Articles | Volume 21, issue 8
https://doi.org/10.5194/nhess-21-2407-2021
© Author(s) 2021. 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-21-2407-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Aug 2021
Research article |
| 17 Aug 2021
| 17 Aug 2021
Social sensing of high-impact rainfall events worldwide: a benchmark comparison against manually curated impact observations
College of Engineering, Maths and Physical Sciences, University of
Exeter, Exeter EX4 4SB, UK
Rudy Arthur
College of Engineering, Maths and Physical Sciences, University of
Exeter, Exeter EX4 4SB, UK
Joanne Robbins
Met Office, Exeter EX1 3PB, UK
Hywel T. P. Williams
College of Engineering, Maths and Physical Sciences, University of
Exeter, Exeter EX4 4SB, UK
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James Hickey, James Young, Michelle Spruce, Ravi Pandit, Hywel Williams, Rudy Arthur, Wendy Stovall, and Matthew Head
Nat. Hazards Earth Syst. Sci., 25, 1681–1696, https://doi.org/10.5194/nhess-25-1681-2025, https://doi.org/10.5194/nhess-25-1681-2025, 2025
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Protecting lives and livelihoods during volcanic eruptions is the key challenge in volcanology. Analysing social media usage during volcanic crises can help us better understand the impacts of volcanic eruptions and how warning messages are received and actioned, to eventually better protect those people and their livelihoods. Our work shows how social media data could be used in real time during a volcanic crisis to learn more about volcanic eruptions.
James Hickey, James Young, Michelle Spruce, Ravi Pandit, Hywel Williams, Rudy Arthur, Wendy Stovall, and Matthew Head
Nat. Hazards Earth Syst. Sci., 25, 1681–1696, https://doi.org/10.5194/nhess-25-1681-2025, https://doi.org/10.5194/nhess-25-1681-2025, 2025
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Protecting lives and livelihoods during volcanic eruptions is the key challenge in volcanology. Analysing social media usage during volcanic crises can help us better understand the impacts of volcanic eruptions and how warning messages are received and actioned, to eventually better protect those people and their livelihoods. Our work shows how social media data could be used in real time during a volcanic crisis to learn more about volcanic eruptions.
David MacLeod, Mary Kilavi, Emmah Mwangi, Maurine Ambani, Michael Osunga, Joanne Robbins, Richard Graham, Pedram Rowhani, and Martin C. Todd
Nat. Hazards Earth Syst. Sci., 21, 261–277, https://doi.org/10.5194/nhess-21-261-2021, https://doi.org/10.5194/nhess-21-261-2021, 2021
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Forecasts of natural hazards save lives. But the accuracy of forecasts must be evaluated before use. Here we evaluate heavy rainfall advisories over Kenya. We assess their ability to anticipate heavy rainfall and show how well they warned of recent floods which had significant impacts. We find that although they effectively warn of heavy rainfall and flooding, issues such as a lack of spatial detail limit their utility for systematic approaches to preparedness.
J. C. Robbins and M. G. Petterson
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-3-4871-2015, https://doi.org/10.5194/nhessd-3-4871-2015, 2015
Revised manuscript has not been submitted
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This paper outlines approaches for developing a regional landslide inventory in a data sparse region, with a specific focus on Papua New Guinea (PNG). In addition, analyses of landslide events which occurred in PNG between 1970 and 2013 are reviewed in detail. Results show that there is a strong climatic control on landslide-triggering events (at a range of temporal and spatial scales) and that the majority of landslides in the PNG landslide inventory are initiated by rainfall related triggers.
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Compound events in Germany in 2018: drivers and case studies
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The anomalously thundery month of June 1925 in southwest Spain: description and synoptic analysis
Spatial identification of regions exposed to multi-hazards at the pan-European level
Classification of North Atlantic and European extratropical cyclones using multiple measures of intensity
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Joseph W. Gallear, Marcelo Valadares Galdos, Marcelo Zeri, and Andrew Hartley
Nat. Hazards Earth Syst. Sci., 25, 1521–1541, https://doi.org/10.5194/nhess-25-1521-2025, https://doi.org/10.5194/nhess-25-1521-2025, 2025
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In Brazil, drought is of national concern and can have major consequences for agriculture. Here, we determine how to develop forecasts for drought stress on vegetation health using machine learning. Results aim to inform future developments in operational drought monitoring at the National Centre for Monitoring and Early Warning of Natural Disasters (CEMADEN) in Brazil. This information is essential for disaster preparedness and planning of future actions to support areas affected by drought.
Thomas Schwitalla, Lisa Jach, Volker Wulfmeyer, and Kirsten Warrach-Sagi
Nat. Hazards Earth Syst. Sci., 25, 1405–1424, https://doi.org/10.5194/nhess-25-1405-2025, https://doi.org/10.5194/nhess-25-1405-2025, 2025
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During recent decades, Europe has experienced increasing periods of severe drought and heatwave. To provide an overview of how land-surface conditions shape land–atmosphere (LA) coupling, the interannual LA coupling strength variability for the summer seasons of 1991–2022 is investigated by means of ERA5 data. The results clearly reflect ongoing climate change by a shift in the coupling relationships towards reinforced heating and drying by the land surface.
Marcos Roberto Benso, Roberto Fray Silva, Gabriela Chiquito Gesualdo, Antonio Mauro Saraiva, Alexandre Cláudio Botazzo Delbem, Patricia Angélica Alves Marques, José Antonio Marengo, and Eduardo Mario Mendiondo
Nat. Hazards Earth Syst. Sci., 25, 1387–1404, https://doi.org/10.5194/nhess-25-1387-2025, https://doi.org/10.5194/nhess-25-1387-2025, 2025
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This study applies climate extreme indices to assess climate risks to food security. Using an explainable machine learning analysis, key climate indices affecting maize and soybean yields in Brazil were identified. Results reveal the temporal sensitivity of these indices and critical yield loss thresholds, informing policy and adaptation strategies.
Juan F. Dueñas, Edda Kunze, Huiying Li, and Matthias C. Rillig
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We investigated the potential of adding mixtures composed of minimum dosages of several popular amendment types to soil. Our goal was to increase the resistance of agricultural soil to drought stress. We found that adding mixtures of three to five amendment types increased the capacity of soil to retain water, reduced soil erosion, and increased fungal abundance while buffering soil from drastic changes in pH. More research is encouraged to validate this approach.
François Collet, Margot Bador, Julien Boé, Laurent Dubus, and Bénédicte Jourdier
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Our aim is to characterize the observed evolution of compound winter low-wind and cold events impacting the French electricity system. The frequency of compound events exhibits a decrease over the 1950–2022 period, which is likely due to a decrease in cold days. Large-scale atmospheric circulation is an important driver of compound event occurrence and has likely contributed to the decrease in cold days, while we cannot draw conclusions on its influence on the decrease in compound events.
Fabio Dioguardi, Giovanni Chiodini, and Antonio Costa
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We investigate the correlation between heavy-rainfall events and three associated natural hazards along the German rail network using GIS analyses and random-effects logistic models. The results show that 23 % of floods, 14 % of gravitational mass movements, and 2 % of tree fall events between 2017 and 2020 occurred after a heavy-rainfall event, and the probability of occurrence of flood and tree fall events significantly increased. This study contributes to more resilient rail transport.
Daniel G. Kingston, Liam Cooper, David A. Lavers, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 25, 675–682, https://doi.org/10.5194/nhess-25-675-2025, https://doi.org/10.5194/nhess-25-675-2025, 2025
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Extreme rainfall comprises a major hydrohazard for New Zealand and is commonly associated with atmospheric rivers – narrow plumes of very high atmospheric moisture transport. Here, we focus on improved forecasting of these events by testing a forecasting tool previously applied to similar situations in western Europe. However, our results for New Zealand suggest the performance of this forecasting tool may vary depending on geographical setting.
Tiago M. Ferreira, Ricardo M. Trigo, Tomás H. Gaspar, Joaquim G. Pinto, and Alexandre M. Ramos
Nat. Hazards Earth Syst. Sci., 25, 609–623, https://doi.org/10.5194/nhess-25-609-2025, https://doi.org/10.5194/nhess-25-609-2025, 2025
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We investigate the synoptic evolution associated with the occurrence of an atmospheric river that led to a 24 h record-breaking extreme precipitation event (120.3 mm) in Lisbon, Portugal, on 13 December 2022. The synoptic background allowed the formation, on 10 December, of an atmospheric river associated with a deep extratropical cyclone and with a high moisture content and an inflow of moisture, due to the warm conveyor belt, throughout its life cycle. The system made landfall on 12 December.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim G. Pinto, Markus Augenstein, Ting-Chen Chen, Hendrik Feldmann, Petra Friederichs, Daniel Gliksman, Laura Goulier, Karsten Haustein, Jens Heinke, Lisa Jach, Florian Knutzen, Stefan Kollet, Jürg Luterbacher, Niklas Luther, Susanna Mohr, Christoph Mudersbach, Christoph Müller, Efi Rousi, Felix Simon, Laura Suarez-Gutierrez, Svenja Szemkus, Sara M. Vallejo-Bernal, Odysseas Vlachopoulos, and Frederik Wolf
Nat. Hazards Earth Syst. Sci., 25, 541–564, https://doi.org/10.5194/nhess-25-541-2025, https://doi.org/10.5194/nhess-25-541-2025, 2025
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Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
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The use of numerical weather prediction models enables the forecasting of hazardous weather situations. The incorporation of new temperature and relative humidity observations from personal weather stations into the French limited-area model is evaluated in this study. This leads to the improvement of the associated near-surface variables of the model during the first hours of the forecast. Examples are provided for a sea breeze case during a heatwave and a fog episode.
Francisco Javier Acero, Manuel Antón, Alejandro Jesús Pérez Aparicio, Nieves Bravo-Paredes, Víctor Manuel Sánchez Carrasco, María Cruz Gallego, José Agustín García, Marcelino Núñez, Irene Tovar, Javier Vaquero-Martínez, and José Manuel Vaquero
Nat. Hazards Earth Syst. Sci., 25, 305–320, https://doi.org/10.5194/nhess-25-305-2025, https://doi.org/10.5194/nhess-25-305-2025, 2025
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The month of June 1925 was found to be exceptional in the southwest interior of the Iberian Peninsula due to the large number of thunderstorms and their significant impacts, with serious losses of human lives and material resources. We analyzed this event from different, complementary perspectives: reconstruction of the history of the events from newspapers, study of monthly meteorological variables of the longest series available, and the analysis of the meteorological synoptic situation.
Tiberiu-Eugen Antofie, Stefano Luoni, Aloïs Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci., 25, 287–304, https://doi.org/10.5194/nhess-25-287-2025, https://doi.org/10.5194/nhess-25-287-2025, 2025
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This is the first study that uses spatial patterns (clusters/hotspots) and meta-analysis in order to identify the regions at a European level at risk of multi-hazards. The findings point out the socioeconomic dimension as a determining factor in the potential risk of multi-hazards. The outcome provides valuable input for the disaster risk management policy support and will assist national authorities on the implementation of a multi-hazard approach in national risk assessment preparation.
Joona Cornér, Clément Bouvier, Benjamin Doiteau, Florian Pantillon, and Victoria A. Sinclair
Nat. Hazards Earth Syst. Sci., 25, 207–229, https://doi.org/10.5194/nhess-25-207-2025, https://doi.org/10.5194/nhess-25-207-2025, 2025
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Classification reduces the considerable variability between extratropical cyclones (ETCs) and thus simplifies studying their representation in climate models and changes in the future climate. In this paper we present an objective classification of ETCs using measures of ETC intensity. This is motivated by the aim of finding a set of ETC intensity measures which together comprehensively describe both the dynamical and impact-relevant nature of ETC intensity.
Cedric G. Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant
Nat. Hazards Earth Syst. Sci., 25, 147–168, https://doi.org/10.5194/nhess-25-147-2025, https://doi.org/10.5194/nhess-25-147-2025, 2025
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The present study addresses the predictability of heat waves at subseasonal timescales in West African cities over the period 2001–2020. Two models, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office models, were evaluated using two reanalyses: ERA5 and MERRA. The results suggest that at subseasonal timescales, the forecast models provide a better forecast than climatology, but the hit rate and false alarm rate are sub-optimal.
Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Mortimer M. Müller, Joni-Pekka Pietikäinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Sarah Veit, Julian Wendler, Elena Xoplaki, and Daniel Gliksman
Nat. Hazards Earth Syst. Sci., 25, 77–117, https://doi.org/10.5194/nhess-25-77-2025, https://doi.org/10.5194/nhess-25-77-2025, 2025
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Our research, involving 22 European scientists, investigated drought and heat impacts on forests in 2018–2022. Findings reveal that climate extremes are intensifying, with central Europe being most severely impacted. The southern region showed resilience due to historical drought exposure, while northern and Alpine areas experienced emerging or minimal impacts. The study highlights the need for region-specific strategies, improved data collection, and sustainable practices to safeguard forests.
Georgy Ayzel and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 25, 41–47, https://doi.org/10.5194/nhess-25-41-2025, https://doi.org/10.5194/nhess-25-41-2025, 2025
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Forecasting rainfall over the next hour is an essential feature of early warning systems. Deep learning (DL) has emerged as a powerful alternative to conventional nowcasting technologies, but it still struggles to adequately predict impact-relevant heavy rainfall. We think that DL could do much better if the training tasks were defined more specifically and that such specification presents an opportunity to better align the output of nowcasting models with actual user requirements.
Monica Ionita, Petru Vaideanu, Bogdan Antonescu, Catalin Roibu, Qiyun Ma, and Viorica Nagavciuc
Nat. Hazards Earth Syst. Sci., 24, 4683–4706, https://doi.org/10.5194/nhess-24-4683-2024, https://doi.org/10.5194/nhess-24-4683-2024, 2024
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Eastern Europe's heat wave history is explored from 1885 to 2023, with a focus on pre-1960 events. The study reveals two periods with more frequent and intense heat waves (HWs): 1920s–1960s and 1980s–present. The research highlights the importance of a long-term perspective, revealing that extreme heat events have occurred throughout the entire study period, and it emphasizes the combined influence of climate change and natural variations on increasing HW severity.
Tristan Shepherd, Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Nat. Hazards Earth Syst. Sci., 24, 4473–4505, https://doi.org/10.5194/nhess-24-4473-2024, https://doi.org/10.5194/nhess-24-4473-2024, 2024
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A historic derecho in the USA is presented. The 29 June 2012 derecho caused more than 20 deaths and millions of US dollars of damage. We use a regional climate model to understand how model fidelity changes under different initial conditions. We find changes drive different convective conditions, resulting in large variation in the simulated hazards. The variation using different reanalysis data shows that framing these results in the context of contemporary and future climate is a challenge.
Lena Wilhelm, Cornelia Schwierz, Katharina Schröer, Mateusz Taszarek, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 3869–3894, https://doi.org/10.5194/nhess-24-3869-2024, https://doi.org/10.5194/nhess-24-3869-2024, 2024
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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.
Marc Lemus-Canovas, Sergi Gonzalez-Herrero, Laura Trapero, Anna Albalat, Damian Insua-Costa, Martin Senande-Rivera, and Gonzalo Miguez-Macho
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-192, https://doi.org/10.5194/nhess-2024-192, 2024
Revised manuscript accepted for NHESS
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This study explores the 2022 heatwaves in the Pyrenees, examining the factors that contributed to their intensity and distribution. The June event was driven by strong winds that created uneven temperature patterns, while the July heatwave featured calmer conditions and more uniform temperatures. Human-driven climate change has made these heatwaves more severe compared to the past. This research helps us better understand how climate change affects extreme weather in mountainous regions.
Ilona Láng-Ritter, Terhi Kristiina Laurila, Antti Mäkelä, Hilppa Gregow, and VIctoria Anne SInclair
EGUsphere, https://doi.org/10.5194/egusphere-2024-3019, https://doi.org/10.5194/egusphere-2024-3019, 2024
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We present a classification method for extratropical cyclones and windstorms and show their impacts on Finland's electricity grid by analysing 92 most damaging windstorms (2005–2018). The southwest- and northwest-originating windstorms cause the most damage to the power grid. The most relevant parameters for damage are the wind gust speed and extent of wind gusts. Windstorms are more frequent and damaging in autumn and winter, but weaker wind speeds in summer also cause significant damage.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024, https://doi.org/10.5194/nhess-24-3479-2024, 2024
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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.
Lou Brett, Christopher J. White, Daniela I.V. Domeisen, Bart van den Hurk, Philip Ward, and Jakob Zscheischler
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-182, https://doi.org/10.5194/nhess-2024-182, 2024
Revised manuscript under review for NHESS
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Compound events, where multiple weather or climate hazards occur together, pose significant risks to both society and the environment. These events, like simultaneous wind and rain, can have more severe impacts than single hazards. Our review of compound event research from 2012–2022 reveals a rise in studies, especially on events that occur concurrently, hot and dry events and compounding flooding. The review also highlights opportunities for research in the coming years.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
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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.
Katharina Küpfer, Alexandre Tuel, and Michael Kunz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2803, https://doi.org/10.5194/egusphere-2024-2803, 2024
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Using loss data, we assess when and how single and multiple types of meteorological extremes (river floods and heavy rainfall events, windstorms and convective gusts, and hail). We find that the combination of several types of hazards clusters robustly on a seasonal scale, whereas only some single hazard types occur in clusters. This can be associated with higher losses compared to isolated events. We argue for the relevance of jointly considering multiple types of hazards.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024, https://doi.org/10.5194/nhess-24-3035-2024, 2024
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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.
Jinfang Yin, Feng Li, Mingxin Li, Rudi Xia, Xinghua Bao, Jisong Sun, and Xudong Liang
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-145, https://doi.org/10.5194/nhess-2024-145, 2024
Revised manuscript accepted for NHESS
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A persistent severe rainfall event occurred over North China in July 2023, which was regarded as one of the precipitation extremes of 2023 globally. The extreme rainfall was significant underestimated by forecasters at that time. Flooding from this event affected 1.3 million people, causing severe human casualties and significant economic losses. In this study, we examined the convective initiation and subsequent persistent heavy rainfall over North China based on simulations with the WRF model.
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024, https://doi.org/10.5194/nhess-24-2633-2024, 2024
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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.
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.
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.
Andreas Trojand, Henning Rust, and Uwe Ulbrich
EGUsphere, https://doi.org/10.5194/egusphere-2024-1506, https://doi.org/10.5194/egusphere-2024-1506, 2024
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The study investigates how the intensity of previous windstorm events and the time between two events affect the vulnerability of residential buildings in Germany. By analyzing 23 years of data, it was found that higher intensity of previous events generally reduces vulnerability in subsequent storms, while shorter intervals between events increase vulnerability. The results emphasize the approach of considering vulnerability in risk assessments as temporal dynamic.
Shao-Yi Lee, Sicheng He, and Tetsuya Takemi
EGUsphere, https://doi.org/10.5194/egusphere-2024-1304, https://doi.org/10.5194/egusphere-2024-1304, 2024
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Summer rainfall extremes over western Japan were calculated every year, using radar, rain-gauges, and model. Similar regions were determined by machine learning. The relationships between regional rainfall extremes and Pacific climate modes. The modelled relationships were similar to the observed ones for the El Niño-Southern Oscillation and the warming trend. However, the model did not reproduce the relationship for Pacific Decadal Variability.
Cees de Valk and Henk van den Brink
EGUsphere, https://doi.org/10.5194/egusphere-2024-912, https://doi.org/10.5194/egusphere-2024-912, 2024
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Recently updated flood safety norms in the Netherlands prescribe that sea dikes and other flood-protecting structures should withstand high sea levels reached very rarely, locally down to only once in 10 million years. We show that such levels can be estimated with reasonable accuracy by the cautious use of very large datasets of numerical simulations of weather and storm surge.
Natalia Korhonen, Otto Hyvärinen, Virpi Kollanus, Timo Lanki, Juha Jokisalo, Risto Kosonen, David S. Richardson, and Kirsti Jylhä
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-75, https://doi.org/10.5194/nhess-2024-75, 2024
Revised manuscript accepted for NHESS
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The skill of hindcasts of the European Centre for Medium-Range Weather Forecasts in forecasting heat wave days (periods with the 5-day moving average temperature being above its local summer 90th percentile) over Europe 1 to 4 weeks ahead is examined. The heat wave days forecasts show potential in warning of heat risk in 1–2 weeks in advance, and enhanced accuracy in forecasting prolonged heat waves, in lead times of up to 3 weeks, when the heat wave had initiated prior to the forecast issuance.
Andi Xhelaj and Massimiliano Burlando
Nat. Hazards Earth Syst. Sci., 24, 1657–1679, https://doi.org/10.5194/nhess-24-1657-2024, https://doi.org/10.5194/nhess-24-1657-2024, 2024
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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.
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.
Cited articles
Aisha, T. S., Wok, S., Manaf, A. M. A., and Ismail, R.: Exploring the Use of
Social Media During the 2014 Flood in Malaysia, Procedia - Soc. Behav. Sci.,
211, 931–937, https://doi.org/10.1016/J.SBSPRO.2015.11.123, 2015.
Arthur, R., Boulton, C. A., Shotton, H., and Williams, H. T. P.: Social
sensing of floods in the UK, available at:
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0189327
(last access: 17 December 2020), 2018.
Bossu, R., Fallou, L., Landès, M., Roussel, F., Julien-Laferrière,
S., Roch, J., and Steed, R.: Rapid Public Information and Situational Awareness After the November 26, 2019, Albania Earthquake: Lessons Learned
From the LastQuake System, Front. Earth Sci., 8, 235, https://doi.org/10.3389/feart.2020.00235, 2020.
Boulton, C. A., Shotton, H., and Williams, H. T. P.: Using social media to
detect and locate wildfires, in Tenth International AAAI Conference on Web
and Social Media, AAAI, available at:
https://www.aaai.org/ocs/index.php/ICWSM/ICWSM16/paper/view/13204 (last access: 14 October 2019), 2016.
Brouwer, T., Eilander, D., van Loenen, A., Booij, M. J., Wijnberg, K. M.,
Verkade, J. S., and Wagemaker, J.: Probabilistic flood extent estimates from
social media flood observations, Nat. Hazards Earth Syst. Sci., 17, 735–747, https://doi.org/10.5194/nhess-17-735-2017, 2017.
Campbell, R., Beardsley, D., and Sezin, T.: Impact-based Forecasting and
Warning: Weather Ready Nations, World Meteorological Organization, available at:
https://public.wmo.int/en/resources/bulletin/impact-based-forecasting-and-warning-weather-ready-nations
(last access: 19 January 2020), 2018.
Cervone, G., Sava, E., Huang, Q., Schnebele, E., Harrison, J., and Waters, N.: Using Twitter for tasking remote-sensing data collection and damage assessment: 2013 Boulder flood case study, Int. J. Remote Sens., 37, 100–124, https://doi.org/10.1080/01431161.2015.1117684, 2016.
Clement, J.: Twitter – Statistics & Facts, Statista, available at: https://www.statista.com/topics/737/twitter/, last access: 19 March 2020.
Cowie, S., Arthur, R., and Williams, H. T. P.: @choo: Tracking Pollen and
Hayfever in the UK Using Social Media, Sensors, 18, 4434, https://doi.org/10.3390/s18124434, 2018.
DBpedia: A Public Data Infrastructure for a Large, Multilingual, Semantic
Knowledge Graph, available at: https://wiki.dbpedia.org/, last access: 13 October 2020.
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, 311, https://doi.org/10.1038/s41597-019-0326-9, 2019.
Dredze, M., Paul, M. J., Bergsma, S., and Tran, H.: Carmen: A Twitter
Geolocation System with Applications to Public Health, available at:
https://pdfs.semanticscholar.org/9bc4/6fb12f2c7fae0e9e56e734e6efb9ca07fd98.pdf
(last access: 17 December 2020), 2013.
Fang, J., Hu, J., Shi, X., and Zhao, L.: Assessing disaster impacts and response using social media data in China: A case study of 2016 Wuhan rainstorm, Int. J. Disast. Risk Reduct., 34, 275–282, https://doi.org/10.1016/j.ijdrr.2018.11.027, 2019.
Geonames: GeoNames, available at: https://www.geonames.org/, last access: 11 June 2020.
Guan, X. and Chen, C.: Using social media data to understand and assess
disasters, Nat. Hazards, 74, 837–850, https://doi.org/10.1007/s11069-014-1217-1, 2014.
Han, X. and Wang, J.: Using social media to mine and analyze public sentiment during a disaster: A case study of the 2018 Shouguang city flood in china, ISPRS Int. J. Geo-Information, available at:
https://www.mdpi.com/2220-9964/8/4/185 (last access: 17 December 2020), 2019.
Kankanamge, N., Yigitcanlar, T., Goonetilleke, A., and Kamruzzaman, M.:
Determining disaster severity through social media analysis: Testing the
methodology with South East Queensland Flood tweets, Int. J. Disast. Risk
Reduct., 42, 101360, https://doi.org/10.1016/j.ijdrr.2019.101360, 2020.
Kim, J. and Hastak, M.: Social network analysis: Characteristics of online
social networks after a disaster, Int. J. Inf. Manage., 38, 86–96,
https://doi.org/10.1016/J.IJINFOMGT.2017.08.003, 2018.
Koehrsen, W.: Beyond Accuracy: Precision and Recall, by Will Koehrsen, Towards Data Science, Towar. Data Sci., available at:
https://towardsdatascience.com/beyond-accuracy-precision-and-recall-3da06bea9f6c
(last access: 2 October 2020), 2018.
Lachlan, K. A., Spence, P. R., Lin, X., and Del Greco, M.: Screaming into the
Wind: Examining the Volume and Content of Tweets Associated with Hurricane
Sandy, Commun. Stud., 65, 500–518, https://doi.org/10.1080/10510974.2014.956941, 2014.
Li, Z., Wang, C., Emrich, C. T., and Guo, D.: A novel approach to leveraging
social media for rapid flood mapping: a case study of the 2015 South Carolina floods, Cartogr. Geogr. Inf. Sci., 45, 97–110, https://doi.org/10.1080/15230406.2016.1271356, 2018.
Liu, X., Zhang, S., Wei, F., and Zhou, M.: Recognizing Named Entities in
Tweets, Association for Computational Linguistics, available at:
http://sourceforge.net/projects/opennlp/ (last access: 19 May 2020), 2011.
Liu, Y., Liu, X., Gao, S., Gong, L., Kang, C., Zhi, Y., Chi, G., and Shi, L.:
Social Sensing: A New Approach to Understanding Our Socioeconomic Environments, Ann. Assoc. Am. Geogr., 105, 512–530, https://doi.org/10.1080/00045608.2015.1018773, 2015.
Mocanu, D., Baronchelli, A., Perra, N., Gonçalves, B., Zhang, Q., and
Vespignani, A.: The Twitter of Babel: Mapping World Languages through
Microblogging Platforms, PLoS One, 8, 61981, https://doi.org/10.1371/journal.pone.0061981, 2013.
Morss, R. E., Demuth, J. L., Lazrus, H., Palen, L., Barton, C. M., Davis, C.
A., Snyder, C., Wilhelmi, O. V., Anderson, K. M., Ahijevych, D. A., Anderson, J., Bica, M., Fossell, K. R., Henderson, J., Kogan, M., Stowe, K., Watts, J., Morss, R. E., Demuth, J. L., Lazrus, H., Palen, L., Barton, C. M., Davis, C. A., Snyder, C., Wilhelmi, O. V., Anderson, K. M., Ahijevych, D. A., Anderson, J., Bica, M., Fossell, K. R., Henderson, J., Kogan, M., Stowe, K., and Watts, J.: Hazardous Weather Prediction and Communication in the Modern Information Environment, B. Am. Meteorol. Soc., 98, 2653–2674, https://doi.org/10.1175/BAMS-D-16-0058.1, 2017.
Morstatter, F., Pfeffer, J., Liu, H., and Carley, K. M.: Is the Sample Good
Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose,
in: Proceedings of the 7th International Conference on Weblogs and Social
Media, ICWSM 2013, AAAI Press, 400–408, arxiv: preprint, available at:
http://arxiv.org/abs/1306.5204 (last access: 14 October 2019), 2013.
Niles, M. T., Emery, B. F., Reagan, A. J., Dodds, P. S., and Danforth, C. M.:
Social media usage patterns during natural hazards, edited by: Lozano, S.,
PLoS One, 14, e0210484, https://doi.org/10.1371/journal.pone.0210484, 2019.
Rainear, A. M., Lachlan, K. A., Oeldorf-Hirsch, A., and DeVoss, C. L.:
Examining twitter content of state emergency management during Hurricane
Joaquin, Commun. Res. Rep., 35, 325–334, https://doi.org/10.1080/08824096.2018.1503945, 2018.
Robbins, J. C. and Titley, H. A.: Evaluating high-impact precipitation
forecasts from the Met Office Global Hazard Map (GHM) using a global impact
database, Meteorol. Appl., 25, 548–560, https://doi.org/10.1002/met.1720, 2018.
Rossi, C., Acerbo, F. S., Ylinen, K., Juga, I., Nurmi, P., Bosca, A., Tarasconi, F., Cristoforetti, M., and Alikadic, A.: Early detection and
information extraction for weather-induced floods using social media streams, Int. J. Disast. Risk Reduct., 30, 145–157, https://doi.org/10.1016/j.ijdrr.2018.03.002, 2018.
Sakaki, T., Okazaki, M., and Matsuo, Y.: Earthquake shakes Twitter users, in:
Proceedings of the 19th international conference on World wide web – WWW '10, ACM Press, New York, USA, p. 851, 2010.
Schulz, A., Hadjakos, A., Paulheim, H., Nachtwey, J., and Uhlhäuser, M.:
A Multi-Indicator Approach for Geolocalization of Tweets, in: Proceedings of
the 7th International Conference on Weblogs and Social Media, ICWSM 2013,
AAAI Press, 573–582, available at:
https://www.aaai.org/ocs/index.php/ICWSM/ICWSM13/paper/viewFile/6063/6397
(last access: 17 December 2020), 2013.
Seda-lab: Social_Sensing, available on request at: https://github.com/seda-lab/social_sensing, last access: 17 December 2020.
Sit, M. A., Koylu, C., and Demir, I.: Identifying disaster-related tweets and
their semantic, spatial and temporal context using deep learning, natural
language processing and spatial analysis: a case study of Hurricane Irma, Int. J. Digit. Earth, 12, 1205–1229, https://doi.org/10.1080/17538947.2018.1563219, 2019.
Spruce, M., Arthur, R., and Williams, H. T. P.: Using social media to measure
impacts of named storm events in the United Kingdom and Ireland, Meteorol.
Appl., 27, e1887, https://doi.org/10.1002/met.1887, 2020.
Stewart, M. C. and Gail Wilson, B.: The dynamic role of social media during
Hurricane #Sandy: An introduction of the STREMII model to weather the storm of the crisis lifecycle, Comput. Human Behav., 54, 639–646,
https://doi.org/10.1016/J.CHB.2015.07.009, 2016.
Twitter: More on Restricted Use Cases, available at: https://developer.twitter.com/en/developer-terms/more-on-restricted-use-cases, last access: 17 December 2020.
Wang, D., Kaplan, L., Le, H., and Abdelzaher, T.: On truth discovery in social sensing: A maximum likelihood estimation approach, in: IPSN'12 –
Proceedings of the 11th International Conference on Information Processing
in Sensor Networks, ACM Press, New York, USA, 233–244, 2012.
Wang, D., Szymanski, B. K., Abdelzaher, T., Ji, H., and Kaplan, L.: The age
of social sensing, Computer (Long. Beach. Calif)., 52, 36–45,
https://doi.org/10.1109/MC.2018.2890173, 2019.
Wu, D. and Cui, Y.: Disaster early warning and damage assessment analysis
using social media data and geo-location information, Decis. Support Syst.,
111, 48–59, https://doi.org/10.1016/j.dss.2018.04.005, 2018.
Zou, L., Lam, N. S. N., Cai, H., and Qiang, Y.: Mining Twitter Data for
Improved Understanding of Disaster Resilience, Ann. Am. Assoc. Geogr., 108, 1422–1441, https://doi.org/10.1080/24694452.2017.1421897, 2018.
Short summary
Despite increased use of impact-based weather warnings, the social impacts of extreme weather events lie beyond the reach of conventional meteorological observations and remain difficult to quantify. This study compares data collected from the social media platform Twitter with a manually curated database of high-impact rainfall events across the globe between January–June 2017. Twitter is found to be a good detector of impactful rainfall events and, therefore, a useful source of impact data.
Despite increased use of impact-based weather warnings, the social impacts of extreme weather...
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