Articles | Volume 20, issue 6
https://doi.org/10.5194/nhess-20-1765-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-20-1765-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Brief communication
| 
17 Jun 2020
Brief communication |
| 17 Jun 2020
| 17 Jun 2020
Brief communication: The role of using precipitation or river discharge data when assessing global coastal compound flooding
Emanuele Bevacqua
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
Invited contribution by Emanuele Bevacqua, recipient of the Outstanding Student Poster and PICO (OSPP) Award 2018.
Michalis I. Vousdoukas
Joint Research Centre (JRC), European Commission, Ispra, Italy
Theodore G. Shepherd
Department of Meteorology, University of Reading, Reading, UK
Mathieu Vrac
Laboratoire des Sciences du Climat et de l'Environnement, CNRS/IPSL, Gif-sur-Yvette, France
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Derrick Muheki, Axel A. J. Deijns, Emanuele Bevacqua, Gabriele Messori, Jakob Zscheischler, and Wim Thiery
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Nat. Hazards Earth Syst. Sci., 22, 3897–3915, https://doi.org/10.5194/nhess-22-3897-2022, https://doi.org/10.5194/nhess-22-3897-2022, 2022
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Sandy dunes protect the hinterland from coastal flooding during storms. Thus, models that can efficiently predict dune erosion are critical for coastal zone management and early warning systems. Here we develop such a model for the Dutch coast based on machine learning techniques, allowing for dune erosion estimations in a matter of seconds relative to available computationally expensive models. Validation of the model against benchmark data and observations shows good agreement.
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
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Philipp Breul, Paulo Ceppi, and Theodore G. Shepherd
Weather Clim. Dynam., 3, 645–658, https://doi.org/10.5194/wcd-3-645-2022, https://doi.org/10.5194/wcd-3-645-2022, 2022
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Understanding how the mid-latitude jet stream will respond to a changing climate is highly important. Unfortunately, climate models predict a wide variety of possible responses. Theoretical frameworks can link an internal jet variability timescale to its response. However, we show that stratospheric influence approximately doubles the internal timescale, inflating predicted responses. We demonstrate an approach to account for the stratospheric influence and recover correct response predictions.
Wilson C. H. Chan, Theodore G. Shepherd, Katie Facer-Childs, Geoff Darch, and Nigel W. Arnell
Hydrol. Earth Syst. Sci., 26, 1755–1777, https://doi.org/10.5194/hess-26-1755-2022, https://doi.org/10.5194/hess-26-1755-2022, 2022
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We select the 2010–2012 UK drought and investigate an alternative unfolding of the drought from changes to its attributes. We created storylines of drier preconditions, alternative seasonal contributions, a third dry winter, and climate change. Storylines of the 2010–2012 drought show alternative situations that could have resulted in worse conditions than observed. Event-based storylines exploring plausible situations are used that may lead to high impacts and help stress test existing systems.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
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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
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Adam A. Scaife, Mark P. Baldwin, Amy H. Butler, Andrew J. Charlton-Perez, Daniela I. V. Domeisen, Chaim I. Garfinkel, Steven C. Hardiman, Peter Haynes, Alexey Yu Karpechko, Eun-Pa Lim, Shunsuke Noguchi, Judith Perlwitz, Lorenzo Polvani, Jadwiga H. Richter, John Scinocca, Michael Sigmond, Theodore G. Shepherd, Seok-Woo Son, and David W. J. Thompson
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Great progress has been made in computer modelling and simulation of the whole climate system, including the stratosphere. Since the late 20th century we also gained a much clearer understanding of how the stratosphere interacts with the lower atmosphere. The latest generation of numerical prediction systems now explicitly represents the stratosphere and its interaction with surface climate, and here we review its role in long-range predictions and projections from weeks to decades ahead.
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
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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
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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.
Piero Lionello, David Barriopedro, Christian Ferrarin, Robert J. Nicholls, Mirko Orlić, Fabio Raicich, Marco Reale, Georg Umgiesser, Michalis Vousdoukas, and Davide Zanchettin
Nat. Hazards Earth Syst. Sci., 21, 2705–2731, https://doi.org/10.5194/nhess-21-2705-2021, https://doi.org/10.5194/nhess-21-2705-2021, 2021
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In this review we describe the factors leading to the extreme water heights producing the floods of Venice. We discuss the different contributions, their relative importance, and the resulting compound events. We highlight the role of relative sea level rise and the observed past and very likely future increase in extreme water heights, showing that they might be up to 160 % higher at the end of the 21st century than presently.
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
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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
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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.
Linda van Garderen, Frauke Feser, and Theodore G. Shepherd
Nat. Hazards Earth Syst. Sci., 21, 171–186, https://doi.org/10.5194/nhess-21-171-2021, https://doi.org/10.5194/nhess-21-171-2021, 2021
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The storyline method is used to quantify the effect of climate change on a particular extreme weather event using a global atmospheric model by simulating the event with and without climate change. We present the method and its successful application for the climate change signals of the European 2003 and the Russian 2010 heatwaves.
Marlene Kretschmer, Giuseppe Zappa, and Theodore G. Shepherd
Weather Clim. Dynam., 1, 715–730, https://doi.org/10.5194/wcd-1-715-2020, https://doi.org/10.5194/wcd-1-715-2020, 2020
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The winds in the polar stratosphere affect the weather in the mid-latitudes, making it important to understand potential changes in response to global warming. However, climate model projections disagree on how this so-called polar vortex will change in the future. Here we show that sea ice loss in the Barents and Kara (BK) seas plays a central role in this. The time when the BK seas become ice-free differs between models, which explains some of the disagreement regarding vortex projections.
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
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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.
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
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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
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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
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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
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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
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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.
Panagiotis Athanasiou, Ap van Dongeren, Alessio Giardino, Michalis Vousdoukas, Sandra Gaytan-Aguilar, and Roshanka Ranasinghe
Earth Syst. Sci. Data, 11, 1515–1529, https://doi.org/10.5194/essd-11-1515-2019, https://doi.org/10.5194/essd-11-1515-2019, 2019
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This dataset provides the spatial distribution of nearshore slopes at a resolution of 1 km along the global coastline. The calculation was based on available global topo-bathymetric datasets and ocean wave reanalysis. The calculated slopes show skill in capturing the spatial variability of the nearshore slopes when compared against local observations. The importance of this variability is presented with a global coastal retreat assessment for an arbitrary sea level rise scenario.
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
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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
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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
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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
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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.
Michalis I. Vousdoukas, Dimitrios Bouziotas, Alessio Giardino, Laurens M. Bouwer, Lorenzo Mentaschi, Evangelos Voukouvalas, and Luc Feyen
Nat. Hazards Earth Syst. Sci., 18, 2127–2142, https://doi.org/10.5194/nhess-18-2127-2018, https://doi.org/10.5194/nhess-18-2127-2018, 2018
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We examine sources of epistemic uncertainty in coastal flood risk models. We find that uncertainty from sea level estimations can be higher than that related to greenhouse gas emissions or climate prediction errors. Of comparable importance is information on coastal protection levels and the topography. In the absence of large datasets with sufficient resolution and accuracy, the last two factors are the main bottlenecks in terms of estimating coastal flood risks at large scales.
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
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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
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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.
Dominik Paprotny, Michalis I. Vousdoukas, Oswaldo Morales-Nápoles, Sebastiaan N. Jonkman, and Luc Feyen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-132, https://doi.org/10.5194/hess-2018-132, 2018
Preprint withdrawn
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
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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
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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
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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
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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.
Isavela N. Monioudi, Adonis F. Velegrakis, Antonis E. Chatzipavlis, Anastasios Rigos, Theophanis Karambas, Michalis I. Vousdoukas, Thomas Hasiotis, Nikoletta Koukourouvli, Pascal Peduzzi, Eva Manoutsoglou, Serafim E. Poulos, and Michael B. Collins
Nat. Hazards Earth Syst. Sci., 17, 449–466, https://doi.org/10.5194/nhess-17-449-2017, https://doi.org/10.5194/nhess-17-449-2017, 2017
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This work constitutes the first comprehensive attempt to record the spatial characteristics of the Aegean island beaches (Greece) and assess the long-term and episodic sea level rise (SLR) impacts under different scenarios. Results suggest that Aegean beaches may be particularly vulnerable to SLRs, where severe impacts which could be devastating are projected by 2100. Appropriate coastal "setback zone" policies should be adopted, as they form a significant environmental and economic resource.
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
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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.
Lorenzo Mentaschi, Michalis Vousdoukas, Evangelos Voukouvalas, Ludovica Sartini, Luc Feyen, Giovanni Besio, and Lorenzo Alfieri
Hydrol. Earth Syst. Sci., 20, 3527–3547, https://doi.org/10.5194/hess-20-3527-2016, https://doi.org/10.5194/hess-20-3527-2016, 2016
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The climate is subject to variations which must be considered
studying the intensity and frequency of extreme events.
We introduce in this paper a new methodology
for the study of variable extremes, which consists in detecting
the pattern of variability of a time series, and applying these patterns
to the analysis of the extreme events.
This technique comes with advantages with respect to the previous ones
in terms of accuracy, simplicity, and robustness.
Michalis I. Vousdoukas, Evangelos Voukouvalas, Lorenzo Mentaschi, Francesco Dottori, Alessio Giardino, Dimitrios Bouziotas, Alessandra Bianchi, Peter Salamon, and Luc Feyen
Nat. Hazards Earth Syst. Sci., 16, 1841–1853, https://doi.org/10.5194/nhess-16-1841-2016, https://doi.org/10.5194/nhess-16-1841-2016, 2016
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Coastal flooding has severe socioeconomic impacts that are projected to increase under the changing climate. The present contribution reports on efforts towards a new methodology for mapping coastal flood hazard at European scale, combining the contribution of waves, improved inundation modeling and an open, physics-based framework which can be constantly upgraded whenever new and more accurate data become available.
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
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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.
C. McLandress, T. G. Shepherd, A. I. Jonsson, T. von Clarmann, and B. Funke
Atmos. Chem. Phys., 15, 9271–9284, https://doi.org/10.5194/acp-15-9271-2015, https://doi.org/10.5194/acp-15-9271-2015, 2015
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This is the first paper of its kind describing a method for merging the long-term satellite records of global stratospheric temperature from SSU and AMSU to yield a continuous data set from 1979 to present (and beyond). Since global-mean stratospheric temperature is close to radiative equilibrium, our "extended" SSU data set is an important climate record for the detection and attribution of anthropogenic influence.
V. Matthias, T. G. Shepherd, P. Hoffmann, and M. Rapp
Ann. Geophys., 33, 199–206, https://doi.org/10.5194/angeo-33-199-2015, https://doi.org/10.5194/angeo-33-199-2015, 2015
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A vertical coupling process in the northern high-latitude middle atmosphere has been identified during the equinox transitions, which we call the “hiccup” and which acts like a “mini sudden stratospheric warming (SSW)”. We study the average characteristics of the hiccup based on a composite analysis using a nudged model. A comparison of the average characteristics of hiccups and SSWs shows both similarities and differences between the two vertical coupling processes.
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
C. McLandress, D. A. Plummer, and T. G. Shepherd
Atmos. Chem. Phys., 14, 1547–1555, https://doi.org/10.5194/acp-14-1547-2014, https://doi.org/10.5194/acp-14-1547-2014, 2014
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Lena Wilhelm, Cornelia Schwierz, Katharina Schröer, Mateusz Taszarek, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 3869–3894, https://doi.org/10.5194/nhess-24-3869-2024, https://doi.org/10.5194/nhess-24-3869-2024, 2024
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In our study we used statistical models to reconstruct past hail days in Switzerland from 1959–2022. This new time series reveals a significant increase in hail day occurrences over the last 7 decades. We link this trend to increases in moisture and instability variables in the models. This time series can now be used to unravel the complexities of Swiss hail occurrence and to understand what drives its year-to-year variability.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024, https://doi.org/10.5194/nhess-24-3479-2024, 2024
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To effectively track and identify droughts, we developed a novel integrated drought index that combines the effects of precipitation, temperature, and soil moisture on drought. After comparison and verification, the integrated drought index shows superior performance compared to a single meteorological drought index or agricultural drought index in terms of drought identification.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 24, 3445–3460, https://doi.org/10.5194/nhess-24-3445-2024, https://doi.org/10.5194/nhess-24-3445-2024, 2024
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European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological loss index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high-impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci., 24, 3267–3277, https://doi.org/10.5194/nhess-24-3267-2024, https://doi.org/10.5194/nhess-24-3267-2024, 2024
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The train effect is related to convective cells that pass over the same place. Trains produce heavy rainfall and sometimes floods and are reported in North America during spring and summer. In Israel, 17 trains associated with Cyprus lows were identified by radar images and were found within the cold sector south of the low center and in the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km; last 1–3 h; and yield 35 mm of rainfall up to 60 mm.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
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A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024, https://doi.org/10.5194/nhess-24-3035-2024, 2024
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We have used the temperature and relative humidity sensors in smartphones to estimate the vapor pressure deficit (VPD), an important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal shows the potential for using smartphone data to compliment the regular weather station network while also providing high spatial resolution of the VPD index.
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, https://doi.org/10.5194/nhess-24-2939-2024, 2024
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High-impact river floods are often caused by extreme precipitation. Flood protection relies on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties in the return values can be substantially reduced compared to observational estimates.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
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Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024, https://doi.org/10.5194/nhess-24-2793-2024, 2024
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Weather prediction uncertainties can be described as sets of possible scenarios – a technique called ensemble prediction. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024, https://doi.org/10.5194/nhess-24-2633-2024, 2024
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What’s the worst that could happen? Recent floods are often claimed to be beyond our imagination. Imagination is the picturing of a situation in our mind and the emotions that we connect with this situation. But why is this important for disasters? This survey found that when we cannot imagine a devastating flood, we are not preparing in advance. Severe-weather forecasts and warnings need to advance in order to trigger our imagination of what might happen and enable us to start preparing.
Georgy Ayzel and Maik Heistermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1945, https://doi.org/10.5194/egusphere-2024-1945, 2024
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Forecasting rainfall over the next hour is an essential feature of early warning systems. Deep learning has emerged as a powerful alternative to conventional nowcasting technologies, but it still struggles to adequately predict impact-relevant heavy rainfall. We think that DL could do much better if the training tasks were defined more specifically, and that such a specification presents an opportunity to better align the output of nowcasting models with actual user requirements.
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024, https://doi.org/10.5194/nhess-24-2541-2024, 2024
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The study presents an open-source model to determine the occurrence of hail damage to field crops and grapevines after hailstorms in Switzerland based on radar, agricultural land use data, and insurance damage reports. The model performs best at 8 km resolution for field crops and 1 km for grapevine and in the main production areas. Highlighting performance trade-offs and the relevance of user needs, the study is a first step towards the assessment of risk and damage for crops in Switzerland.
Dieter Roel Poelman, Hannes Kohlmann, and Wolfgang Schulz
Nat. Hazards Earth Syst. Sci., 24, 2511–2522, https://doi.org/10.5194/nhess-24-2511-2024, https://doi.org/10.5194/nhess-24-2511-2024, 2024
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EUCLID's lightning data unveil distinctive ground strike point (GSP) patterns in Europe. Over seas, GSPs per flash surpass inland, reaching a minimum in the Alps. Mountainous areas like the Alps and Pyrenees have the closest GSP separation, highlighting terrain elevation's impact. The daily peak current correlates with average GSPs per flash. These findings could significantly influence lightning protection measures, urging a focus on GSP density rather than flash density for risk assessment.
Nicola Loglisci, Giorgio Boni, Arianna Cauteruccio, Francesco Faccini, Massimo Milelli, Guido Paliaga, and Antonio Parodi
Nat. Hazards Earth Syst. Sci., 24, 2495–2510, https://doi.org/10.5194/nhess-24-2495-2024, https://doi.org/10.5194/nhess-24-2495-2024, 2024
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We analyse the meteo-hydrological features of the 27 and 28 August 2023 event that occurred in Genoa. Rainfall observations were made using rain gauge networks based on either official networks or citizen science networks. The merged analysis stresses the spatial variability in the precipitation, which cannot be captured by the current spatial density of authoritative stations. Results show that at minimal distances the variations in cumulated rainfall over a sub-hourly duration are significant.
Ellina Agayar, Franziska Aemisegger, Moshe Armon, Alexander Scherrmann, and Heini Wernli
Nat. Hazards Earth Syst. Sci., 24, 2441–2459, https://doi.org/10.5194/nhess-24-2441-2024, https://doi.org/10.5194/nhess-24-2441-2024, 2024
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This study presents the results of a climatological investigation of extreme precipitation events (EPEs) in Ukraine for the period 1979–2019. During all seasons EPEs are associated with pronounced upper-level potential vorticity (PV) anomalies. In addition, we find distinct seasonal and regional differences in moisture sources. Several extreme precipitation cases demonstrate the importance of these processes, complemented by a detailed synoptic analysis.
Antonio Giordani, Michael Kunz, Kristopher M. Bedka, Heinz Jürgen Punge, Tiziana Paccagnella, Valentina Pavan, Ines M. L. Cerenzia, and Silvana Di Sabatino
Nat. Hazards Earth Syst. Sci., 24, 2331–2357, https://doi.org/10.5194/nhess-24-2331-2024, https://doi.org/10.5194/nhess-24-2331-2024, 2024
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To improve the challenging representation of hazardous hailstorms, a proxy for hail frequency based on satellite detections, convective parameters from high-resolution reanalysis, and crowd-sourced reports is tested and presented. Hail likelihood peaks in mid-summer at 15:00 UTC over northern Italy and shows improved agreement with observations compared to previous estimates. By separating ambient signatures based on hail severity, enhanced appropriateness for large-hail occurrence is found.
Claire L. Ryder, Clément Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
Nat. Hazards Earth Syst. Sci., 24, 2263–2284, https://doi.org/10.5194/nhess-24-2263-2024, https://doi.org/10.5194/nhess-24-2263-2024, 2024
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Desert dust poses a hazard to aircraft via degradation of engine components. This has financial implications for the aviation industry and results in increased fuel burn with climate impacts. Here we quantify dust ingestion by aircraft engines at airports worldwide. We find Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. Dust ingestion can be reduced by changing take-off times and the altitude of holding patterns.
Khalil Ur Rahman, Songhao Shang, Khaled Saeed Balkhair, Hamza Farooq Gabriel, Khan Zaib Jadoon, and Kifayat Zaman
Nat. Hazards Earth Syst. Sci., 24, 2191–2214, https://doi.org/10.5194/nhess-24-2191-2024, https://doi.org/10.5194/nhess-24-2191-2024, 2024
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This paper assesses the impact of drought (meteorological drought) on the hydrological alterations in major rivers of the Indus Basin. Threshold regression and range of variability analysis are used to determine the drought severity and times where drought has caused low flows and extreme low flows (identified using indicators of hydrological alterations). Moreover, this study also examines the degree of alterations in river flows due to drought using the hydrological alteration factor.
Alexander Frank Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Nat. Hazards Earth Syst. Sci., 24, 2115–2132, https://doi.org/10.5194/nhess-24-2115-2024, https://doi.org/10.5194/nhess-24-2115-2024, 2024
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The risk posed to ships by Arctic cyclones has seldom been quantified due to the lack of publicly available historical Arctic ship track data. This study investigates historical Arctic ship tracks, cyclone tracks, and shipping incident reports to determine the number of shipping incidents caused by the passage of Arctic cyclones. Results suggest that Arctic cyclones have not been hazardous to ships and that ships are resilient to the rough sea conditions caused by Arctic cyclones.
Joona Samuel Cornér, Clément Gael Francis Bouvier, Benjamin Doiteau, Florian Pantillon, and Victoria Anne Sinclair
EGUsphere, https://doi.org/10.5194/egusphere-2024-1749, https://doi.org/10.5194/egusphere-2024-1749, 2024
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Classification reduces the considerable variability between extratropical cyclones (ETC) and thus simplifies studying their representation in climate models and changes in the future climate. In this paper we present an objective classification of ETCs using measures of ETC intensity. This is motivated by the aim of finding a set of ETC intensity measures which together comprehensively describe both the dynamical and impact-relevant nature of ETC intensity.
Niklas Ebers, Kai Schröter, and Hannes Müller-Thomy
Nat. Hazards Earth Syst. Sci., 24, 2025–2043, https://doi.org/10.5194/nhess-24-2025-2024, https://doi.org/10.5194/nhess-24-2025-2024, 2024
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Future changes in sub-daily rainfall extreme values are essential in various hydrological fields, but climate scenarios typically offer only daily resolution. One solution is rainfall generation. With a temperature-dependent rainfall generator climate scenario data were disaggregated to 5 min rainfall time series for 45 locations across Germany. The analysis of the future 5 min rainfall time series showed an increase in the rainfall extremes values for rainfall durations of 5 min and 1 h.
Ran Zhu and Lei Chen
Nat. Hazards Earth Syst. Sci., 24, 1937–1950, https://doi.org/10.5194/nhess-24-1937-2024, https://doi.org/10.5194/nhess-24-1937-2024, 2024
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There is a positive correlation between the frequency of Jianghuai cyclone activity and precipitation during the Meiyu period. Its occurrence frequency has an obvious decadal variation, which corresponds well with the quasi-periodic and decadal variation in precipitation during the Meiyu period. This study provides a reference for the long-term and short-term forecasting of precipitation during the Meiyu period.
Andi Xhelaj and Massimiliano Burlando
Nat. Hazards Earth Syst. Sci., 24, 1657–1679, https://doi.org/10.5194/nhess-24-1657-2024, https://doi.org/10.5194/nhess-24-1657-2024, 2024
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The study provides an in-depth analysis of a severe downburst event in Sânnicolau Mare, Romania, utilizing an analytical model and optimization algorithm. The goal is to explore a multitude of generating solutions and to identify potential alternatives to the optimal solution. Advanced data analysis techniques help to discern three main distinct storm scenarios. For this particular event, the best overall solution from the optimization algorithm shows promise in reconstructing the downburst.
Monica Ionita, Petru Vaideanu, Bogdan Antonescu, Catalin Roibu, Qiyun Ma, and Viorica Nagavciuc
EGUsphere, https://doi.org/10.5194/egusphere-2024-1207, https://doi.org/10.5194/egusphere-2024-1207, 2024
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Eastern Europe's heatwave history is explored from 1885 to 2023, with a focus on pre-1960 events. The study reveals two periods with more frequent and intense heatwaves (HW): 1920s–1960s and 1980s–present. The research highlights the importance of a long-term perspective, revealing that extreme heat events have occurred throughout the entire study period and it emphasizes the combined influence of climate change and natural variations on increasing HW severity.
Luca G. Severino, Chahan M. Kropf, Hilla Afargan-Gerstman, Christopher Fairless, Andries Jan de Vries, Daniela I. V. Domeisen, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 1555–1578, https://doi.org/10.5194/nhess-24-1555-2024, https://doi.org/10.5194/nhess-24-1555-2024, 2024
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We combine climate projections from 30 climate models with a climate risk model to project winter windstorm damages in Europe under climate change. We study the uncertainty and sensitivity factors related to the modelling of hazard, exposure and vulnerability. We emphasize high uncertainties in the damage projections, with climate models primarily driving the uncertainty. We find climate change reshapes future European windstorm risk by altering damage locations and intensity.
Daniel Krieger, Sebastian Brune, Johanna Baehr, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 1539–1554, https://doi.org/10.5194/nhess-24-1539-2024, https://doi.org/10.5194/nhess-24-1539-2024, 2024
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Previous studies found that climate models can predict storm activity in the German Bight well for averages of 5–10 years but struggle in predicting the next winter season. Here, we improve winter storm activity predictions by linking them to physical phenomena that occur before the winter. We guess the winter storm activity from these phenomena and discard model solutions that stray too far from the guess. The remaining solutions then show much higher prediction skill for storm activity.
João P. A. Martins, Sara Caetano, Carlos Pereira, Emanuel Dutra, and Rita M. Cardoso
Nat. Hazards Earth Syst. Sci., 24, 1501–1520, https://doi.org/10.5194/nhess-24-1501-2024, https://doi.org/10.5194/nhess-24-1501-2024, 2024
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Over Europe, 2022 was truly exceptional in terms of extreme heat conditions, both in terms of temperature anomalies and their temporal and spatial extent. The satellite all-sky land surface temperature (LST) is used to provide a climatological context to extreme heat events. Where drought conditions prevail, LST anomalies are higher than 2 m air temperature anomalies. ERA5-Land does not represent this effect correctly due to a misrepresentation of vegetation anomalies.
Rudolf Brázdil, Kateřina Chromá, and Pavel Zahradníček
Nat. Hazards Earth Syst. Sci., 24, 1437–1457, https://doi.org/10.5194/nhess-24-1437-2024, https://doi.org/10.5194/nhess-24-1437-2024, 2024
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The official mortality data in the Czech Republic in 1919–2022 are used to show long-term fluctuations in the number of fatalities caused by excessive natural cold and heat, lightning, natural disasters, and falls on ice/snow, as well as the sex and age of the deceased, based on certain meteorological, historical, and socioeconomic factors that strongly influence changes in the number and structure of such fatalities. Knowledge obtained is usable in risk management for the preservation of lives.
Ben Maybee, Cathryn E. Birch, Steven J. Böing, Thomas Willis, Linda Speight, Aurore N. Porson, Charlie Pilling, Kay L. Shelton, and Mark A. Trigg
Nat. Hazards Earth Syst. Sci., 24, 1415–1436, https://doi.org/10.5194/nhess-24-1415-2024, https://doi.org/10.5194/nhess-24-1415-2024, 2024
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This paper presents the development and verification of FOREWARNS, a novel method for regional-scale forecasting of surface water flooding. We detail outcomes from a workshop held with UK forecast users, who indicated they valued the forecasts and would use them to complement national guidance. We use results of objective forecast tests against flood observations over northern England to show that this confidence is justified and that FOREWARNS meets the needs of UK flood responders.
Ashbin Jaison, Asgeir Sorteberg, Clio Michel, and Øyvind Breivik
Nat. Hazards Earth Syst. Sci., 24, 1341–1355, https://doi.org/10.5194/nhess-24-1341-2024, https://doi.org/10.5194/nhess-24-1341-2024, 2024
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The present study uses daily insurance losses and wind speeds to fit storm damage functions at the municipality level of Norway. The results show that the damage functions accurately estimate losses associated with extreme damaging events and can reconstruct their spatial patterns. However, there is no single damage function that performs better than another. A newly devised damage–no-damage classifier shows some skill in predicting extreme damaging events.
Madlen Peter, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 24, 1261–1285, https://doi.org/10.5194/nhess-24-1261-2024, https://doi.org/10.5194/nhess-24-1261-2024, 2024
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The paper introduces a statistical modeling approach describing daily extreme precipitation in Germany more accurately by including changes within the year and between the years simultaneously. The changing seasonality over years is regionally divergent and mainly weak. However, some regions stand out with a more pronounced linear rise of summer intensities, indicating a possible climate change signal. Improved modeling of extreme precipitation is beneficial for risk assessment and adaptation.
Faye Hulton and David M. Schultz
Nat. Hazards Earth Syst. Sci., 24, 1079–1098, https://doi.org/10.5194/nhess-24-1079-2024, https://doi.org/10.5194/nhess-24-1079-2024, 2024
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Large hail devastates crops and property and can injure and kill people and livestock. Hail reports are collected by individual countries, so understanding where and when large hail occurs across Europe is an incomplete undertaking. We use the European Severe Weather Database to evaluate the quality of reports by year and by country since 2000. Despite its short record, the dataset appears to represent aspects of European large-hail climatology reliably.
Patrick Olschewski, Mame Diarra Bousso Dieng, Hassane Moutahir, Brian Böker, Edwin Haas, Harald Kunstmann, and Patrick Laux
Nat. Hazards Earth Syst. Sci., 24, 1099–1134, https://doi.org/10.5194/nhess-24-1099-2024, https://doi.org/10.5194/nhess-24-1099-2024, 2024
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We applied a multivariate and dependency-preserving bias correction method to climate model output for the Greater Mediterranean Region and investigated potential changes in false-spring events (FSEs) and heat–drought compound events (HDCEs). Results project an increase in the frequency of FSEs in middle and late spring as well as increases in frequency, intensity, and duration for HDCEs. This will potentially aggravate the risk of crop loss and failure and negatively impact food security.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 24, 907–927, https://doi.org/10.5194/nhess-24-907-2024, https://doi.org/10.5194/nhess-24-907-2024, 2024
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Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. The incorporation of new observations from personal weather stations into the French limited-area model is evaluated. It leads to a significant improvement in the modelling of the surface pressure field up to 9 h ahead. Their incorporation improves the location and intensity of the heavy precipitation event that occurred in the South of France in September 2021.
Timo Schmid, Raphael Portmann, Leonie Villiger, Katharina Schröer, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 847–872, https://doi.org/10.5194/nhess-24-847-2024, https://doi.org/10.5194/nhess-24-847-2024, 2024
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Hailstorms cause severe damage to buildings and cars, which motivates a detailed risk assessment. Here, we present a new open-source hail damage model based on radar data in Switzerland. The model successfully estimates the correct order of magnitude of car and building damages for most large hail events over 20 years. However, large uncertainty remains in the geographical distribution of modelled damages, which can be improved for individual events by using crowdsourced hail reports.
Colin Raymond, Anamika Shreevastava, Emily Slinskey, and Duane Waliser
Nat. Hazards Earth Syst. Sci., 24, 791–801, https://doi.org/10.5194/nhess-24-791-2024, https://doi.org/10.5194/nhess-24-791-2024, 2024
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How can we systematically understand what causes high levels of atmospheric humidity and thus heat stress? Here we argue that atmospheric rivers can be a useful tool, based on our finding that in several US regions, atmospheric rivers and humid heat occur close together in space and time. Most typically, an atmospheric river transports moisture which heightens heat stress, with precipitation following a day later. These effects tend to be larger for stronger and more extensive systems.
Joseph Smith, Cathryn Birch, John Marsham, Simon Peatman, Massimo Bollasina, and George Pankiewicz
Nat. Hazards Earth Syst. Sci., 24, 567–582, https://doi.org/10.5194/nhess-24-567-2024, https://doi.org/10.5194/nhess-24-567-2024, 2024
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Nowcasting uses observations to make predictions of the atmosphere on short timescales and is particularly applicable to the Maritime Continent, where storms rapidly develop and cause natural disasters. This paper evaluates probabilistic and deterministic satellite nowcasting algorithms over the Maritime Continent. We show that the probabilistic approach is most skilful at small scales (~ 60 km), whereas the deterministic approach is most skilful at larger scales (~ 200 km).
Julia Miller, Andrea Böhnisch, Ralf Ludwig, and Manuela I. Brunner
Nat. Hazards Earth Syst. Sci., 24, 411–428, https://doi.org/10.5194/nhess-24-411-2024, https://doi.org/10.5194/nhess-24-411-2024, 2024
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We assess the impacts of climate change on fire danger for 1980–2099 in different landscapes of central Europe, using the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by 2099. High fire danger (FWI > 21.3) becomes the mean condition by 2099 under an RCP8.5 scenario. This study highlights the potential for severe fire events in central Europe from a meteorological perspective.
Clemens Schwingshackl, Anne Sophie Daloz, Carley Iles, Kristin Aunan, and Jana Sillmann
Nat. Hazards Earth Syst. Sci., 24, 331–354, https://doi.org/10.5194/nhess-24-331-2024, https://doi.org/10.5194/nhess-24-331-2024, 2024
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Ambient heat in European cities will substantially increase under global warming, as projected by three heat metrics calculated from high-resolution climate model simulations. While the heat metrics consistently project high levels of ambient heat for several cities, in other cities the projected heat levels vary considerably across the three heat metrics. Using complementary heat metrics for projections of ambient heat is thus important for assessments of future risks from heat stress.
Dragan Petrovic, Benjamin Fersch, and Harald Kunstmann
Nat. Hazards Earth Syst. Sci., 24, 265–289, https://doi.org/10.5194/nhess-24-265-2024, https://doi.org/10.5194/nhess-24-265-2024, 2024
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The influence of model resolution and settings on the reproduction of heat waves in Germany between 1980–2009 is analyzed. Outputs from a high-resolution model with settings tailored to the target region are compared to those from coarser-resolution models with more general settings. Neither the increased resolution nor the tailored model settings are found to add significant value to the heat wave simulation. The models exhibit a large spread, indicating that the choice of model can be crucial.
Josep Bonsoms, Juan I. López-Moreno, Esteban Alonso-González, César Deschamps-Berger, and Marc Oliva
Nat. Hazards Earth Syst. Sci., 24, 245–264, https://doi.org/10.5194/nhess-24-245-2024, https://doi.org/10.5194/nhess-24-245-2024, 2024
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Climate warming is changing mountain snowpack patterns, leading in some cases to rain-on-snow (ROS) events. Here we analyzed near-present ROS and its sensitivity to climate warming across the Pyrenees. ROS increases during the coldest months of the year but decreases in the warmest months and areas under severe warming due to snow cover depletion. Faster snow ablation is anticipated in the coldest and northern slopes of the range. Relevant implications in mountain ecosystem are anticipated.
Tiberiu-Eugen Antofie, Stefano Luoni, Alois Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-220, https://doi.org/10.5194/nhess-2023-220, 2024
Preprint under review for NHESS
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This is the first study that uses spatial patterns (clusters/hot-spots) and meta-analysis in order to identify the regions at European level at risk to multi-hazards. The findings point out the socio-economic dimension as determinant factor for the risk potential to multi-hazard. The outcome provides valuable input for the Disaster Risk Management policy support and will assist national authorities on the implementation of a multi-hazard approach in the National Risk Assessments preparation.
Matthew D. K. Priestley, David B. Stephenson, Adam A. Scaife, Daniel Bannister, Christopher J. T. Allen, and David Wilkie
Nat. Hazards Earth Syst. Sci., 23, 3845–3861, https://doi.org/10.5194/nhess-23-3845-2023, https://doi.org/10.5194/nhess-23-3845-2023, 2023
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This research presents a model for estimating extreme gusts associated with European windstorms. Using observed storm footprints we are able to calculate the return level of events at the 200-year return period. The largest gusts are found across NW Europe, and these are larger when the North Atlantic Oscillation is positive. Using theoretical future climate states we find that return levels are likely to increase across NW Europe to levels that are unprecedented compared to historical storms.
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
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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
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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
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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
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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
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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.
Francisco Javier Acero, Manuel Antón, Alejandro Jesús Pérez Aparicio, Nieves Bravo-Paredes, Víctor Manuel Sánchez Carrasco, María Cruz Gallego, José Agustín García, Marcelino Núñez, Irene Tovar, Javier Vaquero-Martínez, and José Manuel Vaquero
EGUsphere, https://doi.org/10.5194/egusphere-2023-2522, https://doi.org/10.5194/egusphere-2023-2522, 2023
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The month of June 1925 was detected as exceptional in the SW interior of Iberia due to the large number of thunderstorms and the significant impacts that caused, with serious losses in human lives and material resources. We analyzed this event from different, complementary perspectives: the reconstruction of the history of the events from newspapers; the study of monthly meteorological variables of the longest series available in Iberia; and the analysis of the meteorological synoptic situation.
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
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This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.
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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.
Coastal compound flooding (CF), caused by interacting storm surges and high water runoff, is...
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