
Madlen Peter, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 24, 1261–1285, https://doi.org/10.5194/nhess-24-1261-2024, https://doi.org/10.5194/nhess-24-1261-2024, 2024
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The paper introduces a statistical modeling approach describing daily extreme precipitation in Germany more accurately by including changes within the year and between the years simultaneously. The changing seasonality over years is regionally divergent and mainly weak. However, some regions stand out with a more pronounced linear rise of summer intensities, indicating a possible climate change signal. Improved modeling of extreme precipitation is beneficial for risk assessment and adaptation.
Faye Hulton and David M. Schultz
Nat. Hazards Earth Syst. Sci., 24, 1079–1098, https://doi.org/10.5194/nhess-24-1079-2024, https://doi.org/10.5194/nhess-24-1079-2024, 2024
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Large hail devastates crops and property and can injure and kill people and livestock. Hail reports are collected by individual countries, so understanding where and when large hail occurs across Europe is an incomplete undertaking. We use the European Severe Weather Database to evaluate the quality of reports by year and by country since 2000. Despite its short record, the dataset appears to represent aspects of European large-hail climatology reliably.
Patrick Olschewski, Mame Diarra Bousso Dieng, Hassane Moutahir, Brian Böker, Edwin Haas, Harald Kunstmann, and Patrick Laux
Nat. Hazards Earth Syst. Sci., 24, 1099–1134, https://doi.org/10.5194/nhess-24-1099-2024, https://doi.org/10.5194/nhess-24-1099-2024, 2024
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We applied a multivariate and dependency-preserving bias correction method to climate model output for the Greater Mediterranean Region and investigated potential changes in false-spring events (FSEs) and heat–drought compound events (HDCEs). Results project an increase in the frequency of FSEs in middle and late spring as well as increases in frequency, intensity, and duration for HDCEs. This will potentially aggravate the risk of crop loss and failure and negatively impact food security.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 24, 907–927, https://doi.org/10.5194/nhess-24-907-2024, https://doi.org/10.5194/nhess-24-907-2024, 2024
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Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. The incorporation of new observations from personal weather stations into the French limited-area model is evaluated. It leads to a significant improvement in the modelling of the surface pressure field up to 9 h ahead. Their incorporation improves the location and intensity of the heavy precipitation event that occurred in the South of France in September 2021.
Timo Schmid, Raphael Portmann, Leonie Villiger, Katharina Schröer, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 847–872, https://doi.org/10.5194/nhess-24-847-2024, https://doi.org/10.5194/nhess-24-847-2024, 2024
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Hailstorms cause severe damage to buildings and cars, which motivates a detailed risk assessment. Here, we present a new open-source hail damage model based on radar data in Switzerland. The model successfully estimates the correct order of magnitude of car and building damages for most large hail events over 20 years. However, large uncertainty remains in the geographical distribution of modelled damages, which can be improved for individual events by using crowdsourced hail reports.
Colin Raymond, Anamika Shreevastava, Emily Slinskey, and Duane Waliser
Nat. Hazards Earth Syst. Sci., 24, 791–801, https://doi.org/10.5194/nhess-24-791-2024, https://doi.org/10.5194/nhess-24-791-2024, 2024
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How can we systematically understand what causes high levels of atmospheric humidity and thus heat stress? Here we argue that atmospheric rivers can be a useful tool, based on our finding that in several US regions, atmospheric rivers and humid heat occur close together in space and time. Most typically, an atmospheric river transports moisture which heightens heat stress, with precipitation following a day later. These effects tend to be larger for stronger and more extensive systems.
Joseph Smith, Cathryn Birch, John Marsham, Simon Peatman, Massimo Bollasina, and George Pankiewicz
Nat. Hazards Earth Syst. Sci., 24, 567–582, https://doi.org/10.5194/nhess-24-567-2024, https://doi.org/10.5194/nhess-24-567-2024, 2024
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Nowcasting uses observations to make predictions of the atmosphere on short timescales and is particularly applicable to the Maritime Continent, where storms rapidly develop and cause natural disasters. This paper evaluates probabilistic and deterministic satellite nowcasting algorithms over the Maritime Continent. We show that the probabilistic approach is most skilful at small scales (~ 60 km), whereas the deterministic approach is most skilful at larger scales (~ 200 km).
Julia Miller, Andrea Böhnisch, Ralf Ludwig, and Manuela I. Brunner
Nat. Hazards Earth Syst. Sci., 24, 411–428, https://doi.org/10.5194/nhess-24-411-2024, https://doi.org/10.5194/nhess-24-411-2024, 2024
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We assess the impacts of climate change on fire danger for 1980–2099 in different landscapes of central Europe, using the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by 2099. High fire danger (FWI > 21.3) becomes the mean condition by 2099 under an RCP8.5 scenario. This study highlights the potential for severe fire events in central Europe from a meteorological perspective.
Joy Ommer, Jess Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
EGUsphere, https://doi.org/10.5194/egusphere-2024-296, https://doi.org/10.5194/egusphere-2024-296, 2024
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What’s the worst that could happen? Recent floods are often claimed that they were beyond our imagination. Imagination is the picturing of a situation in our mind and the emotions that we connect with this situation. But why is this important for disasters? This survey found that when we cannot imagine a devastating flood, we are not preparing in advance. Severe weather forecast and warning need to advance to trigger our imagination of what might be about to happen and start preparing.
Clemens Schwingshackl, Anne Sophie Daloz, Carley Iles, Kristin Aunan, and Jana Sillmann
Nat. Hazards Earth Syst. Sci., 24, 331–354, https://doi.org/10.5194/nhess-24-331-2024, https://doi.org/10.5194/nhess-24-331-2024, 2024
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Ambient heat in European cities will substantially increase under global warming, as projected by three heat metrics calculated from high-resolution climate model simulations. While the heat metrics consistently project high levels of ambient heat for several cities, in other cities the projected heat levels vary considerably across the three heat metrics. Using complementary heat metrics for projections of ambient heat is thus important for assessments of future risks from heat stress.
Dragan Petrovic, Benjamin Fersch, and Harald Kunstmann
Nat. Hazards Earth Syst. Sci., 24, 265–289, https://doi.org/10.5194/nhess-24-265-2024, https://doi.org/10.5194/nhess-24-265-2024, 2024
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The influence of model resolution and settings on the reproduction of heat waves in Germany between 1980–2009 is analyzed. Outputs from a high-resolution model with settings tailored to the target region are compared to those from coarser-resolution models with more general settings. Neither the increased resolution nor the tailored model settings are found to add significant value to the heat wave simulation. The models exhibit a large spread, indicating that the choice of model can be crucial.
Josep Bonsoms, Juan I. López-Moreno, Esteban Alonso-González, César Deschamps-Berger, and Marc Oliva
Nat. Hazards Earth Syst. Sci., 24, 245–264, https://doi.org/10.5194/nhess-24-245-2024, https://doi.org/10.5194/nhess-24-245-2024, 2024
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Climate warming is changing mountain snowpack patterns, leading in some cases to rain-on-snow (ROS) events. Here we analyzed near-present ROS and its sensitivity to climate warming across the Pyrenees. ROS increases during the coldest months of the year but decreases in the warmest months and areas under severe warming due to snow cover depletion. Faster snow ablation is anticipated in the coldest and northern slopes of the range. Relevant implications in mountain ecosystem are anticipated.
François Bouttier and Hugo Marchal
EGUsphere, https://doi.org/10.5194/egusphere-2023-3111, https://doi.org/10.5194/egusphere-2023-3111, 2024
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Weather prediction uncertainties can be described as sets of possible scenarios – a technique called 'ensemble prediction'. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity, space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitations.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-215, https://doi.org/10.5194/nhess-2023-215, 2024
Revised manuscript accepted for NHESS
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'Train effect' is related to convective cells that pass over the same place. Trains produce heavy rainfall, sometimes floods, and reported in N. America during spring and summer. In Israel, 17 trains were identified by radar images, associated with Cyprus Lows, sharing the following features: Found at the cold sector south of the low center, at the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km, last 1–3 hours and yield 35 mm rainfall, up to 60 mm.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-211, https://doi.org/10.5194/nhess-2023-211, 2024
Revised manuscript accepted for NHESS
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We have used the temperature and relative humidity sensors in smartphones to estimate the Vapor Pressure Deficit (VPD), and important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal show the potential for using smartphone data to both compliment the regular weather station network, while also providing high spatial resolution of the VPD index.
Matthew D. K. Priestley, David B. Stephenson, Adam A. Scaife, Daniel Bannister, Christopher J. T. Allen, and David Wilkie
Nat. Hazards Earth Syst. Sci., 23, 3845–3861, https://doi.org/10.5194/nhess-23-3845-2023, https://doi.org/10.5194/nhess-23-3845-2023, 2023
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This research presents a model for estimating extreme gusts associated with European windstorms. Using observed storm footprints we are able to calculate the return level of events at the 200-year return period. The largest gusts are found across NW Europe, and these are larger when the North Atlantic Oscillation is positive. Using theoretical future climate states we find that return levels are likely to increase across NW Europe to levels that are unprecedented compared to historical storms.
Tadeusz Chmielewski and Piotr A. Bońkowski
Nat. Hazards Earth Syst. Sci., 23, 3839–3844, https://doi.org/10.5194/nhess-23-3839-2023, https://doi.org/10.5194/nhess-23-3839-2023, 2023
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The paper deals with wind speeds of extreme wind events in Poland and the descriptions of their effects. Two recent estimations developed by the Institute of Meteorology and Water Management in Warsaw and by Halina Lorenc are presented and briefly described. The 37 annual maximum gusts of wind speeds measured between 1971 and 2007 are analysed. Based on the measured and estimated wind speeds, the authors suggest new estimations for extreme winds that may occur in Poland.
Erik Holmgren and Erik Kjellström
EGUsphere, https://doi.org/10.5194/egusphere-2023-2879, https://doi.org/10.5194/egusphere-2023-2879, 2023
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Associating extreme weather events to changes in the climate remains difficult. We have explored how these relationships can be investigated using a more common method, and relying solely on long-running observational records of temperature and precipitation.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
Jingyu Wang, Jiwen Fan, and Zhe Feng
Nat. Hazards Earth Syst. Sci., 23, 3823–3838, https://doi.org/10.5194/nhess-23-3823-2023, https://doi.org/10.5194/nhess-23-3823-2023, 2023
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Hail and tornadoes are devastating hazards responsible for significant property damage and economic losses in the United States. Quantifying the connection between hazard events and mesoscale convective systems (MCSs) is of great significance for improving predictability, as well as for better understanding the influence of the climate-scale perturbations. A 14-year statistical dataset of MCS-related hazard production is presented.
Ruijiao Jiang, Guoping Zhang, Shudong Wang, Bing Xue, Zhengshuai Xie, Tingzhao Yu, Kuoyin Wang, Jin Ding, and Xiaoxiang Zhu
Nat. Hazards Earth Syst. Sci., 23, 3747–3759, https://doi.org/10.5194/nhess-23-3747-2023, https://doi.org/10.5194/nhess-23-3747-2023, 2023
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Lightning activity in China is analyzed. Low latitudes, undulating terrain, seaside, and humid surfaces are beneficial for lightning occurrence. Summer of the year or afternoon of the day is the high period. Large cloud-to-ground lightning frequency always corresponds to a small ratio and weak intensity of positive cloud-to-ground lightning on either a temporal or spatial scale. Interestingly, the discharge intensity difference between the two types of lightning shrinks on the Tibetan Plateau.
George Pacey, Stephan Pfahl, Lisa Schielicke, and Kathrin Wapler
Nat. Hazards Earth Syst. Sci., 23, 3703–3721, https://doi.org/10.5194/nhess-23-3703-2023, https://doi.org/10.5194/nhess-23-3703-2023, 2023
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Cold fronts are often associated with areas of intense precipitation (cells) and sometimes with hazards such as flooding, hail and lightning. We find that cold-frontal cell days are associated with higher cell frequency and cells are typically more intense. We also show both spatially and temporally where cells are most frequent depending on their cell-front distance. These results are an important step towards a deeper understanding of cold-frontal storm climatology and improved forecasting.
Francesco Battaglioli, Pieter Groenemeijer, Ivan Tsonevsky, and Tomàš Púčik
Nat. Hazards Earth Syst. Sci., 23, 3651–3669, https://doi.org/10.5194/nhess-23-3651-2023, https://doi.org/10.5194/nhess-23-3651-2023, 2023
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Probabilistic models for lightning and large hail were developed across Europe using lightning observations and hail reports. These models accurately predict the occurrence of lightning and large hail several days in advance. In addition, the hail model was shown to perform significantly better than the state-of-the-art forecasting methods. These results suggest that the models developed in this study may help improve forecasting of convective hazards and eventually limit the associated risks.
Rosa Claudia Torcasio, Alessandra Mascitelli, Eugenio Realini, Stefano Barindelli, Giulio Tagliaferro, Silvia Puca, Stefano Dietrich, and Stefano Federico
Nat. Hazards Earth Syst. Sci., 23, 3319–3336, https://doi.org/10.5194/nhess-23-3319-2023, https://doi.org/10.5194/nhess-23-3319-2023, 2023
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This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.
Florian Ruff and Stephan Pfahl
EGUsphere, https://doi.org/10.5194/egusphere-2023-2057, https://doi.org/10.5194/egusphere-2023-2057, 2023
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High-impact river floods are often caused by very extreme precipitation. Flood protection rely on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties of the return values can be substantially reduced compared to observational estimates.
Gerd Bürger and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 3065–3077, https://doi.org/10.5194/nhess-23-3065-2023, https://doi.org/10.5194/nhess-23-3065-2023, 2023
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Our subject is a new catalogue of radar-based heavy rainfall events (CatRaRE) over Germany and how it relates to the concurrent atmospheric circulation. We classify reanalyzed daily atmospheric fields of convective indices according to CatRaRE, using conventional statistical and more recent machine learning algorithms, and apply them to present and future atmospheres. Increasing trends are projected for CatRaRE-type probabilities, from reanalyzed as well as from simulated atmospheric fields.
Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling
Nat. Hazards Earth Syst. Sci., 23, 2915–2936, https://doi.org/10.5194/nhess-23-2915-2023, https://doi.org/10.5194/nhess-23-2915-2023, 2023
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There is still no full understanding of the relation between drought impacts and drought indices in the Horn of Africa where water scarcity and arid regions are also present. This study assesses their relation in Kenya. A random forest model reveals that each region, aggregated by aridity, has its own set of predictors for every impact category. Water scarcity was not found to be related to aridity. Understanding these relations contributes to the development of drought early warning systems.
Marie Hundhausen, Hendrik Feldmann, Natalie Laube, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 23, 2873–2893, https://doi.org/10.5194/nhess-23-2873-2023, https://doi.org/10.5194/nhess-23-2873-2023, 2023
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Using a convection-permitting regional climate ensemble, the magnitude of heat waves (HWs) over Germany is projected to increase by 26 % (100 %) in a 2 °C (3 °C) warmer world. The increase is strongest in late summer, relatively homogeneous in space, and accompanied by increasing variance in HW length. Tailored parameters to climate adaptation to heat revealed dependency on major landscapes, and a nonlinear, exponential increase for parameters characterizing strong heat stress is expected.
Pauline Rivoire, Olivia Martius, Philippe Naveau, and Alexandre Tuel
Nat. Hazards Earth Syst. Sci., 23, 2857–2871, https://doi.org/10.5194/nhess-23-2857-2023, https://doi.org/10.5194/nhess-23-2857-2023, 2023
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Heavy precipitation can lead to floods and landslides, resulting in widespread damage and significant casualties. Some of its impacts can be mitigated if reliable forecasts and warnings are available. In this article, we assess the capacity of the precipitation forecast provided by ECMWF to predict heavy precipitation events on a subseasonal-to-seasonal (S2S) timescale over Europe. We find that the forecast skill of such events is generally higher in winter than in summer.
Stephen Cusack
Nat. Hazards Earth Syst. Sci., 23, 2841–2856, https://doi.org/10.5194/nhess-23-2841-2023, https://doi.org/10.5194/nhess-23-2841-2023, 2023
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The link from European windstorm research findings to insurance applications is strengthened by a new storm loss history spanning 1950 to 2022. It is based on ERA5 winds, together with long-term trends from observed gusts for improved validation. Correlations between losses and climate indices are around 0.4 for interannual variations, rising to 0.7 for decadal variations. A significant divergence between standard climate indices and storm losses over the past 20 years needs further research.
Felix Erdmann, Olivier Caumont, and Eric Defer
Nat. Hazards Earth Syst. Sci., 23, 2821–2840, https://doi.org/10.5194/nhess-23-2821-2023, https://doi.org/10.5194/nhess-23-2821-2023, 2023
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This work develops a novel lightning data assimilation (LDA) technique to make use of Meteosat Third Generation (MTG) Lightning Imager (LI) data in a regional, convection-permitting numerical weather prediction model. The approach combines statistical Bayesian and 3-dimensional variational methods. Our LDA can promote missing convection and suppress spurious convection in the initial state of the model, and it has similar skill to the operational radar data assimilation for rainfall forecasts.
Haojie Huang, Linfei Bai, Hao Shen, Xiaoqi Ding, Rui Wang, and Haibin Lü
Nat. Hazards Earth Syst. Sci., 23, 2807–2819, https://doi.org/10.5194/nhess-23-2807-2023, https://doi.org/10.5194/nhess-23-2807-2023, 2023
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The super cyclonic storm Amphan occurred in the central Bay of Bengal in May 2020, and a phytoplankton bloom occurred. Its dynamic mechanism was first researched. An inertial oscillation with a 2 d period appeared and lasted for approximately 2 weeks. With the weakened thermocline and thinner barrier layer thickness, nitrate and Chl a were uplifted to the upper ocean by upwelling. With the high photosynthetically available radiation, a phytoplankton bloom occurred.
Klaus Haslinger, Wolfgang Schöner, Jakob Abermann, Gregor Laaha, Konrad Andre, Marc Olefs, and Roland Koch
Nat. Hazards Earth Syst. Sci., 23, 2749–2768, https://doi.org/10.5194/nhess-23-2749-2023, https://doi.org/10.5194/nhess-23-2749-2023, 2023
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Future changes of surface water availability in Austria are investigated. Alterations of the climatic water balance and its components are analysed along different levels of elevation. Results indicate in general wetter conditions with particular shifts in timing of the snow melt season. On the contrary, an increasing risk for summer droughts is apparent due to increasing year-to-year variability and decreasing snow melt under future climate conditions.
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
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The effect of climate change on rockfall probability in the German low mountain regions is investigated in observations and in 23 different climate scenario simulations. Under a pessimistic greenhouse gas scenario, the simulations suggest a decrease in rockfall probability. This reduction is mainly caused by a decrease in the number of freeze–thaw cycles due to higher atmospheric temperatures.
Cited articles
Abatzoglou, J. T., Dobrowski, S. Z., and Parks, S. A.: Multivariate climate
departures have outpaced univariate changes across global lands, Sci. Rep.,
10, 3891, https://doi.org/10.1038/s41598-020-60270-5, 2020. a
Bevacqua, E., Maraun, D., Hobæk Haff, I., Widmann, M., and Vrac, M.: Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy), Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, 2017. a
Bevacqua, E., Maraun, D., Vousdoukas, M. I., Voukouvalas, E., Vrac, M.,
Mentaschi, L., and Widmann, M.: Higher probability of compound flooding from
precipitation and storm surge in Europe under anthropogenic climate change,
Sci. Adv., 5, eaaw5531, https://doi.org/10.1126/sciadv.aaw5531, 2019. a, b, c, d
Bevacqua, E., De Michele, C., Manning, C., Couasnon, A., Ribeiro, A. F. S.,
Ramos, A. M., Vignotto, E., Bastos, A., Blesic, S., Durante, F., et al.:
Bottom-up identification of key elements of compound events, ESS Open Archive [preprint], 29, https://doi.org/10.1002/essoar.10507809.1, 23 August 2021. a
Bevacqua, E., Zappa, G., Lehner, F., and Zscheischler, J.: Precipitation trends
determine future occurrences of compound hot–dry events, Nat. Clim. Chang., 12, 350–355,
https://doi.org/10.1038/s41558-022-01309-5, 2022. a
Bindoff, N., Stott, P., AchutaRao, K., Allen, M., Gillett, N., Gutzler, D.,
Hansingo, K., Hegerl, G., Hu, Y., Jain, S., Mokhov, I., Overland, J.,
Perlwitz, J., Sebbari, R., and Zhang, X.: Detection and Attribution of
Climate Change: from Global to Regional, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M. Allen,
S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Sect. 10,
Cambridge University Press, pp. 867–952, https://doi.org/10.1017/CBO9781107415324.022, 2013. a
Bonhomme, R.: Bases and limits to using ‘degree.day’ units, Eur. J. Agron.,
13, 1–10, https://doi.org/10.1016/S1161-0301(00)00058-7, 2000. a
Boucher, O., Denvil, S., Levavasseur, G., Cozic, A., Caubel, A., Foujols,
M.-A., Meurdesoif, Y., Cadule, P., Devilliers, M., Ghattas, J., Lebas, N.,
Lurton, T., Mellul, L., Musat, I., Mignot, J., and Cheruy, F.: IPSL
IPSL-CM6A-LR model output prepared for CMIP6 CMIP,
https://doi.org/10.22033/ESGF/CMIP6.1534, 2018. a
Brunner, M. I., Swain, D. L., Gilleland, E., and Wood, A. W.: Increasing
importance of temperature as a contributor to the spatial extent of
streamflow drought, Environ. Res. Lett., 16, 024038,
https://doi.org/10.1088/1748-9326/abd2f0, 2021. a
Calafat, F. M., Wahl, T., Tadesse, M. G., and Sparrow, S. N.: Trends in Europe
storm surge extremes match the rate of sea-level rise, Nature, 603,
841–845, https://doi.org/10.1038/s41586-022-04426-5, 2022. a
Cannon, A. J.: Multivariate quantile mapping bias correction: an
N-dimensional probability density function transform for climate model
simulations of multiple variables, Clim. Dynam., 50, 31–49,
https://doi.org/10.1007/s00382-017-3580-6, 2018. a, b
Cherchi, A., Fogli, P. G., Lovato, T., Peano, D., Iovino, D., Gualdi, S.,
Masina, S., Scoccimarro, E., Materia, S., Bellucci, A., and Navarra, A.:
Global Mean Climate and Main Patterns of Variability in the CMCC-CM2 Coupled
Model, J. Adv. Model. Earth Syst., 11, 185–209, https://doi.org/10.1029/2018MS001369,
2019. a
Chiang, F., Greve, P., Mazdiyasni, O., Wada, Y., and AghaKouchak, A.: A
Multivariate Conditional Probability Ratio Framework for the Detection and
Attribution of Compound Climate Extremes, Geophys. Res. Lett., 48,
e2021GL094361, https://doi.org/10.1029/2021GL094361, 2021. a
Christensen, J., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I., Jones,
R., Kolli, R., Kwon, W.-T., Laprise, R., Rueda, V., Mearns, L., Menéndez,
C., Räisänen, J., Rinke, A., Sarr, A., and Whetton, P.: Regional climate
projections. Climate change 2007: The physical science basis, Contribution
of Working Group I to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and
Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY,
USA, pp. 847–940, ISBN: 978-0-521-88009-1, 2007. a
De Luca, P., Messori, G., Pons, F. M. E., and Faranda, D.: Dynamical systems
theory sheds new light on compound climate extremes in Europe and Eastern
North America, Q. J. Roy. Meteor. Soc., 146, 1636–1650,
https://doi.org/10.1002/qj.3757, 2020a. a
De Luca, P., Messori, G., Wilby, R. L., Mazzoleni, M., and Di Baldassarre, G.: Concurrent wet and dry hydrological extremes at the global scale, Earth Syst. Dynam., 11, 251–266, https://doi.org/10.5194/esd-11-251-2020, 2020b. a
Diffenbaugh, N. and Scherer, M.: Observational and model evidence of global
emergence of permanent, unprecedented heat in the 20th and 21st centuries,
Clim. Change, 107, 615–624, https://doi.org/10.1007/s10584-011-0112-y, 2011. a
Diffenbaugh, N. S., Swain, D. L., and Touma, D.: Anthropogenic warming has
increased drought risk in California, Proc. Natl. Acad. Sci. USA, 112,
3931–3936, https://doi.org/10.1073/pnas.1422385112, 2015. a
EC-Earth: EC-Earth-Consortium EC-Earth3 model output prepared for CMIP6
ScenarioMIP ssp585, https://doi.org/10.22033/ESGF/CMIP6.4912, 2019. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Faranda, D., Vrac, M., Yiou, P., Jézéquel, A., and Thao, S.: Changes in
Future Synoptic Circulation Patterns: Consequences for Extreme Event
Attribution, Geophys. Res. Lett., 47, e2020GL088002,
https://doi.org/10.1029/2020GL088002, 2020. a
Fink, A. H., Brücher, T., Ermert, V., Krüger, A., and Pinto, J. G.: The European storm Kyrill in January 2007: synoptic evolution, meteorological impacts and some considerations with respect to climate change, Nat. Hazards Earth Syst. Sci., 9, 405–423, https://doi.org/10.5194/nhess-9-405-2009, 2009. a
Fischer, E. M., Sedláček, J., Hawkins, E., and Knutti, R.: Models agree on
forced response pattern of precipitation and temperature extremes, Geophys.
Res. Lett., 41, 8554–8562, https://doi.org/10.1002/2014GL062018, 2014. a, b
Frame, D., Joshi, M., Hawkins, E., Harrington, L., and Róiste, M.:
Population-based emergence of unfamiliar climates, Nat. Clim. Chang., 7,
407–411, https://doi.org/10.1038/nclimate3297, 2017. a
François, B. and Vrac, M.: Codes for the article “Time of emergence of compound events:
contribution of univariate and dependence properties”, Zenodo [code],
https://doi.org/10.5281/zenodo.7509302, 2023. a
François, B., Vrac, M., Cannon, A. J., Robin, Y., and Allard, D.: Multivariate bias corrections of climate simulations: which benefits for which losses?, Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, 2020. a
François, B., Thao, S., and Vrac, M.: Adjusting spatial dependence of climate
model outputs with cycle-consistent adversarial networks, Clim. Dynam., 57,
3323–3353, https://doi.org/10.1007/s00382-021-05869-8, 2021. a
Gaetani, M., Janicot, S., Vrac, M., Famien, A. M., and Sultan, B.:
Robust assessment of the time of emergence of precipitation change in
West Africa, Sci. Rep., 10, 7670, https://doi.org/10.1038/s41598-020-63782-2, 2020. a, b
Garcia de Cortazar-Atauri, I., Brisson, N., and Gaudillere, J.: Performance of
several models for predicting budburst date of grapevine (Vitis vinifera
L.), Int. J. Biometeorol., 53, 317–326, https://doi.org/10.1007/s00484-009-0217-4,
2009. a, b
Genest, C., Remillard, B., and Beaudoin, D.: Goodness-of-fit tests for
copulas: A review and a power study, Insur. Math. Econ., 44, 199–213,
https://doi.org/10.1016/j.insmatheco.2007.10.005, 2009. a
Giorgi, F. and Bi, X.: Time of emergence (TOE) of GHG-forced precipitation
change hot-spots, Geophys. Res. Lett., 36, L06709, https://doi.org/10.1029/2009GL037593, 2009. a
Guo, H., John, J. G., Blanton, C., McHugh, C., Nikonov, S., Radhakrishnan, A.,
Rand, K., Zadeh, N. T., Balaji, V., Durachta, J., Dupuis, C., Menzel, R.,
Robinson, T., Underwood, S., Vahlenkamp, H., Dunne, K. A., Gauthier, P. P.,
Ginoux, P., Griffies, S. M., Hallberg, R., Harrison, M., Hurlin, W., Lin, P.,
Malyshev, S., Naik, V., Paulot, F., Paynter, D. J., Ploshay, J., Schwarzkopf,
D. M., Seman, C. J., Shao, A., Silvers, L., Wyman, B., Yan, X., Zeng, Y.,
Adcroft, A., Dunne, J. P., Held, I. M., Krasting, J. P., Horowitz, L. W.,
Milly, C., Shevliakova, E., Winton, M., Zhao, M., and Zhang, R.: NOAA-GFDL
GFDL-CM4 model output prepared for CMIP6 ScenarioMIP ssp585,
https://doi.org/10.22033/ESGF/CMIP6.9268, 2018. a
Guo, Q., Chen, J., Zhang, X., Shen, M., Chen, H., and Guo, S.: A new two-stage
multivariate quantile mapping method for bias correcting climate model
outputs, Clim. Dynam., 53, 3603–3623, https://doi.org/10.1007/s00382-019-04729-w,
2019. a
Hawkins, E. and Sutton, R.: Time of emergence of climate signals, Geophys. Res.
Lett., 39, L01702, https://doi.org/10.1029/2011GL050087, 2012. a, b, c
Hillier, J., Matthews, T., Wilby, R., and Murphy, C.: Multi-hazard
dependencies can increase or decrease risk, Nat. Clim. Chang., 10, 1–4,
https://doi.org/10.1038/s41558-020-0832-y, 2020. a
Hofert, M., Mächler, M., and McNeil, A. J.: Likelihood inference for
Archimedean copulas in high dimensions under known margins, J. Multivar.
Anal., 110, 133–150, https://doi.org/10.1016/j.jmva.2012.02.019, 2012. a
Hofert, M., Kojadinovic, I., Maechler, M., and Yan, J.: copula: Multivariate
Dependence with Copulas, R package version 1.0-1, https://CRAN.R-project.org/package=copula (last access: 9 March 2022), 2020. a
Huang, W. and Prokhorov, A.: A Goodness-of-fit Test for Copulas, Econom.
Rev., 33, 751–771, https://doi.org/10.1080/07474938.2012.690692, 2014. a
IPCC: Climate Change 2021: The Physical Science Basis.
Contribution of Working Group I to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896, in press, 2023. a, b
Jézéquel, A., Bevacqua, E., d'Andrea, F., Thao, S., Vautard, R.,
Vrac, M., and Yiou, P.: Conditional and residual trends of singular hot days
in Europe, Environ. Res. Lett., 15, 064018,
https://doi.org/10.1088/1748-9326/ab76dd, 2020. a, b
Jiang, F., Hu, R.-j., Zhang, Y.-w., Li, X., and Tong, L.: Variations and
trends of onset, cessation and length of climatic growing season over
Xinjiang, NW China, Theor. Appl. Climatol., 106, 449–458,
https://doi.org/10.1007/s00704-011-0445-5, 2011. a
King, A. D., Donat, M. G., Fischer, E. M., Hawkins, E., Alexander, L. V.,
Karoly, D. J., Dittus, A. J., Lewis, S. C., and Perkins, S. E.: The timing
of anthropogenic emergence in simulated climate extremes, Environ. Res.
Lett., 10, 094015, https://doi.org/10.1088/1748-9326/10/9/094015, 2015. a
Kiriliouk, A. and Naveau, P.: Climate extreme event attribution using
multivariate peaks-over-thresholds modeling and counterfactual theory, Ann.
Appl. Stat., 14, 1342–1358, https://doi.org/10.1214/20-AOAS1355, 2020. a
Lamichhane, J.-R.: Rising risks of late-spring frosts in a changing climate,
Nat. Clim. Chang., 11, 554–555, https://doi.org/10.1038/s41558-021-01090-x, 2021. a
Leonard, M., Westra, S., Phatak, A., Lambert, M., Hurk, B., Mcinnes, K.,
Risbey, J., Schuster, S., Jakob, D., and Stafford Smith, M.: A compound event
framework for understanding extreme impacts, Wiley Interdiscip. Rev. Clim.
Change, 5, 113–128, 2014. a
Li, L.: CAS FGOALS-g3 model output prepared for CMIP6 ScenarioMIP ssp585,
https://doi.org/10.22033/ESGF/CMIP6.3503, 2019. a
Liberato, M. L.: The 19 January 2013 windstorm over the North Atlantic:
large-scale dynamics and impacts on Iberia, Weather. Clim. Extremes, 5–6,
16–28, https://doi.org/10.1016/j.wace.2014.06.002, 2014. a
Liu, Q., Piao, S., Janssens, I., Fu, Y., Peng, S., Lian, X., Ciais, P., Myneni,
R., Penuelas, J., and Wang, T.: Extension of the growing season increases
vegetation exposure to frost, Nat. Commun., 9, 426,
https://doi.org/10.1038/s41467-017-02690-y, 2018a. a
Liu, Y., Cheng, Y., Zhang, X., Li, X., and Cao, S.: Combined Exceedance
Probability Assessment of Water Quality Indicators Based on Multivariate
Joint Probability Distribution in Urban Rivers, Water, 10, 971,
https://doi.org/10.3390/w10080971, 2018b. a
Lobell, D. B. and Burke, M. B.: Why are agricultural impacts of climate change
so uncertain? The importance of temperature relative to precipitation,
Environ. Res. Lett., 3, 034007, https://doi.org/10.1088/1748-9326/3/3/034007, 2008. a
Mahlstein, I., Knutti, R., Solomon, S., and Portmann, R. W.: Early onset of
significant local warming in low latitude countries, Environ. Res. Lett., 6,
034009, https://doi.org/10.1088/1748-9326/6/3/034009, 2011. a
Mahlstein, I., Hegerl, G., and Solomon, S.: Emerging local warming signals in
observational data, Geophys. Res. Lett., 39, L21711, https://doi.org/10.1029/2012GL053952,
2012. a
Manning, C., Widmann, M., Bevacqua, E., Loon, A. F. V., Maraun, D., and Vrac,
M.: Soil Moisture Drought in Europe: A Compound Event of Precipitation and
Potential Evapotranspiration on Multiple Time Scales, J. Hydrometeorol., 19,
1255–1271, https://doi.org/10.1175/JHM-D-18-0017.1, 2018. a, b
Manning, C., Widmann, M., Bevacqua, E., Loon, A. F. V., Maraun, D., and Vrac,
M.: Increased probability of compound long-duration dry and hot events in
Europe during summer (1950–2013), Environ. Res. Lett., 14,
094006, https://doi.org/10.1088/1748-9326/ab23bf, 2019. a
Maraun, D.: When will trends in European mean and heavy daily precipitation
emerge?, Environ. Res. Lett., 8, 014004,
https://doi.org/10.1088/1748-9326/8/1/014004, 2013. a, b, c
Martius, O., Pfahl, S., and Chevalier, C.: A global quantification of compound
precipitation and wind extremes, Geophys. Res. Lett., 43, 7709–7717,
https://doi.org/10.1002/2016GL070017, 2016. a
Mazdiyasni, O. and AghaKouchak, A.: Substantial increase in concurrent
droughts and heatwaves in the United States, P. Natl. Acad. Sci. USA,
112, 11484–11489, https://doi.org/10.1073/pnas.1422945112, 2015. a
Mehrotra, R. and Sharma, A.: A Resampling Approach for Correcting Systematic
Spatiotemporal Biases for Multiple Variables in a Changing Climate, Water
Resour. Res., 55, 754–770, https://doi.org/10.1029/2018WR023270, 2019. a
Messmer, M. and Simmonds, I.: Global analysis of cyclone-induced compound
precipitation and wind extreme events, Weather. Clim. Extremes, 32,
100324, https://doi.org/10.1016/j.wace.2021.100324, 2021. a
Nasr, A. A., Wahl, T., Rashid, M. M., Camus, P., and Haigh, I. D.: Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline, Hydrol. Earth Syst. Sci., 25, 6203–6222, https://doi.org/10.5194/hess-25-6203-2021, 2021. a
Nelsen, R. B.: An Introduction to Copulas, Springer Series in
Statistics, 2nd edn., Springer, https://doi.org/10.1007/0-387-28678-0, 2006. a
Ossó, A., Allan, R., Hawkins, E., Shaffrey, L., and Maraun, D.: Emerging new
climate extremes over Europe, Clim. Dyn., 58, 487–501,
https://doi.org/10.1007/s00382-021-05917-3, 2022. a, b, c, d
Pfleiderer, P., Menke, I., and Schleussner, C.-F.: Increasing risks of apple
tree frost damage under climate change, Clim. Change, 157, 515–525,
https://doi.org/10.1007/s10584-019-02570-y, 2019. a
Pohl, E., Grenier, C., Vrac, M., and Kageyama, M.: Emerging climate signals in the Lena River catchment: a non-parametric statistical approach, Hydrol. Earth Syst. Sci., 24, 2817–2839, https://doi.org/10.5194/hess-24-2817-2020, 2020. a
Rana, A., Hamid, M., and Qin, Y.: Understanding the Joint Behavior of
Temperature and Precipitation for Climate Change Impact Studies, Theor.
Appl. Climatol., 129, https://doi.org/10.1007/s00704-016-1774-1, 2017. a
Raveh-Rubin, S. and Wernli, H.: Large-scale wind and precipitation extremes in
the Mediterranean: a climatological analysis for 1979–2012, Q. J. Roy.
Meteor. Soc., 141, 2404–2417, https://doi.org/10.1002/qj.2531, 2015. a
Raymond, C., Matthews, T., and Horton, R. M.: The emergence of heat and
humidity too severe for human tolerance, Sci. Adv., 6, eaaw1838,
https://doi.org/10.1126/sciadv.aaw1838, 2020. a
Raymond, C., Suarez-Gutierrez, L., Kornhuber, K., Pascolini-Campbell, M.,
Sillmann, J., and Waliser, D. E.: Increasing spatiotemporal proximity of heat
and precipitation extremes in a warming world quantified by a large model
ensemble, Environ. Res. Lett., 17, 035005, https://doi.org/10.1088/1748-9326/ac5712,
2022. a, b
Reinert, M., Pineau-Guillou, L., Raillard, N., and Chapron, B.: Seasonal Shift
in Storm Surges at Brest Revealed by Extreme Value Analysis, J. Geophys.
Res. Oceans, 126, e2021JC017794, https://doi.org/10.1029/2021JC017794, 2021. a
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O’Neill, B. C.,
Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp,
A., Cuaresma, J. C., KC, S., Leimbach, M., Jiang, L., Kram, T., Rao, S.,
Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Da
Silva, L. A., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D.,
Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G.,
Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J. C., Kainuma, M.,
Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A.,
and Tavoni, M.: The Shared Socioeconomic Pathways and their energy, land
use, and greenhouse gas emissions implications: An overview, Global Environ. Chang., 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009,
2017. a
Ridder, N., Pitman, A., and Ukkola, A.: Do CMIP6 Climate Models simulate
Global or Regional Compound Events skilfully?, Geophys. Res. Lett., 48, e2020GL091152,
https://doi.org/10.1029/2020GL091152, 2021. a, b
Ridder, N., Ukkola, A., Pitman, A., and Perkins-Kirkpatrick, S.: Increased
occurrence of high impact compound events under climate change, NPJ Clim.
Atmos. Sci., 5, 3, https://doi.org/10.1038/s41612-021-00224-4, 2022. a
Robin, Y., Vrac, M., Naveau, P., and Yiou, P.: Multivariate stochastic bias corrections with optimal transport, Hydrol. Earth Syst. Sci., 23, 773–786, https://doi.org/10.5194/hess-23-773-2019, 2019. a
Ruosteenoja, K., Räisänen, J., Venäläinen, A., and Kämäräinen, M.:
Projections for the duration and degree days of the thermal growing season
in Europe derived from CMIP5 model output, Int. J. Climatol., 36,
3039–3055, https://doi.org/10.1002/joc.4535, 2016. a
Russo, S., Sillmann, J., and Sterl, A.: Humid heat waves at different warming
levels, Sci. Rep., 7, 7477, https://doi.org/10.1038/s41598-017-07536-7, 2017. a
Sadegh, M., Ragno, E., and AghaKouchak, A.: Multivariate Copula Analysis
Toolbox (MvCAT): Describing dependence and underlying uncertainty using a
Bayesian framework, Water Resour. Res., 53, 5166–5183,
https://doi.org/10.1002/2016WR020242, 2017. a
Salvadori, G., de Michele, C., Kottegoda, N., and Rosso, R.: Extremes in
Nature: An Approach Using Copulas, Water Science and
Technology Library, Springer, Dordrecht, the Netherlands,
https://doi.org/10.1007/1-4020-4415-1, 2007. a
Salvadori, G., De Michele, C., and Durante, F.: On the return period and design in a multivariate framework, Hydrol. Earth Syst. Sci., 15, 3293–3305, https://doi.org/10.5194/hess-15-3293-2011, 2011. a
Salvadori, G., Durante, F., De Michele, C., Bernardi, M., and Petrella, L.: A
multivariate copula-based framework for dealing with hazard scenarios and
failure probabilities, Water Resour. Res., 52, 3701–3721,
https://doi.org/10.1002/2015WR017225, 2016. a
Schölzel, C. and Friederichs, P.: Multivariate non-normally distributed random variables in climate research – introduction to the copula approach, Nonlin. Processes Geophys., 15, 761–772, https://doi.org/10.5194/npg-15-761-2008, 2008. a
Schär, C.: Climate extremes: The worst heat waves to come, Nat. Clim.
Chang., 6, 128–129, https://doi.org/10.1038/nclimate2864, 2015. a
Serinaldi, F.: Dismissing return periods!, Stoch. Environ. Res. Risk Assess.,
29, 1179–1189, https://doi.org/10.1007/s00477-014-0916-1, 2014. a
Serinaldi, F.: Can we tell more than we can know? The limits of bivariate
drought analyses in the United States, Stoch. Environ. Res. Risk Assess.,
30, 1691–1704, 2015. a
Sgubin, G., Swingedouw, D., Dayon, G., Garcia de Cortazar-Atauri, I., Ollat,
N., Page, C., and van Leeuwen, C.: The risk of tardive frost damage in
French vineyards in a changing climate, Agric. For. Meteorol., 250–251,
226–242, https://doi.org/10.1016/j.agrformet.2017.12.253, 2018. a
Shepherd, T. G.: A Common Framework for Approaches to Extreme Event
Attribution, Curr. Clim. Change Rep., 2, 28–38,
https://doi.org/10.1007/s40641-016-0033-y, 2016. a
Shiau, J.: Return Period of Bivariate Distributed Hydrological Events, Stoch.
Environ. Res. Risk Assess., 17, 42–57, https://doi.org/10.1007/s00477-003-0125-9,
2003. a
Shiogama, H., Abe, M., and Tatebe, H.: MIROC MIROC6 model output prepared for
CMIP6 ScenarioMIP, https://doi.org/10.22033/ESGF/CMIP6.898, 2019. a
Singh, H., Najafi, M., and Cannon, A.: Characterizing non-stationary compound
extreme events in a changing climate based on large-ensemble climate
simulations, Clim. Dynam., 56, 1–17, https://doi.org/10.1007/s00382-020-05538-2,
2021a. a, b, c
Singh, J., Ashfaq, M., Skinner, C. B., Anderson, W. B., and Singh, D.:
Amplified risk of spatially compounding droughts during co-occurrences of
modes of natural ocean variability, NPJ Clim. Atmos. Sci., 4, 7,
https://doi.org/10.1038/s41612-021-00161-2, 2021b. a
Skaugen, T. E. and Tveito, O. E.: Growing-season and degree-day scenario in
Norway for 2021–2050, Clim. Res., 26, 221–232, 2004. a
Sklar, A.: Fonctions de Répartition à n Dimensions et Leurs Marges,
Publications de l’Institut Statistique de l’Université de Paris, 8,
229–231, 1959. a
Stott, P. A., Stone, D. A., and Allen, M. R.: Human contribution to the
European heatwave of 2003, Nature, 432, 610–614, https://doi.org/10.1038/nature03089,
2004. a
Stott, P. A., Christidis, N., Otto, F. E. L., Sun, Y., Vanderlinden, J.-P., van
Oldenborgh, G. J., Vautard, R., von Storch, H., Walton, P., Yiou, P., and
Zwiers, F. W.: Attribution of extreme weather and climate-related events,
Wiley Interdiscip. Rev. Clim. Change, 7, 23–41, https://doi.org/10.1002/wcc.380, 2016. a
Swart, N. C., Cole, J. N., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett,
N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G.,
Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L.,
von Salzen, K., Yang, D., Winter, B., and Sigmond, M.: CCCma CanESM5 model
output prepared for CMIP6 ScenarioMIP, https://doi.org/10.22033/ESGF/CMIP6.1317, 2019. a
Tavakol, A., Rahmani, V., and Harrington Jr., J.: Probability of compound climate extremes
in a changing climate: A copula-based study of hot, dry, and windy events in
the central United States, Environ. Res. Lett., 15, 104058,
https://doi.org/10.1088/1748-9326/abb1ef, 2020. a
Unterberger, C., Brunner, L., Nabernegg, S., Steininger, K. W., Steiner, A. K.,
Stabentheiner, E., Monschein, S., and Truhetz, H.: Spring frost risk for
regional apple production under a warmer climate, PLOS ONE, 13, 1–18,
https://doi.org/10.1371/journal.pone.0200201, 2018. a
Vautard, R., van Oldenborgh, G. J., Bonnet, R., Li, S., Robin, Y., Kew, S., Philip, S., Soubeyroux, J.-M., Dubuisson, B., Viovy, N., Reichstein, M., Otto, F., and Garcia de Cortazar-Atauri, I.: Human influence on growing-period frosts like the early April 2021 in Central France, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2022-41, in review, 2022. a, b, c, d
Venzon, D. J. and Moolgavkar, S. H.: A Method for Computing
Profile-Likelihood-Based Confidence Intervals, J. R. Stat. Soc. Ser. C Appl.
Stat., 37, 87–94, 1988. a
Villalobos-Herrera, R., Bevacqua, E., Ribeiro, A. F. S., Auld, G., Crocetti, L., Mircheva, B., Ha, M., Zscheischler, J., and De Michele, C.: Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards, Nat. Hazards Earth Syst. Sci., 21, 1867–1885, https://doi.org/10.5194/nhess-21-1867-2021, 2021. a
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1 model output prepared for CMIP6 CMIP,
https://doi.org/10.22033/ESGF/CMIP6.1375, 2018. a
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6
ScenarioMIP ssp585, https://doi.org/10.22033/ESGF/CMIP6.4225, 2019. a
Volodin, E., Mortikov, E., Gritsun, A., Lykossov, V., Galin, V., Diansky, N.,
Gusev, A., Kostrykin, S., Iakovlev, N., Shestakova, A., and Emelina, S.: INM
INM-CM4-8 model output prepared for CMIP6 ScenarioMIP,
https://doi.org/10.22033/ESGF/CMIP6.12321, 2019a. a
Volodin, E., Mortikov, E., Gritsun, A., Lykossov, V., Galin, V., Diansky, N.,
Gusev, A., Kostrykin, S., Iakovlev, N., Shestakova, A., and Emelina, S.: INM
INM-CM5-0 model output prepared for CMIP6 ScenarioMIP ssp585,
https://doi.org/10.22033/ESGF/CMIP6.12338, 2019b. a
Vrac, M.: Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction, Hydrol. Earth Syst. Sci., 22, 3175–3196, https://doi.org/10.5194/hess-22-3175-2018, 2018. a
Vrac, M. and Thao, S.: R2D2 v2.0: accounting for temporal dependences in multivariate bias correction via analogue rank resampling, Geosci. Model Dev., 13, 5367–5387, https://doi.org/10.5194/gmd-13-5367-2020, 2020. a
Vrac, M., Chédin, A., and Diday, E.: Clustering a Global Field of Atmospheric
Profiles by Mixture Decomposition of Copulas, J. Atmos. Ocean Technol., 22,
1445–1459, https://doi.org/10.1175/JTECH1795.1, 2005. a
Vrac, M., Thao, S., and Yiou, P.: Changes in temperature-precipitation
correlations over Europe: Are climate models reliable?, Clim. Dynam.,
https://doi.org/10.1007/s00382-022-06436-5, 2022a. a, b, c, d
Vrac, M., Thao, S., and Yiou, P.: Should multivariate bias corrections of
climate simulations account for changes of rank correlation over time?, J. Geophys. Res.-Atmos., 127, e2022JD036562, https://doi.org/10.1029/2022JD036562,
2022b. a
Wahl, T., Jain, S., Bender, J., Meyers, S., and Luther, M.: Increasing risk of
compound flooding from storm surge and rainfall for major US cities, Nat.
Clim. Chang., 5, 1093–1097, https://doi.org/10.1038/nclimate2736, 2015. a, b
White, H.: Maximum Likelihood Estimation of Misspecified Models,
Econometrica, 50, 1–25, 1982. a
Wieners, K.-H., Giorgetta, M., Jungclaus, J., Reick, C., Esch, M., Bittner, M.,
Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch,
J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I.,
Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S.,
Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K.,
Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von
Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H.,
Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner,
E.: MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 ScenarioMIP ssp585,
https://doi.org/10.22033/ESGF/CMIP6.6705, 2019. a
Yue, S. and Rasmussen, P.: Bivariate frequency analysis: Discussion of some
useful concepts in hydrological application, Hydrol. Process., 16,
2881–2898, https://doi.org/10.1002/hyp.1185, 2002. a, b
Yukimoto, S., Koshiro, T., Kawai, H., Oshima, N., Yoshida, K., Urakawa, S.,
Tsujino, H., Deushi, M., Tanaka, T., Hosaka, M., Yoshimura, H., Shindo, E.,
Mizuta, R., Ishii, M., Obata, A., and Adachi, Y.: MRI MRI-ESM2.0 model output
prepared for CMIP6 CMIP, https://doi.org/10.22033/ESGF/CMIP6.621, 2019.
a
Zscheischler, J. and Lehner, F.: Attributing compound events to anthropogenic
climate change, B. Am. Meteorol. Soc., 103, E936–E953,
https://doi.org/10.1175/BAMS-D-21-0116.1, 2021. a, b, c
Zscheischler, J. and Seneviratne, S.: Dependence of drivers affects risks
associated with compound events, Sci. Adv., 3, e1700263,
https://doi.org/10.1126/sciadv.1700263, 2017. a, b, c, d
Zscheischler, J., Michalak, A. M., Schwalm, C., Mahecha, M. D., Huntzinger,
D. N., Reichstein, M., Berthier, G., Ciais, P., Cook, R. B., El-Masri, B.,
Huang, M., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Mao, J., Peng, S.,
Poulter, B., Ricciuto, D., Shi, X., Tao, B., Tian, H., Viovy, N., Wang, W.,
Wei, Y., Yang, J., and Zeng, N.: Impact of large-scale climate extremes on
biospheric carbon fluxes: An intercomparison based on MsTMIP data, Glob.
Biogeochem. Cycles, 28, 585–600, https://doi.org/10.1002/2014GB004826, 2014. a
Zscheischler, J., Westra, S., Hurk, B., Seneviratne, S., Ward, P., Pitman, A.,
AghaKouchak, A., Bresch, D., Leonard, M., Wahl, T., and Zhang, X.: Future
climate risk from compound events, Nat. Clim. Chang., 8, 469–477,
https://doi.org/10.1038/s41558-018-0156-3, 2018. a
Zscheischler, J., Fischer, E. M., and Lange, S.: The effect of univariate bias adjustment on multivariate hazard estimates, Earth Syst. Dynam., 10, 31–43, https://doi.org/10.5194/esd-10-31-2019, 2019. a
Short summary
Compound events (CEs) result from a combination of several climate phenomena. In this study, we propose a new methodology to assess the time of emergence of CE probabilities and to quantify the contribution of marginal and dependence properties of climate phenomena to the overall CE probability changes. By applying our methodology to two case studies, we show the importance of considering changes in both marginal and dependence properties for future risk assessments related to CEs.
Compound events (CEs) result from a combination of several climate phenomena. In this study, we...
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