Articles | Volume 24, issue 11
https://doi.org/10.5194/nhess-24-3869-2024
© Author(s) 2024. 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-24-3869-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Reconstructing hail days in Switzerland with statistical models (1959–2022)
Institute of Geography, Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Cornelia Schwierz
Office of Meteorology and Climatology, MeteoSwiss, Zurich, Switzerland
Katharina Schröer
Institute of Environmental Social Sciences and Geography, University of Freiburg, Freiburg, Germany
Mateusz Taszarek
Department of Meteorology and Climatology, Adam Mickiewicz University, Poznan, Poland
Olivia Martius
Institute of Geography, Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Related authors
Killian P. Brennan and Lena Wilhelm
EGUsphere, https://doi.org/10.5194/egusphere-2024-3924, https://doi.org/10.5194/egusphere-2024-3924, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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In this study, we discovered that natural dust carried into Europe significantly increases the likelihood of hailstorms. By analyzing dust data, weather records, and hail reports, we found that moderate dust levels lead to more frequent hail, while very high or low dust amounts reduce it. Adding dust information into statistical models improved forecasting skills. We aimed to understand how dust affects hailstorms.
Lucas Pfister, Lena Wilhelm, Yuri Brugnara, Noemi Imfeld, and Stefan Brönnimann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1346, https://doi.org/10.5194/egusphere-2024-1346, 2024
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Our work compares different machine learning approaches for creating long-term classifications of daily atmospheric circulation patterns using input data from surface meteorological observations. Our comparison reveals a so-called feedforward neural network to perform best in this task. Using this model, we present a daily reconstruction of the CAP9 weather type classification for Central Europe back to 1728.
Killian P. Brennan and Lena Wilhelm
EGUsphere, https://doi.org/10.5194/egusphere-2024-3924, https://doi.org/10.5194/egusphere-2024-3924, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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In this study, we discovered that natural dust carried into Europe significantly increases the likelihood of hailstorms. By analyzing dust data, weather records, and hail reports, we found that moderate dust levels lead to more frequent hail, while very high or low dust amounts reduce it. Adding dust information into statistical models improved forecasting skills. We aimed to understand how dust affects hailstorms.
Hugo Banderier, Alexandre Tuel, Tim Woollings, and Olivia Martius
EGUsphere, https://doi.org/10.5194/egusphere-2024-3029, https://doi.org/10.5194/egusphere-2024-3029, 2024
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The jet stream is the main feature of the upper level flow, and drives the weather at the surface. It is stronger and better defined in winter, and has mostly been studied in that season. However, it is very important for (extreme) weather in summer. In this work, we improve and use two existing and complementary methods to study the jet stream(s) in the Euro-Atlantic sector, with a focus on summer. We find that our methods can verify each other and agree on interesting signals and trends.
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.
Duncan Pappert, Alexandre Tuel, Dim Coumou, Mathieu Vrac, and Olivia Martius
EGUsphere, https://doi.org/10.5194/egusphere-2024-2980, https://doi.org/10.5194/egusphere-2024-2980, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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This study examines the mechanisms that characterise long-lasting (persistent) and short hot spells in Europe in a comparative framework. By analysing weather data, we found that long spells in Southwestern Europe are typically preceded by dry soil conditions and driven by multiple persistence-inducing mechanisms. In contrast, short spells occur in a more transient atmospheric situation and exhibit fewer drivers. Understanding persistent heat extremes can help improve their prediction.
Edgar Dolores-Tesillos, Olivia Martius, and Julian Quinting
EGUsphere, https://doi.org/10.5194/egusphere-2024-2878, https://doi.org/10.5194/egusphere-2024-2878, 2024
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An accurate representation of synoptic weather systems in climate models is required to estimate their societal and economic impacts under climate warming. Current climate models poorly represent the frequency of atmospheric blocking. Few studies have analysed the role of moist processes as a source of bias of blocks. Here, we implement ELIAS2.0, a deep learning tool, to validate the representation of moist processes in CMIP6 models and their link to the Euro-Atlantic blocking biases.
Raphaël Rousseau-Rizzi, Shira Raveh-Rubin, Jennifer L. Catto, Alice Portal, Yonatan Givon, and Olivia Martius
Weather Clim. Dynam., 5, 1079–1101, https://doi.org/10.5194/wcd-5-1079-2024, https://doi.org/10.5194/wcd-5-1079-2024, 2024
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We identify situations when rain and wind, rain and wave, or heat and dust hazards co-occur within Mediterranean cyclones. These hazard combinations are associated with risk to infrastructure, risk of coastal flooding and risk of respiratory issues. The presence of Mediterranean cyclones is associated with increased probability of all three hazard combinations. We identify weather configurations and cyclone structures, particularly those associated with specific co-occurrence combinations.
Alice Portal, Shira Raveh-Rubin, Jennifer L. Catto, Yonatan Givon, and Olivia Martius
Weather Clim. Dynam., 5, 1043–1060, https://doi.org/10.5194/wcd-5-1043-2024, https://doi.org/10.5194/wcd-5-1043-2024, 2024
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Mediterranean cyclones are associated with extended rain, wind, and wave impacts. Although beneficial for regional water resources, their passage may induce extreme weather, which is especially impactful when multiple hazards combine together. Here we show how the passage of Mediterranean cyclones increases the likelihood of rain–wind and wave–wind compounding and how compound–cyclone statistics vary by region and season, depending on the presence of specific airflows around the cyclone.
Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius
Atmos. Meas. Tech., 17, 4529–4552, https://doi.org/10.5194/amt-17-4529-2024, https://doi.org/10.5194/amt-17-4529-2024, 2024
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We present a verification of two products based on weather radars to detect the presence of hail and estimate its size. Radar products are remote detection of hail, so they must be verified against ground-based observations. We use reports from users of the Swiss Weather Services phone app to do the verification. We found that the product estimating the presence of hail provides fair results but that it should be recalibrated and that estimating the hail size with radar is more challenging.
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, https://doi.org/10.5194/nhess-24-1975-2024, 2024
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The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.
Lucas Pfister, Lena Wilhelm, Yuri Brugnara, Noemi Imfeld, and Stefan Brönnimann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1346, https://doi.org/10.5194/egusphere-2024-1346, 2024
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Our work compares different machine learning approaches for creating long-term classifications of daily atmospheric circulation patterns using input data from surface meteorological observations. Our comparison reveals a so-called feedforward neural network to perform best in this task. Using this model, we present a daily reconstruction of the CAP9 weather type classification for Central Europe back to 1728.
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.
Hélène Barras, Olivia Martius, Luca Nisi, Katharina Schroeer, Alessandro Hering, and Urs Germann
Weather Clim. Dynam., 2, 1167–1185, https://doi.org/10.5194/wcd-2-1167-2021, https://doi.org/10.5194/wcd-2-1167-2021, 2021
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In Switzerland hail may occur several days in a row. Such multi-day hail events may cause significant damage, and understanding and forecasting these events is important. Using reanalysis data we show that weather systems over Europe move slower before and during multi-day hail events compared to single hail days. Surface temperatures are typically warmer and the air more humid over Switzerland and winds are slower on multi-day hail clusters. These results may be used for hail forecasting.
Ana Casanueva, Sven Kotlarski, Sixto Herrera, Andreas M. Fischer, Tord Kjellstrom, and Cornelia Schwierz
Geosci. Model Dev., 12, 3419–3438, https://doi.org/10.5194/gmd-12-3419-2019, https://doi.org/10.5194/gmd-12-3419-2019, 2019
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Given the large number of available data sets and products currently produced for climate impact studies, it is challenging to distil the most accurate and useful information for climate services. This work presents a comparison of methods widely used to generate climate projections, from different sources and at different spatial resolutions, in order to assess the role of downscaling and statistical post-processing (bias correction).
Related subject area
Atmospheric, Meteorological and Climatological Hazards
Examining the Eastern European extreme summer temperatures of 2023 from a long-term perspective: the role of natural variability vs. anthropogenic factors
How well are hazards associated with derechos reproduced in regional climate simulations?
GTDI: a game-theory-based integrated drought index implying hazard-causing and hazard-bearing impact change
Insurance loss model vs. meteorological loss index – how comparable are their loss estimates for European windstorms?
Intense rains in Israel associated with the train effect
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
On the potential of using smartphone sensors for wildfire hazard estimation through citizen science
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations
Probabilistic short-range forecasts of high-precipitation events: optimal decision thresholds and predictability limits
Surprise floods: the role of our imagination in preparing for disasters
Brief Communication: Training of AI-based nowcasting models for rainfall early warning should take into account user requirements
Modelling crop hail damage footprints with single-polarization radar: the roles of spatial resolution, hail intensity, and cropland density
Insights into ground strike point properties in Europe through the EUCLID lightning location system
The role of citizen science in assessing the spatiotemporal pattern of rainfall events in urban areas: a case study in the city of Genoa, Italy
The Record-Breaking Precipitation Event of December 2022 in Portugal
Precipitation extremes in Ukraine from 1979 to 2019: climatology, large-scale flow conditions, and moisture sources
Characterizing hail-prone environments using convection-permitting reanalysis and overshooting top detections over south-central Europe
Aircraft engine dust ingestion at global airports
Assimilation of temperature and relative humidity observations from personal weather stations in AROME-France
Catchment-scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan
The risk of synoptic-scale Arctic cyclones to shipping
Classification of North Atlantic and European extratropical cyclones using multiple measures of intensity
Brief communication: Forecasting extreme precipitation from atmospheric rivers in New Zealand
Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data
Climatic characteristics of the Jianghuai cyclone and its linkage with precipitation during the Meiyu period from 1961 to 2020
Application of the teaching–learning-based optimization algorithm to an analytical model of thunderstorm outflows to analyze the variability of the downburst kinematic and geometric parameters
Projections and uncertainties of winter windstorm damage in Europe in a changing climate
Improving seasonal predictions of German Bight storm activity
A satellite view of the exceptionally warm summer of 2022 over Europe
Demographic yearbooks as a source of weather-related fatalities: the Czech Republic, 1919–2022
FOREWARNS: development and multifaceted verification of enhanced regional-scale surface water flood forecasts
Assessment of wind–damage relations for Norway using 36 years of daily insurance data
Compound winter low wind and cold events impacting the French electricity system: observed evolution and role of large-scale circulation
Interannual variations in the seasonal cycle of extreme precipitation in Germany and the response to climate change
Climatology of large hail in Europe: characteristics of the European Severe Weather Database
Amplified potential for vegetation stress under climate-change-induced intensifying compound extreme events in the Greater Mediterranean Region
Assimilation of surface pressure observations from personal weather stations in AROME-France
An open-source radar-based hail damage model for buildings and cars
Linkages between atmospheric rivers and humid heat across the United States
A data-driven framework for assessing climatic impact-drivers in the context of food security
Evaluating pySTEPS optical flow algorithms for convection nowcasting over the Maritime Continent using satellite data
Climate change impacts on regional fire weather in heterogeneous landscapes of central Europe
High-resolution projections of ambient heat for major European cities using different heat metrics
Heat wave characteristics: evaluation of regional climate model performances for Germany
Rain-on-snow responses to warmer Pyrenees: a sensitivity analysis using a physically based snow hydrological model
Spatial identification of regions at risk to multi-hazards at pan European level: an implemented methodological approach
Are heavy rainfall events a major trigger of associated natural hazards along the German rail network?
Return levels of extreme European windstorms, their dependency on the North Atlantic Oscillation, and potential future risks
Probabilistic hazard assessment of the gas emission of Mefite d’Ansanto, Southern Italy
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.
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.
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.
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.
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024, https://doi.org/10.5194/nhess-24-2633-2024, 2024
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What’s the worst that could happen? Recent floods are often claimed to be 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 forecasts and warnings need to advance in order to trigger our imagination of what might happen and enable us to start preparing.
Georgy Ayzel and Maik Heistermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1945, https://doi.org/10.5194/egusphere-2024-1945, 2024
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Forecasting rainfall over the next hour is an essential feature of early warning systems. Deep learning 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 a specification presents an opportunity to better align the output of nowcasting models with actual user requirements.
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024, https://doi.org/10.5194/nhess-24-2541-2024, 2024
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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.
Tiago M. Ferreira, Ricardo M. Trigo, Tomás H. Gaspar, Joaquim G. Pinto, and Alexandre M. Ramos
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-130, https://doi.org/10.5194/nhess-2024-130, 2024
Revised manuscript accepted for NHESS
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Here we investigate the synoptic evolution associated with the occurrence of an atmospheric river leading 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 day 12.
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.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
EGUsphere, https://doi.org/10.5194/egusphere-2024-1673, https://doi.org/10.5194/egusphere-2024-1673, 2024
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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.
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.
Joona Samuel Cornér, Clément Gael Francis Bouvier, Benjamin Doiteau, Florian Pantillon, and Victoria Anne Sinclair
EGUsphere, https://doi.org/10.5194/egusphere-2024-1749, https://doi.org/10.5194/egusphere-2024-1749, 2024
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Classification reduces the considerable variability between extratropical cyclones (ETC) 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.
Daniel G. Kingston, Liam Cooper, David A. Lavers, and David M. Hannah
EGUsphere, https://doi.org/10.5194/egusphere-2024-1742, https://doi.org/10.5194/egusphere-2024-1742, 2024
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Extreme rainfall comprises a major hydro-hazard 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 geographic setting.
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.
François Collet, Margot Bador, Julien Boé, Laurent Dubus, and Bénédicte Jourdier
EGUsphere, https://doi.org/10.5194/egusphere-2024-903, https://doi.org/10.5194/egusphere-2024-903, 2024
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The objective of this study 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 high interannual variability and a decrease over the 1950–2022 period. We further show that the regional atmospheric circulation is an important driver of compound events occurence, but do not strongly contributes to the observed decrease.
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.
Marcos Roberto Benso, Roberto Fray Silva, Gabriela Gesualdo Chiquito, Antonio Mauro Saraiva, Alexandre Cláudio Botazzo Delbem, Patricia Angélica Alves Marques, and Eduardo Mario Mendiondo
EGUsphere, https://doi.org/10.5194/egusphere-2023-3002, https://doi.org/10.5194/egusphere-2023-3002, 2024
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The production of food is susceptible to several climate hazards such as droughts, excessive rainfall, and heat waves. In this paper, we present a methodology that uses artificial intelligence for assessing the impact of climate risks on food production. Our methodology helps us to automatically select the most relevant indices and critical thresholds of these indices that when surpassed can increase the danger of crop yield loss.
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.
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.
Tiberiu-Eugen Antofie, Stefano Luoni, Alois Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-220, https://doi.org/10.5194/nhess-2023-220, 2024
Revised manuscript accepted for NHESS
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This is the first study that uses spatial patterns (clusters/hot-spots) and meta-analysis in order to identify the regions at European level at risk to multi-hazards. The findings point out the socio-economic dimension as determinant factor for the risk potential to multi-hazard. 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 the National Risk Assessments preparation.
Sonja Szymczak, Frederick Bott, Vigile Marie Fabella, and Katharina Fricke
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-196, https://doi.org/10.5194/nhess-2023-196, 2023
Revised manuscript accepted for NHESS
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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 flood, 14 % of gravitational mass movements and 2 % of tree fall events between 2017–2020 occurred after a heavy rainfall event and the probability of occurrence of flood and tree fall events is significantly increased. The study contributes to more resilient rail transport.
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.
Fabio Dioguardi, Giovanni Chiodini, and Antonio Costa
EGUsphere, https://doi.org/10.5194/egusphere-2023-2867, https://doi.org/10.5194/egusphere-2023-2867, 2023
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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 had already been lethal for 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 concentration at defined probability levels and of the probability to overcome specified CO2 concentrations over specified time intervals.
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Short summary
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.
In our study we used statistical models to reconstruct past hail days in Switzerland from...
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