Articles | Volume 24, issue 4
https://doi.org/10.5194/nhess-24-1415-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-1415-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Apr 2024
Research article |
| 24 Apr 2024
| 24 Apr 2024
FOREWARNS: development and multifaceted verification of enhanced regional-scale surface water flood forecasts
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, United Kingdom
Cathryn E. Birch
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, United Kingdom
Steven J. Böing
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, United Kingdom
Thomas Willis
School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom
Linda Speight
School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, United Kingdom
Aurore N. Porson
Met Office, Exeter, EX1 3PB, United Kingdom
Charlie Pilling
Flood Forecasting Centre, Exeter, EX1 3PB, United Kingdom
Kay L. Shelton
JBA Consulting, Skipton, BD23 3FD, United Kingdom
Mark A. Trigg
School of Civil Engineering, University of Leeds, Leeds, LS2 9JT, United Kingdom
Related authors
No articles found.
Helen Hooker, Sarah Dance, David Mason, John Bevington, and Kay Shelton
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-178, https://doi.org/10.5194/hess-2024-178, 2024
Revised manuscript under review for HESS
Short summary
Short summary
This study introduces a method that uses satellite data to enhance flood map selection for forecast-based financing applications. Tested on the 2022 Pakistan floods, it successfully triggered flood maps in four out of five regions, including those with urban areas. The approach ensures timely humanitarian aid by updating flood maps, even when initial triggers are missed, aiding in better disaster preparedness and risk management.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
Short summary
Short summary
This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Declan L. Finney, Alan M. Blyth, Martin Gallagher, Huihui Wu, Graeme J. Nott, Michael I. Biggerstaff, Richard G. Sonnenfeld, Martin Daily, Dan Walker, David Dufton, Keith Bower, Steven Böing, Thomas Choularton, Jonathan Crosier, James Groves, Paul R. Field, Hugh Coe, Benjamin J. Murray, Gary Lloyd, Nicholas A. Marsden, Michael Flynn, Kezhen Hu, Navaneeth M. Thamban, Paul I. Williams, Paul J. Connolly, James B. McQuaid, Joseph Robinson, Zhiqiang Cui, Ralph R. Burton, Gordon Carrie, Robert Moore, Steven J. Abel, Dave Tiddeman, and Graydon Aulich
Earth Syst. Sci. Data, 16, 2141–2163, https://doi.org/10.5194/essd-16-2141-2024, https://doi.org/10.5194/essd-16-2141-2024, 2024
Short summary
Short summary
The DCMEX (Deep Convective Microphysics Experiment) project undertook an aircraft- and ground-based measurement campaign of New Mexico deep convective clouds during July–August 2022. The campaign coordinated a broad range of instrumentation measuring aerosol, cloud physics, radar signals, thermodynamics, dynamics, electric fields, and weather. The project's objectives included the utilisation of these data with satellite observations to study the anvil cloud radiative effect.
Joseph Smith, Cathryn Birch, John Marsham, Simon Peatman, Massimo Bollasina, and George Pankiewicz
Nat. Hazards Earth Syst. Sci., 24, 567–582, https://doi.org/10.5194/nhess-24-567-2024, https://doi.org/10.5194/nhess-24-567-2024, 2024
Short summary
Short summary
Nowcasting uses observations to make predictions of the atmosphere on short timescales and is particularly applicable to the Maritime Continent, where storms rapidly develop and cause natural disasters. This paper evaluates probabilistic and deterministic satellite nowcasting algorithms over the Maritime Continent. We show that the probabilistic approach is most skilful at small scales (~ 60 km), whereas the deterministic approach is most skilful at larger scales (~ 200 km).
Zhiqiang Cui, Alan Blyth, Ralph Burton, Sandrine Bony, Steven Böing, Alan Gadian, and Leif Denby
EGUsphere, https://doi.org/10.5194/egusphere-2023-1999, https://doi.org/10.5194/egusphere-2023-1999, 2023
Preprint archived
Short summary
Short summary
Cumulus clouds near Barbados can influence how much heat and energy reaches the Earth's surface. A cluster of clouds resembling a flower is presented. Satellite images, dropsonde data, and weather data are used to understand how this cloud system developed. A significant feature was the appearance of a large area of rain at the centre of the cloud system during its later stages. The paper also studied the environmental conditions around the cloud system.
Helen Hooker, Sarah L. Dance, David C. Mason, John Bevington, and Kay Shelton
Nat. Hazards Earth Syst. Sci., 23, 2769–2785, https://doi.org/10.5194/nhess-23-2769-2023, https://doi.org/10.5194/nhess-23-2769-2023, 2023
Short summary
Short summary
Ensemble forecasts of flood inundation produce maps indicating the probability of flooding. A new approach is presented to evaluate the spatial performance of an ensemble flood map forecast by comparison against remotely observed flooding extents. This is important for understanding forecast uncertainties and improving flood forecasting systems.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
Short summary
Short summary
Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Mike Bush, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Aravindakshan Jayakumar, Huw Lewis, Adrian Lock, Marion Mittermaier, Saji Mohandas, Rachel North, Aurore Porson, Belinda Roux, Stuart Webster, and Mark Weeks
Geosci. Model Dev., 16, 1713–1734, https://doi.org/10.5194/gmd-16-1713-2023, https://doi.org/10.5194/gmd-16-1713-2023, 2023
Short summary
Short summary
Building on the baseline of RAL1, the RAL2 science configuration is used for regional modelling around the UM partnership and in operations at the Met Office. RAL2 has been tested in different parts of the world including Australia, India and the UK. RAL2 increases medium and low cloud amounts in the mid-latitudes compared to RAL1, leading to improved cloud forecasts and a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates.
Mirianna Budimir, Alison Sneddon, Issy Nelder, Sarah Brown, Amy Donovan, and Linda Speight
Geosci. Commun., 5, 151–175, https://doi.org/10.5194/gc-5-151-2022, https://doi.org/10.5194/gc-5-151-2022, 2022
Short summary
Short summary
This paper extracts key learning from two case studies (India and Mozambique), outlining solutions and approaches to challenges in developing forecast products. These lessons and solutions can be used by forecasters and practitioners to support the development of useful, appropriate, and co-designed forecast information for institutional decision-makers to support more effective early action in advance of disasters.
Mark V. Bernhofen, Mark A. Trigg, P. Andrew Sleigh, Christopher C. Sampson, and Andrew M. Smith
Nat. Hazards Earth Syst. Sci., 21, 2829–2847, https://doi.org/10.5194/nhess-21-2829-2021, https://doi.org/10.5194/nhess-21-2829-2021, 2021
Short summary
Short summary
The use of different global datasets to calculate flood exposure can lead to differences in global flood exposure estimates. In this study, we use three global population datasets and a simple measure of a river’s flood susceptibility (based on the terrain alone) to explore how the choice of population data and the size of river represented in global flood models affect global and national flood exposure estimates.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Jennifer Saxby, Julia Crook, Simon Peatman, Cathryn Birch, Juliane Schwendike, Maria Valdivieso da Costa, Juan Manuel Castillo Sanchez, Chris Holloway, Nicholas P. Klingaman, Ashis Mitra, and Huw Lewis
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2021-46, https://doi.org/10.5194/wcd-2021-46, 2021
Preprint withdrawn
Short summary
Short summary
This study assesses the ability of the new Met Office IND1 numerical model to simulate tropical cyclones and their associated hazards, such as high winds and heavy rainfall. The new system consists of both atmospheric and oceanic models coupled together, allowing us to explore the sensitivity of cyclones to important air–sea feedbacks. We find that the model can accurately simulate tropical cyclone position, structure, and intensity, which are crucial for predicting and mitigating hazards.
J. Browse, K. S. Carslaw, G. W. Mann, C. E. Birch, S. R. Arnold, and C. Leck
Atmos. Chem. Phys., 14, 7543–7557, https://doi.org/10.5194/acp-14-7543-2014, https://doi.org/10.5194/acp-14-7543-2014, 2014
Related subject area
Atmospheric, Meteorological and Climatological Hazards
GTDI: a game-theory-based integrated drought index implying hazard-causing and hazard-bearing impact change
Insurance loss model vs. meteorological loss index – how comparable are their loss estimates for European windstorms?
Intense rains in Israel associated with the train effect
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
On the potential of using smartphone sensors for wildfire hazard estimation through citizen science
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations
Probabilistic short-range forecasts of high-precipitation events: optimal decision thresholds and predictability limits
Surprise floods: the role of our imagination in preparing for disasters
Modelling crop hail damage footprints with single-polarization radar: the roles of spatial resolution, hail intensity, and cropland density
Insights into ground strike point properties in Europe through the EUCLID lightning location system
The role of citizen science in assessing the spatiotemporal pattern of rainfall events in urban areas: a case study in the city of Genoa, Italy
Precipitation extremes in Ukraine from 1979 to 2019: climatology, large-scale flow conditions, and moisture sources
Characterizing hail-prone environments using convection-permitting reanalysis and overshooting top detections over south-central Europe
Aircraft engine dust ingestion at global airports
Catchment-scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan
The risk of synoptic-scale Arctic cyclones to shipping
Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data
Climatic characteristics of the Jianghuai cyclone and its linkage with precipitation during the Meiyu period from 1961 to 2020
Application of the teaching–learning-based optimization algorithm to an analytical model of thunderstorm outflows to analyze the variability of the downburst kinematic and geometric parameters
Examining the Eastern European heatwave of 2023 from a long-term perspective: the role of natural variability vs. anthropogenic factors
Projections and uncertainties of winter windstorm damage in Europe in a changing climate
Improving seasonal predictions of German Bight storm activity
A satellite view of the exceptionally warm summer of 2022 over Europe
Demographic yearbooks as a source of weather-related fatalities: the Czech Republic, 1919–2022
Assessment of wind–damage relations for Norway using 36 years of daily insurance data
Interannual variations in the seasonal cycle of extreme precipitation in Germany and the response to climate change
Climatology of large hail in Europe: characteristics of the European Severe Weather Database
Amplified potential for vegetation stress under climate-change-induced intensifying compound extreme events in the Greater Mediterranean Region
Assimilation of surface pressure observations from personal weather stations in AROME-France
An open-source radar-based hail damage model for buildings and cars
Linkages between atmospheric rivers and humid heat across the United States
A modelled multi-decadal hailday time series for Switzerland
Evaluating pySTEPS optical flow algorithms for convection nowcasting over the Maritime Continent using satellite data
Climate change impacts on regional fire weather in heterogeneous landscapes of central Europe
High-resolution projections of ambient heat for major European cities using different heat metrics
Heat wave characteristics: evaluation of regional climate model performances for Germany
Rain-on-snow responses to warmer Pyrenees: a sensitivity analysis using a physically based snow hydrological model
Spatial identification of regions at risk to multi-hazards at pan European level: an implemented methodological approach
Return levels of extreme European windstorms, their dependency on the North Atlantic Oscillation, and potential future risks
Wind as a natural hazard in Poland
Climatological occurrences of hail and tornadoes associated with mesoscale convective systems in the United States
Characteristics of cloud-to-ground lightning (CG) and differences between +CG and −CG strokes in China regarding the China National Lightning Detection Network
The climatology and nature of warm-season convective cells in cold-frontal environments over Germany
Forecasting large hail and lightning using additive logistic regression models and the ECMWF reforecasts
The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model
Shallow and deep learning of extreme rainfall events from convective atmospheres
Linking reported drought impacts with drought indices, water scarcity and aridity: the case of Kenya
Future heat extremes and impacts in a convection-permitting climate ensemble over Germany
Assessment of subseasonal-to-seasonal (S2S) ensemble extreme precipitation forecast skill over Europe
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024, https://doi.org/10.5194/nhess-24-3479-2024, 2024
Short summary
Short summary
To effectively track and identify droughts, we developed a novel integrated drought index that combines the effects of precipitation, temperature, and soil moisture on drought. After comparison and verification, the integrated drought index shows superior performance compared to a single meteorological drought index or agricultural drought index in terms of drought identification.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 24, 3445–3460, https://doi.org/10.5194/nhess-24-3445-2024, https://doi.org/10.5194/nhess-24-3445-2024, 2024
Short summary
Short summary
European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological loss index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high-impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci., 24, 3267–3277, https://doi.org/10.5194/nhess-24-3267-2024, https://doi.org/10.5194/nhess-24-3267-2024, 2024
Short summary
Short summary
The train effect is related to convective cells that pass over the same place. Trains produce heavy rainfall and sometimes floods and are reported in North America during spring and summer. In Israel, 17 trains associated with Cyprus lows were identified by radar images and were found within the cold sector south of the low center and in the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km; last 1–3 h; and yield 35 mm of rainfall up to 60 mm.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
Short summary
Short summary
A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024, https://doi.org/10.5194/nhess-24-3035-2024, 2024
Short summary
Short summary
We have used the temperature and relative humidity sensors in smartphones to estimate the vapor pressure deficit (VPD), an important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal shows the potential for using smartphone data to compliment the regular weather station network while also providing high spatial resolution of the VPD index.
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, https://doi.org/10.5194/nhess-24-2939-2024, 2024
Short summary
Short summary
High-impact river floods are often caused by extreme precipitation. Flood protection relies on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties in the return values can be substantially reduced compared to observational estimates.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
Short summary
Short summary
Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024, https://doi.org/10.5194/nhess-24-2793-2024, 2024
Short summary
Short summary
Weather prediction uncertainties can be described as sets of possible scenarios – a technique called ensemble prediction. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024, https://doi.org/10.5194/nhess-24-2633-2024, 2024
Short summary
Short summary
What’s the worst that could happen? Recent floods are often claimed to be beyond our imagination. Imagination is the picturing of a situation in our mind and the emotions that we connect with this situation. But why is this important for disasters? This survey found that when we cannot imagine a devastating flood, we are not preparing in advance. Severe-weather forecasts and warnings need to advance in order to trigger our imagination of what might happen and enable us to start preparing.
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024, https://doi.org/10.5194/nhess-24-2541-2024, 2024
Short summary
Short summary
The study presents an open-source model to determine the occurrence of hail damage to field crops and grapevines after hailstorms in Switzerland based on radar, agricultural land use data, and insurance damage reports. The model performs best at 8 km resolution for field crops and 1 km for grapevine and in the main production areas. Highlighting performance trade-offs and the relevance of user needs, the study is a first step towards the assessment of risk and damage for crops in Switzerland.
Dieter Roel Poelman, Hannes Kohlmann, and Wolfgang Schulz
Nat. Hazards Earth Syst. Sci., 24, 2511–2522, https://doi.org/10.5194/nhess-24-2511-2024, https://doi.org/10.5194/nhess-24-2511-2024, 2024
Short summary
Short summary
EUCLID's lightning data unveil distinctive ground strike point (GSP) patterns in Europe. Over seas, GSPs per flash surpass inland, reaching a minimum in the Alps. Mountainous areas like the Alps and Pyrenees have the closest GSP separation, highlighting terrain elevation's impact. The daily peak current correlates with average GSPs per flash. These findings could significantly influence lightning protection measures, urging a focus on GSP density rather than flash density for risk assessment.
Nicola Loglisci, Giorgio Boni, Arianna Cauteruccio, Francesco Faccini, Massimo Milelli, Guido Paliaga, and Antonio Parodi
Nat. Hazards Earth Syst. Sci., 24, 2495–2510, https://doi.org/10.5194/nhess-24-2495-2024, https://doi.org/10.5194/nhess-24-2495-2024, 2024
Short summary
Short summary
We analyse the meteo-hydrological features of the 27 and 28 August 2023 event that occurred in Genoa. Rainfall observations were made using rain gauge networks based on either official networks or citizen science networks. The merged analysis stresses the spatial variability in the precipitation, which cannot be captured by the current spatial density of authoritative stations. Results show that at minimal distances the variations in cumulated rainfall over a sub-hourly duration are significant.
Ellina Agayar, Franziska Aemisegger, Moshe Armon, Alexander Scherrmann, and Heini Wernli
Nat. Hazards Earth Syst. Sci., 24, 2441–2459, https://doi.org/10.5194/nhess-24-2441-2024, https://doi.org/10.5194/nhess-24-2441-2024, 2024
Short summary
Short summary
This study presents the results of a climatological investigation of extreme precipitation events (EPEs) in Ukraine for the period 1979–2019. During all seasons EPEs are associated with pronounced upper-level potential vorticity (PV) anomalies. In addition, we find distinct seasonal and regional differences in moisture sources. Several extreme precipitation cases demonstrate the importance of these processes, complemented by a detailed synoptic analysis.
Antonio Giordani, Michael Kunz, Kristopher M. Bedka, Heinz Jürgen Punge, Tiziana Paccagnella, Valentina Pavan, Ines M. L. Cerenzia, and Silvana Di Sabatino
Nat. Hazards Earth Syst. Sci., 24, 2331–2357, https://doi.org/10.5194/nhess-24-2331-2024, https://doi.org/10.5194/nhess-24-2331-2024, 2024
Short summary
Short summary
To improve the challenging representation of hazardous hailstorms, a proxy for hail frequency based on satellite detections, convective parameters from high-resolution reanalysis, and crowd-sourced reports is tested and presented. Hail likelihood peaks in mid-summer at 15:00 UTC over northern Italy and shows improved agreement with observations compared to previous estimates. By separating ambient signatures based on hail severity, enhanced appropriateness for large-hail occurrence is found.
Claire L. Ryder, Clément Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
Nat. Hazards Earth Syst. Sci., 24, 2263–2284, https://doi.org/10.5194/nhess-24-2263-2024, https://doi.org/10.5194/nhess-24-2263-2024, 2024
Short summary
Short summary
Desert dust poses a hazard to aircraft via degradation of engine components. This has financial implications for the aviation industry and results in increased fuel burn with climate impacts. Here we quantify dust ingestion by aircraft engines at airports worldwide. We find Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. Dust ingestion can be reduced by changing take-off times and the altitude of holding patterns.
Khalil Ur Rahman, Songhao Shang, Khaled Saeed Balkhair, Hamza Farooq Gabriel, Khan Zaib Jadoon, and Kifayat Zaman
Nat. Hazards Earth Syst. Sci., 24, 2191–2214, https://doi.org/10.5194/nhess-24-2191-2024, https://doi.org/10.5194/nhess-24-2191-2024, 2024
Short summary
Short summary
This paper assesses the impact of drought (meteorological drought) on the hydrological alterations in major rivers of the Indus Basin. Threshold regression and range of variability analysis are used to determine the drought severity and times where drought has caused low flows and extreme low flows (identified using indicators of hydrological alterations). Moreover, this study also examines the degree of alterations in river flows due to drought using the hydrological alteration factor.
Alexander Frank Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Nat. Hazards Earth Syst. Sci., 24, 2115–2132, https://doi.org/10.5194/nhess-24-2115-2024, https://doi.org/10.5194/nhess-24-2115-2024, 2024
Short summary
Short summary
The risk posed to ships by Arctic cyclones has seldom been quantified due to the lack of publicly available historical Arctic ship track data. This study investigates historical Arctic ship tracks, cyclone tracks, and shipping incident reports to determine the number of shipping incidents caused by the passage of Arctic cyclones. Results suggest that Arctic cyclones have not been hazardous to ships and that ships are resilient to the rough sea conditions caused by Arctic cyclones.
Niklas Ebers, Kai Schröter, and Hannes Müller-Thomy
Nat. Hazards Earth Syst. Sci., 24, 2025–2043, https://doi.org/10.5194/nhess-24-2025-2024, https://doi.org/10.5194/nhess-24-2025-2024, 2024
Short summary
Short summary
Future changes in sub-daily rainfall extreme values are essential in various hydrological fields, but climate scenarios typically offer only daily resolution. One solution is rainfall generation. With a temperature-dependent rainfall generator climate scenario data were disaggregated to 5 min rainfall time series for 45 locations across Germany. The analysis of the future 5 min rainfall time series showed an increase in the rainfall extremes values for rainfall durations of 5 min and 1 h.
Ran Zhu and Lei Chen
Nat. Hazards Earth Syst. Sci., 24, 1937–1950, https://doi.org/10.5194/nhess-24-1937-2024, https://doi.org/10.5194/nhess-24-1937-2024, 2024
Short summary
Short summary
There is a positive correlation between the frequency of Jianghuai cyclone activity and precipitation during the Meiyu period. Its occurrence frequency has an obvious decadal variation, which corresponds well with the quasi-periodic and decadal variation in precipitation during the Meiyu period. This study provides a reference for the long-term and short-term forecasting of precipitation during the Meiyu period.
Andi Xhelaj and Massimiliano Burlando
Nat. Hazards Earth Syst. Sci., 24, 1657–1679, https://doi.org/10.5194/nhess-24-1657-2024, https://doi.org/10.5194/nhess-24-1657-2024, 2024
Short summary
Short summary
The study provides an in-depth analysis of a severe downburst event in Sânnicolau Mare, Romania, utilizing an analytical model and optimization algorithm. The goal is to explore a multitude of generating solutions and to identify potential alternatives to the optimal solution. Advanced data analysis techniques help to discern three main distinct storm scenarios. For this particular event, the best overall solution from the optimization algorithm shows promise in reconstructing the downburst.
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
Short summary
Short summary
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
Short summary
Short summary
We combine climate projections from 30 climate models with a climate risk model to project winter windstorm damages in Europe under climate change. We study the uncertainty and sensitivity factors related to the modelling of hazard, exposure and vulnerability. We emphasize high uncertainties in the damage projections, with climate models primarily driving the uncertainty. We find climate change reshapes future European windstorm risk by altering damage locations and intensity.
Daniel Krieger, Sebastian Brune, Johanna Baehr, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 1539–1554, https://doi.org/10.5194/nhess-24-1539-2024, https://doi.org/10.5194/nhess-24-1539-2024, 2024
Short summary
Short summary
Previous studies found that climate models can predict storm activity in the German Bight well for averages of 5–10 years but struggle in predicting the next winter season. Here, we improve winter storm activity predictions by linking them to physical phenomena that occur before the winter. We guess the winter storm activity from these phenomena and discard model solutions that stray too far from the guess. The remaining solutions then show much higher prediction skill for storm activity.
João P. A. Martins, Sara Caetano, Carlos Pereira, Emanuel Dutra, and Rita M. Cardoso
Nat. Hazards Earth Syst. Sci., 24, 1501–1520, https://doi.org/10.5194/nhess-24-1501-2024, https://doi.org/10.5194/nhess-24-1501-2024, 2024
Short summary
Short summary
Over Europe, 2022 was truly exceptional in terms of extreme heat conditions, both in terms of temperature anomalies and their temporal and spatial extent. The satellite all-sky land surface temperature (LST) is used to provide a climatological context to extreme heat events. Where drought conditions prevail, LST anomalies are higher than 2 m air temperature anomalies. ERA5-Land does not represent this effect correctly due to a misrepresentation of vegetation anomalies.
Rudolf Brázdil, Kateřina Chromá, and Pavel Zahradníček
Nat. Hazards Earth Syst. Sci., 24, 1437–1457, https://doi.org/10.5194/nhess-24-1437-2024, https://doi.org/10.5194/nhess-24-1437-2024, 2024
Short summary
Short summary
The official mortality data in the Czech Republic in 1919–2022 are used to show long-term fluctuations in the number of fatalities caused by excessive natural cold and heat, lightning, natural disasters, and falls on ice/snow, as well as the sex and age of the deceased, based on certain meteorological, historical, and socioeconomic factors that strongly influence changes in the number and structure of such fatalities. Knowledge obtained is usable in risk management for the preservation of lives.
Ashbin Jaison, Asgeir Sorteberg, Clio Michel, and Øyvind Breivik
Nat. Hazards Earth Syst. Sci., 24, 1341–1355, https://doi.org/10.5194/nhess-24-1341-2024, https://doi.org/10.5194/nhess-24-1341-2024, 2024
Short summary
Short summary
The present study uses daily insurance losses and wind speeds to fit storm damage functions at the municipality level of Norway. The results show that the damage functions accurately estimate losses associated with extreme damaging events and can reconstruct their spatial patterns. However, there is no single damage function that performs better than another. A newly devised damage–no-damage classifier shows some skill in predicting extreme damaging events.
Madlen Peter, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 24, 1261–1285, https://doi.org/10.5194/nhess-24-1261-2024, https://doi.org/10.5194/nhess-24-1261-2024, 2024
Short summary
Short summary
The paper introduces a statistical modeling approach describing daily extreme precipitation in Germany more accurately by including changes within the year and between the years simultaneously. The changing seasonality over years is regionally divergent and mainly weak. However, some regions stand out with a more pronounced linear rise of summer intensities, indicating a possible climate change signal. Improved modeling of extreme precipitation is beneficial for risk assessment and adaptation.
Faye Hulton and David M. Schultz
Nat. Hazards Earth Syst. Sci., 24, 1079–1098, https://doi.org/10.5194/nhess-24-1079-2024, https://doi.org/10.5194/nhess-24-1079-2024, 2024
Short summary
Short summary
Large hail devastates crops and property and can injure and kill people and livestock. Hail reports are collected by individual countries, so understanding where and when large hail occurs across Europe is an incomplete undertaking. We use the European Severe Weather Database to evaluate the quality of reports by year and by country since 2000. Despite its short record, the dataset appears to represent aspects of European large-hail climatology reliably.
Patrick Olschewski, Mame Diarra Bousso Dieng, Hassane Moutahir, Brian Böker, Edwin Haas, Harald Kunstmann, and Patrick Laux
Nat. Hazards Earth Syst. Sci., 24, 1099–1134, https://doi.org/10.5194/nhess-24-1099-2024, https://doi.org/10.5194/nhess-24-1099-2024, 2024
Short summary
Short summary
We applied a multivariate and dependency-preserving bias correction method to climate model output for the Greater Mediterranean Region and investigated potential changes in false-spring events (FSEs) and heat–drought compound events (HDCEs). Results project an increase in the frequency of FSEs in middle and late spring as well as increases in frequency, intensity, and duration for HDCEs. This will potentially aggravate the risk of crop loss and failure and negatively impact food security.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 24, 907–927, https://doi.org/10.5194/nhess-24-907-2024, https://doi.org/10.5194/nhess-24-907-2024, 2024
Short summary
Short summary
Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. The incorporation of new observations from personal weather stations into the French limited-area model is evaluated. It leads to a significant improvement in the modelling of the surface pressure field up to 9 h ahead. Their incorporation improves the location and intensity of the heavy precipitation event that occurred in the South of France in September 2021.
Timo Schmid, Raphael Portmann, Leonie Villiger, Katharina Schröer, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 847–872, https://doi.org/10.5194/nhess-24-847-2024, https://doi.org/10.5194/nhess-24-847-2024, 2024
Short summary
Short summary
Hailstorms cause severe damage to buildings and cars, which motivates a detailed risk assessment. Here, we present a new open-source hail damage model based on radar data in Switzerland. The model successfully estimates the correct order of magnitude of car and building damages for most large hail events over 20 years. However, large uncertainty remains in the geographical distribution of modelled damages, which can be improved for individual events by using crowdsourced hail reports.
Colin Raymond, Anamika Shreevastava, Emily Slinskey, and Duane Waliser
Nat. Hazards Earth Syst. Sci., 24, 791–801, https://doi.org/10.5194/nhess-24-791-2024, https://doi.org/10.5194/nhess-24-791-2024, 2024
Short summary
Short summary
How can we systematically understand what causes high levels of atmospheric humidity and thus heat stress? Here we argue that atmospheric rivers can be a useful tool, based on our finding that in several US regions, atmospheric rivers and humid heat occur close together in space and time. Most typically, an atmospheric river transports moisture which heightens heat stress, with precipitation following a day later. These effects tend to be larger for stronger and more extensive systems.
Lena Wilhelm, Cornelia Schwierz, Katharina Schröer, Mateusz Taszarek, and Olivia Martius
EGUsphere, https://doi.org/10.5194/egusphere-2024-371, https://doi.org/10.5194/egusphere-2024-371, 2024
Short summary
Short summary
In our study we used statistical models to reconstruct past haildays in Switzerland from 1959–2022. This new timeseries reveals a significant increase in hail occurrences over the last seven decades. We link this trend to climate factors, showcasing the impact of increasing moisture and instability in the atmosphere. The last two decades have seen a surge in early hailseason events. This time series can now be used to study what drives the strong year-to-year variability of Swiss hailstorms.
Joseph Smith, Cathryn Birch, John Marsham, Simon Peatman, Massimo Bollasina, and George Pankiewicz
Nat. Hazards Earth Syst. Sci., 24, 567–582, https://doi.org/10.5194/nhess-24-567-2024, https://doi.org/10.5194/nhess-24-567-2024, 2024
Short summary
Short summary
Nowcasting uses observations to make predictions of the atmosphere on short timescales and is particularly applicable to the Maritime Continent, where storms rapidly develop and cause natural disasters. This paper evaluates probabilistic and deterministic satellite nowcasting algorithms over the Maritime Continent. We show that the probabilistic approach is most skilful at small scales (~ 60 km), whereas the deterministic approach is most skilful at larger scales (~ 200 km).
Julia Miller, Andrea Böhnisch, Ralf Ludwig, and Manuela I. Brunner
Nat. Hazards Earth Syst. Sci., 24, 411–428, https://doi.org/10.5194/nhess-24-411-2024, https://doi.org/10.5194/nhess-24-411-2024, 2024
Short summary
Short summary
We assess the impacts of climate change on fire danger for 1980–2099 in different landscapes of central Europe, using the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by 2099. High fire danger (FWI > 21.3) becomes the mean condition by 2099 under an RCP8.5 scenario. This study highlights the potential for severe fire events in central Europe from a meteorological perspective.
Clemens Schwingshackl, Anne Sophie Daloz, Carley Iles, Kristin Aunan, and Jana Sillmann
Nat. Hazards Earth Syst. Sci., 24, 331–354, https://doi.org/10.5194/nhess-24-331-2024, https://doi.org/10.5194/nhess-24-331-2024, 2024
Short summary
Short summary
Ambient heat in European cities will substantially increase under global warming, as projected by three heat metrics calculated from high-resolution climate model simulations. While the heat metrics consistently project high levels of ambient heat for several cities, in other cities the projected heat levels vary considerably across the three heat metrics. Using complementary heat metrics for projections of ambient heat is thus important for assessments of future risks from heat stress.
Dragan Petrovic, Benjamin Fersch, and Harald Kunstmann
Nat. Hazards Earth Syst. Sci., 24, 265–289, https://doi.org/10.5194/nhess-24-265-2024, https://doi.org/10.5194/nhess-24-265-2024, 2024
Short summary
Short summary
The influence of model resolution and settings on the reproduction of heat waves in Germany between 1980–2009 is analyzed. Outputs from a high-resolution model with settings tailored to the target region are compared to those from coarser-resolution models with more general settings. Neither the increased resolution nor the tailored model settings are found to add significant value to the heat wave simulation. The models exhibit a large spread, indicating that the choice of model can be crucial.
Josep Bonsoms, Juan I. López-Moreno, Esteban Alonso-González, César Deschamps-Berger, and Marc Oliva
Nat. Hazards Earth Syst. Sci., 24, 245–264, https://doi.org/10.5194/nhess-24-245-2024, https://doi.org/10.5194/nhess-24-245-2024, 2024
Short summary
Short summary
Climate warming is changing mountain snowpack patterns, leading in some cases to rain-on-snow (ROS) events. Here we analyzed near-present ROS and its sensitivity to climate warming across the Pyrenees. ROS increases during the coldest months of the year but decreases in the warmest months and areas under severe warming due to snow cover depletion. Faster snow ablation is anticipated in the coldest and northern slopes of the range. Relevant implications in mountain ecosystem are anticipated.
Tiberiu-Eugen Antofie, Stefano Luoni, Alois Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-220, https://doi.org/10.5194/nhess-2023-220, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
This is the first study that uses spatial patterns (clusters/hot-spots) and meta-analysis in order to identify the regions at European level at risk to multi-hazards. The findings point out the socio-economic dimension as determinant factor for the risk potential to multi-hazard. The outcome provides valuable input for the Disaster Risk Management policy support and will assist national authorities on the implementation of a multi-hazard approach in the National Risk Assessments preparation.
Matthew D. K. Priestley, David B. Stephenson, Adam A. Scaife, Daniel Bannister, Christopher J. T. Allen, and David Wilkie
Nat. Hazards Earth Syst. Sci., 23, 3845–3861, https://doi.org/10.5194/nhess-23-3845-2023, https://doi.org/10.5194/nhess-23-3845-2023, 2023
Short summary
Short summary
This research presents a model for estimating extreme gusts associated with European windstorms. Using observed storm footprints we are able to calculate the return level of events at the 200-year return period. The largest gusts are found across NW Europe, and these are larger when the North Atlantic Oscillation is positive. Using theoretical future climate states we find that return levels are likely to increase across NW Europe to levels that are unprecedented compared to historical storms.
Tadeusz Chmielewski and Piotr A. Bońkowski
Nat. Hazards Earth Syst. Sci., 23, 3839–3844, https://doi.org/10.5194/nhess-23-3839-2023, https://doi.org/10.5194/nhess-23-3839-2023, 2023
Short summary
Short summary
The paper deals with wind speeds of extreme wind events in Poland and the descriptions of their effects. Two recent estimations developed by the Institute of Meteorology and Water Management in Warsaw and by Halina Lorenc are presented and briefly described. The 37 annual maximum gusts of wind speeds measured between 1971 and 2007 are analysed. Based on the measured and estimated wind speeds, the authors suggest new estimations for extreme winds that may occur in Poland.
Jingyu Wang, Jiwen Fan, and Zhe Feng
Nat. Hazards Earth Syst. Sci., 23, 3823–3838, https://doi.org/10.5194/nhess-23-3823-2023, https://doi.org/10.5194/nhess-23-3823-2023, 2023
Short summary
Short summary
Hail and tornadoes are devastating hazards responsible for significant property damage and economic losses in the United States. Quantifying the connection between hazard events and mesoscale convective systems (MCSs) is of great significance for improving predictability, as well as for better understanding the influence of the climate-scale perturbations. A 14-year statistical dataset of MCS-related hazard production is presented.
Ruijiao Jiang, Guoping Zhang, Shudong Wang, Bing Xue, Zhengshuai Xie, Tingzhao Yu, Kuoyin Wang, Jin Ding, and Xiaoxiang Zhu
Nat. Hazards Earth Syst. Sci., 23, 3747–3759, https://doi.org/10.5194/nhess-23-3747-2023, https://doi.org/10.5194/nhess-23-3747-2023, 2023
Short summary
Short summary
Lightning activity in China is analyzed. Low latitudes, undulating terrain, seaside, and humid surfaces are beneficial for lightning occurrence. Summer of the year or afternoon of the day is the high period. Large cloud-to-ground lightning frequency always corresponds to a small ratio and weak intensity of positive cloud-to-ground lightning on either a temporal or spatial scale. Interestingly, the discharge intensity difference between the two types of lightning shrinks on the Tibetan Plateau.
George Pacey, Stephan Pfahl, Lisa Schielicke, and Kathrin Wapler
Nat. Hazards Earth Syst. Sci., 23, 3703–3721, https://doi.org/10.5194/nhess-23-3703-2023, https://doi.org/10.5194/nhess-23-3703-2023, 2023
Short summary
Short summary
Cold fronts are often associated with areas of intense precipitation (cells) and sometimes with hazards such as flooding, hail and lightning. We find that cold-frontal cell days are associated with higher cell frequency and cells are typically more intense. We also show both spatially and temporally where cells are most frequent depending on their cell-front distance. These results are an important step towards a deeper understanding of cold-frontal storm climatology and improved forecasting.
Francesco Battaglioli, Pieter Groenemeijer, Ivan Tsonevsky, and Tomàš Púčik
Nat. Hazards Earth Syst. Sci., 23, 3651–3669, https://doi.org/10.5194/nhess-23-3651-2023, https://doi.org/10.5194/nhess-23-3651-2023, 2023
Short summary
Short summary
Probabilistic models for lightning and large hail were developed across Europe using lightning observations and hail reports. These models accurately predict the occurrence of lightning and large hail several days in advance. In addition, the hail model was shown to perform significantly better than the state-of-the-art forecasting methods. These results suggest that the models developed in this study may help improve forecasting of convective hazards and eventually limit the associated risks.
Rosa Claudia Torcasio, Alessandra Mascitelli, Eugenio Realini, Stefano Barindelli, Giulio Tagliaferro, Silvia Puca, Stefano Dietrich, and Stefano Federico
Nat. Hazards Earth Syst. Sci., 23, 3319–3336, https://doi.org/10.5194/nhess-23-3319-2023, https://doi.org/10.5194/nhess-23-3319-2023, 2023
Short summary
Short summary
This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.
Gerd Bürger and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 3065–3077, https://doi.org/10.5194/nhess-23-3065-2023, https://doi.org/10.5194/nhess-23-3065-2023, 2023
Short summary
Short summary
Our subject is a new catalogue of radar-based heavy rainfall events (CatRaRE) over Germany and how it relates to the concurrent atmospheric circulation. We classify reanalyzed daily atmospheric fields of convective indices according to CatRaRE, using conventional statistical and more recent machine learning algorithms, and apply them to present and future atmospheres. Increasing trends are projected for CatRaRE-type probabilities, from reanalyzed as well as from simulated atmospheric fields.
Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling
Nat. Hazards Earth Syst. Sci., 23, 2915–2936, https://doi.org/10.5194/nhess-23-2915-2023, https://doi.org/10.5194/nhess-23-2915-2023, 2023
Short summary
Short summary
There is still no full understanding of the relation between drought impacts and drought indices in the Horn of Africa where water scarcity and arid regions are also present. This study assesses their relation in Kenya. A random forest model reveals that each region, aggregated by aridity, has its own set of predictors for every impact category. Water scarcity was not found to be related to aridity. Understanding these relations contributes to the development of drought early warning systems.
Marie Hundhausen, Hendrik Feldmann, Natalie Laube, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 23, 2873–2893, https://doi.org/10.5194/nhess-23-2873-2023, https://doi.org/10.5194/nhess-23-2873-2023, 2023
Short summary
Short summary
Using a convection-permitting regional climate ensemble, the magnitude of heat waves (HWs) over Germany is projected to increase by 26 % (100 %) in a 2 °C (3 °C) warmer world. The increase is strongest in late summer, relatively homogeneous in space, and accompanied by increasing variance in HW length. Tailored parameters to climate adaptation to heat revealed dependency on major landscapes, and a nonlinear, exponential increase for parameters characterizing strong heat stress is expected.
Pauline Rivoire, Olivia Martius, Philippe Naveau, and Alexandre Tuel
Nat. Hazards Earth Syst. Sci., 23, 2857–2871, https://doi.org/10.5194/nhess-23-2857-2023, https://doi.org/10.5194/nhess-23-2857-2023, 2023
Short summary
Short summary
Heavy precipitation can lead to floods and landslides, resulting in widespread damage and significant casualties. Some of its impacts can be mitigated if reliable forecasts and warnings are available. In this article, we assess the capacity of the precipitation forecast provided by ECMWF to predict heavy precipitation events on a subseasonal-to-seasonal (S2S) timescale over Europe. We find that the forecast skill of such events is generally higher in winter than in summer.
Cited articles
Aldridge, T., Gunawan, O., Moore, R. J., Cole, S. J., Boyce, G., and Cowling, R.: Developing an impact library for forecasting surface water flood risk, J. Flood Risk Manag., 13, 1–19, https://doi.org/10.1111/jfr3.12641, 2020.
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013.
Archer, D., O'Donnell, G., Lamb, R., Warren, S., and Fowler, H. J.: Historical flash floods in England: New regional chronologies and database, J. Flood Risk Manag., 12, e12526, https://doi.org/10.1111/JFR3.12526, 2019.
Archer, D. R. and Fowler, H. J.: Characterising flash flood response to intense rainfall and impacts using historical information and gauged data in Britain, J. Flood Risk Manag., 11, S121–S133, https://doi.org/10.1111/JFR3.12187, 2018.
Arnal, L., Ramos, M.-H., Coughlan de Perez, E., Cloke, H. L., Stephens, E., Wetterhall, F., van Andel, S. J., and Pappenberger, F.: Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game, Hydrol. Earth Syst. Sci., 20, 3109–3128, https://doi.org/10.5194/hess-20-3109-2016, 2016.
Arnal, L., Anspoks, L., Manson, S., Neumann, J., Norton, T., Stephens, E., Wolfenden, L., and Cloke, H. L.: “Are We talking just a bit of water out of bank? or is it Armageddon?” Front line perspectives on transitioning to probabilistic fluvial flood forecasts in England, Geosci. Commun., 3, 203–232, https://doi.org/10.5194/GC-3-203-2020, 2020.
Beck, J., Bouttier, F., Wiegand, L., Gebhardt, C., Eagle, C., and Roberts, N.: Development and verification of two convection-allowing multi-model ensembles over Western Europe, Q. J. Roy. Meteor. Soc., 142, 2808–2826, https://doi.org/10.1002/QJ.2870, 2016.
Bell, V. A., Kay, A. L., Jones, R. G., Moore, R. J., and Reynard, N. S.: Use of soil data in a grid-based hydrological model to estimate spatial variation in changing flood risk across the UK, J. Hydrol., 377, 335–350, https://doi.org/10.1016/j.jhydrol.2009.08.031, 2009.
Birch, C. E., Rabb, B. L., Böing, S. J., Shelton, K. L., Lamb, R., Hunter, N., Trigg, M. A., Hines, A., Taylor, A. L., Pilling, C., and Dale, M.: Enhanced surface water flood forecasts: User-led development and testing, J. Flood Risk Manag., 14, 1–15, https://doi.org/10.1111/jfr3.12691, 2021.
Böing, S. J., Birch, C. E., Rabb, B. L., and Shelton, K. L.: A percentile-based approach to rainfall scenario construction for surface-water flood forecasts, Meteorol. Appl., 27, 1–16, https://doi.org/10.1002/met.1963, 2020.
Böing, S. J., Maybee, B., and Willis, T.: sjboeing/fast_rainfall_processing: FOREWARNS publication version of code (1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.10987887, 2024.
Brousseau, P., Berre, L., Bouttier, F., and Desroziers, G.: Background-error covariances for a convective-scale data-assimilation system: AROME–France 3D-Var, Q. J. Roy. Meteor. Soc., 137, 409–422, https://doi.org/10.1002/QJ.750, 2011.
Brousseau, P., Seity, Y., Ricard, D., and Léger, J.: Improvement of the forecast of convective activity from the AROME-France system, Q. J. Roy. Meteor. Soc., 142, 2231–2243, https://doi.org/10.1002/QJ.2822, 2016.
de Bruijn, J. A., de Moel, H., Jongman, B., Wagemaker, J., and Aerts, J. C. J. H.: TAGGS: Grouping Tweets to Improve Global Geoparsing for Disaster Response, J. Geovisualization Spat. Anal., 2, 1–14, https://doi.org/10.1007/S41651-017-0010-6/TABLES/4, 2018.
de Bruijn, J. A., de Moel, H., Jongman, B., de Ruiter, M. C., Wagemaker, J., and Aerts, J. C. J. H.: A global database of historic and real-time flood events based on social media, Sci. Data, 6, 1–12, https://doi.org/10.1038/s41597-019-0326-9, 2019.
Chen, Y., Paschalis, A., Kendon, E., Kim, D., and Onof, C.: Changing Spatial Structure of Summer Heavy Rainfall, Using Convection-Permitting Ensemble, Geophys. Res. Lett., 48, e2020GL090903, https://doi.org/10.1029/2020GL090903, 2021.
Cole, S. J., Moore, R. J., and Mattingley, P. S.: Surface Water Flooding Component for NHP HIM: Phase 1 report. Contract Report to the Environment Agency, Research Contractor: Centre for Ecology & Hydrology, 55 pp., https://nora.nerc.ac.uk/id/eprint/513835 (last access: 18 April 2024), 2015.
Coles, D., Yu, D., Wilby, R. L., Green, D., and Herring, Z.: Beyond “flood hotspots”: Modelling emergency service accessibility during flooding in York, UK, J. Hydrol., 546, 419–436, https://doi.org/10.1016/J.JHYDROL.2016.12.013, 2017.
DEFRA: Surface Water Management: An Action Plan, Department for Environment Food and Rural Affairs, 41 pp., https://www.gov.uk/government/publications/surface-water-management-action-plan (last access: 19 April 2024), 2018.
Demeritt, D., Nobert, S., Cloke, H. L., and Pappenberger, F.: The European Flood Alert System and the communication, perception, and use of ensemble predictions for operational flood risk management, Hydrol. Process., 27, 147–157, https://doi.org/10.1002/HYP.9419, 2013.
Dottori, F., Kalas, M., Salamon, P., Bianchi, A., Alfieri, L., and Feyen, L.: An operational procedure for rapid flood risk assessment in Europe, Nat. Hazards Earth Syst. Sci., 17, 1111–1126, https://doi.org/10.5194/nhess-17-1111-2017, 2017.
Environment Agency: A National Assessment of Flood Risk, https://assets.publishing.service.gov.uk/media/5a7ba398ed915d4147621ad6/geho0609bqds-e-e.pdf (last access: 18 April 2024), 2009.
Environment Agency: What is the Risk of Flooding from Surface Water map?, 51 pp., https://assets.publishing.service.gov.uk/media/5db6ded540f0b6379a7acbb8/What-is-the-Risk-of-Flooding-from-Surface-Water-Map.pdf (last access: 18 April 2024), 2019.
Erickson, M. J., Kastman, J. S., Albright, B., Perfater, S., Nelson, J. A., Schumacher, R. S., and Herman, G. R.: Verification results from the 2017 HMT–WPC flash flood and intense rainfall experiment, J. Appl. Meteorol. Climatol., 58, 2591–2604, https://doi.org/10.1175/JAMC-D-19-0097.1, 2019.
Erickson, M. J., Albright, B., and Nelson, J. A.: Verifying and redefining the weather prediction center's excessive rainfall outlook forecast product, Weather Forecast., 36, 325–340, https://doi.org/10.1175/WAF-D-20-0020.1, 2021.
Ferro, C. A. T. and Stephenson, D. B.: Extremal dependence indices: Improved Verification measures for deterministic forecasts of rare binary events, Weather Forecast., 26, 699–713, https://doi.org/10.1175/WAF-D-10-05030.1, 2011.
Flack, D. L. A., Skinner, C. J., Hawkness-Smith, L., O'Donnell, G., Thompson, R. J., Waller, J. A., Chen, A. S., Moloney, J., Largeron, C., Xia, X., Blenkinsop, S., Champion, A. J., Perks, M. T., Quinn, N., and Speight, L. J.: Recommendations for improving integration in national end-to-end flood forecasting systems: An overview of the FFIR (Flooding From Intense Rainfall) programme, Water, 11, 725, https://doi.org/10.3390/w11040725, 2019.
Frick, J. and Hegg, C.: Can end-users' flood management decision making be improved by information about forecast uncertainty?, Atmos. Res., 100, 296–303, https://doi.org/10.1016/J.ATMOSRES.2010.12.006, 2011.
Frogner, I. L., Singleton, A. T., Køltzow, M., and Andrae, U.: Convection-permitting ensembles: Challenges related to their design and use, Q. J. Roy. Meteor. Soc., 145, 90–106, https://doi.org/10.1002/QJ.3525, 2019a.
Frogner, I. L., Andrae, U. L. F., Bojarova, J., Callado, A., Escribà, P. A. U., Feddersen, H., Hally, A., Kauhanen, J., Randriamampianina, R., Singleton, A., Smet, G., van der Veen, S., and Vignes, O. L. E.: HarmonEPS – The HARMONIE Ensemble Prediction System, Weather Forecast., 34, 1909–1937, https://doi.org/10.1175/WAF-D-19-0030.1, 2019b.
Georgakakos, K. P., Modrick, T. M., Shamir, E., Campbell, R., Cheng, Z., Jubach, R., Sperfslage, J. A., Spencer, C. R., and Banks, R.: The Flash Flood Guidance System Implementation Worldwide: A Successful Multidecadal Research-to-Operations Effort, B. Am. Meteorol. Soc., 103, E665–E679, https://doi.org/10.1175/BAMS-D-20-0241.1, 2022.
Golding, B., Roberts, N., Leoncini, G., Mylne, K., and Swinbank, R.: MOGREPS-UK convection-permitting ensemble products for surface water flood forecasting: Rationale and first results, J. Hydrometeorol., 17, 1383–1406, https://doi.org/10.1175/JHM-D-15-0083.1, 2016.
Golding, B. (Ed.): Towards the “Perfect” Weather Warning, Springer International Publishing, https://doi.org/10.1007/978-3-030-98989-7, 2022.
Gourley, J. J., Erlingis, J. M., Hong, Y., and Wells, E. B.: Evaluation of tools used for monitoring and forecasting flash floods in the united states, Weather Forecast., 27, 158–173, https://doi.org/10.1175/WAF-D-10-05043.1, 2012.
Greater London Authority: Surface Water Flooding in London: Rountable Progress Report, 44 pp., https://www.london.gov.uk/sites/default/files/flooding_progress_report_final_1.pdf (last access: 18 April 2024), 2022.
Green, D., Yu, D., Pattison, I., Wilby, R., Bosher, L., Patel, R., Thompson, P., Trowell, K., Draycon, J., Halse, M., Yang, L., and Ryley, T.: City-scale accessibility of emergency responders operating during flood events, Nat. Hazards Earth Syst. Sci., 17, 1–16, https://doi.org/10.5194/nhess-17-1-2017, 2017.
Hagelin, S., Son, J., Swinbank, R., McCabe, A., Roberts, N., and Tennant, W.: The Met Office convective-scale ensemble, MOGREPS-UK, Q. J. Roy. Meteor. Soc., 143, 2846–2861, https://doi.org/10.1002/qj.3135, 2017.
Hand, W. H., Fox, N. I., and Collier, C. G.: A study of twentieth-century extreme rainfall events in the United Kingdom with implications for forecasting, Meteorol. Appl., 11, 15–31, https://doi.org/10.1017/S1350482703001117, 2004.
Harrison, D. L., Driscoll, S. J., and Kitchen, M.: Improving precipitation estimates from weather radar using quality control and correction techniques, Meteorol. Appl., 7, 135–144, https://doi.org/10.1017/S1350482700001468, 2000.
Harrison, D. L., Norman, K., Pierce, C., and Gaussiat, N.: Radar products for hydrological applications in the UK, Proc. Inst. Civ. Eng. Water Manag., 165, 89–103, https://doi.org/10.1680/wama.2012.165.2.89, 2012.
Hawcroft, M., Lavender, S., Copsey, D., Milton, S., Rodríguez, J., Tennant, W., Webster, S., and Cowan, T.: The Benefits of Ensemble Prediction for Forecasting an Extreme Event: The Queensland Floods of February 2019, Mon. Weather Rev., 149, 2391–2408, https://doi.org/10.1175/MWR-D-20-0330.1, 2021.
Henonin, J., Russo, B., Mark, O., and Gourbesville, P.: Real-time urban flood forecasting and modelling – a state of the art, J. Hydroinform., 15, 717–736, https://doi.org/10.2166/HYDRO.2013.132, 2013.
Herman, G. R. and Schumacher, R. S.: Flash flood verification: Pondering precipitation proxies, J. Hydrometeorol., 19, 1753–1776, https://doi.org/10.1175/JHM-D-18-0092.1, 2018.
Jackson, H.: Urban flash flooding in England – an exciting new project, Circ. – Newsl. Br. Hydrol. Soc., 156, 14–15, 2023.
Kendon, E. J., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan, S. C., and Senior, C. A.: Heavier summer downpours with climate change revealed by weather forecast resolution model, Nat. Clim. Chang., 4, 570–576, https://doi.org/10.1038/nclimate2258, 2014.
Kendon, M.: Met Office case studies of past severe weather events: Heavy rainfall July 2019, 8 pp., https://www.metoffice.gov.uk/binaries/content/assets/metofficegovuk/pdf/weather/learn-about/uk-past-events/interesting/2019/2019_008_july_rainfall.pdf (last access: 18 April 2024), 2019.
Kirk, P. J., Clark, M. R., and Creed, E.: Weather Observations Website, Weather, 76, 47–49, https://doi.org/10.1002/WEA.3856, 2021.
Klasa, C., Arpagaus, M., Walser, A., and Wernli, H.: An evaluation of the convection-permitting ensemble COSMO-E for three contrasting precipitation events in Switzerland, Q. J. Roy. Meteor. Soc., 144, 744–764, https://doi.org/10.1002/QJ.3245, 2018.
Lehner, B. and Grill, G.: Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems, Hydrol. Process., 27, 2171–2186, https://doi.org/10.1002/HYP.9740, 2013.
MacLeod, D., Kilavi, M., Mwangi, E., Ambani, M., Osunga, M., Robbins, J., Graham, R., Rowhani, P., and Todd, M. C.: Are Kenya Meteorological Department heavy rainfall advisories useful for forecast-based early action and early preparedness for flooding?, Nat. Hazards Earth Syst. Sci., 21, 261–277, https://doi.org/10.5194/nhess-21-261-2021, 2021.
McCabe, A., Swinbank, R., Tennant, W., and Lock, A.: Representing model uncertainty in the Met Office convection-permitting ensemble prediction system and its impact on fog forecasting, Q. J. Roy. Meteor. Soc., 142, 2897–2910, https://doi.org/10.1002/qj.2876, 2016.
McEwen, L., Stokes, A., Crowley, K., and Roberts, C.: Using role-play for expert science communication with professional stakeholders in flood risk management, J. Geogr. Higher Educ., 38, 277–300, https://doi.org/10.1080/03098265.2014.911827, 2014.
Merz, B., Kuhlicke, C., Kunz, M., Pittore, M., Babeyko, A., Bresch, D. N., Domeisen, D. I. V., Feser, F., Koszalka, I., Kreibich, H., Pantillon, F., Parolai, S., Pinto, J. G., Punge, H. J., Rivalta, E., Schröter, K., Strehlow, K., Weisse, R., and Wurpts, A.: Impact Forecasting to Support Emergency Management of Natural Hazards, Rev. Geophys., 58, e2020RG000704, https://doi.org/10.1029/2020RG000704, 2020.
Met Office: Met Office Rain Radar Data from the NIMROD System, NCAS British Atmospheric Data Centre [data set], http://catalogue.ceda.ac.uk/uuid/82adec1f896af6169112d09cc1174499 (last access: 18 April 2024), 2003.
Milan, M., Macpherson, B., Tubbs, R., Dow, G., Inverarity, G., Mittermaier, M., Halloran, G., Kelly, G., Li, D., Maycock, A., Payne, T., Piccolo, C., Stewart, L., and Wlasak, M.: Hourly 4D-Var in the Met Office UKV operational forecast model, Q. J. Roy. Meteor. Soc., 146, 1281–1301, https://doi.org/10.1002/QJ.3737, 2020.
Mittermaier, M. P.: Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts, Nat. Hazards Earth Syst. Sci., 8, 445–460, https://doi.org/10.5194/nhess-8-445-2008, 2008.
Moore, R. J., Cole, S. J., Dunn, S., Ghimire, S., Golding, B. W., Pierce, C. E., Roberts, N. M., and Speight, L.: Surface water flood forecasting for urban communities: CREW report CRW2012_03, https://www.crew.ac.uk/sites/www.crew.ac.uk/files/sites/default/files/publication/CREW Surface water flood forecasting for urban communities_full report.pdf (last access: 18 April 2024), 2015.
Neal, R. A., Boyle, P., Grahame, N., Mylne, K., and Sharpe, M.: Ensemble based first guess support towards a risk-based severe weather warning service, Meteorol. Appl., 21, 563–577, https://doi.org/10.1002/met.1377, 2014.
North, R., Trueman, M., Mittermaier, M., and Rodwell, M. J.: An assessment of the SEEPS and SEDI metrics for the verification of 6 h forecast precipitation accumulations, Meteorol. Appl., 20, 164–175, https://doi.org/10.1002/met.1405, 2013.
Ochoa-Rodríguez, S., Wang, L. P., Thraves, L., Johnston, A., and Onof, C.: Surface water flood warnings in England: overview, assessment and recommendations based on survey responses and workshops, J. Flood Risk Manag., 11, S211–S221, https://doi.org/10.1111/jfr3.12195, 2018.
Pilling, C.: New developments at the Flood Forecasting Centre: operations and flood risk guidance, Urban Water III, 1, 237–248, https://doi.org/10.2495/uw160211, 2016.
Porson, A. N., Carr, J. M., Hagelin, S., Darvell, R., North, R., Walters, D., Mylne, K. R., Mittermaier, M. P., Willington, S., and Macpherson, B.: Recent upgrades to the Met Office convective-scale ensemble: An hourly time-lagged 5-day ensemble, Q. J. Roy. Meteor. Soc., 146, 3245–3265, https://doi.org/10.1002/qj.3844, 2020.
Ramos, M. H., van Andel, S. J., and Pappenberger, F.: Do probabilistic forecasts lead to better decisions?, Hydrol. Earth Syst. Sci., 17, 2219–2232, https://doi.org/10.5194/hess-17-2219-2013, 2013.
Raynaud, L., Pechin, I., Arbogast, P., Rottner, L., and Destouches, M.: Object-based verification metrics applied to the evaluation and weighting of convective-scale precipitation forecasts, Q. J. Roy. Meteor. Soc., 145, 1992–2008, https://doi.org/10.1002/QJ.3540, 2019.
Roberts, N., Ayliffe, B., Evans, G., Moseley, S., Rust, F., Sandford, C., Trzeciak, T., Abernethy, P., Beard, L., Crosswaite, N., Fitzpatrick, B., Flowerdew, J., Gale, T., Holly, L., Hopkinson, A., Hurst, K., Jackson, S., Jones, C., Mylne, K., Sampson, C., Sharpe, M., Wright, B., Backhouse, S., Baker, M., Brierley, D., Booton, A., Bysouth, C., Coulson, R., Coultas, S., Crocker, R., Harbord, R., Howard, K., Hughes, T., Mittermaier, M., Petch, J., Pillinger, T., Smart, V., Smith, E., and Worsfold, M.: IMPROVER: the new probabilistic post processing system at the UK Met Office, B. Am. Meteorol. Soc., 1–31, https://doi.org/10.1175/bams-d-21-0273.1, 2023.
Roebber, P. J.: Visualizing multiple measures of forecast quality, Weather Forecast., 24, 601–608, https://doi.org/10.1175/2008WAF2222159.1, 2009.
Saint-Martin, C., Fouchier, C., Javelle, P., Douvinet, J., and Vinet, F.: Assessing the exposure to floods to estimate the risk of flood-related damage in French Mediterranean basins, 3rd Eur. Conf. Flood Risk Manag. FLOODRisk 2016, E3SE3S Web Conf., 7, 04013, https://doi.org/10.1051/e3sconf/20160704013, 2016.
Schwartz, C. S. and Sobash, R. A.: Generating probabilistic forecasts from convection-allowing ensembles using neighborhood approaches: A review and recommendations, Mon. Weather Rev., 145, 3397–3418, https://doi.org/10.1175/MWR-D-16-0400.1, 2017.
Sharpe, M. A.: A flexible approach to the objective verification of warnings, Meteorol. Appl., 23, 65–75, https://doi.org/10.1002/met.1530, 2016.
Sharpe, M. A., Bysouth, C. E., and Stretton, R. L.: How well do Met Office post-processed site-specific probabilistic forecasts predict relative-extreme events?, Meteorol. Appl., 25, 23–32, https://doi.org/10.1002/met.1665, 2018.
Smith, L., Liang, Q., James, P., and Lin, W.: Assessing the utility of social media as a data source for flood risk management using a real-time modelling framework, J. Flood Risk Manag., 10, 370–380, https://doi.org/10.1111/JFR3.12154, 2017.
Speight, L., Cole, S. J., Moore, R. J., Pierce, C., Wright, B., Golding, B., Cranston, M., Tavendale, A., Dhondia, J., and Ghimire, S.: Developing surface water flood forecasting capabilities in Scotland: an operational pilot for the 2014 Commonwealth Games in Glasgow, J. Flood Risk Manag., 11, S884–S901, https://doi.org/10.1111/jfr3.12281, 2018.
Speight, L. J., Cranston, M. D., White, C. J., and Kelly, L.: Operational and emerging capabilities for surface water flood forecasting, Wiley Interdiscip. Rev. Water, 8, 1–24, https://doi.org/10.1002/wat2.1517, 2021.
Stephenson, D. B., Casati, B., Ferro, C. A. T., and Wilson, C. A.: The extreme dependency score: a non-vanishing measure for forecasts of rare events, Meteorol. Appl., 15, 41–50, https://doi.org/10.1002/met, 2008.
Stewart, E. J., Jones, D. A., Svensson, C., Morris, D. G., Dempsey, P., Dent, J. E., Collier, C. G., and Anderson, C. A.: Reservoir Safety – Long Return Period Rainfall, Technical Report (two volumes), Project FD2613 WS 194/2/39, DEFRA/EA FCERM R&D Programme, https://assets.publishing.service.gov.uk/media/602e43e2e90e0709e3127489/_long_return_report_1.pdf (last access: 18 April 2024), 2013.
Swinbank, R., Friederichs, P., and Wahl, S.: Forecasting high-impact weather using ensemble prediction systems, in: Dynamical Prediction of Large Scale High-Impact Weather Climate Events, edited by: Li, J., Swinbank, R., Grotjahn, R., and Volkert, H., 95–112, https://doi.org/10.1017/CBO9781107775541.008, 2016.
Tennant, W.: Improving initial condition perturbations for MOGREPS-UK, Q. J. Roy. Meteor. Soc., 2324–2336, 141, https://doi.org/10.1002/qj.2524, 2015.
Vesuviano, G.: The FEH22 rainfall depth-duration-frequency (DDF) model, 103 pp., Science centre technical report, https://fehwebdocs.hydrosolutions.co.uk/.attachments/The FEH22 rainfall depth-duration-frequency (DDF) model-caa11347-4ff7-4c89-b707-bf5bb1c05d79.pdf (last access: 18 April 2024), 2022.
Vesuviano, G., Stewart, E., Spencer, P., and Miller, J. D.: The effect of depth-duration-frequency model recalibration on rainfall return period estimates, J. Flood Risk Manag., 14, e12703, https://doi.org/10.1111/JFR3.12703, 2021.
Welles, E., Sorooshian, S., Carter, G., and Olsen, B.: Hydrologic verification: A call for action and collaboration, B. Am. Meteorol. Soc., 88, 503–511, https://doi.org/10.1175/BAMS-88-4-503, 2007.
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences: Fourth Edition, Elsevier B.V., Oxford, ISBN 978-0-12-815823-4, 2019.
Witherow, M. A., Sazara, C., Winter-Arboleda, I. M., Elbakary, M. I., Cetin, M., and Iftekharuddin, K. M.: Floodwater detection on roadways from crowdsourced images, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 7, 529–540, https://doi.org/10.1080/21681163.2018.1488223, 2018.
Wu, W., Emerton, R., Duan, Q., Wood, A. W., Wetterhall, F., and Robertson, D. E.: Ensemble flood forecasting: Current status and future opportunities, Wiley Interdiscip. Rev. Water, 7, e1432, https://doi.org/10.1002/WAT2.1432, 2020.
Yu, D. and Coulthard, T. J.: Evaluating the importance of catchment hydrological parameters for urban surface water flood modelling using a simple hydro-inundation model, J. Hydrol., 524, 385–400, https://doi.org/10.1016/J.JHYDROL.2015.02.040, 2015.
Zhang, Q., Li, L., Ebert, B., Golding, B., Johnston, D., Mills, B., Panchuk, S., Potter, S., Riemer, M., Sun, J., Taylor, A., Jones, S., Ruti, P., and Keller, J.: Increasing the value of weather-related warnings, Sci. Bull., 64, 647–649, https://doi.org/10.1016/J.SCIB.2019.04.003, 2019.
Short summary
This paper presents the development and verification of FOREWARNS, a novel method for regional-scale forecasting of surface water flooding. We detail outcomes from a workshop held with UK forecast users, who indicated they valued the forecasts and would use them to complement national guidance. We use results of objective forecast tests against flood observations over northern England to show that this confidence is justified and that FOREWARNS meets the needs of UK flood responders.
This paper presents the development and verification of FOREWARNS, a novel method for...
Altmetrics
Final-revised paper
Preprint