Articles | Volume 23, issue 1
https://doi.org/10.5194/nhess-23-21-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-21-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Jan 2023
Research article |
| 11 Jan 2023
| 11 Jan 2023
Time of emergence of compound events: contribution of univariate and dependence properties
Bastien François
CORRESPONDING AUTHOR
Laboratoire des Sciences du Climat et l’Environnement (LSCE-IPSL) CNRS/CEA/UVSQ, UMR8212, Université Paris-Saclay, Gif-sur-Yvette, France
Mathieu Vrac
Laboratoire des Sciences du Climat et l’Environnement (LSCE-IPSL) CNRS/CEA/UVSQ, UMR8212, Université Paris-Saclay, Gif-sur-Yvette, France
Related authors
Denis Allard, Mathieu Vrac, Bastien François, and Iñaki García de Cortázar-Atauri
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-102, https://doi.org/10.5194/hess-2024-102, 2024
Preprint under review for HESS
Short summary
Short summary
Atmospheric variables from climate models often present biases relative to the past. In order to use these models to assess the impact of climate change on processes of interest, it is necessary to correct these biases. We tested several Multivariate Bias Correction Methods (MBCMs) for 5 physical variables that are input variables for 4 process models. We provide recommendations regarding the use of MBCMs when multivariate and time dependent processes are involved.
Bastien François, Khalil Teber, Lou Brett, Richard Leeding, Luis Gimeno-Sotelo, Daniela I. V. Domeisen, Laura Suarez-Gutierrez, and Emanuele Bevacqua
EGUsphere, https://doi.org/10.5194/egusphere-2024-2079, https://doi.org/10.5194/egusphere-2024-2079, 2024
Short summary
Short summary
Spatially compounding wind and precipitation (CWP) extremes can lead to severe impacts on society. We find that concurrent climate variability modes favor the occurrence of such wintertime spatially compounding events in the Northern Hemisphere, and can even amplify the number of regions and population exposed. Our analysis highlights the importance of considering the interplay between variability modes to improve risk management of such spatially compounding events.
Lina Teckentrup, Martin G. De Kauwe, Gab Abramowitz, Andrew J. Pitman, Anna M. Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
Short summary
Short summary
Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
Bastien François, Mathieu Vrac, Alex J. Cannon, Yoann Robin, and Denis Allard
Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, https://doi.org/10.5194/esd-11-537-2020, 2020
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.
Denis Allard, Mathieu Vrac, Bastien François, and Iñaki García de Cortázar-Atauri
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-102, https://doi.org/10.5194/hess-2024-102, 2024
Preprint under review for HESS
Short summary
Short summary
Atmospheric variables from climate models often present biases relative to the past. In order to use these models to assess the impact of climate change on processes of interest, it is necessary to correct these biases. We tested several Multivariate Bias Correction Methods (MBCMs) for 5 physical variables that are input variables for 4 process models. We provide recommendations regarding the use of MBCMs when multivariate and time dependent processes are involved.
Bastien François, Khalil Teber, Lou Brett, Richard Leeding, Luis Gimeno-Sotelo, Daniela I. V. Domeisen, Laura Suarez-Gutierrez, and Emanuele Bevacqua
EGUsphere, https://doi.org/10.5194/egusphere-2024-2079, https://doi.org/10.5194/egusphere-2024-2079, 2024
Short summary
Short summary
Spatially compounding wind and precipitation (CWP) extremes can lead to severe impacts on society. We find that concurrent climate variability modes favor the occurrence of such wintertime spatially compounding events in the Northern Hemisphere, and can even amplify the number of regions and population exposed. Our analysis highlights the importance of considering the interplay between variability modes to improve risk management of such spatially compounding events.
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, Gianmarco Mengaldo, and Robert Vautard
Weather Clim. Dynam., 5, 959–983, https://doi.org/10.5194/wcd-5-959-2024, https://doi.org/10.5194/wcd-5-959-2024, 2024
Short summary
Short summary
We introduce ClimaMeter, a tool offering real-time insights into extreme-weather events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analysed two distinct events, showcasing ClimaMeter's global relevance.
Mathieu Vrac, Denis Allard, Grégoire Mariéthoz, Soulivanh Thao, and Lucas Schmutz
Earth Syst. Dynam., 15, 735–762, https://doi.org/10.5194/esd-15-735-2024, https://doi.org/10.5194/esd-15-735-2024, 2024
Short summary
Short summary
We aim to combine multiple global climate models (GCMs) to enhance the robustness of future projections. We introduce a novel approach, called "α pooling", aggregating the cumulative distribution functions (CDFs) of the models into a CDF more aligned with historical data. The new CDFs allow us to perform bias adjustment of all the raw climate simulations at once. Experiments with European temperature and precipitation demonstrate the superiority of this approach over conventional techniques.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Proc. IAHS, 385, 121–127, https://doi.org/10.5194/piahs-385-121-2024, https://doi.org/10.5194/piahs-385-121-2024, 2024
Short summary
Short summary
This study assesses the impact of climate change on the timing, seasonality and magnitude of mean annual minimum (MAM) flows and annual maximum flows (AMF) in the Volta River basin (VRB). Several climate change projection data are use to simulate river flow under multiple greenhouse gas emission scenarios. Future projections show that AMF could increase with various magnitude but negligible shift in time across the VRB, while MAM could decrease with up to 14 days of delay in occurrence.
Lina Teckentrup, Martin G. De Kauwe, Gab Abramowitz, Andrew J. Pitman, Anna M. Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
Short summary
Short summary
Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
Cedric Gacial Ngoungue Langue, Christophe Lavaysse, Mathieu Vrac, and Cyrille Flamant
Nat. Hazards Earth Syst. Sci., 23, 1313–1333, https://doi.org/10.5194/nhess-23-1313-2023, https://doi.org/10.5194/nhess-23-1313-2023, 2023
Short summary
Short summary
Heat waves (HWs) are climatic hazards that affect the planet. We assess here uncertainties encountered in the process of HW detection and analyse their recent trends in West Africa using reanalysis data. Three types of uncertainty have been investigated. We identified 6 years with higher frequency of HWs, possibly due to higher sea surface temperatures in the equatorial Atlantic. We noticed an increase in HW characteristics during the last decade, which could be a consequence of climate change.
Antoine Grisart, Mathieu Casado, Vasileios Gkinis, Bo Vinther, Philippe Naveau, Mathieu Vrac, Thomas Laepple, Bénédicte Minster, Frederic Prié, Barbara Stenni, Elise Fourré, Hans Christian Steen-Larsen, Jean Jouzel, Martin Werner, Katy Pol, Valérie Masson-Delmotte, Maria Hoerhold, Trevor Popp, and Amaelle Landais
Clim. Past, 18, 2289–2301, https://doi.org/10.5194/cp-18-2289-2022, https://doi.org/10.5194/cp-18-2289-2022, 2022
Short summary
Short summary
This paper presents a compilation of high-resolution (11 cm) water isotopic records, including published and new measurements, for the last 800 000 years from the EPICA Dome C ice core, Antarctica. Using this new combined water isotopes (δ18O and δD) dataset, we study the variability and possible influence of diffusion at the multi-decadal to multi-centennial scale. We observe a stronger variability at the onset of the interglacial interval corresponding to a warm period.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022, https://doi.org/10.5194/hess-26-1481-2022, 2022
Short summary
Short summary
Climate change impacts on water resources in the Volta River basin are investigated under various global warming scenarios. Results reveal contrasting changes in future hydrological processes and water availability, depending on greenhouse gas emission scenarios, with implications for floods and drought occurrence over the 21st century. These findings provide insights for the elaboration of regional adaptation and mitigation strategies for climate change.
Yoann Robin and Mathieu Vrac
Earth Syst. Dynam., 12, 1253–1273, https://doi.org/10.5194/esd-12-1253-2021, https://doi.org/10.5194/esd-12-1253-2021, 2021
Short summary
Short summary
We propose a new multivariate downscaling and bias correction approach called
time-shifted multivariate bias correction, which aims to correct temporal dependencies in addition to inter-variable and spatial ones. Our method is evaluated in a
perfect model experimentcontext where simulations are used as pseudo-observations. The results show a large reduction of the biases in the temporal properties, while inter-variable and spatial dependence structures are still correctly adjusted.
Cedric G. Ngoungue Langue, Christophe Lavaysse, Mathieu Vrac, Philippe Peyrillé, and Cyrille Flamant
Weather Clim. Dynam., 2, 893–912, https://doi.org/10.5194/wcd-2-893-2021, https://doi.org/10.5194/wcd-2-893-2021, 2021
Short summary
Short summary
This work assesses the forecast of the temperature over the Sahara, a key driver of the West African Monsoon, at a seasonal timescale. The seasonal models are able to reproduce the climatological state and some characteristics of the temperature during the rainy season in the Sahel. But, because of errors in the timing, the forecast skill scores are significant only for the first 4 weeks.
Anna Denvil-Sommer, Marion Gehlen, and Mathieu Vrac
Ocean Sci., 17, 1011–1030, https://doi.org/10.5194/os-17-1011-2021, https://doi.org/10.5194/os-17-1011-2021, 2021
Short summary
Short summary
In this work we explored design options for a future Atlantic-scale observational network enabling the release of carbon system estimates by combining data streams from various platforms. We used outputs of a physical–biogeochemical global ocean model at sites of real-world observations to reconstruct surface ocean pCO2 by applying a non-linear feed-forward neural network. The results provide important information for future BGC-Argo deployment, i.e. important regions and the number of floats.
Mathieu Vrac and Soulivanh Thao
Geosci. Model Dev., 13, 5367–5387, https://doi.org/10.5194/gmd-13-5367-2020, https://doi.org/10.5194/gmd-13-5367-2020, 2020
Short summary
Short summary
We propose a multivariate bias correction (MBC) method to adjust the spatial and/or inter-variable properties of climate simulations, while also accounting for their temporal dependences (e.g., autocorrelations).
It consists on a method reordering the ranks of the time series according to their multivariate distance to a reference time series.
Results show that temporal correlations are improved while spatial and inter-variable correlations are still satisfactorily corrected.
Emanuele Bevacqua, Michalis I. Vousdoukas, Theodore G. Shepherd, and Mathieu Vrac
Nat. Hazards Earth Syst. Sci., 20, 1765–1782, https://doi.org/10.5194/nhess-20-1765-2020, https://doi.org/10.5194/nhess-20-1765-2020, 2020
Short summary
Short summary
Coastal compound flooding (CF), caused by interacting storm surges and high water runoff, is typically studied based on concurring storm surge extremes with either precipitation or river discharge extremes. Globally, these two approaches show similar CF spatial patterns, especially where the CF potential is the highest. Deviations between the two approaches increase with the catchment size. The precipitation-based analysis allows for considering
local-rainfall-driven CF and CF in small rivers.
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.
Eric Pohl, Christophe Grenier, Mathieu Vrac, and Masa Kageyama
Hydrol. Earth Syst. Sci., 24, 2817–2839, https://doi.org/10.5194/hess-24-2817-2020, https://doi.org/10.5194/hess-24-2817-2020, 2020
Short summary
Short summary
Existing approaches to quantify the emergence of climate change require several user choices that make these approaches less objective. We present an approach that uses a minimum number of choices and showcase its application in the extremely sensitive, permafrost-dominated region of eastern Siberia. Designed as a Python toolbox, it allows for incorporating climate model, reanalysis, and in situ data to make use of numerous existing data sources and reduce uncertainties in obtained estimates.
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 24, 2841–2854, https://doi.org/10.5194/hess-24-2841-2020, https://doi.org/10.5194/hess-24-2841-2020, 2020
Short summary
Short summary
At subdaily resolution, rain intensity exhibits a strong variability in space and time due to the diversity of processes that produce rain (e.g., frontal storms, mesoscale convective systems and local convection). In this paper we explore a new method to simulate rain type time series conditional to meteorological covariates. Afterwards, we apply stochastic rain type simulation to the downscaling of precipitation of a regional climate model.
Florentin Breton, Mathieu Vrac, Pascal Yiou, Pradeebane Vaittinada Ayar, and Aglaé Jézéquel
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-26, https://doi.org/10.5194/esd-2020-26, 2020
Revised manuscript not accepted
Short summary
Short summary
We investigate North Atlantic weather seasonality over 1979–2100 by classifying year-round fields of 500 hPa geopotential height from one reanalysis dataset and 12 climate models. Generally, models have seasonal structures similar to the reanalyses. Historical winter (summer) conditions decrease (increase), due to uniform Z500 increase (i.e. uniform warming). However, relative to the increasing Z500 seasonal cycle, future seasonality (spatial patterns, seasonal cycle) appears almost stationary.
Giulia Carella, Mathieu Vrac, Hélène Brogniez, Pascal Yiou, and Hélène Chepfer
Earth Syst. Sci. Data, 12, 1–20, https://doi.org/10.5194/essd-12-1-2020, https://doi.org/10.5194/essd-12-1-2020, 2020
Short summary
Short summary
Observations of relative humidity for ice clouds over the tropical oceans from a passive microwave sounder are downscaled by incorporating the high-resolution variability derived from simultaneous co-located cloud profiles from a lidar. By providing a method to generate pseudo-observations of relative humidity at high spatial resolution, this work will help revisit some of the current key barriers in atmospheric science.
Anna Denvil-Sommer, Marion Gehlen, Mathieu Vrac, and Carlos Mejia
Geosci. Model Dev., 12, 2091–2105, https://doi.org/10.5194/gmd-12-2091-2019, https://doi.org/10.5194/gmd-12-2091-2019, 2019
Short summary
Short summary
This work is dedicated to a new model that reconstructs the surface ocean partial pressure of carbon dioxide (pCO2) over the global ocean on a monthly 1°×1° grid. The model is based on a feed-forward neural network and represents the nonlinear relationships between pCO2 and the ocean drivers. Reconstructed pCO2 has a satisfying accuracy compared to independent observational data and shows a good agreement in seasonal and interannual variability with three existing mapping methods.
Yoann Robin, Mathieu Vrac, Philippe Naveau, and Pascal Yiou
Hydrol. Earth Syst. Sci., 23, 773–786, https://doi.org/10.5194/hess-23-773-2019, https://doi.org/10.5194/hess-23-773-2019, 2019
Short summary
Short summary
Bias correction methods are used to calibrate climate model outputs with respect to observations. In this article, a non-stationary, multivariate and stochastic bias correction method is developed based on optimal transport, accounting for inter-site and inter-variable correlations. Optimal transport allows us to construct a joint distribution that minimizes energy spent in bias correction. Our methodology is tested on precipitation and temperatures over 12 locations in southern France.
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 22, 5919–5933, https://doi.org/10.5194/hess-22-5919-2018, https://doi.org/10.5194/hess-22-5919-2018, 2018
Short summary
Short summary
We propose a method for unsupervised classification of the space–time–intensity structure of weather radar images. The resulting classes are interpreted as rain types, i.e. pools of rain fields with homogeneous statistical properties. Rain types can in turn be used to define stationary periods for further stochastic rainfall modelling. The application of rain typing to real data indicates that non-stationarity can be significant within meteorological seasons, and even within a single storm.
Claire Waelbroeck, Sylvain Pichat, Evelyn Böhm, Bryan C. Lougheed, Davide Faranda, Mathieu Vrac, Lise Missiaen, Natalia Vazquez Riveiros, Pierre Burckel, Jörg Lippold, Helge W. Arz, Trond Dokken, François Thil, and Arnaud Dapoigny
Clim. Past, 14, 1315–1330, https://doi.org/10.5194/cp-14-1315-2018, https://doi.org/10.5194/cp-14-1315-2018, 2018
Short summary
Short summary
Recording the precise timing and sequence of events is essential for understanding rapid climate changes and improving climate model predictive skills. Here, we precisely assess the relative timing between ocean and atmospheric changes, both recorded in the same deep-sea core over the last 45 kyr. We show that decreased mid-depth water mass transport in the western equatorial Atlantic preceded increased rainfall over the adjacent continent by 120 to 980 yr, depending on the type of climate event.
Guillaume Latombe, Ariane Burke, Mathieu Vrac, Guillaume Levavasseur, Christophe Dumas, Masa Kageyama, and Gilles Ramstein
Geosci. Model Dev., 11, 2563–2579, https://doi.org/10.5194/gmd-11-2563-2018, https://doi.org/10.5194/gmd-11-2563-2018, 2018
Short summary
Short summary
It is still unclear how climate conditions, and especially climate variability, influenced the spatial distribution of past human populations. Global climate models (GCMs) cannot simulate climate at sufficiently fine scale for this purpose. We propose a statistical method to obtain fine-scale climate projections for 15 000 years ago from coarse-scale GCM outputs. Our method agrees with local reconstructions from fossil and pollen data, and generates sensible climate variability maps over Europe.
Mathieu Vrac
Hydrol. Earth Syst. Sci., 22, 3175–3196, https://doi.org/10.5194/hess-22-3175-2018, https://doi.org/10.5194/hess-22-3175-2018, 2018
Short summary
Short summary
This study presents a multivariate bias correction method named R2D2 to adjust both the 1d-distributions and inter-variable/site dependence structures of climate simulations in a high-dimensional context, while providing some stochasticity. R2D2 is tested on temperature and precipitation reanalyses and illustrated on future simulations. In both cases, R2D2 is able to correct the spatial and physical dependence, opening proper use of climate simulations for impact (e.g. hydrological) models.
Adjoua Moise Famien, Serge Janicot, Abe Delfin Ochou, Mathieu Vrac, Dimitri Defrance, Benjamin Sultan, and Thomas Noël
Earth Syst. Dynam., 9, 313–338, https://doi.org/10.5194/esd-9-313-2018, https://doi.org/10.5194/esd-9-313-2018, 2018
Short summary
Short summary
This study uses the cumulative distribution function transform (CDF-t) method to provide bias-corrected data over Africa using WFDEI as a reference dataset. It is shown that CDF-t is very effective in removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets, particularly for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields.
Emanuele Bevacqua, Douglas Maraun, Ingrid Hobæk Haff, Martin Widmann, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, https://doi.org/10.5194/hess-21-2701-2017, 2017
Short summary
Short summary
We develop a conceptual model to quantify the risk of compound events (CEs), i.e. extreme impacts to society which are driven by statistically dependent climatic variables. Based on this model we study compound floods, i.e. joint storm surge and high river level, in Ravenna (Italy). The model includes meteorological predictors which (1) provide insight into the physical processes underlying CEs, as well as into the temporal variability, and (2) allow us to statistically downscale CEs.
Pascal Yiou, Aglaé Jézéquel, Philippe Naveau, Frederike E. L. Otto, Robert Vautard, and Mathieu Vrac
Adv. Stat. Clim. Meteorol. Oceanogr., 3, 17–31, https://doi.org/10.5194/ascmo-3-17-2017, https://doi.org/10.5194/ascmo-3-17-2017, 2017
Short summary
Short summary
The attribution of classes of extreme events, such as heavy precipitation or heatwaves, relies on the estimate of small probabilities (with and without climate change). Such events are connected to the large-scale atmospheric circulation. This paper links such probabilities with properties of the atmospheric circulation by using a Bayesian decomposition. We test this decomposition on a case of extreme precipitation in the UK, in January 2014.
Claudia Volosciuk, Douglas Maraun, Mathieu Vrac, and Martin Widmann
Hydrol. Earth Syst. Sci., 21, 1693–1719, https://doi.org/10.5194/hess-21-1693-2017, https://doi.org/10.5194/hess-21-1693-2017, 2017
Short summary
Short summary
For impact modeling, infrastructure design, or adaptation strategy planning, high-quality climate data on the point scale are often demanded. Due to the scale gap between gridbox and point scale and biases in climate models, we combine a statistical bias correction and a stochastic downscaling model and apply it to climate model-simulated precipitation. The method performs better in summer than in winter and in winter best for mild winter climate (Mediterranean) and worst for continental winter.
Jérôme Pernin, Mathieu Vrac, Cyril Crevoisier, and Alain Chédin
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 115–136, https://doi.org/10.5194/ascmo-2-115-2016, https://doi.org/10.5194/ascmo-2-115-2016, 2016
Short summary
Short summary
Here, we propose a classification methodology of various space-time atmospheric datasets into discrete air mass groups homogeneous in temperature and humidity through a probabilistic point of view: both the classification process and the data are probabilistic. Unlike conventional classification algorithms, this methodology provides the probability of belonging to each class as well as the corresponding uncertainty, which can be used in various applications.
Benjamin Grouillet, Denis Ruelland, Pradeebane Vaittinada Ayar, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 20, 1031–1047, https://doi.org/10.5194/hess-20-1031-2016, https://doi.org/10.5194/hess-20-1031-2016, 2016
Short summary
Short summary
This original paper provides a guideline to select statistical downscaling methods (SDMs) in climate change impact studies (CCIS) to minimize uncertainty from downscaling. Three SDMs were applied to NCEP reanalysis and 2 GCM data values. We then analyzed the sensitivity of the hydrological model to the various downscaled data via 5 hydrological indicators representing the main features of the hydrograph. Our results enable selection of the appropriate SDMs to be used to build climate scenarios.
P. Yiou, M. Boichu, R. Vautard, M. Vrac, S. Jourdain, E. Garnier, F. Fluteau, and L. Menut
Clim. Past, 10, 797–809, https://doi.org/10.5194/cp-10-797-2014, https://doi.org/10.5194/cp-10-797-2014, 2014
Related subject area
Atmospheric, Meteorological and Climatological Hazards
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
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
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
Interannual variations in the seasonal cycle of extreme precipitation in Germany and the response to climate change
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
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
GTDI: a gaming integrated drought index implying hazard causing and bearing impacts changing
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
Insurance loss model vs meteorological loss index – How comparable are their loss estimates for European windstorms?
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
Intense rains in Israel associated with the 'Train effect'
On the potential of using smartphone sensors for wildfire hazard estimation
Return levels of extreme European windstorms, their dependency on the North Atlantic Oscillation, and potential future risks
Wind as a natural hazard in Poland
Climatological occurrences of hail and tornadoes associated with mesoscale convective systems in the United States
Characteristics of cloud-to-ground lightning (CG) and differences between +CG and −CG strokes in China regarding the China National Lightning Detection Network
The climatology and nature of warm-season convective cells in cold-frontal environments over Germany
Forecasting large hail and lightning using additive logistic regression models and the ECMWF reforecasts
The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model
Shallow and deep learning of extreme rainfall events from convective atmospheres
Linking reported drought impacts with drought indices, water scarcity and aridity: the case of Kenya
Future heat extremes and impacts in a convection-permitting climate ensemble over Germany
Assessment of subseasonal-to-seasonal (S2S) ensemble extreme precipitation forecast skill over Europe
A long record of European windstorm losses and its comparison to standard climate indices
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.
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.
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
The present study uses daily insurance losses and wind speeds to fit storm damage functions at the municipality level of Norway. The results show that the damage functions accurately estimate losses associated with extreme damaging events and can reconstruct their spatial patterns. However, there is no single damage function that performs better than another. A newly devised damage–no-damage classifier shows some skill in predicting extreme damaging events.
Madlen Peter, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 24, 1261–1285, https://doi.org/10.5194/nhess-24-1261-2024, https://doi.org/10.5194/nhess-24-1261-2024, 2024
Short summary
Short summary
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.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
EGUsphere, https://doi.org/10.5194/egusphere-2024-322, https://doi.org/10.5194/egusphere-2024-322, 2024
Short summary
Short summary
A computer model that simulates the climate of south-eastern 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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-45, https://doi.org/10.5194/nhess-2024-45, 2024
Revised manuscript accepted for NHESS
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 to a single meteorological drought index or agricultural drought index in drought identification.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-16, https://doi.org/10.5194/nhess-2024-16, 2024
Revised manuscript accepted for NHESS
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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 under review for NHESS
Short summary
Short summary
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.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-215, https://doi.org/10.5194/nhess-2023-215, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
'Train effect' is related to convective cells that pass over the same place. Trains produce heavy rainfall, sometimes floods, and reported in N. America during spring and summer. In Israel, 17 trains were identified by radar images, associated with Cyprus Lows, sharing the following features: Found at the cold sector south of the low center, at the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km, last 1–3 hours and yield 35 mm rainfall, up to 60 mm.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-211, https://doi.org/10.5194/nhess-2023-211, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
We have used the temperature and relative humidity sensors in smartphones to estimate the Vapor Pressure Deficit (VPD), and important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal show the potential for using smartphone data to both compliment the regular weather station network, while also providing high spatial resolution of the VPD index.
Matthew D. K. Priestley, David B. Stephenson, Adam A. Scaife, Daniel Bannister, Christopher J. T. Allen, and David Wilkie
Nat. Hazards Earth Syst. Sci., 23, 3845–3861, https://doi.org/10.5194/nhess-23-3845-2023, https://doi.org/10.5194/nhess-23-3845-2023, 2023
Short summary
Short summary
This research presents a model for estimating extreme gusts associated with European windstorms. Using observed storm footprints we are able to calculate the return level of events at the 200-year return period. The largest gusts are found across NW Europe, and these are larger when the North Atlantic Oscillation is positive. Using theoretical future climate states we find that return levels are likely to increase across NW Europe to levels that are unprecedented compared to historical storms.
Tadeusz Chmielewski and Piotr A. Bońkowski
Nat. Hazards Earth Syst. Sci., 23, 3839–3844, https://doi.org/10.5194/nhess-23-3839-2023, https://doi.org/10.5194/nhess-23-3839-2023, 2023
Short summary
Short summary
The paper deals with wind speeds of extreme wind events in Poland and the descriptions of their effects. Two recent estimations developed by the Institute of Meteorology and Water Management in Warsaw and by Halina Lorenc are presented and briefly described. The 37 annual maximum gusts of wind speeds measured between 1971 and 2007 are analysed. Based on the measured and estimated wind speeds, the authors suggest new estimations for extreme winds that may occur in Poland.
Jingyu Wang, Jiwen Fan, and Zhe Feng
Nat. Hazards Earth Syst. Sci., 23, 3823–3838, https://doi.org/10.5194/nhess-23-3823-2023, https://doi.org/10.5194/nhess-23-3823-2023, 2023
Short summary
Short summary
Hail and tornadoes are devastating hazards responsible for significant property damage and economic losses in the United States. Quantifying the connection between hazard events and mesoscale convective systems (MCSs) is of great significance for improving predictability, as well as for better understanding the influence of the climate-scale perturbations. A 14-year statistical dataset of MCS-related hazard production is presented.
Ruijiao Jiang, Guoping Zhang, Shudong Wang, Bing Xue, Zhengshuai Xie, Tingzhao Yu, Kuoyin Wang, Jin Ding, and Xiaoxiang Zhu
Nat. Hazards Earth Syst. Sci., 23, 3747–3759, https://doi.org/10.5194/nhess-23-3747-2023, https://doi.org/10.5194/nhess-23-3747-2023, 2023
Short summary
Short summary
Lightning activity in China is analyzed. Low latitudes, undulating terrain, seaside, and humid surfaces are beneficial for lightning occurrence. Summer of the year or afternoon of the day is the high period. Large cloud-to-ground lightning frequency always corresponds to a small ratio and weak intensity of positive cloud-to-ground lightning on either a temporal or spatial scale. Interestingly, the discharge intensity difference between the two types of lightning shrinks on the Tibetan Plateau.
George Pacey, Stephan Pfahl, Lisa Schielicke, and Kathrin Wapler
Nat. Hazards Earth Syst. Sci., 23, 3703–3721, https://doi.org/10.5194/nhess-23-3703-2023, https://doi.org/10.5194/nhess-23-3703-2023, 2023
Short summary
Short summary
Cold fronts are often associated with areas of intense precipitation (cells) and sometimes with hazards such as flooding, hail and lightning. We find that cold-frontal cell days are associated with higher cell frequency and cells are typically more intense. We also show both spatially and temporally where cells are most frequent depending on their cell-front distance. These results are an important step towards a deeper understanding of cold-frontal storm climatology and improved forecasting.
Francesco Battaglioli, Pieter Groenemeijer, Ivan Tsonevsky, and Tomàš Púčik
Nat. Hazards Earth Syst. Sci., 23, 3651–3669, https://doi.org/10.5194/nhess-23-3651-2023, https://doi.org/10.5194/nhess-23-3651-2023, 2023
Short summary
Short summary
Probabilistic models for lightning and large hail were developed across Europe using lightning observations and hail reports. These models accurately predict the occurrence of lightning and large hail several days in advance. In addition, the hail model was shown to perform significantly better than the state-of-the-art forecasting methods. These results suggest that the models developed in this study may help improve forecasting of convective hazards and eventually limit the associated risks.
Rosa Claudia Torcasio, Alessandra Mascitelli, Eugenio Realini, Stefano Barindelli, Giulio Tagliaferro, Silvia Puca, Stefano Dietrich, and Stefano Federico
Nat. Hazards Earth Syst. Sci., 23, 3319–3336, https://doi.org/10.5194/nhess-23-3319-2023, https://doi.org/10.5194/nhess-23-3319-2023, 2023
Short summary
Short summary
This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.
Gerd Bürger and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 3065–3077, https://doi.org/10.5194/nhess-23-3065-2023, https://doi.org/10.5194/nhess-23-3065-2023, 2023
Short summary
Short summary
Our subject is a new catalogue of radar-based heavy rainfall events (CatRaRE) over Germany and how it relates to the concurrent atmospheric circulation. We classify reanalyzed daily atmospheric fields of convective indices according to CatRaRE, using conventional statistical and more recent machine learning algorithms, and apply them to present and future atmospheres. Increasing trends are projected for CatRaRE-type probabilities, from reanalyzed as well as from simulated atmospheric fields.
Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling
Nat. Hazards Earth Syst. Sci., 23, 2915–2936, https://doi.org/10.5194/nhess-23-2915-2023, https://doi.org/10.5194/nhess-23-2915-2023, 2023
Short summary
Short summary
There is still no full understanding of the relation between drought impacts and drought indices in the Horn of Africa where water scarcity and arid regions are also present. This study assesses their relation in Kenya. A random forest model reveals that each region, aggregated by aridity, has its own set of predictors for every impact category. Water scarcity was not found to be related to aridity. Understanding these relations contributes to the development of drought early warning systems.
Marie Hundhausen, Hendrik Feldmann, Natalie Laube, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 23, 2873–2893, https://doi.org/10.5194/nhess-23-2873-2023, https://doi.org/10.5194/nhess-23-2873-2023, 2023
Short summary
Short summary
Using a convection-permitting regional climate ensemble, the magnitude of heat waves (HWs) over Germany is projected to increase by 26 % (100 %) in a 2 °C (3 °C) warmer world. The increase is strongest in late summer, relatively homogeneous in space, and accompanied by increasing variance in HW length. Tailored parameters to climate adaptation to heat revealed dependency on major landscapes, and a nonlinear, exponential increase for parameters characterizing strong heat stress is expected.
Pauline Rivoire, Olivia Martius, Philippe Naveau, and Alexandre Tuel
Nat. Hazards Earth Syst. Sci., 23, 2857–2871, https://doi.org/10.5194/nhess-23-2857-2023, https://doi.org/10.5194/nhess-23-2857-2023, 2023
Short summary
Short summary
Heavy precipitation can lead to floods and landslides, resulting in widespread damage and significant casualties. Some of its impacts can be mitigated if reliable forecasts and warnings are available. In this article, we assess the capacity of the precipitation forecast provided by ECMWF to predict heavy precipitation events on a subseasonal-to-seasonal (S2S) timescale over Europe. We find that the forecast skill of such events is generally higher in winter than in summer.
Stephen Cusack
Nat. Hazards Earth Syst. Sci., 23, 2841–2856, https://doi.org/10.5194/nhess-23-2841-2023, https://doi.org/10.5194/nhess-23-2841-2023, 2023
Short summary
Short summary
The link from European windstorm research findings to insurance applications is strengthened by a new storm loss history spanning 1950 to 2022. It is based on ERA5 winds, together with long-term trends from observed gusts for improved validation. Correlations between losses and climate indices are around 0.4 for interannual variations, rising to 0.7 for decadal variations. A significant divergence between standard climate indices and storm losses over the past 20 years needs further research.
Cited articles
Abatzoglou, J. T., Dobrowski, S. Z., and Parks, S. A.: Multivariate climate
departures have outpaced univariate changes across global lands, Sci. Rep.,
10, 3891, https://doi.org/10.1038/s41598-020-60270-5, 2020. a
Bevacqua, E., Maraun, D., Hobæk Haff, I., Widmann, M., and Vrac, M.: Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy), Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, 2017. a
Bevacqua, E., Maraun, D., Vousdoukas, M. I., Voukouvalas, E., Vrac, M.,
Mentaschi, L., and Widmann, M.: Higher probability of compound flooding from
precipitation and storm surge in Europe under anthropogenic climate change,
Sci. Adv., 5, eaaw5531, https://doi.org/10.1126/sciadv.aaw5531, 2019. a, b, c, d
Bevacqua, E., De Michele, C., Manning, C., Couasnon, A., Ribeiro, A. F. S.,
Ramos, A. M., Vignotto, E., Bastos, A., Blesic, S., Durante, F., et al.:
Bottom-up identification of key elements of compound events, ESS Open Archive [preprint], 29, https://doi.org/10.1002/essoar.10507809.1, 23 August 2021. a
Bevacqua, E., Zappa, G., Lehner, F., and Zscheischler, J.: Precipitation trends
determine future occurrences of compound hot–dry events, Nat. Clim. Chang., 12, 350–355,
https://doi.org/10.1038/s41558-022-01309-5, 2022. a
Bindoff, N., Stott, P., AchutaRao, K., Allen, M., Gillett, N., Gutzler, D.,
Hansingo, K., Hegerl, G., Hu, Y., Jain, S., Mokhov, I., Overland, J.,
Perlwitz, J., Sebbari, R., and Zhang, X.: Detection and Attribution of
Climate Change: from Global to Regional, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M. Allen,
S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Sect. 10,
Cambridge University Press, pp. 867–952, https://doi.org/10.1017/CBO9781107415324.022, 2013. a
Bonhomme, R.: Bases and limits to using ‘degree.day’ units, Eur. J. Agron.,
13, 1–10, https://doi.org/10.1016/S1161-0301(00)00058-7, 2000. a
Boucher, O., Denvil, S., Levavasseur, G., Cozic, A., Caubel, A., Foujols,
M.-A., Meurdesoif, Y., Cadule, P., Devilliers, M., Ghattas, J., Lebas, N.,
Lurton, T., Mellul, L., Musat, I., Mignot, J., and Cheruy, F.: IPSL
IPSL-CM6A-LR model output prepared for CMIP6 CMIP,
https://doi.org/10.22033/ESGF/CMIP6.1534, 2018. a
Brunner, M. I., Swain, D. L., Gilleland, E., and Wood, A. W.: Increasing
importance of temperature as a contributor to the spatial extent of
streamflow drought, Environ. Res. Lett., 16, 024038,
https://doi.org/10.1088/1748-9326/abd2f0, 2021. a
Calafat, F. M., Wahl, T., Tadesse, M. G., and Sparrow, S. N.: Trends in Europe
storm surge extremes match the rate of sea-level rise, Nature, 603,
841–845, https://doi.org/10.1038/s41586-022-04426-5, 2022. a
Cannon, A. J.: Multivariate quantile mapping bias correction: an
N-dimensional probability density function transform for climate model
simulations of multiple variables, Clim. Dynam., 50, 31–49,
https://doi.org/10.1007/s00382-017-3580-6, 2018. a, b
Cherchi, A., Fogli, P. G., Lovato, T., Peano, D., Iovino, D., Gualdi, S.,
Masina, S., Scoccimarro, E., Materia, S., Bellucci, A., and Navarra, A.:
Global Mean Climate and Main Patterns of Variability in the CMCC-CM2 Coupled
Model, J. Adv. Model. Earth Syst., 11, 185–209, https://doi.org/10.1029/2018MS001369,
2019. a
Chiang, F., Greve, P., Mazdiyasni, O., Wada, Y., and AghaKouchak, A.: A
Multivariate Conditional Probability Ratio Framework for the Detection and
Attribution of Compound Climate Extremes, Geophys. Res. Lett., 48,
e2021GL094361, https://doi.org/10.1029/2021GL094361, 2021. a
Christensen, J., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I., Jones,
R., Kolli, R., Kwon, W.-T., Laprise, R., Rueda, V., Mearns, L., Menéndez,
C., Räisänen, J., Rinke, A., Sarr, A., and Whetton, P.: Regional climate
projections. Climate change 2007: The physical science basis, Contribution
of Working Group I to the Fourth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and
Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY,
USA, pp. 847–940, ISBN: 978-0-521-88009-1, 2007. a
De Luca, P., Messori, G., Pons, F. M. E., and Faranda, D.: Dynamical systems
theory sheds new light on compound climate extremes in Europe and Eastern
North America, Q. J. Roy. Meteor. Soc., 146, 1636–1650,
https://doi.org/10.1002/qj.3757, 2020a. a
De Luca, P., Messori, G., Wilby, R. L., Mazzoleni, M., and Di Baldassarre, G.: Concurrent wet and dry hydrological extremes at the global scale, Earth Syst. Dynam., 11, 251–266, https://doi.org/10.5194/esd-11-251-2020, 2020b. a
Diffenbaugh, N. and Scherer, M.: Observational and model evidence of global
emergence of permanent, unprecedented heat in the 20th and 21st centuries,
Clim. Change, 107, 615–624, https://doi.org/10.1007/s10584-011-0112-y, 2011. a
Diffenbaugh, N. S., Swain, D. L., and Touma, D.: Anthropogenic warming has
increased drought risk in California, Proc. Natl. Acad. Sci. USA, 112,
3931–3936, https://doi.org/10.1073/pnas.1422385112, 2015. a
EC-Earth: EC-Earth-Consortium EC-Earth3 model output prepared for CMIP6
ScenarioMIP ssp585, https://doi.org/10.22033/ESGF/CMIP6.4912, 2019. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Faranda, D., Vrac, M., Yiou, P., Jézéquel, A., and Thao, S.: Changes in
Future Synoptic Circulation Patterns: Consequences for Extreme Event
Attribution, Geophys. Res. Lett., 47, e2020GL088002,
https://doi.org/10.1029/2020GL088002, 2020. a
Fink, A. H., Brücher, T., Ermert, V., Krüger, A., and Pinto, J. G.: The European storm Kyrill in January 2007: synoptic evolution, meteorological impacts and some considerations with respect to climate change, Nat. Hazards Earth Syst. Sci., 9, 405–423, https://doi.org/10.5194/nhess-9-405-2009, 2009. a
Fischer, E. M., Sedláček, J., Hawkins, E., and Knutti, R.: Models agree on
forced response pattern of precipitation and temperature extremes, Geophys.
Res. Lett., 41, 8554–8562, https://doi.org/10.1002/2014GL062018, 2014. a, b
Frame, D., Joshi, M., Hawkins, E., Harrington, L., and Róiste, M.:
Population-based emergence of unfamiliar climates, Nat. Clim. Chang., 7,
407–411, https://doi.org/10.1038/nclimate3297, 2017. a
François, B. and Vrac, M.: Codes for the article “Time of emergence of compound events:
contribution of univariate and dependence properties”, Zenodo [code],
https://doi.org/10.5281/zenodo.7509302, 2023. a
François, B., Vrac, M., Cannon, A. J., Robin, Y., and Allard, D.: Multivariate bias corrections of climate simulations: which benefits for which losses?, Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, 2020. a
François, B., Thao, S., and Vrac, M.: Adjusting spatial dependence of climate
model outputs with cycle-consistent adversarial networks, Clim. Dynam., 57,
3323–3353, https://doi.org/10.1007/s00382-021-05869-8, 2021. a
Gaetani, M., Janicot, S., Vrac, M., Famien, A. M., and Sultan, B.:
Robust assessment of the time of emergence of precipitation change in
West Africa, Sci. Rep., 10, 7670, https://doi.org/10.1038/s41598-020-63782-2, 2020. a, b
Garcia de Cortazar-Atauri, I., Brisson, N., and Gaudillere, J.: Performance of
several models for predicting budburst date of grapevine (Vitis vinifera
L.), Int. J. Biometeorol., 53, 317–326, https://doi.org/10.1007/s00484-009-0217-4,
2009. a, b
Genest, C., Remillard, B., and Beaudoin, D.: Goodness-of-fit tests for
copulas: A review and a power study, Insur. Math. Econ., 44, 199–213,
https://doi.org/10.1016/j.insmatheco.2007.10.005, 2009. a
Giorgi, F. and Bi, X.: Time of emergence (TOE) of GHG-forced precipitation
change hot-spots, Geophys. Res. Lett., 36, L06709, https://doi.org/10.1029/2009GL037593, 2009. a
Guo, H., John, J. G., Blanton, C., McHugh, C., Nikonov, S., Radhakrishnan, A.,
Rand, K., Zadeh, N. T., Balaji, V., Durachta, J., Dupuis, C., Menzel, R.,
Robinson, T., Underwood, S., Vahlenkamp, H., Dunne, K. A., Gauthier, P. P.,
Ginoux, P., Griffies, S. M., Hallberg, R., Harrison, M., Hurlin, W., Lin, P.,
Malyshev, S., Naik, V., Paulot, F., Paynter, D. J., Ploshay, J., Schwarzkopf,
D. M., Seman, C. J., Shao, A., Silvers, L., Wyman, B., Yan, X., Zeng, Y.,
Adcroft, A., Dunne, J. P., Held, I. M., Krasting, J. P., Horowitz, L. W.,
Milly, C., Shevliakova, E., Winton, M., Zhao, M., and Zhang, R.: NOAA-GFDL
GFDL-CM4 model output prepared for CMIP6 ScenarioMIP ssp585,
https://doi.org/10.22033/ESGF/CMIP6.9268, 2018. a
Guo, Q., Chen, J., Zhang, X., Shen, M., Chen, H., and Guo, S.: A new two-stage
multivariate quantile mapping method for bias correcting climate model
outputs, Clim. Dynam., 53, 3603–3623, https://doi.org/10.1007/s00382-019-04729-w,
2019. a
Hawkins, E. and Sutton, R.: Time of emergence of climate signals, Geophys. Res.
Lett., 39, L01702, https://doi.org/10.1029/2011GL050087, 2012. a, b, c
Hillier, J., Matthews, T., Wilby, R., and Murphy, C.: Multi-hazard
dependencies can increase or decrease risk, Nat. Clim. Chang., 10, 1–4,
https://doi.org/10.1038/s41558-020-0832-y, 2020. a
Hofert, M., Mächler, M., and McNeil, A. J.: Likelihood inference for
Archimedean copulas in high dimensions under known margins, J. Multivar.
Anal., 110, 133–150, https://doi.org/10.1016/j.jmva.2012.02.019, 2012. a
Hofert, M., Kojadinovic, I., Maechler, M., and Yan, J.: copula: Multivariate
Dependence with Copulas, R package version 1.0-1, https://CRAN.R-project.org/package=copula (last access: 9 March 2022), 2020. a
Huang, W. and Prokhorov, A.: A Goodness-of-fit Test for Copulas, Econom.
Rev., 33, 751–771, https://doi.org/10.1080/07474938.2012.690692, 2014. a
IPCC: Climate Change 2021: The Physical Science Basis.
Contribution of Working Group I to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896, in press, 2023. a, b
Jézéquel, A., Bevacqua, E., d'Andrea, F., Thao, S., Vautard, R.,
Vrac, M., and Yiou, P.: Conditional and residual trends of singular hot days
in Europe, Environ. Res. Lett., 15, 064018,
https://doi.org/10.1088/1748-9326/ab76dd, 2020. a, b
Jiang, F., Hu, R.-j., Zhang, Y.-w., Li, X., and Tong, L.: Variations and
trends of onset, cessation and length of climatic growing season over
Xinjiang, NW China, Theor. Appl. Climatol., 106, 449–458,
https://doi.org/10.1007/s00704-011-0445-5, 2011. a
King, A. D., Donat, M. G., Fischer, E. M., Hawkins, E., Alexander, L. V.,
Karoly, D. J., Dittus, A. J., Lewis, S. C., and Perkins, S. E.: The timing
of anthropogenic emergence in simulated climate extremes, Environ. Res.
Lett., 10, 094015, https://doi.org/10.1088/1748-9326/10/9/094015, 2015. a
Kiriliouk, A. and Naveau, P.: Climate extreme event attribution using
multivariate peaks-over-thresholds modeling and counterfactual theory, Ann.
Appl. Stat., 14, 1342–1358, https://doi.org/10.1214/20-AOAS1355, 2020. a
Lamichhane, J.-R.: Rising risks of late-spring frosts in a changing climate,
Nat. Clim. Chang., 11, 554–555, https://doi.org/10.1038/s41558-021-01090-x, 2021. a
Leonard, M., Westra, S., Phatak, A., Lambert, M., Hurk, B., Mcinnes, K.,
Risbey, J., Schuster, S., Jakob, D., and Stafford Smith, M.: A compound event
framework for understanding extreme impacts, Wiley Interdiscip. Rev. Clim.
Change, 5, 113–128, 2014. a
Li, L.: CAS FGOALS-g3 model output prepared for CMIP6 ScenarioMIP ssp585,
https://doi.org/10.22033/ESGF/CMIP6.3503, 2019. a
Liberato, M. L.: The 19 January 2013 windstorm over the North Atlantic:
large-scale dynamics and impacts on Iberia, Weather. Clim. Extremes, 5–6,
16–28, https://doi.org/10.1016/j.wace.2014.06.002, 2014. a
Liu, Q., Piao, S., Janssens, I., Fu, Y., Peng, S., Lian, X., Ciais, P., Myneni,
R., Penuelas, J., and Wang, T.: Extension of the growing season increases
vegetation exposure to frost, Nat. Commun., 9, 426,
https://doi.org/10.1038/s41467-017-02690-y, 2018a. a
Liu, Y., Cheng, Y., Zhang, X., Li, X., and Cao, S.: Combined Exceedance
Probability Assessment of Water Quality Indicators Based on Multivariate
Joint Probability Distribution in Urban Rivers, Water, 10, 971,
https://doi.org/10.3390/w10080971, 2018b. a
Lobell, D. B. and Burke, M. B.: Why are agricultural impacts of climate change
so uncertain? The importance of temperature relative to precipitation,
Environ. Res. Lett., 3, 034007, https://doi.org/10.1088/1748-9326/3/3/034007, 2008. a
Mahlstein, I., Knutti, R., Solomon, S., and Portmann, R. W.: Early onset of
significant local warming in low latitude countries, Environ. Res. Lett., 6,
034009, https://doi.org/10.1088/1748-9326/6/3/034009, 2011. a
Mahlstein, I., Hegerl, G., and Solomon, S.: Emerging local warming signals in
observational data, Geophys. Res. Lett., 39, L21711, https://doi.org/10.1029/2012GL053952,
2012. a
Manning, C., Widmann, M., Bevacqua, E., Loon, A. F. V., Maraun, D., and Vrac,
M.: Soil Moisture Drought in Europe: A Compound Event of Precipitation and
Potential Evapotranspiration on Multiple Time Scales, J. Hydrometeorol., 19,
1255–1271, https://doi.org/10.1175/JHM-D-18-0017.1, 2018. a, b
Manning, C., Widmann, M., Bevacqua, E., Loon, A. F. V., Maraun, D., and Vrac,
M.: Increased probability of compound long-duration dry and hot events in
Europe during summer (1950–2013), Environ. Res. Lett., 14,
094006, https://doi.org/10.1088/1748-9326/ab23bf, 2019. a
Maraun, D.: When will trends in European mean and heavy daily precipitation
emerge?, Environ. Res. Lett., 8, 014004,
https://doi.org/10.1088/1748-9326/8/1/014004, 2013. a, b, c
Martius, O., Pfahl, S., and Chevalier, C.: A global quantification of compound
precipitation and wind extremes, Geophys. Res. Lett., 43, 7709–7717,
https://doi.org/10.1002/2016GL070017, 2016. a
Mazdiyasni, O. and AghaKouchak, A.: Substantial increase in concurrent
droughts and heatwaves in the United States, P. Natl. Acad. Sci. USA,
112, 11484–11489, https://doi.org/10.1073/pnas.1422945112, 2015. a
Mehrotra, R. and Sharma, A.: A Resampling Approach for Correcting Systematic
Spatiotemporal Biases for Multiple Variables in a Changing Climate, Water
Resour. Res., 55, 754–770, https://doi.org/10.1029/2018WR023270, 2019. a
Messmer, M. and Simmonds, I.: Global analysis of cyclone-induced compound
precipitation and wind extreme events, Weather. Clim. Extremes, 32,
100324, https://doi.org/10.1016/j.wace.2021.100324, 2021. a
Nasr, A. A., Wahl, T., Rashid, M. M., Camus, P., and Haigh, I. D.: Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline, Hydrol. Earth Syst. Sci., 25, 6203–6222, https://doi.org/10.5194/hess-25-6203-2021, 2021. a
Nelsen, R. B.: An Introduction to Copulas, Springer Series in
Statistics, 2nd edn., Springer, https://doi.org/10.1007/0-387-28678-0, 2006. a
Ossó, A., Allan, R., Hawkins, E., Shaffrey, L., and Maraun, D.: Emerging new
climate extremes over Europe, Clim. Dyn., 58, 487–501,
https://doi.org/10.1007/s00382-021-05917-3, 2022. a, b, c, d
Pfleiderer, P., Menke, I., and Schleussner, C.-F.: Increasing risks of apple
tree frost damage under climate change, Clim. Change, 157, 515–525,
https://doi.org/10.1007/s10584-019-02570-y, 2019. a
Pohl, E., Grenier, C., Vrac, M., and Kageyama, M.: Emerging climate signals in the Lena River catchment: a non-parametric statistical approach, Hydrol. Earth Syst. Sci., 24, 2817–2839, https://doi.org/10.5194/hess-24-2817-2020, 2020. a
Rana, A., Hamid, M., and Qin, Y.: Understanding the Joint Behavior of
Temperature and Precipitation for Climate Change Impact Studies, Theor.
Appl. Climatol., 129, https://doi.org/10.1007/s00704-016-1774-1, 2017. a
Raveh-Rubin, S. and Wernli, H.: Large-scale wind and precipitation extremes in
the Mediterranean: a climatological analysis for 1979–2012, Q. J. Roy.
Meteor. Soc., 141, 2404–2417, https://doi.org/10.1002/qj.2531, 2015. a
Raymond, C., Matthews, T., and Horton, R. M.: The emergence of heat and
humidity too severe for human tolerance, Sci. Adv., 6, eaaw1838,
https://doi.org/10.1126/sciadv.aaw1838, 2020. a
Raymond, C., Suarez-Gutierrez, L., Kornhuber, K., Pascolini-Campbell, M.,
Sillmann, J., and Waliser, D. E.: Increasing spatiotemporal proximity of heat
and precipitation extremes in a warming world quantified by a large model
ensemble, Environ. Res. Lett., 17, 035005, https://doi.org/10.1088/1748-9326/ac5712,
2022. a, b
Reinert, M., Pineau-Guillou, L., Raillard, N., and Chapron, B.: Seasonal Shift
in Storm Surges at Brest Revealed by Extreme Value Analysis, J. Geophys.
Res. Oceans, 126, e2021JC017794, https://doi.org/10.1029/2021JC017794, 2021. a
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O’Neill, B. C.,
Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp,
A., Cuaresma, J. C., KC, S., Leimbach, M., Jiang, L., Kram, T., Rao, S.,
Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Da
Silva, L. A., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D.,
Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G.,
Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J. C., Kainuma, M.,
Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A.,
and Tavoni, M.: The Shared Socioeconomic Pathways and their energy, land
use, and greenhouse gas emissions implications: An overview, Global Environ. Chang., 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009,
2017. a
Ridder, N., Pitman, A., and Ukkola, A.: Do CMIP6 Climate Models simulate
Global or Regional Compound Events skilfully?, Geophys. Res. Lett., 48, e2020GL091152,
https://doi.org/10.1029/2020GL091152, 2021. a, b
Ridder, N., Ukkola, A., Pitman, A., and Perkins-Kirkpatrick, S.: Increased
occurrence of high impact compound events under climate change, NPJ Clim.
Atmos. Sci., 5, 3, https://doi.org/10.1038/s41612-021-00224-4, 2022. a
Robin, Y., Vrac, M., Naveau, P., and Yiou, P.: Multivariate stochastic bias corrections with optimal transport, Hydrol. Earth Syst. Sci., 23, 773–786, https://doi.org/10.5194/hess-23-773-2019, 2019. a
Ruosteenoja, K., Räisänen, J., Venäläinen, A., and Kämäräinen, M.:
Projections for the duration and degree days of the thermal growing season
in Europe derived from CMIP5 model output, Int. J. Climatol., 36,
3039–3055, https://doi.org/10.1002/joc.4535, 2016. a
Russo, S., Sillmann, J., and Sterl, A.: Humid heat waves at different warming
levels, Sci. Rep., 7, 7477, https://doi.org/10.1038/s41598-017-07536-7, 2017. a
Sadegh, M., Ragno, E., and AghaKouchak, A.: Multivariate Copula Analysis
Toolbox (MvCAT): Describing dependence and underlying uncertainty using a
Bayesian framework, Water Resour. Res., 53, 5166–5183,
https://doi.org/10.1002/2016WR020242, 2017. a
Salvadori, G., de Michele, C., Kottegoda, N., and Rosso, R.: Extremes in
Nature: An Approach Using Copulas, Water Science and
Technology Library, Springer, Dordrecht, the Netherlands,
https://doi.org/10.1007/1-4020-4415-1, 2007. a
Salvadori, G., De Michele, C., and Durante, F.: On the return period and design in a multivariate framework, Hydrol. Earth Syst. Sci., 15, 3293–3305, https://doi.org/10.5194/hess-15-3293-2011, 2011. a
Salvadori, G., Durante, F., De Michele, C., Bernardi, M., and Petrella, L.: A
multivariate copula-based framework for dealing with hazard scenarios and
failure probabilities, Water Resour. Res., 52, 3701–3721,
https://doi.org/10.1002/2015WR017225, 2016. a
Schölzel, C. and Friederichs, P.: Multivariate non-normally distributed random variables in climate research – introduction to the copula approach, Nonlin. Processes Geophys., 15, 761–772, https://doi.org/10.5194/npg-15-761-2008, 2008. a
Schär, C.: Climate extremes: The worst heat waves to come, Nat. Clim.
Chang., 6, 128–129, https://doi.org/10.1038/nclimate2864, 2015. a
Serinaldi, F.: Dismissing return periods!, Stoch. Environ. Res. Risk Assess.,
29, 1179–1189, https://doi.org/10.1007/s00477-014-0916-1, 2014. a
Serinaldi, F.: Can we tell more than we can know? The limits of bivariate
drought analyses in the United States, Stoch. Environ. Res. Risk Assess.,
30, 1691–1704, 2015. a
Sgubin, G., Swingedouw, D., Dayon, G., Garcia de Cortazar-Atauri, I., Ollat,
N., Page, C., and van Leeuwen, C.: The risk of tardive frost damage in
French vineyards in a changing climate, Agric. For. Meteorol., 250–251,
226–242, https://doi.org/10.1016/j.agrformet.2017.12.253, 2018. a
Shepherd, T. G.: A Common Framework for Approaches to Extreme Event
Attribution, Curr. Clim. Change Rep., 2, 28–38,
https://doi.org/10.1007/s40641-016-0033-y, 2016. a
Shiau, J.: Return Period of Bivariate Distributed Hydrological Events, Stoch.
Environ. Res. Risk Assess., 17, 42–57, https://doi.org/10.1007/s00477-003-0125-9,
2003. a
Shiogama, H., Abe, M., and Tatebe, H.: MIROC MIROC6 model output prepared for
CMIP6 ScenarioMIP, https://doi.org/10.22033/ESGF/CMIP6.898, 2019. a
Singh, H., Najafi, M., and Cannon, A.: Characterizing non-stationary compound
extreme events in a changing climate based on large-ensemble climate
simulations, Clim. Dynam., 56, 1–17, https://doi.org/10.1007/s00382-020-05538-2,
2021a. a, b, c
Singh, J., Ashfaq, M., Skinner, C. B., Anderson, W. B., and Singh, D.:
Amplified risk of spatially compounding droughts during co-occurrences of
modes of natural ocean variability, NPJ Clim. Atmos. Sci., 4, 7,
https://doi.org/10.1038/s41612-021-00161-2, 2021b. a
Skaugen, T. E. and Tveito, O. E.: Growing-season and degree-day scenario in
Norway for 2021–2050, Clim. Res., 26, 221–232, 2004. a
Sklar, A.: Fonctions de Répartition à n Dimensions et Leurs Marges,
Publications de l’Institut Statistique de l’Université de Paris, 8,
229–231, 1959. a
Stott, P. A., Stone, D. A., and Allen, M. R.: Human contribution to the
European heatwave of 2003, Nature, 432, 610–614, https://doi.org/10.1038/nature03089,
2004. a
Stott, P. A., Christidis, N., Otto, F. E. L., Sun, Y., Vanderlinden, J.-P., van
Oldenborgh, G. J., Vautard, R., von Storch, H., Walton, P., Yiou, P., and
Zwiers, F. W.: Attribution of extreme weather and climate-related events,
Wiley Interdiscip. Rev. Clim. Change, 7, 23–41, https://doi.org/10.1002/wcc.380, 2016. a
Swart, N. C., Cole, J. N., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett,
N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G.,
Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L.,
von Salzen, K., Yang, D., Winter, B., and Sigmond, M.: CCCma CanESM5 model
output prepared for CMIP6 ScenarioMIP, https://doi.org/10.22033/ESGF/CMIP6.1317, 2019. a
Tavakol, A., Rahmani, V., and Harrington Jr., J.: Probability of compound climate extremes
in a changing climate: A copula-based study of hot, dry, and windy events in
the central United States, Environ. Res. Lett., 15, 104058,
https://doi.org/10.1088/1748-9326/abb1ef, 2020. a
Unterberger, C., Brunner, L., Nabernegg, S., Steininger, K. W., Steiner, A. K.,
Stabentheiner, E., Monschein, S., and Truhetz, H.: Spring frost risk for
regional apple production under a warmer climate, PLOS ONE, 13, 1–18,
https://doi.org/10.1371/journal.pone.0200201, 2018. a
Vautard, R., van Oldenborgh, G. J., Bonnet, R., Li, S., Robin, Y., Kew, S., Philip, S., Soubeyroux, J.-M., Dubuisson, B., Viovy, N., Reichstein, M., Otto, F., and Garcia de Cortazar-Atauri, I.: Human influence on growing-period frosts like the early April 2021 in Central France, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2022-41, in review, 2022. a, b, c, d
Venzon, D. J. and Moolgavkar, S. H.: A Method for Computing
Profile-Likelihood-Based Confidence Intervals, J. R. Stat. Soc. Ser. C Appl.
Stat., 37, 87–94, 1988. a
Villalobos-Herrera, R., Bevacqua, E., Ribeiro, A. F. S., Auld, G., Crocetti, L., Mircheva, B., Ha, M., Zscheischler, J., and De Michele, C.: Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards, Nat. Hazards Earth Syst. Sci., 21, 1867–1885, https://doi.org/10.5194/nhess-21-1867-2021, 2021. a
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1 model output prepared for CMIP6 CMIP,
https://doi.org/10.22033/ESGF/CMIP6.1375, 2018. a
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6
ScenarioMIP ssp585, https://doi.org/10.22033/ESGF/CMIP6.4225, 2019. a
Volodin, E., Mortikov, E., Gritsun, A., Lykossov, V., Galin, V., Diansky, N.,
Gusev, A., Kostrykin, S., Iakovlev, N., Shestakova, A., and Emelina, S.: INM
INM-CM4-8 model output prepared for CMIP6 ScenarioMIP,
https://doi.org/10.22033/ESGF/CMIP6.12321, 2019a. a
Volodin, E., Mortikov, E., Gritsun, A., Lykossov, V., Galin, V., Diansky, N.,
Gusev, A., Kostrykin, S., Iakovlev, N., Shestakova, A., and Emelina, S.: INM
INM-CM5-0 model output prepared for CMIP6 ScenarioMIP ssp585,
https://doi.org/10.22033/ESGF/CMIP6.12338, 2019b. a
Vrac, M.: Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction, Hydrol. Earth Syst. Sci., 22, 3175–3196, https://doi.org/10.5194/hess-22-3175-2018, 2018. a
Vrac, M. and Thao, S.: R2D2 v2.0: accounting for temporal dependences in multivariate bias correction via analogue rank resampling, Geosci. Model Dev., 13, 5367–5387, https://doi.org/10.5194/gmd-13-5367-2020, 2020. a
Vrac, M., Chédin, A., and Diday, E.: Clustering a Global Field of Atmospheric
Profiles by Mixture Decomposition of Copulas, J. Atmos. Ocean Technol., 22,
1445–1459, https://doi.org/10.1175/JTECH1795.1, 2005. a
Vrac, M., Thao, S., and Yiou, P.: Changes in temperature-precipitation
correlations over Europe: Are climate models reliable?, Clim. Dynam.,
https://doi.org/10.1007/s00382-022-06436-5, 2022a. a, b, c, d
Vrac, M., Thao, S., and Yiou, P.: Should multivariate bias corrections of
climate simulations account for changes of rank correlation over time?, J. Geophys. Res.-Atmos., 127, e2022JD036562, https://doi.org/10.1029/2022JD036562,
2022b. a
Wahl, T., Jain, S., Bender, J., Meyers, S., and Luther, M.: Increasing risk of
compound flooding from storm surge and rainfall for major US cities, Nat.
Clim. Chang., 5, 1093–1097, https://doi.org/10.1038/nclimate2736, 2015. a, b
White, H.: Maximum Likelihood Estimation of Misspecified Models,
Econometrica, 50, 1–25, 1982. a
Wieners, K.-H., Giorgetta, M., Jungclaus, J., Reick, C., Esch, M., Bittner, M.,
Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch,
J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I.,
Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S.,
Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K.,
Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von
Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H.,
Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner,
E.: MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 ScenarioMIP ssp585,
https://doi.org/10.22033/ESGF/CMIP6.6705, 2019. a
Yue, S. and Rasmussen, P.: Bivariate frequency analysis: Discussion of some
useful concepts in hydrological application, Hydrol. Process., 16,
2881–2898, https://doi.org/10.1002/hyp.1185, 2002. a, b
Yukimoto, S., Koshiro, T., Kawai, H., Oshima, N., Yoshida, K., Urakawa, S.,
Tsujino, H., Deushi, M., Tanaka, T., Hosaka, M., Yoshimura, H., Shindo, E.,
Mizuta, R., Ishii, M., Obata, A., and Adachi, Y.: MRI MRI-ESM2.0 model output
prepared for CMIP6 CMIP, https://doi.org/10.22033/ESGF/CMIP6.621, 2019.
a
Zscheischler, J. and Lehner, F.: Attributing compound events to anthropogenic
climate change, B. Am. Meteorol. Soc., 103, E936–E953,
https://doi.org/10.1175/BAMS-D-21-0116.1, 2021. a, b, c
Zscheischler, J. and Seneviratne, S.: Dependence of drivers affects risks
associated with compound events, Sci. Adv., 3, e1700263,
https://doi.org/10.1126/sciadv.1700263, 2017. a, b, c, d
Zscheischler, J., Michalak, A. M., Schwalm, C., Mahecha, M. D., Huntzinger,
D. N., Reichstein, M., Berthier, G., Ciais, P., Cook, R. B., El-Masri, B.,
Huang, M., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Mao, J., Peng, S.,
Poulter, B., Ricciuto, D., Shi, X., Tao, B., Tian, H., Viovy, N., Wang, W.,
Wei, Y., Yang, J., and Zeng, N.: Impact of large-scale climate extremes on
biospheric carbon fluxes: An intercomparison based on MsTMIP data, Glob.
Biogeochem. Cycles, 28, 585–600, https://doi.org/10.1002/2014GB004826, 2014. a
Zscheischler, J., Westra, S., Hurk, B., Seneviratne, S., Ward, P., Pitman, A.,
AghaKouchak, A., Bresch, D., Leonard, M., Wahl, T., and Zhang, X.: Future
climate risk from compound events, Nat. Clim. Chang., 8, 469–477,
https://doi.org/10.1038/s41558-018-0156-3, 2018. a
Zscheischler, J., Fischer, E. M., and Lange, S.: The effect of univariate bias adjustment on multivariate hazard estimates, Earth Syst. Dynam., 10, 31–43, https://doi.org/10.5194/esd-10-31-2019, 2019. a
Short summary
Compound events (CEs) result from a combination of several climate phenomena. In this study, we propose a new methodology to assess the time of emergence of CE probabilities and to quantify the contribution of marginal and dependence properties of climate phenomena to the overall CE probability changes. By applying our methodology to two case studies, we show the importance of considering changes in both marginal and dependence properties for future risk assessments related to CEs.
Compound events (CEs) result from a combination of several climate phenomena. In this study, we...
Altmetrics
Final-revised paper
Preprint