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
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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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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Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 1: Analysis and cloud-resolving simulation
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Uncovering the veil of night light changes in times of catastrophe
Time of emergence of compound events: contribution of univariate and dependence properties
Skillful decadal prediction of German Bight storm activity
Droughts in Germany: performance of regional climate models in reproducing observed characteristics
Analysis of the relationship between yield in cereals and remotely sensed fAPAR in the framework of monitoring drought impacts in Europe
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Nat. Hazards Earth Syst. Sci., 23, 1139–1155, https://doi.org/10.5194/nhess-23-1139-2023, https://doi.org/10.5194/nhess-23-1139-2023, 2023
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This paper focuses on investigating the thresholds of extreme precipitation using sub-daily records in the Ganjiang River basin using gamma distribution, the L-moment method and the Mann–Kendall (M–K) test. The main findings are (1) run 3 (36 h) precipitation events would be key events for flood monitoring. (2）The intensity and the occasional probability of extreme precipitation will increase in spring in the future in stations like Yifeng, Zhangshu and Ningdu.
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Nat. Hazards Earth Syst. Sci., 23, 1045–1058, https://doi.org/10.5194/nhess-23-1045-2023, https://doi.org/10.5194/nhess-23-1045-2023, 2023
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A deep frost occurred in early April 2021, inducing severe damages in grapevine and fruit trees in France. We found that such extreme frosts occurring after the start of the growing season such as those of April 2021 are currently about 2°C colder [0.5 °C to 3.3 °C] in observations than in preindustrial climate. This observed intensification of growing-period frosts is attributable, at least in part, to human-caused climate change, making the 2021 event 50 % more likely [10 %–110 %].
Diego S. Carrió
Nat. Hazards Earth Syst. Sci., 23, 847–869, https://doi.org/10.5194/nhess-23-847-2023, https://doi.org/10.5194/nhess-23-847-2023, 2023
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The accurate prediction of medicanes still remains a key challenge in the scientific community because of their poor predictability. In this study we assimilate different observations to improve the trajectory and intensity forecasts of the Qendresa Medicane. Results show the importance of using data assimilation techniques to improve the estimate of the atmospheric flow in the upper-level atmosphere, which has been shown to be key to improve the prediction of Qendresa.
Chung-Chieh Wang and Duc Van Nguyen
Nat. Hazards Earth Syst. Sci., 23, 771–788, https://doi.org/10.5194/nhess-23-771-2023, https://doi.org/10.5194/nhess-23-771-2023, 2023
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A record-breaking rainfall event over central Vietnam is investigated. Key factors include the combined effect of northeasterly wind, easterly wind blowing to central Vietnam from the western North Pacific (WNP), southeasterly wind, local topography, and high sea surface temperature (SST) over WNP and the South China Sea (SCS). The cloud-resolving storm simulator (CReSS) is applied to simulate this event. The results show that the model mostly captured the quantitative rainfall of this event.
Yi Yang, Douglas Maraun, Albert Ossó, and Jianping Tang
Nat. Hazards Earth Syst. Sci., 23, 693–709, https://doi.org/10.5194/nhess-23-693-2023, https://doi.org/10.5194/nhess-23-693-2023, 2023
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This study quantifies the spatiotemporal variation and characteristics of compound long-duration dry and hot events in China over the 1961–2014 period. The results show that over the past few decades, there has been a substantial increase in the frequency of these compound events across most parts of China, which is dominated by rising temperatures. We detect a strong increase in the spatially contiguous areas experiencing concurrent dry and hot conditions.
Isabella Aitkenhead, Yuriy Kuleshov, Jessica Bhardwaj, Zhi-Weng Chua, Chayn Sun, and Suelynn Choy
Nat. Hazards Earth Syst. Sci., 23, 553–586, https://doi.org/10.5194/nhess-23-553-2023, https://doi.org/10.5194/nhess-23-553-2023, 2023
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A case study assessing drought risk in Papua New Guinea (PNG) provinces for retrospective years (2014–2020) was conducted to demonstrate the development and validate the application of a tailored and semi-dynamic drought risk assessment methodology. Hazard, vulnerability, and exposure indicators appropriate for monitoring drought in PNG provinces were selected. The risk assessment accurately indicated a strong drought event in 2015–2016 and a moderate event in 2019.
Anna Karali, Konstantinos V. Varotsos, Christos Giannakopoulos, Panagiotis P. Nastos, and Maria Hatzaki
Nat. Hazards Earth Syst. Sci., 23, 429–445, https://doi.org/10.5194/nhess-23-429-2023, https://doi.org/10.5194/nhess-23-429-2023, 2023
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As climate change leads to more frequent and severe fires, forecasting fire danger before fire season begins can support fire management. This study aims to provide high-resolution probabilistic seasonal fire danger forecasts in a Mediterranean environment and assess their ability to capture years with increased fire activity. Results indicate that forecasts are skillful in predicting above-normal fire danger conditions and can be exploited by regional authorities in fire prevention management.
Vincent Schippers and Wouter Botzen
Nat. Hazards Earth Syst. Sci., 23, 179–204, https://doi.org/10.5194/nhess-23-179-2023, https://doi.org/10.5194/nhess-23-179-2023, 2023
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Researchers studying economic impacts of natural disasters increasingly use night light as a proxy for local economic activity, when socioeconomic data are unavailable. But often it is unclear what changes in light intensity represent in the context of disasters. We study this in detail for Hurricane Katrina and find a strong correlation with building damage and changes in population and employment. We conclude that night light data are useful to study local impacts of natural disasters.
Bastien François and Mathieu Vrac
Nat. Hazards Earth Syst. Sci., 23, 21–44, https://doi.org/10.5194/nhess-23-21-2023, https://doi.org/10.5194/nhess-23-21-2023, 2023
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Compound events (CEs) result from a combination of several climate phenomena. In this study, we propose a new methodology to assess the time of emergence of CE probabilities and to quantify the contribution of marginal and dependence properties of climate phenomena to the overall CE probability changes. By applying our methodology to two case studies, we show the importance of considering changes in both marginal and dependence properties for future risk assessments related to CEs.
Daniel Krieger, Sebastian Brune, Patrick Pieper, Ralf Weisse, and Johanna Baehr
Nat. Hazards Earth Syst. Sci., 22, 3993–4009, https://doi.org/10.5194/nhess-22-3993-2022, https://doi.org/10.5194/nhess-22-3993-2022, 2022
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Accurate predictions of storm activity are desirable for coastal management. We investigate how well a climate model can predict storm activity in the German Bight 1–10 years in advance. We let the model predict the past, compare these predictions to observations, and analyze whether the model is doing better than simple statistical predictions. We find that the model generally shows good skill for extreme periods, but the prediction timeframes with good skill depend on the type of prediction.
Dragan Petrovic, Benjamin Fersch, and Harald Kunstmann
Nat. Hazards Earth Syst. Sci., 22, 3875–3895, https://doi.org/10.5194/nhess-22-3875-2022, https://doi.org/10.5194/nhess-22-3875-2022, 2022
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The influence of model resolution and settings on drought reproduction in Germany between 1980–2009 is investigated here. 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. Gridded observational data sets serve as reference. Regarding the reproduction of drought characteristics, all models perform on a similar level, while for trends, only the modified model produces reliable outputs.
Carmelo Cammalleri, Niall McCormick, and Andrea Toreti
Nat. Hazards Earth Syst. Sci., 22, 3737–3750, https://doi.org/10.5194/nhess-22-3737-2022, https://doi.org/10.5194/nhess-22-3737-2022, 2022
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We evaluated the ability of vegetation indices derived from satellite data to capture annual yield variations across Europe. The strength of the relationship varies throughout the year, with March–October representing the optimal period in most cases. Spatial differences were also observed, with the best results obtained in the Mediterranean regions.
Alberto Caldas-Alvarez, Markus Augenstein, Georgy Ayzel, Klemens Barfus, Ribu Cherian, Lisa Dillenardt, Felix Fauer, Hendrik Feldmann, Maik Heistermann, Alexia Karwat, Frank Kaspar, Heidi Kreibich, Etor Emanuel Lucio-Eceiza, Edmund P. Meredith, Susanna Mohr, Deborah Niermann, Stephan Pfahl, Florian Ruff, Henning W. Rust, Lukas Schoppa, Thomas Schwitalla, Stella Steidl, Annegret H. Thieken, Jordis S. Tradowsky, Volker Wulfmeyer, and Johannes Quaas
Nat. Hazards Earth Syst. Sci., 22, 3701–3724, https://doi.org/10.5194/nhess-22-3701-2022, https://doi.org/10.5194/nhess-22-3701-2022, 2022
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In a warming climate, extreme precipitation events are becoming more frequent. To advance our knowledge on such phenomena, we present a multidisciplinary analysis of a selected case study that took place on 29 June 2017 in the Berlin metropolitan area. Our analysis provides evidence of the extremeness of the case from the atmospheric and the impacts perspectives as well as new insights on the physical mechanisms of the event at the meteorological and climate scales.
Julia F. Lockwood, Galina S. Guentchev, Alexander Alabaster, Simon J. Brown, Erika J. Palin, Malcolm J. Roberts, and Hazel E. Thornton
Nat. Hazards Earth Syst. Sci., 22, 3585–3606, https://doi.org/10.5194/nhess-22-3585-2022, https://doi.org/10.5194/nhess-22-3585-2022, 2022
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We describe how we developed a set of 1300 years' worth of European winter windstorm footprints, using a multi-model ensemble of high-resolution global climate models, for use by the insurance industry to analyse windstorm risk. The large amount of data greatly reduces uncertainty on risk estimates compared to using shorter observational data sets and also allows the relationship between windstorm risk and predictable large-scale climate indices to be quantified.
Ed Hawkins, Philip Brohan, Samantha Burgess, Stephen Burt, Gilbert Compo, Suzanne Gray, Ivan Haigh, Hans Hersbach, Kiki Kuijjer, Oscar Martinez-Alvarado, Chesley McColl, Andrew Schurer, Laura Slivinski, and Joanne Williams
EGUsphere, https://doi.org/10.5194/egusphere-2022-1045, https://doi.org/10.5194/egusphere-2022-1045, 2022
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We examine a severe windstorm that occurred in February 1903 and caused significant damage in the UK & Ireland. Using newly digitised weather observations from the time of the storm, combined with a modern weather forecast model, allows us to determine why this storm caused so much damage. We demonstrate that this event is one of the most severe windstorms to affect this region since detailed records began. This approach establishes a new tool to improve assessments of risk from extreme weather.
Haoran Zhu, Priscilla Obeng Oforiwaa, and Guofeng Su
Nat. Hazards Earth Syst. Sci., 22, 3349–3359, https://doi.org/10.5194/nhess-22-3349-2022, https://doi.org/10.5194/nhess-22-3349-2022, 2022
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We promote a new method to detect waterlogging disasters. Residents are directly affected by waterlogging, and we can collect their comments on social networks. Compared to official-authentication and personal-certification users, the microblogs posted by general users can better show the intensity and timing of waterlogging. Through text and sentiment features, we can separate microblogs with waterlogging information from other ones and mark high-risk regions on maps.
Rafaela Jane Delfino, Gerry Bagtasa, Kevin Hodges, and Pier Luigi Vidale
Nat. Hazards Earth Syst. Sci., 22, 3285–3307, https://doi.org/10.5194/nhess-22-3285-2022, https://doi.org/10.5194/nhess-22-3285-2022, 2022
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We showed the effects of altering the choice of cumulus schemes, surface flux options, and spectral nudging with a high level of sensitivity to cumulus schemes in simulating an intense typhoon. We highlight the advantage of using an ensemble of cumulus parameterizations to take into account the uncertainty in simulating typhoons such as Haiyan in 2013. This study is useful in addressing the growing need to plan and prepare for as well as reduce the impacts of intense typhoons in the Philippines.
Emma Elizabeth Aalbers, Erik van Meijgaard, Geert Lenderink, Hylke de Vries, and Bart J. J. M. van den Hurk
EGUsphere, https://doi.org/10.5194/egusphere-2022-954, https://doi.org/10.5194/egusphere-2022-954, 2022
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To examine the impact of global warming on west-central European droughts, we have constructed future analogues of recent summers. Years that went hardly noticed in the present-day climate may emerge as very dry and hot in a warmer world. Extreme droughts like 2018 further intensify and the local temperature rise is much larger than in most summers. These changes can be directly linked to real world events, which make the results very tangible and hence useful for climate change communication.
Pauline Combarnous, Felix Erdmann, Olivier Caumont, Éric Defer, and Maud Martet
Nat. Hazards Earth Syst. Sci., 22, 2943–2962, https://doi.org/10.5194/nhess-22-2943-2022, https://doi.org/10.5194/nhess-22-2943-2022, 2022
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The objective of this study is to prepare the assimilation of satellite lightning data in the French regional numerical weather prediction system. The assimilation of lightning data requires an observation operator, based on empirical relationships between the lightning observations and a set of proxies derived from the numerical weather prediction system variables. We fit machine learning regression models to our data to yield those relationships and to investigate the best proxy for lightning.
Efi Rousi, Andreas H. Fink, Lauren S. Andersen, Florian N. Becker, Goratz Beobide-Arsuaga, Marcus Breil, Giacomo Cozzi, Jens Heinke, Lisa Jach, Deborah Niermann, Dragan Petrovic, Andy Richling, Johannes Riebold, Stella Steidl, Laura Suarez-Gutierrez, Jordis Tradowsky, Dim Coumou, André Düsterhus, Florian Ellsäßer, Georgios Fragkoulidis, Daniel Gliksman, Dörthe Handorf, Karsten Haustein, Kai Kornhuber, Harald Kunstmann, Joaquim G. Pinto, Kirsten Warrach-Sagi, and Elena Xoplaki
EGUsphere, https://doi.org/10.5194/egusphere-2022-813, https://doi.org/10.5194/egusphere-2022-813, 2022
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Here, we present a comprehensive, multi-faceted analysis of the 2018 extreme summer in terms of heat and drought in central and northern Europe with a particular focus on Germany. Using different analysis approaches we study (a) the extremeness and attribution to anthropogenic climate change (climate perspective), as well as (b) the synoptic dynamics in concert with the role of slowly varying boundary conditions at the ocean and continental surfaces (seasonal and weather perspective).
Dirk Thielen, Paolo Ramoni-Perazzi, Mary L. Puche, Marco Marquez, José I. Quintero, Wilmer Rojas, Alberto Quintero, Guillermo Bianchi, Irma A. Soto-Werschitz, and Marco Aurelio Arizapana-Almonacid
EGUsphere, https://doi.org/10.5194/egusphere-2022-763, https://doi.org/10.5194/egusphere-2022-763, 2022
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Extreme El Niño events are significantly different from other El Niños, standing out for their powerful impacts, and are predicted to increase in frequency and intensity. In this regard, we provide valuable and highly strategic information on the similarities and differences between the effects on precipitation from types of extreme El Niño, highlighting spatially and quantitatively, those regions where most extreme precipitation anomalies are most likely to occur in extreme events.
Cedric Gacial Ngoungue Langue, Christophe Lavaysse, Mathieu Vrac, and Cyrille Flamant
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-192, https://doi.org/10.5194/nhess-2022-192, 2022
Revised manuscript accepted for NHESS
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Heat waves (HW) are climatic hazards affecting the planet. We assess here uncertainties encountered in the process of HW detection and analyze their recent trends in West Africa using reanalysis data. Three types of uncertainties have been investigated. We identified 4 years with higher frequency of HW possibly due to higher sea surface temperatures in the Equatorial Atlantic. We noticed an increase in HW characteristics during the last decade, which could be a consequence of climate change.
Cécile Duvillier, Nicolas Eckert, Guillaume Evin, and Michael Deschâtres
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-177, https://doi.org/10.5194/nhess-2022-177, 2022
Revised manuscript accepted for NHESS
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Identification of snow avalanche Potential Release Areas (PRAs) is useful for objective hazard assessment. This study develops a method that efficiently identifies individual PRAs based on terrain analysis and watershed delineation, and demonstrates its efficiency in the French Alps context using an extensive cadastre of past avalanche limits. Crucial steps to reach high accuracy in PRA detection are highlighted and outlooks for further progresses are discussed.
Veit Blauhut, Michael Stoelzle, Lauri Ahopelto, Manuela I. Brunner, Claudia Teutschbein, Doris E. Wendt, Vytautas Akstinas, Sigrid J. Bakke, Lucy J. Barker, Lenka Bartošová, Agrita Briede, Carmelo Cammalleri, Ksenija Cindrić Kalin, Lucia De Stefano, Miriam Fendeková, David C. Finger, Marijke Huysmans, Mirjana Ivanov, Jaak Jaagus, Jiří Jakubínský, Svitlana Krakovska, Gregor Laaha, Monika Lakatos, Kiril Manevski, Mathias Neumann Andersen, Nina Nikolova, Marzena Osuch, Pieter van Oel, Kalina Radeva, Renata J. Romanowicz, Elena Toth, Mirek Trnka, Marko Urošev, Julia Urquijo Reguera, Eric Sauquet, Aleksandra Stevkov, Lena M. Tallaksen, Iryna Trofimova, Anne F. Van Loon, Michelle T. H. van Vliet, Jean-Philippe Vidal, Niko Wanders, Micha Werner, Patrick Willems, and Nenad Živković
Nat. Hazards Earth Syst. Sci., 22, 2201–2217, https://doi.org/10.5194/nhess-22-2201-2022, https://doi.org/10.5194/nhess-22-2201-2022, 2022
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Recent drought events caused enormous damage in Europe. We therefore questioned the existence and effect of current drought management strategies on the actual impacts and how drought is perceived by relevant stakeholders. Over 700 participants from 28 European countries provided insights into drought hazard and impact perception and current management strategies. The study concludes with an urgent need to collectively combat drought risk via a European macro-level drought governance approach.
Chung-Chieh Wang, Pi-Yu Chuang, Shi-Ting Chen, Dong-In Lee, and Kazuhisa Tsuboki
Nat. Hazards Earth Syst. Sci., 22, 1795–1817, https://doi.org/10.5194/nhess-22-1795-2022, https://doi.org/10.5194/nhess-22-1795-2022, 2022
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In this study, cloud-resolving simulations are performed under idealized and uniform southwesterly flow direction and speed to investigate the rainfall regimes in the Mei-yu season and the role of complex mesoscale topography on rainfall without the influence of unwanted disturbances, including a low-Froude number regime where the thermodynamic effects and island circulation dominate, a high-Froude number regime where topographic rainfall in a flow-over scenario prevails, and a mixed regime.
Viorica Nagavciuc, Patrick Scholz, and Monica Ionita
Nat. Hazards Earth Syst. Sci., 22, 1347–1369, https://doi.org/10.5194/nhess-22-1347-2022, https://doi.org/10.5194/nhess-22-1347-2022, 2022
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Here we have assessed the variability and trends of hot and dry summers in Romania. The length, spatial extent, and frequency of heat waves in Romania have increased significantly over the last 70 years, while no significant changes have been observed in the drought conditions. The increased frequency of heat waves, especially after the 1990s, could be partially explained by an increase in the geopotential height over the eastern part of Europe.
Joris Pianezze, Jonathan Beuvier, Cindy Lebeaupin Brossier, Guillaume Samson, Ghislain Faure, and Gilles Garric
Nat. Hazards Earth Syst. Sci., 22, 1301–1324, https://doi.org/10.5194/nhess-22-1301-2022, https://doi.org/10.5194/nhess-22-1301-2022, 2022
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Most numerical weather and oceanic prediction systems do not consider ocean–atmosphere feedback during forecast, and this can lead to significant forecast errors, notably in cases of severe situations. A new high-resolution coupled ocean–atmosphere system is presented in this paper. This forecast-oriented system, based on current regional operational systems and evaluated using satellite and in situ observations, shows that the coupling improves both atmospheric and oceanic forecasts.
Katherine L. Towey, James F. Booth, Alejandra Rodriguez Enriquez, and Thomas Wahl
Nat. Hazards Earth Syst. Sci., 22, 1287–1300, https://doi.org/10.5194/nhess-22-1287-2022, https://doi.org/10.5194/nhess-22-1287-2022, 2022
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Coastal flooding due to storm surge from tropical cyclones is a significant hazard. The influence of tropical cyclone characteristics, including its proximity, intensity, path angle, and speed, on the magnitude of storm surge is examined along the eastern United States. No individual characteristic was found to be strongly related to how much surge occurred at a site, though there is an increased likelihood of high surge occurring when tropical cyclones are both strong and close to a location.
Arnau Amengual
Nat. Hazards Earth Syst. Sci., 22, 1159–1179, https://doi.org/10.5194/nhess-22-1159-2022, https://doi.org/10.5194/nhess-22-1159-2022, 2022
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On 12 and 13 September 2019, a long-lasting heavy precipitation episode resulted in widespread flash flooding over eastern Spain. Well-organized and quasi-stationary convective structures impacted a vast area with rainfall amounts over 200 mm. The very dry initial soil moisture conditions resulted in a dampened hydrological response: until runoff thresholds were exceeded, infiltration-excess generation did not start. This threshold-based behaviour is explored through simple scaling theory.
Benjamin J. Hatchett, Alan M. Rhoades, and Daniel J. McEvoy
Nat. Hazards Earth Syst. Sci., 22, 869–890, https://doi.org/10.5194/nhess-22-869-2022, https://doi.org/10.5194/nhess-22-869-2022, 2022
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Snow droughts, or below-average snowpack, can result from either dry conditions and/or rainfall instead of snowfall. Monitoring snow drought through time and across space is important to evaluate when snow drought onset occurred, its duration, spatial extent, and severity as well as what conditions created it or led to its termination. We present visualization techniques, including a web-based snow-drought-tracking tool, to evaluate snow droughts and assess their impacts in the western US.
Erika Médus, Emma D. Thomassen, Danijel Belušić, Petter Lind, Peter Berg, Jens H. Christensen, Ole B. Christensen, Andreas Dobler, Erik Kjellström, Jonas Olsson, and Wei Yang
Nat. Hazards Earth Syst. Sci., 22, 693–711, https://doi.org/10.5194/nhess-22-693-2022, https://doi.org/10.5194/nhess-22-693-2022, 2022
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We evaluate the skill of a regional climate model, HARMONIE-Climate, to capture the present-day characteristics of heavy precipitation in the Nordic region and investigate the added value provided by a convection-permitting model version. The higher model resolution improves the representation of hourly heavy- and extreme-precipitation events and their diurnal cycle. The results indicate the benefits of convection-permitting models for constructing climate change projections over the region.
Florian Ehmele, Lisa-Ann Kautz, Hendrik Feldmann, Yi He, Martin Kadlec, Fanni D. Kelemen, Hilke S. Lentink, Patrick Ludwig, Desmond Manful, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 22, 677–692, https://doi.org/10.5194/nhess-22-677-2022, https://doi.org/10.5194/nhess-22-677-2022, 2022
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For various applications, it is crucial to have profound knowledge of the frequency, severity, and risk of extreme flood events. Such events are characterized by very long return periods which observations can not cover. We use a large ensemble of regional climate model simulations as input for a hydrological model. Precipitation data were post-processed to reduce systematic errors. The representation of precipitation and discharge is improved, and estimates of long return periods become robust.
Anja T. Rädler
Nat. Hazards Earth Syst. Sci., 22, 659–664, https://doi.org/10.5194/nhess-22-659-2022, https://doi.org/10.5194/nhess-22-659-2022, 2022
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Natural disasters are causing high losses worldwide. To adequately deal with this loss potential, a reinsurer has to quantitatively assess the individual risks of natural catastrophes and how these risks are changing over time with respect to climate change. From a reinsurance perspective, the most pressing scientific challenges related to natural hazards are addressed, and broad changes are suggested that should be achieved by the scientific community to address these hazards in the future.
Jussi Leinonen, Ulrich Hamann, Urs Germann, and John R. Mecikalski
Nat. Hazards Earth Syst. Sci., 22, 577–597, https://doi.org/10.5194/nhess-22-577-2022, https://doi.org/10.5194/nhess-22-577-2022, 2022
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We evaluate the usefulness of different data sources and variables to the short-term prediction (
nowcasting) of severe thunderstorms using machine learning. Machine-learning models are trained with data from weather radars, satellite images, lightning detection and weather forecasts and with terrain elevation data. We analyze the benefits provided by each of the data sources to predicting hazards (heavy precipitation, lightning and hail) caused by the thunderstorms.
Rubina Ansari and Giovanna Grossi
Nat. Hazards Earth Syst. Sci., 22, 287–302, https://doi.org/10.5194/nhess-22-287-2022, https://doi.org/10.5194/nhess-22-287-2022, 2022
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The current research investigated spatio-temporal evolution of wet–dry events collectively, their characteristics, and their transition (wet to dry and dry to wet) across the Upper Jhelum Basin using the standardized precipitation evapotranspiration (SPEI) at a monthly timescale. The results provide significant knowledge to identify and locate most vulnerable geographical hotspots of extreme events, providing the basis for more effective risk reduction and climate change adaptation plans.
Dominik Jackisch, Bi Xuan Yeo, Adam D. Switzer, Shaoneng He, Danica Linda M. Cantarero, Fernando P. Siringan, and Nathalie F. Goodkin
Nat. Hazards Earth Syst. Sci., 22, 213–226, https://doi.org/10.5194/nhess-22-213-2022, https://doi.org/10.5194/nhess-22-213-2022, 2022
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The Philippines is a nation very vulnerable to devastating typhoons. We investigate if stable isotopes of precipitation can be used to detect typhoon activities in the Philippines based on daily isotope measurements from Metropolitan Manila. We find that strong typhoons such as Rammasun, which occurred in July 2014, leave detectable isotopic signals in precipitation. Besides other factors, the distance of the typhoon to the sampling site plays a key role in influencing the signal.
Chung-Chieh Wang, Pi-Yu Chuang, Chih-Sheng Chang, Kazuhisa Tsuboki, Shin-Yi Huang, and Guo-Chen Leu
Nat. Hazards Earth Syst. Sci., 22, 23–40, https://doi.org/10.5194/nhess-22-23-2022, https://doi.org/10.5194/nhess-22-23-2022, 2022
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This study indicated that the Cloud-Resolving Storm Simulator (CReSS) model significantly improved heavy-rainfall quantitative precipitation forecasts in the Taiwan Mei-yu season. At high resolution, the model has higher threat scores and is more skillful in predicting larger rainfall events compared to smaller ones. And the strength of the model mainly lies in the topographic rainfall rather than less predictable and migratory events due to nonlinearity.
Matthieu Plu, Guillaume Bigeard, Bojan Sič, Emanuele Emili, Luca Bugliaro, Laaziz El Amraoui, Jonathan Guth, Beatrice Josse, Lucia Mona, and Dennis Piontek
Nat. Hazards Earth Syst. Sci., 21, 3731–3747, https://doi.org/10.5194/nhess-21-3731-2021, https://doi.org/10.5194/nhess-21-3731-2021, 2021
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Volcanic eruptions that spread out ash over large areas, like Eyjafjallajökull in 2010, may have huge economic consequences due to flight cancellations. In this article, we demonstrate the benefits of source term improvement and of data assimilation for quantifying volcanic ash concentrations. The work, which was supported by the EUNADICS-AV project, is the first one, to our knowledge, that demonstrates the benefit of the assimilation of ground-based lidar data over Europe during an eruption.
Elizaveta Felsche and Ralf Ludwig
Nat. Hazards Earth Syst. Sci., 21, 3679–3691, https://doi.org/10.5194/nhess-21-3679-2021, https://doi.org/10.5194/nhess-21-3679-2021, 2021
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This study applies artificial neural networks to predict drought occurrence in Munich and Lisbon, with a lead time of 1 month. An analysis of the variables that have the highest impact on the prediction is performed. The study shows that the North Atlantic Oscillation index and air pressure 1 month before the event have the highest importance for the prediction. Moreover, it shows that seasonality strongly influences the goodness of prediction for the Lisbon domain.
Benjamin Poschlod
Nat. Hazards Earth Syst. Sci., 21, 3573–3598, https://doi.org/10.5194/nhess-21-3573-2021, https://doi.org/10.5194/nhess-21-3573-2021, 2021
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Three regional climate models (RCMs) are used to simulate extreme daily rainfall in Bavaria statistically occurring once every 10 or even 100 years. Results are validated with observations. The RCMs can reproduce spatial patterns and intensities, and setups with higher spatial resolutions show better results. These findings suggest that RCMs are suitable for assessing the probability of the occurrence of such rare rainfall events.
Heinz Jürgen Punge, Kristopher M. Bedka, Michael Kunz, Sarah D. Bang, and Kyle F. Itterly
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-342, https://doi.org/10.5194/nhess-2021-342, 2021
Revised manuscript accepted for NHESS
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We have estimated the probability of hail events in South Africa using a combination of satellite observations, reanalysis, and insurance loss data. It is found that hail concentrate mainly in the southeast. Multivariate stochastic modeling of event properties, such as multiple events on a day or track dimensions, yields an event catalog for 25 000 years. This can be used to estimate hail risk for return periods of 200 years, required for insurance companies.
Matthieu Plu, Barbara Scherllin-Pirscher, Delia Arnold Arias, Rocio Baro, Guillaume Bigeard, Luca Bugliaro, Ana Carvalho, Laaziz El Amraoui, Kurt Eschbacher, Marcus Hirtl, Christian Maurer, Marie D. Mulder, Dennis Piontek, Lennart Robertson, Carl-Herbert Rokitansky, Fritz Zobl, and Raimund Zopp
Nat. Hazards Earth Syst. Sci., 21, 2973–2992, https://doi.org/10.5194/nhess-21-2973-2021, https://doi.org/10.5194/nhess-21-2973-2021, 2021
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Past volcanic eruptions that spread out ash over large areas, like Eyjafjallajökull in 2010, forced the cancellation of thousands of flights and had huge economic consequences.
In this article, an international team in the H2020 EU-funded EUNADICS-AV project has designed a probabilistic model approach to quantify ash concentrations. This approach is evaluated against measurements, and its potential use to mitigate the impact of future large-scale eruptions is discussed.
Alexandre Tuel and Olivia Martius
Nat. Hazards Earth Syst. Sci., 21, 2949–2972, https://doi.org/10.5194/nhess-21-2949-2021, https://doi.org/10.5194/nhess-21-2949-2021, 2021
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Extreme river discharge may be triggered by large accumulations of precipitation over short time periods, which can result from the successive occurrence of extreme-precipitation events. We find a distinct spatiotemporal pattern in the temporal clustering behavior of precipitation extremes over Switzerland, with clustering occurring on the northern side of the Alps in winter and on their southern side in fall. Clusters tend to be followed by extreme discharge, particularly in the southern Alps.
Patricia Tarín-Carrasco, Sofia Augusto, Laura Palacios-Peña, Nuno Ratola, and Pedro Jiménez-Guerrero
Nat. Hazards Earth Syst. Sci., 21, 2867–2880, https://doi.org/10.5194/nhess-21-2867-2021, https://doi.org/10.5194/nhess-21-2867-2021, 2021
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Uncontrolled wildfires have a substantial impact on the environment and local populations. Although most southern European countries have been impacted by wildfires in the last decades, Portugal has the highest percentage of burned area compared to its whole territory. Under this umbrella, associations between large fires, PM10, and all-cause and cause-specific mortality (circulatory and respiratory) have been explored using Poisson regression models for 2001–2016.
Vincenzo Mazzarella, Rossella Ferretti, Errico Picciotti, and Frank Silvio Marzano
Nat. Hazards Earth Syst. Sci., 21, 2849–2865, https://doi.org/10.5194/nhess-21-2849-2021, https://doi.org/10.5194/nhess-21-2849-2021, 2021
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Forecasting precipitation over the Mediterranean basin is still a challenge. In this context, data assimilation techniques play a key role in improving the initial conditions and consequently the timing and position of the precipitation forecast. For the first time, the ability of a cycling 4D-Var to reproduce a heavy rain event in central Italy, as well as to provide a comparison with the largely used cycling 3D-Var, is evaluated in this study.
Avaronthan Veettil Sreenath, Sukumarapillai Abhilash, and Pattathil Vijaykumar
Nat. Hazards Earth Syst. Sci., 21, 2597–2609, https://doi.org/10.5194/nhess-21-2597-2021, https://doi.org/10.5194/nhess-21-2597-2021, 2021
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Lightning is a multifaceted hazard with widespread negative consequences for the environment and society. We explore how El Niño–Southern Oscillation (ENSO) phases impact the lightning over India by modulating the deep convection and associated atmospheric thermodynamics. Results show that ENSO phases directly influence lightning during monsoon and postmonsoon seasons by pushing the mean position of subtropical westerlies southward.
Folmer Krikken, Flavio Lehner, Karsten Haustein, Igor Drobyshev, and Geert Jan van Oldenborgh
Nat. Hazards Earth Syst. Sci., 21, 2169–2179, https://doi.org/10.5194/nhess-21-2169-2021, https://doi.org/10.5194/nhess-21-2169-2021, 2021
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In this study, we analyse the role of climate change in the forest fires that raged through large parts of Sweden in the summer of 2018 from a meteorological perspective. This is done by studying observationally constrained data and multiple climate models. We find a small reduced probability of such events, based on reanalyses, but a small increased probability due to global warming up to now and a more robust increase in the risk for such events in the future, based on climate models.
Florian Pappenberger, Florence Rabier, and Fabio Venuti
Nat. Hazards Earth Syst. Sci., 21, 2163–2167, https://doi.org/10.5194/nhess-21-2163-2021, https://doi.org/10.5194/nhess-21-2163-2021, 2021
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The European Centre for Medium-Range Weather Forecasts mission is to deliver high-quality global medium‐range (3–15 d ahead of time) weather forecasts and monitoring of the Earth system. We have published a new strategy, and in this paper we discuss what this means for forecasting and monitoring natural hazards.
Elissavet Galanaki, Konstantinos Lagouvardos, Vassiliki Kotroni, Theodore Giannaros, and Christos Giannaros
Nat. Hazards Earth Syst. Sci., 21, 1983–2000, https://doi.org/10.5194/nhess-21-1983-2021, https://doi.org/10.5194/nhess-21-1983-2021, 2021
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A two-way coupled hydrometeorological model (WRF-Hydro) is used for flood forecasting purposes in medium-catchment-size basins in Greece. The results showed the capability of WRF-Hydro to adequately simulate the observed discharge and the slight improvement in terms of quantitative precipitation forecasting compared to the WRF-only simulations.
Frederick W. Letson, Rebecca J. Barthelmie, Kevin I. Hodges, and Sara C. Pryor
Nat. Hazards Earth Syst. Sci., 21, 2001–2020, https://doi.org/10.5194/nhess-21-2001-2021, https://doi.org/10.5194/nhess-21-2001-2021, 2021
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Windstorms during the last 40 years in the US Northeast are identified and characterized using the spatial extent of extreme wind speeds at 100 m height from the ERA5 reanalysis. During all of the top 10 windstorms, wind speeds exceeding the local 99.9th percentile cover at least one-third of the land area in this high-population-density region. These 10 storms followed frequently observed cyclone tracks but have intensities 5–10 times the mean values for cyclones affecting this region.
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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