Articles | Volume 21, issue 6
https://doi.org/10.5194/hess-21-2701-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-2701-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy)
Emanuele Bevacqua
CORRESPONDING AUTHOR
Wegener Center for Climate and Global Change, University of Graz, Graz, Austria
Douglas Maraun
Wegener Center for Climate and Global Change, University of Graz, Graz, Austria
Ingrid Hobæk Haff
Department of Mathematics, University of Oslo, Oslo, Norway
Martin Widmann
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
Mathieu Vrac
Laboratoire des Sciences du Climat et de l'Environnement, CNRS/IPSL, Gif-sur-Yvette, France
Related authors
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
Short summary
Short summary
We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024, https://doi.org/10.5194/nhess-24-2689-2024, 2024
Short summary
Short summary
Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
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.
Derrick Muheki, Axel A. J. Deijns, Emanuele Bevacqua, Gabriele Messori, Jakob Zscheischler, and Wim Thiery
Earth Syst. Dynam., 15, 429–466, https://doi.org/10.5194/esd-15-429-2024, https://doi.org/10.5194/esd-15-429-2024, 2024
Short summary
Short summary
Climate change affects the interaction, dependence, and joint occurrence of climate extremes. Here we investigate the joint occurrence of pairs of river floods, droughts, heatwaves, crop failures, wildfires, and tropical cyclones in East Africa under past and future climate conditions. Our results show that, across all future warming scenarios, the frequency and spatial extent of these co-occurring extremes will increase in this region, particularly in areas close to the Nile and Congo rivers.
Colin Manning, Martin Widmann, Douglas Maraun, Anne F. Van Loon, and Emanuele Bevacqua
Weather Clim. Dynam., 4, 309–329, https://doi.org/10.5194/wcd-4-309-2023, https://doi.org/10.5194/wcd-4-309-2023, 2023
Short summary
Short summary
Climate models differ in their representation of dry spells and high temperatures, linked to errors in the simulation of persistent large-scale anticyclones. Models that simulate more persistent anticyclones simulate longer and hotter dry spells, and vice versa. This information is important to consider when assessing the likelihood of such events in current and future climate simulations so that we can assess the plausibility of their future projections.
Shijie Jiang, Emanuele Bevacqua, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 26, 6339–6359, https://doi.org/10.5194/hess-26-6339-2022, https://doi.org/10.5194/hess-26-6339-2022, 2022
Short summary
Short summary
Using a novel explainable machine learning approach, we investigated the contributions of precipitation, temperature, and day length to different peak discharges, thereby uncovering three primary flooding mechanisms widespread in European catchments. The results indicate that flooding mechanisms have changed in numerous catchments over the past 70 years. The study highlights the potential of artificial intelligence in revealing complex changes in extreme events related to climate change.
Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 21, 1867–1885, https://doi.org/10.5194/nhess-21-1867-2021, https://doi.org/10.5194/nhess-21-1867-2021, 2021
Short summary
Short summary
Climate hazards may be caused by events which have multiple drivers. Here we present a method to break down climate model biases in hazard indicators down to the bias caused by each driving variable. Using simplified fire and heat stress indicators driven by temperature and relative humidity as examples, we show how multivariate indicators may have complex biases and that the relationship between driving variables is a source of bias that must be considered in climate model bias corrections.
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.
T. Alberti, F. Lepreti, A. Vecchio, E. Bevacqua, V. Capparelli, and V. Carbone
Clim. Past, 10, 1751–1762, https://doi.org/10.5194/cp-10-1751-2014, https://doi.org/10.5194/cp-10-1751-2014, 2014
Robin Noyelle, Davide Faranda, Yoann Robin, Mathieu Vrac, and Pascal Yiou
EGUsphere, https://doi.org/10.5194/egusphere-2024-3167, https://doi.org/10.5194/egusphere-2024-3167, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Extreme meteorological and climatological events properties are changing under human caused climate change. Extreme events attribution methods seek to estimate the contribution of global warming in the probability and intensity changes of extreme events. Here we propose a procedure to estimate these quantities for the flow analogues method which compare the observed event to similar events in the past.
Germain Bénard, Marion Gehlen, and Mathieu Vrac
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2024-31, https://doi.org/10.5194/esd-2024-31, 2024
Preprint under review for ESD
Short summary
Short summary
We introduce a novel approach to compare Earth System Model output using a causality-based approach. The analysis of interactions between atmospheric, oceanic, and biogeochemical variables in the North Atlantic Subpolar Gyre highlights the dynamics of each model. This method reveals potential underlying causes of model differences, offering a tool for enhanced model evaluation and improved understanding of complex Earth system dynamics under past and future climates.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2805, https://doi.org/10.5194/egusphere-2024-2805, 2024
Short summary
Short summary
We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Karakoram Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical / machine learning techniques. Our results show this approach outperforms traditional methods, especially in remote, ungauged areas, suggesting it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
Duncan Pappert, Alexandre Tuel, Dim Coumou, Mathieu Vrac, and Olivia Martius
EGUsphere, https://doi.org/10.5194/egusphere-2024-2980, https://doi.org/10.5194/egusphere-2024-2980, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
This study examines the mechanisms that characterise long-lasting (persistent) and short hot spells in Europe in a comparative framework. By analysing weather data, we found that long spells in Southwestern Europe are typically preceded by dry soil conditions and driven by multiple persistence-inducing mechanisms. In contrast, short spells occur in a more transient atmospheric situation and exhibit fewer drivers. Understanding persistent heat extremes can help improve their prediction.
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.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
Short summary
Short summary
We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024, https://doi.org/10.5194/nhess-24-2689-2024, 2024
Short summary
Short summary
Landslides are complex phenomena causing important impacts in vulnerable areas, and they are often triggered by rainfall. Here, we develop a new approach that uses information on the temporal clustering of rainfall, i.e. multiple events close in time, to detect landslide events and compare it with the use of classical empirical rainfall thresholds, considering as a case study the region of Lisbon, Portugal. The results could help to improve the prediction of rainfall-triggered landslides.
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.
Derrick Muheki, Axel A. J. Deijns, Emanuele Bevacqua, Gabriele Messori, Jakob Zscheischler, and Wim Thiery
Earth Syst. Dynam., 15, 429–466, https://doi.org/10.5194/esd-15-429-2024, https://doi.org/10.5194/esd-15-429-2024, 2024
Short summary
Short summary
Climate change affects the interaction, dependence, and joint occurrence of climate extremes. Here we investigate the joint occurrence of pairs of river floods, droughts, heatwaves, crop failures, wildfires, and tropical cyclones in East Africa under past and future climate conditions. Our results show that, across all future warming scenarios, the frequency and spatial extent of these co-occurring extremes will increase in this region, particularly in areas close to the Nile and Congo rivers.
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.
Colin Manning, Martin Widmann, Douglas Maraun, Anne F. Van Loon, and Emanuele Bevacqua
Weather Clim. Dynam., 4, 309–329, https://doi.org/10.5194/wcd-4-309-2023, https://doi.org/10.5194/wcd-4-309-2023, 2023
Short summary
Short summary
Climate models differ in their representation of dry spells and high temperatures, linked to errors in the simulation of persistent large-scale anticyclones. Models that simulate more persistent anticyclones simulate longer and hotter dry spells, and vice versa. This information is important to consider when assessing the likelihood of such events in current and future climate simulations so that we can assess the plausibility of their future projections.
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.
Yi Yang, Douglas Maraun, Albert Ossó, and Jianping Tang
Nat. Hazards Earth Syst. Sci., 23, 693–709, https://doi.org/10.5194/nhess-23-693-2023, https://doi.org/10.5194/nhess-23-693-2023, 2023
Short summary
Short summary
This study quantifies the spatiotemporal variation and characteristics of compound long-duration dry and hot events in China over the 1961–2014 period. The results show that over the past few decades, there has been a substantial increase in the frequency of these compound events across most parts of China, which is dominated by rising temperatures. We detect a strong increase in the spatially contiguous areas experiencing concurrent dry and hot conditions.
Raphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Aditya N. Mishra, Douglas Maraun, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 23, 205–229, https://doi.org/10.5194/nhess-23-205-2023, https://doi.org/10.5194/nhess-23-205-2023, 2023
Short summary
Short summary
In summer 2009 and 2014, rainfall events occurred in the Styrian Basin (Austria), triggering thousands of landslides. Landslide storylines help to show potential future changes under changing environmental conditions. The often neglected uncertainty quantification was the aim of this study. We found uncertainty arising from the landslide model to be of the same order as climate scenario uncertainty. Understanding the dimensions of uncertainty is crucial for allowing informed decision-making.
Bastien François and Mathieu Vrac
Nat. Hazards Earth Syst. Sci., 23, 21–44, https://doi.org/10.5194/nhess-23-21-2023, https://doi.org/10.5194/nhess-23-21-2023, 2023
Short summary
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.
Shijie Jiang, Emanuele Bevacqua, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 26, 6339–6359, https://doi.org/10.5194/hess-26-6339-2022, https://doi.org/10.5194/hess-26-6339-2022, 2022
Short summary
Short summary
Using a novel explainable machine learning approach, we investigated the contributions of precipitation, temperature, and day length to different peak discharges, thereby uncovering three primary flooding mechanisms widespread in European catchments. The results indicate that flooding mechanisms have changed in numerous catchments over the past 70 years. The study highlights the potential of artificial intelligence in revealing complex changes in extreme events related to 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.
Marco Hofmann, Claudia Volosciuk, Martin Dubrovský, Douglas Maraun, and Hans R. Schultz
Earth Syst. Dynam., 13, 911–934, https://doi.org/10.5194/esd-13-911-2022, https://doi.org/10.5194/esd-13-911-2022, 2022
Short summary
Short summary
We modelled water budget developments of viticultural growing regions on the spatial scale of individual vineyard plots with respect to landscape features like the available water capacity of the soils, slope, and aspect of the sites. We used an ensemble of climate simulations and focused on the occurrence of drought stress. The results show a high bandwidth of projected changes where the risk of potential drought stress becomes more apparent in steep-slope regions.
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.
Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 21, 1867–1885, https://doi.org/10.5194/nhess-21-1867-2021, https://doi.org/10.5194/nhess-21-1867-2021, 2021
Short summary
Short summary
Climate hazards may be caused by events which have multiple drivers. Here we present a method to break down climate model biases in hazard indicators down to the bias caused by each driving variable. Using simplified fire and heat stress indicators driven by temperature and relative humidity as examples, we show how multivariate indicators may have complex biases and that the relationship between driving variables is a source of bias that must be considered in climate model bias corrections.
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.
Douglas Maraun and Martin Widmann
Hydrol. Earth Syst. Sci., 22, 4867–4873, https://doi.org/10.5194/hess-22-4867-2018, https://doi.org/10.5194/hess-22-4867-2018, 2018
Short summary
Short summary
Cross-validation of free-running bias-corrected climate change simulations against observations is misleading, because it is typically dominated by internal variability. In particular, a sensible bias correction may be rejected and a non-sensible bias correction may be accepted. We therefore propose to avoid cross-validation when evaluating bias correction of free-running bias-corrected climate change simulations. Instead, one should evaluate temporal, spatial and
process-based aspects.
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.
PAGES Hydro2k Consortium
Clim. Past, 13, 1851–1900, https://doi.org/10.5194/cp-13-1851-2017, https://doi.org/10.5194/cp-13-1851-2017, 2017
Short summary
Short summary
Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited due to a paucity of modern instrumental observations. We review how proxy records of past climate and climate model simulations can be used in tandem to understand hydroclimate variability over the last 2000 years and how these tools can also inform risk assessments of future hydroclimatic extremes.
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.
Anastasios Matsikaris, Martin Widmann, and Johann Jungclaus
Clim. Past, 12, 1555–1563, https://doi.org/10.5194/cp-12-1555-2016, https://doi.org/10.5194/cp-12-1555-2016, 2016
Short summary
Short summary
We have assimilated proxy-based (PAGES 2K) and instrumental (HadCRUT3v) observations into a General Circulation Model (MPI-ESM-CR). Assimilating instrumental data improves the performance of Data Assimilation. No skill on small spatial scales is however found for either of the two schemes. Errors in the assimilated data are therefore not the main reason for this lack of skill; continental mean temperatures cannot provide skill on small spatial scales in palaeoclimate reconstructions.
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.
D. Maraun and M. Widmann
Hydrol. Earth Syst. Sci., 19, 3449–3456, https://doi.org/10.5194/hess-19-3449-2015, https://doi.org/10.5194/hess-19-3449-2015, 2015
A. Matsikaris, M. Widmann, and J. Jungclaus
Clim. Past, 11, 81–93, https://doi.org/10.5194/cp-11-81-2015, https://doi.org/10.5194/cp-11-81-2015, 2015
Short summary
Short summary
We compare an off-line and an on-line ensemble-based data assimilation method, for the climate of the 17th century. Both schemes perform better than the simulations without DA, and similar skill on the continental and hemispheric scales is found. This indicates either a lack of control of the slow components in our setup or a lack of skill in the information propagation on decadal timescales. The temporal consistency of the analysis in the on-line method makes it generally more preferable.
T. Alberti, F. Lepreti, A. Vecchio, E. Bevacqua, V. Capparelli, and V. Carbone
Clim. Past, 10, 1751–1762, https://doi.org/10.5194/cp-10-1751-2014, https://doi.org/10.5194/cp-10-1751-2014, 2014
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
Subject: Coasts and Estuaries | Techniques and Approaches: Modelling approaches
Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models
Mangroves as nature-based mitigation for ENSO-driven compound flood risks in a large river delta
Forecasting estuarine salt intrusion in the Rhine–Meuse delta using an LSTM model
Coastal topography and hydrogeology control critical groundwater gradients and potential beach surface instability during storm surges
Effect of tides on river water behavior over the eastern shelf seas of China
Extreme precipitation events induce high fluxes of groundwater and associated nutrients to coastal ocean
Temporally resolved coastal hypoxia forecasting and uncertainty assessment via Bayesian mechanistic modeling
Assessing the dependence structure between oceanographic, fluvial, and pluvial flooding drivers along the United States coastline
Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: a case study in the Netherlands
Estimating the probability of compound floods in estuarine regions
Accretion, retreat and transgression of coastal wetlands experiencing sea-level rise
Climate change overtakes coastal engineering as the dominant driver of hydrological change in a large shallow lagoon
Dynamic mechanism of an extremely severe saltwater intrusion in the Changjiang estuary in February 2014
A novel approach for the assessment of morphological evolution based on observed water levels in tide-dominated estuaries
Seasonal behaviour of tidal damping and residual water level slope in the Yangtze River estuary: identifying the critical position and river discharge for maximum tidal damping
Sediment budget analysis of the Guayas River using a process-based model
Analytical and numerical study of the salinity intrusion in the Sebou river estuary (Morocco) – effect of the “Super Blood Moon” (total lunar eclipse) of 2015
Linking biogeochemistry to hydro-geometrical variability in tidal estuaries: a generic modeling approach
Impact of the Three Gorges Dam, the South–North Water Transfer Project and water abstractions on the duration and intensity of salt intrusions in the Yangtze River estuary
A 2-D process-based model for suspended sediment dynamics: a first step towards ecological modeling
Revised predictive equations for salt intrusion modelling in estuaries
Impact of the Hoa Binh dam (Vietnam) on water and sediment budgets in the Red River basin and delta
Large-scale suspended sediment transport and sediment deposition in the Mekong Delta
Hydrodynamic controls on oxygen dynamics in a riverine salt wedge estuary, the Yarra River estuary, Australia
Assessing hydrological effects of human interventions on coastal systems: numerical applications to the Venice Lagoon
Environmental flow assessments in estuaries based on an integrated multi-objective method
Modelling climate change effects on a Dutch coastal groundwater system using airborne electromagnetic measurements
An analytical solution for tidal propagation in the Yangtze Estuary, China
Understanding and managing the Westerschelde – synchronizing the physical system and the management system of a complex estuary
David F. Muñoz, Hamed Moftakhari, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 28, 2531–2553, https://doi.org/10.5194/hess-28-2531-2024, https://doi.org/10.5194/hess-28-2531-2024, 2024
Short summary
Short summary
Linking hydrodynamics with machine learning models for compound flood modeling enables a robust characterization of nonlinear interactions among the sources of uncertainty. Such an approach enables the quantification of cascading uncertainty and relative contributions to total uncertainty while also tracking their evolution during compound flooding. The proposed approach is a feasible alternative to conventional statistical approaches designed for uncertainty analyses.
Ignace Pelckmans, Jean-Philippe Belliard, Olivier Gourgue, Luis Elvin Dominguez-Granda, and Stijn Temmerman
Hydrol. Earth Syst. Sci., 28, 1463–1476, https://doi.org/10.5194/hess-28-1463-2024, https://doi.org/10.5194/hess-28-1463-2024, 2024
Short summary
Short summary
The combination of extreme sea levels with increased river flow typically can lead to so-called compound floods. Often these are caused by storms (< 1 d), but climatic events such as El Niño could trigger compound floods over a period of months. We show that the combination of increased sea level and river discharge causes extreme water levels to amplify upstream. Mangrove forests, however, can act as a nature-based flood protection by lowering the extreme water levels coming from the sea.
Bas J. M. Wullems, Claudia C. Brauer, Fedor Baart, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci., 27, 3823–3850, https://doi.org/10.5194/hess-27-3823-2023, https://doi.org/10.5194/hess-27-3823-2023, 2023
Short summary
Short summary
In deltas, saltwater sometimes intrudes far inland and causes problems with freshwater availability. We created a model to forecast salt concentrations at a critical location in the Rhine–Meuse delta in the Netherlands. It requires a rather small number of data to make a prediction and runs fast. It predicts the occurrence of salt concentration peaks well but underestimates the highest peaks. Its speed gives water managers more time to reduce the problems caused by salt intrusion.
Anner Paldor, Nina Stark, Matthew Florence, Britt Raubenheimer, Steve Elgar, Rachel Housego, Ryan S. Frederiks, and Holly A. Michael
Hydrol. Earth Syst. Sci., 26, 5987–6002, https://doi.org/10.5194/hess-26-5987-2022, https://doi.org/10.5194/hess-26-5987-2022, 2022
Short summary
Short summary
Ocean surges can impact the stability of beaches by changing the hydraulic regime. These surge-induced changes in the hydraulic regime have important implications for coastal engineering and for beach morphology. This work uses 3D computer simulations to study how these alterations vary in space and time. We find that certain areas along and across the beach are potentially more vulnerable than others and that previous assumptions regarding the most dangerous places may need to be revised.
Lei Lin, Hao Liu, Xiaomeng Huang, Qingjun Fu, and Xinyu Guo
Hydrol. Earth Syst. Sci., 26, 5207–5225, https://doi.org/10.5194/hess-26-5207-2022, https://doi.org/10.5194/hess-26-5207-2022, 2022
Short summary
Short summary
Earth system (climate) model is an important instrument for projecting the global water cycle and climate change, in which tides are commonly excluded due to the much small timescales compared to the climate. However, we found that tides significantly impact the river water transport pathways, transport timescales, and concentrations in shelf seas. Thus, the tidal effect should be carefully considered in earth system models to accurately project the global water and biogeochemical cycle.
Marc Diego-Feliu, Valentí Rodellas, Aaron Alorda-Kleinglass, Maarten Saaltink, Albert Folch, and Jordi Garcia-Orellana
Hydrol. Earth Syst. Sci., 26, 4619–4635, https://doi.org/10.5194/hess-26-4619-2022, https://doi.org/10.5194/hess-26-4619-2022, 2022
Short summary
Short summary
Rainwater infiltrates aquifers and travels a long subsurface journey towards the ocean where it eventually enters below sea level. In its path towards the sea, water becomes enriched in many compounds that are naturally or artificially present within soils and sediments. We demonstrate that extreme rainfall events may significantly increase the inflow of water to the ocean, thereby increasing the supply of these compounds that are fundamental for the sustainability of coastal ecosystems.
Alexey Katin, Dario Del Giudice, and Daniel R. Obenour
Hydrol. Earth Syst. Sci., 26, 1131–1143, https://doi.org/10.5194/hess-26-1131-2022, https://doi.org/10.5194/hess-26-1131-2022, 2022
Short summary
Short summary
Low oxygen conditions (hypoxia) occur almost every summer in the northern Gulf of Mexico. Here, we present a new approach for forecasting hypoxia from June through September, leveraging a process-based model and an advanced statistical framework. We also show how using spring hydrometeorological information can improve forecast accuracy while reducing uncertainties. The proposed forecasting system shows the potential to support the management of threatened coastal ecosystems and fisheries.
Ahmed A. Nasr, Thomas Wahl, Md Mamunur Rashid, Paula Camus, and Ivan D. Haigh
Hydrol. Earth Syst. Sci., 25, 6203–6222, https://doi.org/10.5194/hess-25-6203-2021, https://doi.org/10.5194/hess-25-6203-2021, 2021
Short summary
Short summary
We analyse dependences between different flooding drivers around the USA coastline, where the Gulf of Mexico and the southeastern and southwestern coasts are regions of high dependence between flooding drivers. Dependence is higher during the tropical season in the Gulf and at some locations on the East Coast but higher during the extratropical season on the West Coast. The analysis gives new insights on locations, driver combinations, and the time of the year when compound flooding is likely.
Víctor M. Santos, Mercè Casas-Prat, Benjamin Poschlod, Elisa Ragno, Bart van den Hurk, Zengchao Hao, Tímea Kalmár, Lianhua Zhu, and Husain Najafi
Hydrol. Earth Syst. Sci., 25, 3595–3615, https://doi.org/10.5194/hess-25-3595-2021, https://doi.org/10.5194/hess-25-3595-2021, 2021
Short summary
Short summary
We present an application of multivariate statistical models to assess compound flooding events in a managed reservoir. Data (from a previous study) were obtained from a physical-based hydrological model driven by a regional climate model large ensemble, providing a time series expanding up to 800 years in length that ensures stable statistics. The length of the data set allows for a sensitivity assessment of the proposed statistical framework to natural climate variability.
Wenyan Wu, Seth Westra, and Michael Leonard
Hydrol. Earth Syst. Sci., 25, 2821–2841, https://doi.org/10.5194/hess-25-2821-2021, https://doi.org/10.5194/hess-25-2821-2021, 2021
Short summary
Short summary
Flood probability estimation is important for applications such as land use planning, reservoir operation, infrastructure design and safety assessments. However, it is a challenging task, especially in estuarine areas where floods are caused by both intense rainfall and storm surge. This study provides a review of approaches to flood probability estimation in these areas. Based on analysis of a real-world river system, guidance on method selection is provided.
Angelo Breda, Patricia M. Saco, Steven G. Sandi, Neil Saintilan, Gerardo Riccardi, and José F. Rodríguez
Hydrol. Earth Syst. Sci., 25, 769–786, https://doi.org/10.5194/hess-25-769-2021, https://doi.org/10.5194/hess-25-769-2021, 2021
Short summary
Short summary
We study accretion, retreat and transgression of mangrove and saltmarsh wetlands affected by sea-level rise (SLR) using simulations on typical configurations with different levels of tidal obstruction. Interactions and feedbacks between flow, sediment deposition, vegetation migration and soil accretion result in wetlands not surviving the predicted high-emission scenario SLR, despite dramatic increases in sediment supply. Previous simplified models overpredict wetland resilience to SLR.
Peisheng Huang, Karl Hennig, Jatin Kala, Julia Andrys, and Matthew R. Hipsey
Hydrol. Earth Syst. Sci., 24, 5673–5697, https://doi.org/10.5194/hess-24-5673-2020, https://doi.org/10.5194/hess-24-5673-2020, 2020
Short summary
Short summary
Our results conclude that the climate change in the past decades has a remarkable effect on the hydrology of a large shallow lagoon with the same magnitude as that caused by the opening of an artificial channel, and it also highlighted the complexity of their interactions. We suggested that the consideration of the projected drying trend is essential in designing management plans associated with planning for environmental water provision and setting water quality loading targets.
Jianrong Zhu, Xinyue Cheng, Linjiang Li, Hui Wu, Jinghua Gu, and Hanghang Lyu
Hydrol. Earth Syst. Sci., 24, 5043–5056, https://doi.org/10.5194/hess-24-5043-2020, https://doi.org/10.5194/hess-24-5043-2020, 2020
Short summary
Short summary
An extremely severe saltwater intrusion event occurred in February 2014 in the Changjiang estuary and seriously influenced the water intake of the reservoir. For the event cause and for freshwater safety, the dynamic mechanism was studied with observed data and a numerical model. The results indicated that this event was caused by a persistent and strong northerly wind, which formed a horizontal estuarine circulation, surpassed seaward runoff and drove highly saline water into the estuary.
Huayang Cai, Ping Zhang, Erwan Garel, Pascal Matte, Shuai Hu, Feng Liu, and Qingshu Yang
Hydrol. Earth Syst. Sci., 24, 1871–1889, https://doi.org/10.5194/hess-24-1871-2020, https://doi.org/10.5194/hess-24-1871-2020, 2020
Short summary
Short summary
Understanding the morphological changes in estuaries due to natural processes and human interventions is especially important with regard to sustainable water management and ecological impacts on the estuarine environment. In this contribution, we explore the morphological evolution in tide-dominated estuaries by means of a novel analytical approach using the observed water levels along the channel. The method could serve as a useful tool to understand the evolution of estuarine morphology.
Huayang Cai, Hubert H. G. Savenije, Erwan Garel, Xianyi Zhang, Leicheng Guo, Min Zhang, Feng Liu, and Qingshu Yang
Hydrol. Earth Syst. Sci., 23, 2779–2794, https://doi.org/10.5194/hess-23-2779-2019, https://doi.org/10.5194/hess-23-2779-2019, 2019
Short summary
Short summary
Tide–river dynamics play an essential role in large-scale river deltas as they exert a tremendous impact on delta morphodynamics, salt intrusion and deltaic ecosystems. For the first time, we illustrate that there is a critical river discharge, beyond which tidal damping is reduced with increasing river discharge, and we explore the underlying mechanism using an analytical model. The results are useful for guiding sustainable water management and sediment transport in tidal rivers.
Pedro D. Barrera Crespo, Erik Mosselman, Alessio Giardino, Anke Becker, Willem Ottevanger, Mohamed Nabi, and Mijail Arias-Hidalgo
Hydrol. Earth Syst. Sci., 23, 2763–2778, https://doi.org/10.5194/hess-23-2763-2019, https://doi.org/10.5194/hess-23-2763-2019, 2019
Short summary
Short summary
Guayaquil, the commercial capital of Ecuador, is located along the Guayas River. The city is among the most vulnerable cities to future flooding ascribed to climate change. Fluvial sedimentation is seen as one of the factors contributing to flooding. This paper describes the dominant processes in the river and the effects of past interventions in the overall sediment budget. This is essential to plan and design effective mitigation measures to face the latent risk that threatens Guayaquil.
Soufiane Haddout, Mohammed Igouzal, and Abdellatif Maslouhi
Hydrol. Earth Syst. Sci., 20, 3923–3945, https://doi.org/10.5194/hess-20-3923-2016, https://doi.org/10.5194/hess-20-3923-2016, 2016
Chiara Volta, Goulven Gildas Laruelle, Sandra Arndt, and Pierre Regnier
Hydrol. Earth Syst. Sci., 20, 991–1030, https://doi.org/10.5194/hess-20-991-2016, https://doi.org/10.5194/hess-20-991-2016, 2016
Short summary
Short summary
A generic estuarine model is applied to three idealized tidal estuaries representing the main hydro-geometrical estuarine classes. The study provides insight into the estuarine biogeochemical dynamics, in particular the air-water CO2/sub> flux, as well as the potential response to future environmental changes and to uncertainties in model parameter values. We believe that our approach could help improving upscaling strategies to better integrate estuaries in regional/global biogeochemical studies.
M. Webber, M. T. Li, J. Chen, B. Finlayson, D. Chen, Z. Y. Chen, M. Wang, and J. Barnett
Hydrol. Earth Syst. Sci., 19, 4411–4425, https://doi.org/10.5194/hess-19-4411-2015, https://doi.org/10.5194/hess-19-4411-2015, 2015
Short summary
Short summary
This paper demonstrates a method for calculating the probability of long-duration salt intrusions in the Yangtze Estuary and examines the impact of the Three Gorges Dam, the South-North Water Transfer Project and local abstractions on that probability. The relationship between river discharge and the intensity and duration of saline intrusions is shown to be probabilistic and continuous. That probability has more than doubled under the normal operating rules for those projects.
F. M. Achete, M. van der Wegen, D. Roelvink, and B. Jaffe
Hydrol. Earth Syst. Sci., 19, 2837–2857, https://doi.org/10.5194/hess-19-2837-2015, https://doi.org/10.5194/hess-19-2837-2015, 2015
Short summary
Short summary
Suspended sediment concentration (SSC) levels are important indicator for the ecology of estuaries. Observations of SSC are difficult to make, therefore we revert to coupled 2-D hydrodynamic-sediment process-based transport models to make predictions in time (seasonal and yearly) and space (meters to kilometers). This paper presents calibration/validation of SSC for the Sacramento-San Joaquin Delta and translates SSC to turbidity in order to couple with ecology models.
J. I. A. Gisen, H. H. G. Savenije, and R. C. Nijzink
Hydrol. Earth Syst. Sci., 19, 2791–2803, https://doi.org/10.5194/hess-19-2791-2015, https://doi.org/10.5194/hess-19-2791-2015, 2015
Short summary
Short summary
We revised the predictive equations for two calibrated parameters in salt intrusion model (the Van der Burgh coefficient K and dispersion coefficient D) using an extended database of 89 salinity profiles including 8 newly conducted salinity measurements. The revised predictive equations consist of easily measured parameters such as the geometry of estuary, tide, friction and the Richardson number. These equations are useful in obtaining the first estimate of salinity distribution in an estuary.
V. D. Vinh, S. Ouillon, T. D. Thanh, and L. V. Chu
Hydrol. Earth Syst. Sci., 18, 3987–4005, https://doi.org/10.5194/hess-18-3987-2014, https://doi.org/10.5194/hess-18-3987-2014, 2014
N. V. Manh, N. V. Dung, N. N. Hung, B. Merz, and H. Apel
Hydrol. Earth Syst. Sci., 18, 3033–3053, https://doi.org/10.5194/hess-18-3033-2014, https://doi.org/10.5194/hess-18-3033-2014, 2014
L. C. Bruce, P. L. M. Cook, I. Teakle, and M. R. Hipsey
Hydrol. Earth Syst. Sci., 18, 1397–1411, https://doi.org/10.5194/hess-18-1397-2014, https://doi.org/10.5194/hess-18-1397-2014, 2014
C. Ferrarin, M. Ghezzo, G. Umgiesser, D. Tagliapietra, E. Camatti, L. Zaggia, and A. Sarretta
Hydrol. Earth Syst. Sci., 17, 1733–1748, https://doi.org/10.5194/hess-17-1733-2013, https://doi.org/10.5194/hess-17-1733-2013, 2013
T. Sun, J. Xu, and Z. F. Yang
Hydrol. Earth Syst. Sci., 17, 751–760, https://doi.org/10.5194/hess-17-751-2013, https://doi.org/10.5194/hess-17-751-2013, 2013
M. Faneca Sànchez, J. L. Gunnink, E. S. van Baaren, G. H. P. Oude Essink, B. Siemon, E. Auken, W. Elderhorst, and P. G. B. de Louw
Hydrol. Earth Syst. Sci., 16, 4499–4516, https://doi.org/10.5194/hess-16-4499-2012, https://doi.org/10.5194/hess-16-4499-2012, 2012
E. F. Zhang, H. H. G. Savenije, S. L. Chen, and X. H. Mao
Hydrol. Earth Syst. Sci., 16, 3327–3339, https://doi.org/10.5194/hess-16-3327-2012, https://doi.org/10.5194/hess-16-3327-2012, 2012
A. van Buuren, L. Gerrits, and G. R. Teisman
Hydrol. Earth Syst. Sci., 14, 2243–2257, https://doi.org/10.5194/hess-14-2243-2010, https://doi.org/10.5194/hess-14-2243-2010, 2010
Cited articles
Aas, K., Czado, C., Frigessi, A., and Bakken, H.: Pair-copula constructions of multiple dependence, Insurance: Mathematics and Economics, 44, 182–198, https://doi.org/10.1016/j.insmatheco.2007.02.001, 2009.
Acar, E. F., Genest, C., and Nešlehová, J.: Beyond simplified pair-copula constructions, J. Multivariate Anal., 110, 74–90, https://doi.org/10.1016/j.jmva.2012.02.001, 2012.
Aghakouchak, A., Cheng, L., Mazdiyasni, O., and Farahmand, A.: Global warming and changes in risk of concurrent climate extremes: Insights from the 2014 California drought, Geophys. Res. Lett., 41, 8847–8852, https://doi.org/10.1002/2014gl062308, 2014.
Arpa Emilia-Romagna: Servizio IdroMeteoClima, Unità Radarmeteorologia, Radarpluviometria, Nowcasting e Reti non convenzionali, Area Centro Funzionale e Sala Operativa Previsioni, Unità gestione Rete idrometeorologica RIRER,Area Modellistica Meteo: Rapporto dell'evento meteorologico del 5 e 6 febbraio 2015, Bologna, Italy, 2015.
Bedford, T. and Cooke, R. M.: Monte Carlo simulation of vine dependent random variables for applications in uncertainty analysis, Proceedings of the European Conference on Safety and Reliability 2001, Turin, Italy, 2001a.
Bedford, T. and Cooke, R. M.: Probability density decomposition for conditionally dependent random variables modeled by vines, Ann. Math. Artif. Intel., 32, 245–268, https://doi.org/10.1023/A:1016725902970, 2001b.
Bedford, T. and Cooke, R. M.: Vines–a new graphical model for dependent random variables, Ann. Stat., 30, 1031–1068, https://doi.org/10.1214/aos/1031689016, 2002.
Bevacqua, E.: CDVineCopulaConditional: Sampling from Conditional C- and D-Vine Copulas, R package version 0.1.0, https://CRAN.R-project.org/package=CDVineCopulaConditional, last access: 1 June 2017.
Brechmann, E. C., Hendrich, K., and Czado, C.: Conditional copula simulation for systemic risk stress testing, Insurance: Mathematics and Economics, 53, 722–732, https://doi.org/10.1016/j.insmatheco.2013.09.009, 2013.
Carbognin, L., Teatini, P., Tosi, L., Strozzi, T., and Tomasin, A.: Present Relative Sea Level Rise in the Northern Adriatic Coastal Area, In: Coastal and marine spatial planning. Marine Research at CNR, DTA/06, CNR – Dipartimento Scienze del Sistema Terra e Tecnologie, Roma, 1147–1162, 2011.
Coles, S.: An introduction to statistical modeling of extreme values, Springer, London, 47–49, 2001.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., Rosnay, P. D., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
De Michele, C., Salvadori, G., Vezzoli, R., and Pecora, S.: Multivariate assessment of droughts: Frequency analysis and dynamic return period, Water Resour. Res., 49, 6985–6994, https://doi.org/10.1002/wrcr.20551, 2013.
Fischer, E. M., Seneviratne, S. I., Vidale, P. L., Lüthi, D., and Schär, C.: Soil Moisture-Atmosphere Interactions during the 2003 European Summer Heat Wave, J. Climate, 20, 5081–5099, https://doi.org/10.1175/jcli4288.1, 2007.
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins, W., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P., Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.: Evaluation of Climate Models, 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., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 790–791, 2013.
Gambolati, G., Teatini, P., and Gonella, M.: GIS simulations of the inundation risk in the coastal lowlands of the Northern Adriatic Sea, Math. Comput. Model., 35, 963–972, https://doi.org/10.1016/s0895-7177(02)00063-8, 2002.
Genest, C. and Favre, A.-C.: Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask, J. Hydrol. Eng., 12, 347–368, https://doi.org/10.1061/(asce)1084-0699(2007)12:4(347), 2007.
Genest, C., Ghoudi, K., and Rivest, L.-P.: A semiparametric estimation procedure of dependence parameters in multivariate families of distributions, Biometrika, 82, 543–552, https://doi.org/10.1093/biomet/82.3.543, 1995.
Giorgi, F., Jones, C., and Asrar, G. R.: Addressing climate information needs at the regional level: the CORDEX framework, WMO Bulletin, 58, 175–183, 2009.
Gräler, B., van den Berg, M. J., Vandenberghe, S., Petroselli, A., Grimaldi, S., De Baets, B., and Verhoest, N. E. C.: Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation, Hydrol. Earth Syst. Sci., 17, 1281–1296, https://doi.org/10.5194/hess-17-1281-2013, 2013.
Gräler, B., Petroselli, A., Grimaldi, S., De Baets, B., and Verhoest, N.: An update on multivariate return periods in hydrology, Proc. IAHS, 373, 175–178, https://doi.org/10.5194/piahs-373-175-2016, 2016.
Heffernan, J. E. and Stephenson, A. G.: ismev: An Introduction to Statistical Modeling of Extreme Values. R package version 1.41, https://CRAN.R-project.org/package=ismev (last access: 1 June 2017), 2016.
Hobæk Haff, I.: Comparison of estimators for pair-copula constructions, J. Multivariate Anal., 110, 91–105, https://doi.org/10.1016/j.jmva.2011.08.013, 2012.
Hobæk Haff, I.: Parameter estimation for pair-copula constructions, Bernoulli, 19, 462–491, https://doi.org/10.3150/12-bej413, 2013.
Hobæk Haff, I., Aas, K., and Frigessi, A.: On the simplified pair-copula construction – Simply useful or too simplistic?, J. Multivariate Anal., 101, 1296–1310, https://doi.org/10.1016/j.jmva.2009.12.001, 2010.
Hobæk Haff, I., Frigessi, A., and Maraun, D.: How well do regional climate models simulate the spatial dependence of precipitation? An application of pair-copula constructions, Journal of Geophysical Research: Atmospheres J. Geophys. Res.-Atmos., 120, 2624–2646, https://doi.org/10.1002/2014jd022748, 2015.
Joe, H.: Families of m-variate distributions with given margins and m(m − 1)∕2 bivariate dependence parameters, Institute of Mathematical Statistics Lecture Notes – Monograph Series Distributions with fixed marginals and related topics, 120–141, https://doi.org/10.1214/lnms/1215452614, 1996.
Joe, H.: Multivariate Models and Multivariate Dependence Concepts, Taylor Francis Ltd, United States, 2014.
Kew, S. F., Selten, F. M., Lenderink, G., and Hazeleger, W.: The simultaneous occurrence of surge and discharge extremes for the Rhine delta, Nat. Hazards Earth Syst. Sci., 13, 2017–2029, https://doi.org/10.5194/nhess-13-2017-2013, 2013.
Klerk, W. J., Winsemius, H. C., Verseveld, W. J. V., Bakker, A. M. R., and Diermanse, F. L. M.: The co-incidence of storm surges and extreme discharges within the Rhine-Meuse Delta, Environ. Res. Lett., 10, 035005, https://doi.org/10.1088/1748-9326/10/3/035005, 2015.
Kurowicka, D. and Cooke, R. M.: Sampling algorithms for generating joint uniform distributions using the vine – copula method, 3rd IASC world conference on Computational Statistics and Data Analysis, Limassol, Cyprus, 2005.
Leonard, M., Westra, S., Phatak, A., Lambert, M., Van den Hurk, B., Mcinnes, K., Risbey, J., Schuster, S., Jakob, D., and Stafford-Smith, M.: A compound event framework for understanding extreme impacts, WIREs Clim Change Wiley Interdisciplinary Reviews: Climate Change, 5, 113–128, https://doi.org/10.1002/wcc.252, 2014.
Lian, J. J., Xu, K., and Ma, C.: Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China, Hydrol. Earth Syst. Sci., 17, 679–689, https://doi.org/10.5194/hess-17-679-2013, 2013.
LIFE PRIMES: Preventing flooding RIsks by Making resilient communitiES: http://ec.europa.eu/environment/life/project/Projects/index.cfm?fuseaction=search.dspPage&n_proj_id=5247, last access: 6 December 2016a.
LIFE PRIMES: Il progetto LIFE PRIMES, http://protezionecivile.regione.emilia-romagna.it/life-primes/progetto/progetto-life-primes/il-progetto-life-primes, last access: 6 December 2016b.
Liu, Z., Zhou, P., Chen, X., and Guan, Y.: A multivariate conditional model for streamflow prediction and spatial precipitation refinement, J. Geophys. Res.-Atmos., 120, 10116–10129, https://doi.org/10.1002/2015jd023787, 2015.
Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J., Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Themeßl, M., Venema, V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and Thiele-Eich, I.: Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user, Rev. Geophys., 48, RG3003, https://doi.org/10.1029/2009rg000314, 2010.
Maraun, D.: Reply to “Comment on “Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue””, J. Climate, 27, 1821–1825, https://doi.org/10.1175/jcli-d-13-00307.1, 2014.
Masina, M., Lamberti, A., and Archetti, R.: Coastal flooding: A copula based approach for estimating the joint probability of water levels and waves, Coast. Eng., 97, 37–52, https://doi.org/10.1016/j.coastaleng.2014.12.010, 2015.
Materia, S., Dirmeyer, P. A., Guo, Z., Alessandri, A., and Navarra, A.: The Sensitivity of Simulated River Discharge to Land Surface Representation and Meteorological Forcings, J. Hydrometeorol., 11, 334–351, https://doi.org/10.1175/2009jhm1162.1, 2010.
Nelsen, R. B.: An introduction to copulas, Springer, New York, 2006.
NOAA, Tides and Currents: https://tidesandcurrents.noaa.gov/, last access: 14 March 2017.
Pathiraja, S., Westra, S., and Sharma, A.: Why continuous simulation? The role of antecedent moisture in design flood estimation, Water Resour. Res., 48, W06534, https://doi.org/10.1029/2011wr010997, 2012.
R Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 1 June 2017), 2016.
Saghafian, B. and Mehdikhani, H.: Drought characterization using a new copula-based trivariate approach, Nat. Hazards, 72, 1391–1407, https://doi.org/10.1007/s11069-013-0921-6, 2013.
Salvadori, G. and De Michele, C.: On the Use of Copulas in Hydrology: Theory and Practice, J. Hydrol. Eng., 12, 369–380, https://doi.org/10.1061/(asce)1084-0699(2007)12:4(369), 2007.
Salvadori, G., De Michele, C., Kottegoda, N. T., and Rosso, R.: Extremes in nature: an approach using Copulas, Springer, Dordrecht, the Netherlands, 2007.
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.
Salvadori, G., Durante, F., Tomasicchio, G., and D'alessandro, F.: Practical guidelines for the multivariate assessment of the structural risk in coastal and off-shore engineering, Coast. Eng., 95, 77–83, https://doi.org/10.1016/j.coastaleng.2014.09.007, 2015.
Salvadori, G., Durante, F., Michele, C. D., 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.
Schepsmeier, U., Stoeber, J., Brechmann, E. C., Graeler, B., Nagler, T., and Erhardt, T.: VineCopula: Statistical Inference of Vine Copulas, R package version 2.0.5, https://CRAN.R-project.org/package=VineCopula (last access: 1 June 2017), 2016.
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.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture-climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010.
Seneviratne, S. I., Nicholls, N., Easterling, D., Goodess, C. M., Kanae, S., Kossin, J., Luo, Y., Marengo, J., Mcinnes, K., Rahimi, M., Reichstein, M., Sorteberg, A., Vera, C., Zhang, X., Rusticucci, M., Semenov, V., Alexander, L. V., Allen, S., Benito, G., Cavazos, T., Clague, J., Conway, D., Della-Marta, P. M., Gerber, M., Gong, S., Goswami, B. N., Hemer, M., Huggel, C., Van den Hurk, B., Kharin, V. V., Kitoh, A., Tank, A. M. K., Li, G., Mason, S., Mcguire, W., Oldenborgh, G. J. V., Orlowsky, B., Smith, S., Thiaw, W., Velegrakis, A., Yiou, P., Zhang, T., Zhou, T., and Zwiers, F. W.: Changes in Climate Extremes and their Impacts on the Natural Physical Environment, Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation Special Report of the Intergovernmental Panel on Climate Change, 109–230, https://doi.org/10.1017/cbo9781139177245.006, 2012.
Serinaldi, F.: Can we tell more than we can know? The limits of bivariate drought analyses in the United States, Stoch. Env. Res. Risk A., 30, 1691, https://doi.org/10.1007/s00477-015-1124-3, 2015.
Serinaldi, F., Bonaccorso, B., Cancelliere, A., and Grimaldi, S.: Probabilistic characterization of drought properties through copulas, Phys. Chem. Earth, 34, 596–605, https://doi.org/10.1016/j.pce.2008.09.004, 2009.
Shiau, J. T.: Return period of bivariate distributed extreme hydrological events, Stoch. Env. Res. Risk A., 17, 42–57, https://doi.org/10.1007/s00477-003-0125-9, 2003.
Shiau, J.-T., Feng, S., and Nadarajah, S.: Assessment of hydrological droughts for the Yellow River, China, using copulas, Hydrol. Process., 21, 2157–2163, https://doi.org/10.1002/hyp.6400, 2007.
Sklar, A.: Fonctions de Répartition à Dimensions et Leurs marges, 8, Publications de l'Institut de Statistique de L'Université de Paris, Paris, France, 1959.
Stöber, J., Joe, H., and Czado, C.: Simplified pair copula constructions – Limitations and extensions, J. Multivariate Anal., 119, 101–118, https://doi.org/10.1016/j.jmva.2013.04.014, 2013.
Svensson, C. and Jones, D. A.: Dependence between extreme sea surge, river flow and precipitation in eastern Britain, Int. J. Climatol., 22, 1149–1168, https://doi.org/10.1002/joc.794, 2002.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/bams-d-11-00094.1, 2012.
Tisseuil, C., Vrac, M., Lek, S., and Wade, A. J.: Statistical downscaling of river flows, J. Hydrol., 385, 279–291, https://doi.org/10.1016/j.jhydrol.2010.02.030, 2010.
Tsimplis, M. N. and Woodworth, P. L.: The global distribution of the seasonal sea level cycle calculated from coastal tide gauge data, J. Geophys. Res., 99, 16031, https://doi.org/10.1029/94jc01115, 1994.
Van Den Brink, H. W., Können, G. P., Opsteegh, J. D., Oldenborgh, G. J. V., and Burgers, G.: Improving 104-year surge level estimates using data of the ECMWF seasonal prediction system, Geophys. Res. Lett., 31, L17210, https://doi.org/10.1029/2004gl020610, 2004.
Van Den Brink, H. W., Können, G. P., Opsteegh, J. D., Oldenborgh, G. J. V., and Burgers, G.: Estimating return periods of extreme events from ECMWF seasonal forecast ensembles, Int. J. Climatol., 25, 1345–1354, https://doi.org/10.1002/joc.1155, 2005.
Van den Hurk, B., Meijgaard, E. V., Valk, P. D., Heeringen, K.-J. V., and Gooijer, J.: Analysis of a compounding surge and precipitation event in the Netherlands, Environ. Res. Lett., 10, 035001, https://doi.org/10.1088/1748-9326/10/3/035001, 2015.
Wahl, T., Jain, S., Bender, J., Meyers, S. D., and Luther, M. E.: Increasing risk of compound flooding from storm surge and rainfall for major US cities, Nature Climate Change, 5, 1093–1097, https://doi.org/10.1038/nclimate2736, 2015.
Widmann, M.: One-Dimensional CCA and SVD, and Their Relationship to Regression Maps, J. Climate, 18, 2785–2792, https://doi.org/10.1175/jcli3424.1, 2005.
Volpi, E. and Fiori, A.: Hydraulic structures subject to bivariate hydrological loads: Return period, design, and risk assessment, Water Resour. Res., 50, 885–897, https://doi.org/10.1002/2013wr014214, 2014.
Zheng, F., Westra, S., and Sisson, S. A.: Quantifying the dependence between extreme rainfall and storm surge in the coastal zone, J. Hydrol., 505, 172–187, https://doi.org/10.1016/j.jhydrol.2013.09.054, 2013.
Zheng, F., Westra, S., Leonard, M., and Sisson, S. A.: Modeling dependence between extreme rainfall and storm surge to estimate coastal flooding risk, Water Resour. Res., 50, 2050–2071, https://doi.org/10.1002/2013wr014616, 2014.
Zheng, F., Leonard, M., and Westra, S.: Efficient joint probability analysis of flood risk, J. Hydroinform., 17, 584, 584–597, https://doi.org/10.2166/hydro.2015.052, 2015.
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.
We develop a conceptual model to quantify the risk of compound events (CEs), i.e. extreme...