Articles | Volume 15, issue 10
https://doi.org/10.5194/nhess-15-2347-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-15-2347-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
15 Oct 2015
Research article |
| 15 Oct 2015
High-resolution analysis of 1 day extreme precipitation in Sicily
M. Maugeri
CORRESPONDING AUTHOR
Department of Physics, Università degli Studi di Milano, Milan, Italy
Institute of Atmospheric Sciences and Climate, CNR, Bologna, Italy
M. Brunetti
Institute of Atmospheric Sciences and Climate, CNR, Bologna, Italy
M. Garzoglio
Department of Physics, Università degli Studi di Milano, Milan, Italy
C. Simolo
Institute of Atmospheric Sciences and Climate, CNR, Bologna, Italy
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In the 2023/24 season, Rio de Janeiro experienced record-breaking heatwaves linked to climate change and El Niño. Our study shows global warming made these extreme temperatures at least 2°C hotter than in pre-industrial times. Heat-related deaths surged, with climate change contributing to 1 in 3 fatalities during the peak event. Without adaptation, future heatwaves will claim even more lives. This underscores the urgent need for policies to mitigate climate impacts from escalating heat threats.
François Collet, Margot Bador, Julien Boé, Laurent Dubus, and Bénédicte Jourdier
Nat. Hazards Earth Syst. Sci., 25, 843–856, https://doi.org/10.5194/nhess-25-843-2025, https://doi.org/10.5194/nhess-25-843-2025, 2025
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Our aim is to characterize the observed evolution of compound winter low-wind and cold events impacting the French electricity system. The frequency of compound events exhibits a decrease over the 1950–2022 period, which is likely due to a decrease in cold days. Large-scale atmospheric circulation is an important driver of compound event occurrence and has likely contributed to the decrease in cold days, while we cannot draw conclusions on its influence on the decrease in compound events.
Fabio Dioguardi, Giovanni Chiodini, and Antonio Costa
Nat. Hazards Earth Syst. Sci., 25, 657–674, https://doi.org/10.5194/nhess-25-657-2025, https://doi.org/10.5194/nhess-25-657-2025, 2025
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We present results of non-volcanic-gas (CO2) hazard assessment at the Mefite d’Ansanto area (Italy) where a cold-gas stream, which has already been lethal to humans and animals, forms in the valleys surrounding the emission zone. We took the uncertainty related to the gas emission and meteorological conditions into account. Results include maps of CO2 concentrations at defined probability levels and the probability of overcoming specified CO2 concentrations over specified time intervals.
Sonja Szymczak, Frederick Bott, Vigile Marie Fabella, and Katharina Fricke
Nat. Hazards Earth Syst. Sci., 25, 683–707, https://doi.org/10.5194/nhess-25-683-2025, https://doi.org/10.5194/nhess-25-683-2025, 2025
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We investigate the correlation between heavy-rainfall events and three associated natural hazards along the German rail network using GIS analyses and random-effects logistic models. The results show that 23 % of floods, 14 % of gravitational mass movements, and 2 % of tree fall events between 2017 and 2020 occurred after a heavy-rainfall event, and the probability of occurrence of flood and tree fall events significantly increased. This study contributes to more resilient rail transport.
Daniel G. Kingston, Liam Cooper, David A. Lavers, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 25, 675–682, https://doi.org/10.5194/nhess-25-675-2025, https://doi.org/10.5194/nhess-25-675-2025, 2025
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Extreme rainfall comprises a major hydrohazard for New Zealand and is commonly associated with atmospheric rivers – narrow plumes of very high atmospheric moisture transport. Here, we focus on improved forecasting of these events by testing a forecasting tool previously applied to similar situations in western Europe. However, our results for New Zealand suggest the performance of this forecasting tool may vary depending on geographical setting.
Tiago M. Ferreira, Ricardo M. Trigo, Tomás H. Gaspar, Joaquim G. Pinto, and Alexandre M. Ramos
Nat. Hazards Earth Syst. Sci., 25, 609–623, https://doi.org/10.5194/nhess-25-609-2025, https://doi.org/10.5194/nhess-25-609-2025, 2025
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We investigate the synoptic evolution associated with the occurrence of an atmospheric river that led to a 24 h record-breaking extreme precipitation event (120.3 mm) in Lisbon, Portugal, on 13 December 2022. The synoptic background allowed the formation, on 10 December, of an atmospheric river associated with a deep extratropical cyclone and with a high moisture content and an inflow of moisture, due to the warm conveyor belt, throughout its life cycle. The system made landfall on 12 December.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim G. 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
Nat. Hazards Earth Syst. Sci., 25, 541–564, https://doi.org/10.5194/nhess-25-541-2025, https://doi.org/10.5194/nhess-25-541-2025, 2025
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Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.
Lixin Song, Feifei Shen, Zhixin He, Dongmei Xu, Aiqing Shu, and Jiajun Chen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-203, https://doi.org/10.5194/nhess-2024-203, 2025
Revised manuscript accepted for NHESS
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When retrieving hydrometeors from reflectivity, there are two methods to allocate hydrometeor types: temperature-based and background hydrometer-dependent schemes. The temperature-based method divides hydrometeor proportions based on the background temperature, while the other scheme calculates average weights of each hydrometeor in various reflectivity intervals from background fields. The blending scheme adaptively combines these methods and is found to improve precipitation forecast accuracy.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 25, 429–449, https://doi.org/10.5194/nhess-25-429-2025, https://doi.org/10.5194/nhess-25-429-2025, 2025
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The use of numerical weather prediction models enables the forecasting of hazardous weather situations. The incorporation of new temperature and relative humidity observations from personal weather stations into the French limited-area model is evaluated in this study. This leads to the improvement of the associated near-surface variables of the model during the first hours of the forecast. Examples are provided for a sea breeze case during a heatwave and a fog episode.
Francisco Javier Acero, Manuel Antón, Alejandro Jesús Pérez Aparicio, Nieves Bravo-Paredes, Víctor Manuel Sánchez Carrasco, María Cruz Gallego, José Agustín García, Marcelino Núñez, Irene Tovar, Javier Vaquero-Martínez, and José Manuel Vaquero
Nat. Hazards Earth Syst. Sci., 25, 305–320, https://doi.org/10.5194/nhess-25-305-2025, https://doi.org/10.5194/nhess-25-305-2025, 2025
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The month of June 1925 was found to be exceptional in the southwest interior of the Iberian Peninsula due to the large number of thunderstorms and their significant impacts, with serious losses of human lives and material resources. We analyzed this event from different, complementary perspectives: reconstruction of the history of the events from newspapers, study of monthly meteorological variables of the longest series available, and the analysis of the meteorological synoptic situation.
Tiberiu-Eugen Antofie, Stefano Luoni, Aloïs Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci., 25, 287–304, https://doi.org/10.5194/nhess-25-287-2025, https://doi.org/10.5194/nhess-25-287-2025, 2025
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This is the first study that uses spatial patterns (clusters/hotspots) and meta-analysis in order to identify the regions at a European level at risk of multi-hazards. The findings point out the socioeconomic dimension as a determining factor in the potential risk of multi-hazards. The outcome provides valuable input for the disaster risk management policy support and will assist national authorities on the implementation of a multi-hazard approach in national risk assessment preparation.
Joona Cornér, Clément Bouvier, Benjamin Doiteau, Florian Pantillon, and Victoria A. Sinclair
Nat. Hazards Earth Syst. Sci., 25, 207–229, https://doi.org/10.5194/nhess-25-207-2025, https://doi.org/10.5194/nhess-25-207-2025, 2025
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Classification reduces the considerable variability between extratropical cyclones (ETCs) and thus simplifies studying their representation in climate models and changes in the future climate. In this paper we present an objective classification of ETCs using measures of ETC intensity. This is motivated by the aim of finding a set of ETC intensity measures which together comprehensively describe both the dynamical and impact-relevant nature of ETC intensity.
Cedric G. Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant
Nat. Hazards Earth Syst. Sci., 25, 147–168, https://doi.org/10.5194/nhess-25-147-2025, https://doi.org/10.5194/nhess-25-147-2025, 2025
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The present study addresses the predictability of heat waves at subseasonal timescales in West African cities over the period 2001–2020. Two models, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office models, were evaluated using two reanalyses: ERA5 and MERRA. The results suggest that at subseasonal timescales, the forecast models provide a better forecast than climatology, but the hit rate and false alarm rate are sub-optimal.
Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Mortimer M. Müller, Joni-Pekka Pietikäinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Sarah Veit, Julian Wendler, Elena Xoplaki, and Daniel Gliksman
Nat. Hazards Earth Syst. Sci., 25, 77–117, https://doi.org/10.5194/nhess-25-77-2025, https://doi.org/10.5194/nhess-25-77-2025, 2025
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Our research, involving 22 European scientists, investigated drought and heat impacts on forests in 2018–2022. Findings reveal that climate extremes are intensifying, with central Europe being most severely impacted. The southern region showed resilience due to historical drought exposure, while northern and Alpine areas experienced emerging or minimal impacts. The study highlights the need for region-specific strategies, improved data collection, and sustainable practices to safeguard forests.
Georgy Ayzel and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 25, 41–47, https://doi.org/10.5194/nhess-25-41-2025, https://doi.org/10.5194/nhess-25-41-2025, 2025
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Forecasting rainfall over the next hour is an essential feature of early warning systems. Deep learning (DL) has emerged as a powerful alternative to conventional nowcasting technologies, but it still struggles to adequately predict impact-relevant heavy rainfall. We think that DL could do much better if the training tasks were defined more specifically and that such specification presents an opportunity to better align the output of nowcasting models with actual user requirements.
Monica Ionita, Petru Vaideanu, Bogdan Antonescu, Catalin Roibu, Qiyun Ma, and Viorica Nagavciuc
Nat. Hazards Earth Syst. Sci., 24, 4683–4706, https://doi.org/10.5194/nhess-24-4683-2024, https://doi.org/10.5194/nhess-24-4683-2024, 2024
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Eastern Europe's heat wave history is explored from 1885 to 2023, with a focus on pre-1960 events. The study reveals two periods with more frequent and intense heat waves (HWs): 1920s–1960s and 1980s–present. The research highlights the importance of a long-term perspective, revealing that extreme heat events have occurred throughout the entire study period, and it emphasizes the combined influence of climate change and natural variations on increasing HW severity.
Tristan Shepherd, Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Nat. Hazards Earth Syst. Sci., 24, 4473–4505, https://doi.org/10.5194/nhess-24-4473-2024, https://doi.org/10.5194/nhess-24-4473-2024, 2024
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A historic derecho in the USA is presented. The 29 June 2012 derecho caused more than 20 deaths and millions of US dollars of damage. We use a regional climate model to understand how model fidelity changes under different initial conditions. We find changes drive different convective conditions, resulting in large variation in the simulated hazards. The variation using different reanalysis data shows that framing these results in the context of contemporary and future climate is a challenge.
Stephen Cusack and Tyler Cox
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-210, https://doi.org/10.5194/nhess-2024-210, 2024
Revised manuscript accepted for NHESS
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Warming seas have been driving greater hailstorm risk in Europe over the past few decades. Modern climate models indicate anthropogenic aerosols caused the observed cooling of seas from about 1900 to the 1970s, while the recent rapid warming is mostly explained by rising greenhouse gases. Current trends in anthropogenic forcing are likely to persist, suggesting seas will continue warming, and hailstorm risk over Europe will continue rising over the next couple of decades, at least.
Lena Wilhelm, Cornelia Schwierz, Katharina Schröer, Mateusz Taszarek, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 3869–3894, https://doi.org/10.5194/nhess-24-3869-2024, https://doi.org/10.5194/nhess-24-3869-2024, 2024
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In our study we used statistical models to reconstruct past hail days in Switzerland from 1959–2022. This new time series reveals a significant increase in hail day occurrences over the last 7 decades. We link this trend to increases in moisture and instability variables in the models. This time series can now be used to unravel the complexities of Swiss hail occurrence and to understand what drives its year-to-year variability.
Diego Saúl Carrió, Vincenzo Mazzarella, and Rossella Ferretti
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-177, https://doi.org/10.5194/nhess-2024-177, 2024
Revised manuscript accepted for NHESS
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Populated coastal regions in the Mediterranean are known to be severely affected by extreme weather events that are initiated over maritime regions. These weather events are known to pose a serious problem in terms of numerical predictability. Different Data Assimilation techniques are used in this study with the main aim of enhancing short-range forecasts of two challenging severe weather events.
Thomas Loridan and Nicolas Bruneau
EGUsphere, https://doi.org/10.5194/egusphere-2024-3253, https://doi.org/10.5194/egusphere-2024-3253, 2024
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Tropical Cyclone (TC) risk models have been used by the insurance industry to quantify occurrence and severity risk since the 90s. To date these models are mostly built from backward looking statistics and portray risk under a static view of the climate. We here introduce a novel approach, based on machine learning, that allows sampling of climate variability when assessing TC risk globally. This is of particular importance when computing forward looking views of TC risk.
Herijaona Hani-Roge Hundilida Randriatsara, Eva Holtanova, Karim Rizwan, Hassen Babaousmail, Mirindra Finaritra Tanteliniaina Rabezanahary, Kokou Romaric Posset, Donnata Alupot, and Brian Odhiambo Ayugi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-191, https://doi.org/10.5194/nhess-2024-191, 2024
Revised manuscript accepted for NHESS
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This study aims to analyze the spatiotemporal characteristics of drought (duration, frequency, severity, intensity) over Madagascar during 1981–2022 by using Standardized Precipitation Index (SPI-3, -6 and -12). Additionally, the impact of drought on vegetation over the studied area was assessed based on the relationship evaluation between SPI and the Normalized Difference Vegetation Index (NDVI) during 2000–2022.
Gwendoline Ducros, Timothy Tiggeloven, Lin Ma, Anne Sophie Daloz, Nina Schuhen, and Marleen C. de Ruiter
EGUsphere, https://doi.org/10.5194/egusphere-2024-3158, https://doi.org/10.5194/egusphere-2024-3158, 2024
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Our study finds that heatwave, drought and wildfire events occurring simultaneously in Scandinavia are pronounced in the summer months; and the heat-drought 2018 event led to a drop in gross domestic product, affecting agriculture and forestry imports, further impacting Europe’s trade balance. This research shows the importance of ripple effects of multi-hazard, and that forest management and adaptation measures are vital to reducing the risks of heat-related multi-hazards in vulnerable areas.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024, https://doi.org/10.5194/nhess-24-3479-2024, 2024
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To effectively track and identify droughts, we developed a novel integrated drought index that combines the effects of precipitation, temperature, and soil moisture on drought. After comparison and verification, the integrated drought index shows superior performance compared to a single meteorological drought index or agricultural drought index in terms of drought identification.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 24, 3445–3460, https://doi.org/10.5194/nhess-24-3445-2024, https://doi.org/10.5194/nhess-24-3445-2024, 2024
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European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological loss index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high-impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
Jannick Fischer, Pieter Groenemeijer, Alois Holzer, Monika Feldmann, Katharina Schröer, Francesco Battaglioli, Lisa Schielicke, Tomáš Púčik, Christoph Gatzen, Bogdan Antonescu, and the TIM Partners
EGUsphere, https://doi.org/10.5194/egusphere-2024-2798, https://doi.org/10.5194/egusphere-2024-2798, 2024
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Strong thunderstorms have been studied mainly over flat terrain and in computer simulations in the past. However, they are particularly frequent near mountain ranges, which emphasizes the need to study storms near mountains. This article gives an overview about our existing knowledge on this topic and presents plans for a large European field campaign with the goals to fill these knowledge gaps, validate tools for thunderstorm warnings, and improve numerical weather prediction near mountains.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci., 24, 3267–3277, https://doi.org/10.5194/nhess-24-3267-2024, https://doi.org/10.5194/nhess-24-3267-2024, 2024
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The train effect is related to convective cells that pass over the same place. Trains produce heavy rainfall and sometimes floods and are reported in North America during spring and summer. In Israel, 17 trains associated with Cyprus lows were identified by radar images and were found within the cold sector south of the low center and in the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km; last 1–3 h; and yield 35 mm of rainfall up to 60 mm.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
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A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
Katharina Küpfer, Alexandre Tuel, and Michael Kunz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2803, https://doi.org/10.5194/egusphere-2024-2803, 2024
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Using loss data, we assess when and how single and multiple types of meteorological extremes (river floods and heavy rainfall events, windstorms and convective gusts, and hail). We find that the combination of several types of hazards clusters robustly on a seasonal scale, whereas only some single hazard types occur in clusters. This can be associated with higher losses compared to isolated events. We argue for the relevance of jointly considering multiple types of hazards.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024, https://doi.org/10.5194/nhess-24-3035-2024, 2024
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We have used the temperature and relative humidity sensors in smartphones to estimate the vapor pressure deficit (VPD), an important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal shows the potential for using smartphone data to compliment the regular weather station network while also providing high spatial resolution of the VPD index.
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, https://doi.org/10.5194/nhess-24-2939-2024, 2024
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High-impact river floods are often caused by extreme precipitation. Flood protection relies 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 in the return values can be substantially reduced compared to observational estimates.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
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Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
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.
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024, https://doi.org/10.5194/nhess-24-2793-2024, 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 and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
Xiaoxiang Guan, Dung Viet Nguyen, Paul Voit, Bruno Merz, Maik Heistermann, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-143, https://doi.org/10.5194/nhess-2024-143, 2024
Revised manuscript accepted for NHESS
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We evaluated a multi-site stochastic regional weather generator (nsRWG) for its ability to capture the cross-scale extremity of high precipitation events (HPEs) in Germany. We generated 100 realizations of 72 years of daily synthetic precipitation data. The performance was assessed using WEI and xWEI indices, which measure event extremity across spatio-temporal scales. Results show nsRWG simulates well the extremity patterns of HPEs, though it overestimates short-duration, small-extent events.
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Short summary
We investigate 1-day precipitation extremes in Sicily and their frequency distribution, based on a dense data set of high-quality, homogenized station records (1921-2005).
Return levels corresponding to 10-, 50- and 100-year periods are produced on a high-resolution grid using a variant of regional frequency analysis combined with regression techniques.
The results, which clearly reflect the complexity of this region, may be useful in the context of extreme precipitation risk assessment.
We investigate 1-day precipitation extremes in Sicily and their frequency distribution, based on...
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