Articles | Volume 19, issue 2
https://doi.org/10.5194/nhess-19-421-2019
© Author(s) 2019. 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-19-421-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Mar 2019
Research article |
| 01 Mar 2019
| 01 Mar 2019
Projected intensification of sub-daily and daily rainfall extremes in convection-permitting climate model simulations over North America: implications for future intensity–duration–frequency curves
Climate Research Division, Environment and Climate Change Canada,
Victoria, Canada
Silvia Innocenti
Institut national de la recherche scientifique,
Centre Eau Terre Environnement, Québec, Canada
Related authors
Gesa Meyer, Elyn R. Humphreys, Joe R. Melton, Alex J. Cannon, and Peter M. Lafleur
Biogeosciences, 18, 3263–3283, https://doi.org/10.5194/bg-18-3263-2021, https://doi.org/10.5194/bg-18-3263-2021, 2021
Short summary
Short summary
Shrub and sedge plant functional types (PFTs) were incorporated in the land surface component of the Canadian Earth System Model to improve representation of Arctic tundra ecosystems. Evaluated against 14 years of non-winter measurements, the magnitude and seasonality of carbon dioxide and energy fluxes at a Canadian dwarf-shrub tundra site were better captured by the shrub PFTs than by previously used grass and tree PFTs. Model simulations showed the tundra site to be an annual net CO2 source.
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
Short summary
Short summary
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.
Zilefac Elvis Asong, Mohamed Ezzat Elshamy, Daniel Princz, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, and Alex Cannon
Earth Syst. Sci. Data, 12, 629–645, https://doi.org/10.5194/essd-12-629-2020, https://doi.org/10.5194/essd-12-629-2020, 2020
Short summary
Short summary
This dataset provides an improved set of forcing data for large-scale hydrological models for climate change impact assessment in the Mackenzie River Basin (MRB). Here, the strengths of two historical datasets were blended to produce a less-biased long-record product for hydrological modelling and climate change impact assessment over the MRB. This product is then used to bias-correct climate projections from the Canadian Regional Climate Model under RCP8.5.
Zilefac Elvis Asong, Mohamed Elshamy, Daniel Princz, Howard Wheater, John Pomeroy, Alain Pietroniro, and Alex Cannon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-249, https://doi.org/10.5194/hess-2019-249, 2019
Publication in HESS not foreseen
Dae Il Jeong, Alex J. Cannon, and Xuebin Zhang
Nat. Hazards Earth Syst. Sci., 19, 857–872, https://doi.org/10.5194/nhess-19-857-2019, https://doi.org/10.5194/nhess-19-857-2019, 2019
Short summary
Short summary
Atmospheric ice accretion caused by freezing precipitation leads to severe damage and failure of buildings and infrastructure. This study investigates projected changes to extreme ice loads used to design infrastructure over North America for future periods of specified global mean temperature change using a Canadian regional climate model. Increases in ice accretion for latitudes higher than 40° N are substantial and would have clear implications for future building and infrastructure design.
Judith Meyer, Irene Kohn, Kerstin Stahl, Kirsti Hakala, Jan Seibert, and Alex J. Cannon
Hydrol. Earth Syst. Sci., 23, 1339–1354, https://doi.org/10.5194/hess-23-1339-2019, https://doi.org/10.5194/hess-23-1339-2019, 2019
Short summary
Short summary
Several multivariate bias correction methods have been developed recently, but only a few studies have tested the effect of multivariate bias correction on hydrological impact projections. This study shows that incorporating or ignoring inter-variable relations between air temperature and precipitation can have a notable effect on the projected snowfall fraction. The effect translated to considerable consequences for the glacio-hydrological responses and streamflow components of the catchments.
Zilefac Elvis Asong, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, Mohamed Ezzat Elshamy, Daniel Princz, and Alex Cannon
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-128, https://doi.org/10.5194/essd-2018-128, 2018
Preprint withdrawn
Short summary
Short summary
Cold regions hydrology is very sensitive to the impacts of climate warming. We need better hydrological models driven by reliable climate data in order to assess hydrologic responses to climate change. Cold regions often have sparse surface observations, particularly at high elevations that generate a major amount of runoff. We produce a long-term dataset that can be used to better understand and represent the seasonal/inter-annual variability of hydrological fluxes and the the timing of runoff.
Hui-Min Wang, Jie Chen, Alex J. Cannon, Chong-Yu Xu, and Hua Chen
Hydrol. Earth Syst. Sci., 22, 3739–3759, https://doi.org/10.5194/hess-22-3739-2018, https://doi.org/10.5194/hess-22-3739-2018, 2018
Short summary
Short summary
Facing a growing number of climate models, many selection methods were proposed to select subsets in the field of climate simulation, but the transferability of their performances to hydrological impacts remains doubtful. We investigate the transferability of climate simulation uncertainty to hydrological impacts using two selection methods, and conclude that envelope-based selection of about 10 climate simulations based on properly chosen climate variables is suggested for impact studies.
Andrew M. Snauffer, William W. Hsieh, Alex J. Cannon, and Markus A. Schnorbus
The Cryosphere, 12, 891–905, https://doi.org/10.5194/tc-12-891-2018, https://doi.org/10.5194/tc-12-891-2018, 2018
Short summary
Short summary
Estimating winter snowpack throughout British Columbia is challenging due to the complex terrain, thick forests, and high snow accumulations present. This paper describes a way to make better snow estimates by combining publicly available data using machine learning, a branch of artificial intelligence research. These improved estimates will help water resources managers better plan for changes in rivers and lakes fed by spring snowmelt and will aid other research that supports such planning.
Gesa Meyer, Elyn R. Humphreys, Joe R. Melton, Alex J. Cannon, and Peter M. Lafleur
Biogeosciences, 18, 3263–3283, https://doi.org/10.5194/bg-18-3263-2021, https://doi.org/10.5194/bg-18-3263-2021, 2021
Short summary
Short summary
Shrub and sedge plant functional types (PFTs) were incorporated in the land surface component of the Canadian Earth System Model to improve representation of Arctic tundra ecosystems. Evaluated against 14 years of non-winter measurements, the magnitude and seasonality of carbon dioxide and energy fluxes at a Canadian dwarf-shrub tundra site were better captured by the shrub PFTs than by previously used grass and tree PFTs. Model simulations showed the tundra site to be an annual net CO2 source.
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
Short summary
Short summary
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.
Zilefac Elvis Asong, Mohamed Ezzat Elshamy, Daniel Princz, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, and Alex Cannon
Earth Syst. Sci. Data, 12, 629–645, https://doi.org/10.5194/essd-12-629-2020, https://doi.org/10.5194/essd-12-629-2020, 2020
Short summary
Short summary
This dataset provides an improved set of forcing data for large-scale hydrological models for climate change impact assessment in the Mackenzie River Basin (MRB). Here, the strengths of two historical datasets were blended to produce a less-biased long-record product for hydrological modelling and climate change impact assessment over the MRB. This product is then used to bias-correct climate projections from the Canadian Regional Climate Model under RCP8.5.
Zilefac Elvis Asong, Mohamed Elshamy, Daniel Princz, Howard Wheater, John Pomeroy, Alain Pietroniro, and Alex Cannon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-249, https://doi.org/10.5194/hess-2019-249, 2019
Publication in HESS not foreseen
Dae Il Jeong, Alex J. Cannon, and Xuebin Zhang
Nat. Hazards Earth Syst. Sci., 19, 857–872, https://doi.org/10.5194/nhess-19-857-2019, https://doi.org/10.5194/nhess-19-857-2019, 2019
Short summary
Short summary
Atmospheric ice accretion caused by freezing precipitation leads to severe damage and failure of buildings and infrastructure. This study investigates projected changes to extreme ice loads used to design infrastructure over North America for future periods of specified global mean temperature change using a Canadian regional climate model. Increases in ice accretion for latitudes higher than 40° N are substantial and would have clear implications for future building and infrastructure design.
Judith Meyer, Irene Kohn, Kerstin Stahl, Kirsti Hakala, Jan Seibert, and Alex J. Cannon
Hydrol. Earth Syst. Sci., 23, 1339–1354, https://doi.org/10.5194/hess-23-1339-2019, https://doi.org/10.5194/hess-23-1339-2019, 2019
Short summary
Short summary
Several multivariate bias correction methods have been developed recently, but only a few studies have tested the effect of multivariate bias correction on hydrological impact projections. This study shows that incorporating or ignoring inter-variable relations between air temperature and precipitation can have a notable effect on the projected snowfall fraction. The effect translated to considerable consequences for the glacio-hydrological responses and streamflow components of the catchments.
Zilefac Elvis Asong, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, Mohamed Ezzat Elshamy, Daniel Princz, and Alex Cannon
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-128, https://doi.org/10.5194/essd-2018-128, 2018
Preprint withdrawn
Short summary
Short summary
Cold regions hydrology is very sensitive to the impacts of climate warming. We need better hydrological models driven by reliable climate data in order to assess hydrologic responses to climate change. Cold regions often have sparse surface observations, particularly at high elevations that generate a major amount of runoff. We produce a long-term dataset that can be used to better understand and represent the seasonal/inter-annual variability of hydrological fluxes and the the timing of runoff.
Hui-Min Wang, Jie Chen, Alex J. Cannon, Chong-Yu Xu, and Hua Chen
Hydrol. Earth Syst. Sci., 22, 3739–3759, https://doi.org/10.5194/hess-22-3739-2018, https://doi.org/10.5194/hess-22-3739-2018, 2018
Short summary
Short summary
Facing a growing number of climate models, many selection methods were proposed to select subsets in the field of climate simulation, but the transferability of their performances to hydrological impacts remains doubtful. We investigate the transferability of climate simulation uncertainty to hydrological impacts using two selection methods, and conclude that envelope-based selection of about 10 climate simulations based on properly chosen climate variables is suggested for impact studies.
Andrew M. Snauffer, William W. Hsieh, Alex J. Cannon, and Markus A. Schnorbus
The Cryosphere, 12, 891–905, https://doi.org/10.5194/tc-12-891-2018, https://doi.org/10.5194/tc-12-891-2018, 2018
Short summary
Short summary
Estimating winter snowpack throughout British Columbia is challenging due to the complex terrain, thick forests, and high snow accumulations present. This paper describes a way to make better snow estimates by combining publicly available data using machine learning, a branch of artificial intelligence research. These improved estimates will help water resources managers better plan for changes in rivers and lakes fed by spring snowmelt and will aid other research that supports such planning.
Silvia Innocenti, Alain Mailhot, and Anne Frigon
Hydrol. Earth Syst. Sci., 21, 5823–5846, https://doi.org/10.5194/hess-21-5823-2017, https://doi.org/10.5194/hess-21-5823-2017, 2017
Short summary
Short summary
The relationship among the extreme rainfall probability distributions and the temporal scales of observation is characterized by the use of scaling models. The validity, the magnitude, and the spatial variability of the estimated scaling laws are evaluated for ~2700 stations in North America. Results demonstrate an improvement of extreme rainfall inference and provide evidence for the influence of both local geographical characteristics and regional climatic features on rainfall scaling.
Related subject area
Atmospheric, Meteorological and Climatological Hazards
Evaluation of machine learning approaches for large-scale agricultural drought forecasts to improve monitoring and preparedness in Brazil
Soil moisture–atmosphere coupling strength over central Europe in the recent warming climate
A data-driven framework for assessing climatic impact drivers in the context of food security
Soil conditioner mixtures as an agricultural management alternative to mitigate drought impacts: a proof of concept
Compound winter low-wind and cold events impacting the French electricity system: observed evolution and role of large-scale circulation
Probabilistic hazard analysis of the gas emission of Mefite d'Ansanto, southern Italy
Are heavy-rainfall events a major trigger of associated natural hazards along the German rail network?
Brief communication: Forecasting extreme precipitation from atmospheric rivers in New Zealand
The record-breaking precipitation event of December 2022 in Portugal
Compound events in Germany in 2018: drivers and case studies
Assimilation of temperature and relative humidity observations from personal weather stations in AROME-France
The anomalously thundery month of June 1925 in southwest Spain: description and synoptic analysis
Spatial identification of regions exposed to multi-hazards at the pan-European level
Classification of North Atlantic and European extratropical cyclones using multiple measures of intensity
Subseasonal forecasts of heat waves in West African cities
Impacts on and damage to European forests from the 2018–2022 heat and drought events
Brief communication: Training of AI-based nowcasting models for rainfall early warning should take into account user requirements
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?
Reconstructing hail days in Switzerland with statistical models (1959–2022)
Exploring the interplay between observed warming, atmospheric circulation, and soil-atmosphere feedbacks on heatwaves in a temperate mountain region
Classifying extratropical cyclones and their impact on Finland’s electricity grid: Insights from 92 damaging windstorms
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
Review article: The growth in compound weather events research in the decade since SREX
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
Impact-based temporal clustering of multiple meteorological hazard types in southwestern Germany
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
The miscellaneous synoptic forcings in the four-day widespread extreme rainfall event over North China in July 2023
Surprise floods: the role of our imagination in preparing for disasters
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
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
Catchment-scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan
The risk of synoptic-scale Arctic cyclones to shipping
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
Verifying the relationships among the variabilities of summer precipitation extremes over western Japan in the d4PDF climate ensemble, monsoon activity, and Pacific sea surface temperature
An appraisal of the value of simulated weather data for quantifying coastal flood hazard in the Netherlands
The usefulness of Extended-Range Probabilistic Forecasts for Heat wave forecasts in Europe
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
Joseph W. Gallear, Marcelo Valadares Galdos, Marcelo Zeri, and Andrew Hartley
Nat. Hazards Earth Syst. Sci., 25, 1521–1541, https://doi.org/10.5194/nhess-25-1521-2025, https://doi.org/10.5194/nhess-25-1521-2025, 2025
Short summary
Short summary
In Brazil, drought is of national concern and can have major consequences for agriculture. Here, we determine how to develop forecasts for drought stress on vegetation health using machine learning. Results aim to inform future developments in operational drought monitoring at the National Centre for Monitoring and Early Warning of Natural Disasters (CEMADEN) in Brazil. This information is essential for disaster preparedness and planning of future actions to support areas affected by drought.
Thomas Schwitalla, Lisa Jach, Volker Wulfmeyer, and Kirsten Warrach-Sagi
Nat. Hazards Earth Syst. Sci., 25, 1405–1424, https://doi.org/10.5194/nhess-25-1405-2025, https://doi.org/10.5194/nhess-25-1405-2025, 2025
Short summary
Short summary
During recent decades, Europe has experienced increasing periods of severe drought and heatwave. To provide an overview of how land-surface conditions shape land–atmosphere (LA) coupling, the interannual LA coupling strength variability for the summer seasons of 1991–2022 is investigated by means of ERA5 data. The results clearly reflect ongoing climate change by a shift in the coupling relationships towards reinforced heating and drying by the land surface.
Marcos Roberto Benso, Roberto Fray Silva, Gabriela Chiquito Gesualdo, Antonio Mauro Saraiva, Alexandre Cláudio Botazzo Delbem, Patricia Angélica Alves Marques, José Antonio Marengo, and Eduardo Mario Mendiondo
Nat. Hazards Earth Syst. Sci., 25, 1387–1404, https://doi.org/10.5194/nhess-25-1387-2025, https://doi.org/10.5194/nhess-25-1387-2025, 2025
Short summary
Short summary
This study applies climate extreme indices to assess climate risks to food security. Using an explainable machine learning analysis, key climate indices affecting maize and soybean yields in Brazil were identified. Results reveal the temporal sensitivity of these indices and critical yield loss thresholds, informing policy and adaptation strategies.
Juan F. Dueñas, Edda Kunze, Huiying Li, and Matthias C. Rillig
Nat. Hazards Earth Syst. Sci., 25, 1377–1386, https://doi.org/10.5194/nhess-25-1377-2025, https://doi.org/10.5194/nhess-25-1377-2025, 2025
Short summary
Short summary
We investigated the potential of adding mixtures composed of minimum dosages of several popular amendment types to soil. Our goal was to increase the resistance of agricultural soil to drought stress. We found that adding mixtures of three to five amendment types increased the capacity of soil to retain water, reduced soil erosion, and increased fungal abundance while buffering soil from drastic changes in pH. More research is encouraged to validate this approach.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
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.
Marc Lemus-Canovas, Sergi Gonzalez-Herrero, Laura Trapero, Anna Albalat, Damian Insua-Costa, Martin Senande-Rivera, and Gonzalo Miguez-Macho
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-192, https://doi.org/10.5194/nhess-2024-192, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study explores the 2022 heatwaves in the Pyrenees, examining the factors that contributed to their intensity and distribution. The June event was driven by strong winds that created uneven temperature patterns, while the July heatwave featured calmer conditions and more uniform temperatures. Human-driven climate change has made these heatwaves more severe compared to the past. This research helps us better understand how climate change affects extreme weather in mountainous regions.
Ilona Láng-Ritter, Terhi Kristiina Laurila, Antti Mäkelä, Hilppa Gregow, and VIctoria Anne SInclair
EGUsphere, https://doi.org/10.5194/egusphere-2024-3019, https://doi.org/10.5194/egusphere-2024-3019, 2024
Short summary
Short summary
We present a classification method for extratropical cyclones and windstorms and show their impacts on Finland's electricity grid by analysing 92 most damaging windstorms (2005–2018). The southwest- and northwest-originating windstorms cause the most damage to the power grid. The most relevant parameters for damage are the wind gust speed and extent of wind gusts. Windstorms are more frequent and damaging in autumn and winter, but weaker wind speeds in summer also cause significant damage.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Lou Brett, Christopher J. White, Daniela I.V. Domeisen, Bart van den Hurk, Philip Ward, and Jakob Zscheischler
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-182, https://doi.org/10.5194/nhess-2024-182, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
Compound events, where multiple weather or climate hazards occur together, pose significant risks to both society and the environment. These events, like simultaneous wind and rain, can have more severe impacts than single hazards. Our review of compound event research from 2012–2022 reveals a rise in studies, especially on events that occur concurrently, hot and dry events and compounding flooding. The review also highlights opportunities for research in the coming years.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Jinfang Yin, Feng Li, Mingxin Li, Rudi Xia, Xinghua Bao, Jisong Sun, and Xudong Liang
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-145, https://doi.org/10.5194/nhess-2024-145, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
A persistent severe rainfall event occurred over North China in July 2023, which was regarded as one of the precipitation extremes of 2023 globally. The extreme rainfall was significant underestimated by forecasters at that time. Flooding from this event affected 1.3 million people, causing severe human casualties and significant economic losses. In this study, we examined the convective initiation and subsequent persistent heavy rainfall over North China based on simulations with the WRF model.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Shao-Yi Lee, Sicheng He, and Tetsuya Takemi
EGUsphere, https://doi.org/10.5194/egusphere-2024-1304, https://doi.org/10.5194/egusphere-2024-1304, 2024
Short summary
Short summary
Summer rainfall extremes over western Japan were calculated every year, using radar, rain-gauges, and model. Similar regions were determined by machine learning. The relationships between regional rainfall extremes and Pacific climate modes. The modelled relationships were similar to the observed ones for the El Niño-Southern Oscillation and the warming trend. However, the model did not reproduce the relationship for Pacific Decadal Variability.
Cees de Valk and Henk van den Brink
EGUsphere, https://doi.org/10.5194/egusphere-2024-912, https://doi.org/10.5194/egusphere-2024-912, 2024
Short summary
Short summary
Recently updated flood safety norms in the Netherlands prescribe that sea dikes and other flood-protecting structures should withstand high sea levels reached very rarely, locally down to only once in 10 million years. We show that such levels can be estimated with reasonable accuracy by the cautious use of very large datasets of numerical simulations of weather and storm surge.
Natalia Korhonen, Otto Hyvärinen, Virpi Kollanus, Timo Lanki, Juha Jokisalo, Risto Kosonen, David S. Richardson, and Kirsti Jylhä
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-75, https://doi.org/10.5194/nhess-2024-75, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
The skill of hindcasts of the European Centre for Medium-Range Weather Forecasts in forecasting heat wave days (periods with the 5-day moving average temperature being above its local summer 90th percentile) over Europe 1 to 4 weeks ahead is examined. The heat wave days forecasts show potential in warning of heat risk in 1–2 weeks in advance, and enhanced accuracy in forecasting prolonged heat waves, in lead times of up to 3 weeks, when the heat wave had initiated prior to the forecast issuance.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Barbero, R., Fowler, H. J., Lenderink, G., and Blenkinsop, S.: Is the
intensification of precipitation extremes with global warming better detected
at hourly than daily resolutions?, Geophys. Res. Lett., 44,
974–983, https://doi.org/10.1002/2016gl071917, 2017. a
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles,
D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25∘ global
gridded precipitation (1979–2015) by merging gauge, satellite, and
reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615,
https://doi.org/10.5194/hess-21-589-2017, 2017a. a, b
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M.,
Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.:
Global-scale evaluation of 22 precipitation datasets using gauge observations
and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217,
https://doi.org/10.5194/hess-21-6201-2017, 2017b. a, b
Blanchet, J., Ceresetti, D., Molinié, G., and Creutin, J.-D.: A regional
GEV scale-invariant framework for Intensity-Duration-Frequency analysis,
J. Hydrol., 540, 82–95, https://doi.org/10.1016/j.jhydrol.2016.06.007, 2016. a
Canadian Standards Association: PLUS 4013 (2nd ed.) – Technical Guide:
Development, Interpretation and Use of Rainfall Intensity-Duration-Frequency
(IDF) Information: Guideline for Canadian Water Resources Practitioners,
Canadian Standards Association, Mississauga, Canada, 2012. a
Cannon, A. J.: Non-crossing nonlinear regression quantiles by monotone
composite quantile regression neural network, with application to rainfall
extremes, Stoch. Env. Res. Risk. A., 32,
3207–3225, https://doi.org/10.1007/s00477-018-1573-6, 2018. a
Cannon, A. J., Sobie, S. R., and Murdock, T. Q.: Bias Correction of GCM
Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in
Quantiles and Extremes?, J. Climate, 28, 6938–6959,
https://doi.org/10.1175/jcli-d-14-00754.1, 2015. a
Coles, S.: An Introduction to Statistical Modeling of Extreme Values,
Springer, London, UK, https://doi.org/10.1007/978-1-4471-3675-0, 2001. a, b
Dai, A., Rasmussen, R. M., Liu, C., Ikeda, K., and Prein, A. F.: A new
mechanism for warm-season precipitation response to global warming based on
convection-permitting simulations, Clim. Dynam.,
https://doi.org/10.1007/s00382-017-3787-6, 2017. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler,
M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J.,
Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N.,
and Vitart, F.: The ERA-Interim reanalysis: configuration and performance
of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Gupta, V. K. and Waymire, E.: Multiscaling properties of spatial rainfall and
river flow distributions, J. Geophys. Res., 95, 1999–2009,
https://doi.org/10.1029/jd095id03p01999, 1990. a
Gutowski Jr., W. J., Giorgi, F., Timbal, B., Frigon, A., Jacob, D., Kang,
H.-S., Raghavan, K., Lee, B., Lennard, C., Nikulin, G., O'Rourke, E., Rixen,
M., Solman, S., Stephenson, T., and Tangang, F.: WCRP COordinated Regional
Downscaling EXperiment (CORDEX): a diagnostic MIP for CMIP6, Geosci. Model
Dev., 9, 4087–4095, https://doi.org/10.5194/gmd-9-4087-2016, 2016. a
Hogg, W. D., Carr, D. A., and Routledge, B.: Rainfall
Intensity-Duration-Frequency Values for Canadian Locations, Tech. Rep. CLI-1-89(IDF), Atmospheric Environment Service, Environment Canada,
available at: ftp://client_climate@ftp.tor.ec.gc.ca/Pub/Engineering_Climate_Dataset/IDF/ (last access: 23 August 2017),
1989. a
Innocenti, S., Mailhot, A., and Frigon, A.: Simple scaling of extreme
precipitation in North America, Hydrol. Earth Syst. Sci., 21, 5823–5846,
https://doi.org/10.5194/hess-21-5823-2017, 2017. a, b, c
Käll, L., Storey, J. D., MacCoss, M. J., and Noble, W. S.: Posterior error
probabilities and false discovery rates: two sides of the same coin, J. Proteome Res., 7, 40–44, https://doi.org/10.1021/pr700739d, 2008. a
Kendon, E. J., Ban, N., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan,
S. C., Evans, J. P., Fosser, G., and Wilkinson, J. M.: Do
convection-permitting regional climate models improve projections of future
precipitation change?, B. Am. Meteorol. Soc., 98,
79–93, https://doi.org/10.1175/BAMS-D-15-0004.1, 2017. a
Kharin, V. V., Zwiers, F. W., Zhang, X., and Wehner, M.: Changes in temperature
and precipitation extremes in the CMIP5 ensemble, Climatic Change, 119,
345–357, https://doi.org/10.1007/s10584-013-0705-8, 2013. a, b
Kharin, V. V., Flato, G. M., Zhang, X., Gillett, N. P., Zwiers, F., and
Anderson, K. J.: Risks from Climate Extremes Change Differently from
1.5 ∘C to 2.0 ∘C Depending on Rarity, Earth's Future, 6,
704–715, https://doi.org/10.1002/2018ef000813, 2018. a, b
Koutsoyiannis, D.: Statistics of extremes and estimation of extreme rainfall:
II. Empirical investigation of long rainfall records/Statistiques de
valeurs extrêmes et estimation de précipitations extrêmes:
II. Recherche empirique sur de longues séries de
précipitations, Hydrolog. Sci. J., 49, 591–610, https://doi.org/10.1623/hysj.49.4.591.54424, 2004. a
Kruschke, J.: Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan,
2nd Edition, Academic Press, London, UK, 2015. a
Kuo, C.-C., Gan, T. Y., and Chan, S.: Regional intensity-duration-frequency
curves derived from ensemble empirical mode decomposition and scaling
property, J. Hydrol. Eng., 18, 66–74,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0000612, 2012. a
Kuo, C.-C., Gan, T. Y., and Gizaw, M.: Potential impact of climate change on
intensity duration frequency curves of central Alberta, Climatic Change,
130, 115–129, https://doi.org/10.1007/s10584-015-1347-9, 2015. a, b
Li, C., Zwiers, F., Zhang, X., and Li, G.: How much information is required to
well-constrain local estimates of future precipitation extremes?,
Earth's Future, 7, 11–24, https://doi.org/10.1029/2018ef001001, 2019. a
Lin, L., Wang, Z., Xu, Y., and Fu, Q.: Sensitivity of precipitation extremes to
radiative forcing of greenhouse gases and aerosols, Geophys. Res. Lett., 43, 9860–9868, https://doi.org/10.1002/2016gl070869, 2016. a, b
Liu, C., Ikeda, K., Rasmussen, R., Barlage, M., Newman, A. J., Prein, A. F.,
Chen, F., Chen, L., Clark, M., Dai, A., Dudhia, J., Eidhammer, T., Gochis, D., Gutmann, E., Kurkute, S., Li, Y.,
Thompson, G., and Yates, D.: Continental-scale
convection-permitting modeling of the current and future climate of North
America, Clim. Dynam., 49, 71–95, https://doi.org/10.1007/s00382-016-3327-9,
2017. a, b, c, d, e, f, g
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T.,
Lamarque, J.-F., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K.,
Thomson, A., Velders, G. J. M., and van Vuuren, D. P.: The RCP greenhouse
gas concentrations and their extensions from 1765 to 2300, Climatic Change,
109, 213–241, https://doi.org/10.1007/s10584-011-0156-z, 2011. a
Mélèse, V., Blanchet, J., and Molinié, G.: Uncertainty estimation
of Intensity-Duration-Frequency relationships: a regional analysis, J. Hydrol., 558, 579–591, https://doi.org/10.1016/j.jhydrol.2017.07.054, 2018. a, b, c
Millar, R. J., Fuglestvedt, J. S., Friedlingstein, P., Rogelj, J., Grubb,
M. J., Matthews, H. D., Skeie, R. B., Forster, P. M., Frame, D. J., and
Allen, M. R.: Emission budgets and pathways consistent with limiting warming
to 1.5 ∘C, Nat. Geosci., 10, 741–747, https://doi.org/10.1038/ngeo3031,
2017. a
Milly, P., Betancourt, J., Falkenmark, M., Hirsch, R., Kundzewicz, Z.,
Lettenmaier, D., and Stouffer, R.: Stationarity is dead: whither water
management?, Science, 319, 573–574, https://doi.org/10.1126/science.1151915, 2008. a
Min, S.-K., Zhang, X., Zwiers, F. W., and Hegerl, G. C.: Human contribution to
more-intense precipitation extremes, Nature, 470, 378–381,
https://doi.org/10.1038/nature09763, 2011. a
National Research Council: National Building Code of Canada. Canadian
Commission on Building and Fire Codes, National Research Council, Ottawa,
Canada, 2015. a
Nguyen, V., Nguyen, T., and Wang, H.: Regional estimation of short duration
rainfall extremes, Water Sci. Technol., 37, 15–19,
https://doi.org/10.1016/S0273-1223(98)00311-4, 1998. a, b
O'Gorman, P. A.: Precipitation Extremes Under Climate Change, Current Climate
Change Reports, 1, 49–59, https://doi.org/10.1007/s40641-015-0009-3, 2015. a
Ouali, D. and Cannon, A. J.: Estimation of rainfall
intensity–duration–frequency curves at ungauged
locations using quantile regression methods, Stoch. Env. Res. Risk. A., 32, 2821–2836,
https://doi.org/10.1007/s00477-018-1564-7, 2018. a
Panthou, G., Mailhot, A., Laurence, E., and Talbot, G.: Relationship between
Surface Temperature and Extreme Rainfalls: A Multi-Time-Scale and Event-Based
Analysis, J. Hydrometeorol., 15, 1999–2011,
https://doi.org/10.1175/jhm-d-14-0020.1, 2014. a
Papalexiou, S. M. and Koutsoyiannis, D.: Battle of extreme value distributions:
A global survey on extreme daily rainfall, Water Resour. Res., 49,
187–201, https://doi.org/10.1029/2012WR012557, 2013. a, b
Pendergrass, A. G.: What precipitation is extreme?, Science, 360, 1072–1073,
https://doi.org/10.1126/science.aat1871, 2018. a, b
Pendergrass, A. G., Lehner, F., Sanderson, B. M., and Xu, Y.: Does extreme
precipitation intensity depend on the emissions scenario?, Geophys. Res. Lett., 42, 8767–8774, https://doi.org/10.1002/2015gl065854, 2015. a
Pfahl, S., O'Gorman, P. A., and Fischer, E. M.: Understanding the regional
pattern of projected future changes in extreme precipitation, Nat. Clim. Change, 7, 423–427, https://doi.org/10.1038/nclimate3287, 2017. a, b
Plummer, M., Best, N., Cowles, K., and Vines, K.: CODA: convergence diagnosis
and output analysis for MCMC, R News, 6, 7–11, 2006. a
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S.,
Schmidli, J., van Lipzig, N. P. M., and Leung, R.: A review on regional
convection-permitting climate modeling: Demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014rg000475,
2015. a
Prein, A. F., Liu, C., Ikeda, K., Bullock, R., Rasmussen, R. M., Holland,
G. J., and Clark, M.: Simulating North American mesoscale convective
systems with a convection-permitting climate model, Clim. Dynam., 1–16, https://doi.org/10.1007/s00382-017-3993-2,
2017a. a
Prein, A. F., Liu, C., Ikeda, K., Trier, S. B., Rasmussen, R. M., Holland,
G. J., and Clark, M. P.: Increased rainfall volume from future convective
storms in the US, Nat. Clim. Change, 7, 880–884,
https://doi.org/10.1038/s41558-017-0007-7, 2017b. a
Raghavendra, A., Dai, A., Milrad, S. M., and Cloutier-Bisbee, S. R.: Floridian
heatwaves and extreme precipitation: future climate projections, Clim. Dynam., https://doi.org/10.1007/s00382-018-4148-9, 2018. a
Rasmussen, K. L., Prein, A. F., Rasmussen, R. M., Ikeda, K., and Liu, C.:
Changes in the convective population and thermodynamic environments in
convection-permitting regional climate simulations over the United States,
Clim. Dynam., https://doi.org/10.1007/s00382-017-4000-7, 2017. a, b, c, d
Rasmussen, R. and Liu, C.: High Resolution WRF Simulations of the Current and
Future Climate of North America, Boulder CO, https://doi.org/10.5065/D6V40SXP, 2017. a
Robinson, D.: Hypothesis Testing and FDR, in: Introduction to Empirical
Bayes: Examples from Baseball Statistics, chap. 5, ASIN: B06WP26J8Q, 212 pp., Amazon Digital Services LLC, Seattle, USA, 2017. a
Shephard, M. W., Mekis, E., Morris, R. J., Feng, Y., Zhang, X., Kilcup, K., and
Fleetwood, R.: Trends in Canadian Short-Duration Extreme Rainfall:
Including an Intensity–Duration–Frequency Perspective, Atmos. Ocean,
52, 398–417, https://doi.org/10.1080/07055900.2014.969677, 2014. a, b
Singh, M. S. and O'Gorman, P. A.: Influence of microphysics on the scaling of
precipitation extremes with temperature, Geophys. Res. Lett., 41,
6037–6044, https://doi.org/10.1002/2014gl061222, 2014. a
Spiegelhalter, D. J., Best, N. G., Carlin, B. P., and van der Linde, A.: The
deviance information criterion: 12 years on, J. R. Stat. Soc. B, 76, 485–493,
https://doi.org/10.1111/rssb.12062, 2014. a
Srivastav, R. K., Schardong, A., and Simonovic, S. P.: Equidistance quantile
matching method for updating IDF Curves under climate change, Water Resour. Manag., 28, 2539–2562, https://doi.org/10.1007/s11269-014-0626-y, 2014. a, b
Storey, J. D.: The positive false discovery rate: a Bayesian
interpretation and the q-value, Ann. Stat. 31, 2013–2035,
2003. a
Svensson, C. and Jones, D.: Review of rainfall frequency estimation methods,
J. Flood Risk. Manag., 3, 296–313,
https://doi.org/10.1111/j.1753-318x.2010.01079.x, 2010. a
Tabari, H., De Troch, R., Giot, O., Hamdi, R., Termonia, P., Saeed, S.,
Brisson, E., Van Lipzig, N., and Willems, P.: Local impact analysis of
climate change on precipitation extremes: are high-resolution climate models
needed for realistic simulations?, Hydrol. Earth Syst. Sci., 20, 3843–3857,
https://doi.org/10.5194/hess-20-3843-2016, 2016. a, b, c
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and
the Experiment Design, B. Am. Meteorol. Soc., 93,
485–498, https://doi.org/10.1175/bams-d-11-00094.1, 2012. a
Toreti, A., Naveau, P., Zampieri, M., Schindler, A., Scoccimarro, E., Xoplaki,
E., Dijkstra, H. A., Gualdi, S., and Luterbacher, J.: Projections of global
changes in precipitation extremes from Coupled Model Intercomparison Project
Phase 5 models, Geophys. Res. Lett., 40, 4887–4892,
https://doi.org/10.1002/grl.50940, 2013. a
Trenberth, K.: Changes in precipitation with climate change, Clim. Res.,
47, 123–138, https://doi.org/10.3354/cr00953, 2011. a
Van de Vyver, H.: Bayesian estimation of rainfall
intensity-duration-frequency relationships, J. Hydrol., 529,
1451–1463, https://doi.org/10.1016/j.jhydrol.2015.08.036, 2015.
a, b, c
Westra, S., Alexander, L. V., and Zwiers, F. W.: Global Increasing Trends in
Annual Maximum Daily Precipitation, J. Climate, 26, 3904–3918,
https://doi.org/10.1175/jcli-d-12-00502.1, 2013a. a
Westra, S., Evans, J. P., Mehrotra, R., and Sharma, A.: A conditional
disaggregation algorithm for generating fine time-scale rainfall data in a
warmer climate, J. Hydrol., 479, 86–99,
https://doi.org/10.1016/j.jhydrol.2012.11.033, 2013b. a
Westra, S., Fowler, H. J., Evans, J. P., Alexander, L. V., Berg, P., Johnson,
F., Kendon, E. J., Lenderink, G., and Roberts, N. M.: Future changes to the
intensity and frequency of short-duration extreme rainfall, Rev. Geophys., 52, 522–555, https://doi.org/10.1002/2014rg000464, 2014. a
Wilks, D. S.: “The Stippling Shows Statistically
Significant Grid Points”: How Research Results are
Routinely Overstated and Overinterpreted, and What to Do about It, B. Am. Meteorol. Soc., 97, 2263–2273,
https://doi.org/10.1175/bams-d-15-00267.1, 2016. a
Xie, P., Joyce, R., Wu, S., Yoo, S.-H., Yarosh, Y., Sun, F., and Lin, R.:
Reprocessed, bias-corrected CMORPH global high-resolution precipitation
estimates from 1998, J. Hydrometeorol., 18, 1617–1641,
https://doi.org/10.1175/JHM-D-16-0168.1, 2017. a, b
Zhang, X., Wan, H., Zwiers, F. W., Hegerl, G. C., and Min, S.-K.: Attributing
intensification of precipitation extremes to human influence, Geophys. Res. Lett., 40, 5252–5257, https://doi.org/10.1002/grl.51010, 2013. a
Zhang, X., Zwiers, F. W., Li, G., Wan, H., and Cannon, A. J.: Complexity in
estimating past and future extreme short-duration rainfall, Nat. Geosci., 10, 255–259, https://doi.org/10.1038/ngeo2911, 2017. a, b
Short summary
Rainfall intensity–duration–frequency (IDF) curves are used as the basis for water resource infrastructure design. Given intensification of the hydrological cycle with global warming, quantitative information on the future extreme rainfall hazard is needed by practitioners. Projected changes in annual maximum rainfall in high-resolution regional climate model simulations result in IDF curves that shift upward and steepen, with greater intensification at short durations and long return periods.
Rainfall intensity–duration–frequency (IDF) curves are used as the basis for water resource...
Altmetrics
Final-revised paper
Preprint