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.
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
Related authors
James Hickey, James Young, Michelle Spruce, Ravi Pandit, Hywel Williams, Rudy Arthur, Wendy Stovall, and Matthew Head
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-3, https://doi.org/10.5194/nhess-2024-3, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
Protecting lives and livelihoods during volcanic eruptions is the key challenge in volcanology. Analysing social media usage during volcanic crises can help 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 crises 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. Discuss., https://doi.org/10.5194/nhess-2024-3, https://doi.org/10.5194/nhess-2024-3, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
Protecting lives and livelihoods during volcanic eruptions is the key challenge in volcanology. Analysing social media usage during volcanic crises can help 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 crises 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
Short summary
Short summary
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
Short summary
Short summary
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.
Related subject area
Atmospheric, Meteorological and Climatological Hazards
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations
Probabilistic short-range forecasts of high-precipitation events: optimal decision thresholds and predictability limits
Surprise floods: the role of our imagination in preparing for disasters
Modelling crop hail damage footprints with single-polarization radar: the roles of spatial resolution, hail intensity, and cropland density
Insights into ground strike point properties in Europe through the EUCLID lightning location system
The role of citizen science in assessing the spatiotemporal pattern of rainfall events in urban areas: a case study in the city of Genoa, Italy
Precipitation extremes in Ukraine from 1979 to 2019: climatology, large-scale flow conditions, and moisture sources
Characterizing hail-prone environments using convection-permitting reanalysis and overshooting top detections over south-central Europe
Aircraft engine dust ingestion at global airports
Catchment-scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan
The risk of synoptic-scale Arctic cyclones to shipping
Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data
Climatic characteristics of the Jianghuai cyclone and its linkage with precipitation during the Meiyu period from 1961 to 2020
Application of the teaching–learning-based optimization algorithm to an analytical model of thunderstorm outflows to analyze the variability of the downburst kinematic and geometric parameters
Projections and uncertainties of winter windstorm damage in Europe in a changing climate
Improving seasonal predictions of German Bight storm activity
A satellite view of the exceptionally warm summer of 2022 over Europe
Demographic yearbooks as a source of weather-related fatalities: the Czech Republic, 1919–2022
FOREWARNS: development and multifaceted verification of enhanced regional-scale surface water flood forecasts
Assessment of wind–damage relations for Norway using 36 years of daily insurance data
Interannual variations in the seasonal cycle of extreme precipitation in Germany and the response to climate change
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
Climatology of large hail in Europe: characteristics of the European Severe Weather Database
Amplified potential for vegetation stress under climate-change-induced intensifying compound extreme events in the Greater Mediterranean Region
GTDI: a gaming integrated drought index implying hazard causing and bearing impacts changing
Assimilation of surface pressure observations from personal weather stations in AROME-France
An open-source radar-based hail damage model for buildings and cars
Linkages between atmospheric rivers and humid heat across the United States
Insurance loss model vs meteorological loss index – How comparable are their loss estimates for European windstorms?
Evaluating pySTEPS optical flow algorithms for convection nowcasting over the Maritime Continent using satellite data
Climate change impacts on regional fire weather in heterogeneous landscapes of central Europe
High-resolution projections of ambient heat for major European cities using different heat metrics
Heat wave characteristics: evaluation of regional climate model performances for Germany
Rain-on-snow responses to warmer Pyrenees: a sensitivity analysis using a physically based snow hydrological model
Spatial identification of regions at risk to multi-hazards at pan European level: an implemented methodological approach
Intense rains in Israel associated with the 'Train effect'
On the potential of using smartphone sensors for wildfire hazard estimation
Return levels of extreme European windstorms, their dependency on the North Atlantic Oscillation, and potential future risks
Wind as a natural hazard in Poland
Climatological occurrences of hail and tornadoes associated with mesoscale convective systems in the United States
Characteristics of cloud-to-ground lightning (CG) and differences between +CG and −CG strokes in China regarding the China National Lightning Detection Network
The climatology and nature of warm-season convective cells in cold-frontal environments over Germany
Forecasting large hail and lightning using additive logistic regression models and the ECMWF reforecasts
The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model
Shallow and deep learning of extreme rainfall events from convective atmospheres
Linking reported drought impacts with drought indices, water scarcity and aridity: the case of Kenya
Future heat extremes and impacts in a convection-permitting climate ensemble over Germany
Assessment of subseasonal-to-seasonal (S2S) ensemble extreme precipitation forecast skill over Europe
A long record of European windstorm losses and its comparison to standard climate indices
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, https://doi.org/10.5194/nhess-24-2939-2024, 2024
Short summary
Short summary
High-impact river floods are often caused by extreme precipitation. Flood protection relies on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties in the return values can be substantially reduced compared to observational estimates.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
Short summary
Short summary
Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024, https://doi.org/10.5194/nhess-24-2793-2024, 2024
Short summary
Short summary
Weather prediction uncertainties can be described as sets of possible scenarios – a technique called ensemble prediction. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024, https://doi.org/10.5194/nhess-24-2633-2024, 2024
Short summary
Short summary
What’s the worst that could happen? Recent floods are often claimed to be beyond our imagination. Imagination is the picturing of a situation in our mind and the emotions that we connect with this situation. But why is this important for disasters? This survey found that when we cannot imagine a devastating flood, we are not preparing in advance. Severe-weather forecasts and warnings need to advance in order to trigger our imagination of what might happen and enable us to start preparing.
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024, https://doi.org/10.5194/nhess-24-2541-2024, 2024
Short summary
Short summary
The study presents an open-source model to determine the occurrence of hail damage to field crops and grapevines after hailstorms in Switzerland based on radar, agricultural land use data, and insurance damage reports. The model performs best at 8 km resolution for field crops and 1 km for grapevine and in the main production areas. Highlighting performance trade-offs and the relevance of user needs, the study is a first step towards the assessment of risk and damage for crops in Switzerland.
Dieter Roel Poelman, Hannes Kohlmann, and Wolfgang Schulz
Nat. Hazards Earth Syst. Sci., 24, 2511–2522, https://doi.org/10.5194/nhess-24-2511-2024, https://doi.org/10.5194/nhess-24-2511-2024, 2024
Short summary
Short summary
EUCLID's lightning data unveil distinctive ground strike point (GSP) patterns in Europe. Over seas, GSPs per flash surpass inland, reaching a minimum in the Alps. Mountainous areas like the Alps and Pyrenees have the closest GSP separation, highlighting terrain elevation's impact. The daily peak current correlates with average GSPs per flash. These findings could significantly influence lightning protection measures, urging a focus on GSP density rather than flash density for risk assessment.
Nicola Loglisci, Giorgio Boni, Arianna Cauteruccio, Francesco Faccini, Massimo Milelli, Guido Paliaga, and Antonio Parodi
Nat. Hazards Earth Syst. Sci., 24, 2495–2510, https://doi.org/10.5194/nhess-24-2495-2024, https://doi.org/10.5194/nhess-24-2495-2024, 2024
Short summary
Short summary
We analyse the meteo-hydrological features of the 27 and 28 August 2023 event that occurred in Genoa. Rainfall observations were made using rain gauge networks based on either official networks or citizen science networks. The merged analysis stresses the spatial variability in the precipitation, which cannot be captured by the current spatial density of authoritative stations. Results show that at minimal distances the variations in cumulated rainfall over a sub-hourly duration are significant.
Ellina Agayar, Franziska Aemisegger, Moshe Armon, Alexander Scherrmann, and Heini Wernli
Nat. Hazards Earth Syst. Sci., 24, 2441–2459, https://doi.org/10.5194/nhess-24-2441-2024, https://doi.org/10.5194/nhess-24-2441-2024, 2024
Short summary
Short summary
This study presents the results of a climatological investigation of extreme precipitation events (EPEs) in Ukraine for the period 1979–2019. During all seasons EPEs are associated with pronounced upper-level potential vorticity (PV) anomalies. In addition, we find distinct seasonal and regional differences in moisture sources. Several extreme precipitation cases demonstrate the importance of these processes, complemented by a detailed synoptic analysis.
Antonio Giordani, Michael Kunz, Kristopher M. Bedka, Heinz Jürgen Punge, Tiziana Paccagnella, Valentina Pavan, Ines M. L. Cerenzia, and Silvana Di Sabatino
Nat. Hazards Earth Syst. Sci., 24, 2331–2357, https://doi.org/10.5194/nhess-24-2331-2024, https://doi.org/10.5194/nhess-24-2331-2024, 2024
Short summary
Short summary
To improve the challenging representation of hazardous hailstorms, a proxy for hail frequency based on satellite detections, convective parameters from high-resolution reanalysis, and crowd-sourced reports is tested and presented. Hail likelihood peaks in mid-summer at 15:00 UTC over northern Italy and shows improved agreement with observations compared to previous estimates. By separating ambient signatures based on hail severity, enhanced appropriateness for large-hail occurrence is found.
Claire L. Ryder, Clément Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
Nat. Hazards Earth Syst. Sci., 24, 2263–2284, https://doi.org/10.5194/nhess-24-2263-2024, https://doi.org/10.5194/nhess-24-2263-2024, 2024
Short summary
Short summary
Desert dust poses a hazard to aircraft via degradation of engine components. This has financial implications for the aviation industry and results in increased fuel burn with climate impacts. Here we quantify dust ingestion by aircraft engines at airports worldwide. We find Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. Dust ingestion can be reduced by changing take-off times and the altitude of holding patterns.
Khalil Ur Rahman, Songhao Shang, Khaled Saeed Balkhair, Hamza Farooq Gabriel, Khan Zaib Jadoon, and Kifayat Zaman
Nat. Hazards Earth Syst. Sci., 24, 2191–2214, https://doi.org/10.5194/nhess-24-2191-2024, https://doi.org/10.5194/nhess-24-2191-2024, 2024
Short summary
Short summary
This paper assesses the impact of drought (meteorological drought) on the hydrological alterations in major rivers of the Indus Basin. Threshold regression and range of variability analysis are used to determine the drought severity and times where drought has caused low flows and extreme low flows (identified using indicators of hydrological alterations). Moreover, this study also examines the degree of alterations in river flows due to drought using the hydrological alteration factor.
Alexander Frank Vessey, Kevin I. Hodges, Len C. Shaffrey, and Jonathan J. Day
Nat. Hazards Earth Syst. Sci., 24, 2115–2132, https://doi.org/10.5194/nhess-24-2115-2024, https://doi.org/10.5194/nhess-24-2115-2024, 2024
Short summary
Short summary
The risk posed to ships by Arctic cyclones has seldom been quantified due to the lack of publicly available historical Arctic ship track data. This study investigates historical Arctic ship tracks, cyclone tracks, and shipping incident reports to determine the number of shipping incidents caused by the passage of Arctic cyclones. Results suggest that Arctic cyclones have not been hazardous to ships and that ships are resilient to the rough sea conditions caused by Arctic cyclones.
Niklas Ebers, Kai Schröter, and Hannes Müller-Thomy
Nat. Hazards Earth Syst. Sci., 24, 2025–2043, https://doi.org/10.5194/nhess-24-2025-2024, https://doi.org/10.5194/nhess-24-2025-2024, 2024
Short summary
Short summary
Future changes in sub-daily rainfall extreme values are essential in various hydrological fields, but climate scenarios typically offer only daily resolution. One solution is rainfall generation. With a temperature-dependent rainfall generator climate scenario data were disaggregated to 5 min rainfall time series for 45 locations across Germany. The analysis of the future 5 min rainfall time series showed an increase in the rainfall extremes values for rainfall durations of 5 min and 1 h.
Ran Zhu and Lei Chen
Nat. Hazards Earth Syst. Sci., 24, 1937–1950, https://doi.org/10.5194/nhess-24-1937-2024, https://doi.org/10.5194/nhess-24-1937-2024, 2024
Short summary
Short summary
There is a positive correlation between the frequency of Jianghuai cyclone activity and precipitation during the Meiyu period. Its occurrence frequency has an obvious decadal variation, which corresponds well with the quasi-periodic and decadal variation in precipitation during the Meiyu period. This study provides a reference for the long-term and short-term forecasting of precipitation during the Meiyu period.
Andi Xhelaj and Massimiliano Burlando
Nat. Hazards Earth Syst. Sci., 24, 1657–1679, https://doi.org/10.5194/nhess-24-1657-2024, https://doi.org/10.5194/nhess-24-1657-2024, 2024
Short summary
Short summary
The study provides an in-depth analysis of a severe downburst event in Sânnicolau Mare, Romania, utilizing an analytical model and optimization algorithm. The goal is to explore a multitude of generating solutions and to identify potential alternatives to the optimal solution. Advanced data analysis techniques help to discern three main distinct storm scenarios. For this particular event, the best overall solution from the optimization algorithm shows promise in reconstructing the downburst.
Luca G. Severino, Chahan M. Kropf, Hilla Afargan-Gerstman, Christopher Fairless, Andries Jan de Vries, Daniela I. V. Domeisen, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 1555–1578, https://doi.org/10.5194/nhess-24-1555-2024, https://doi.org/10.5194/nhess-24-1555-2024, 2024
Short summary
Short summary
We combine climate projections from 30 climate models with a climate risk model to project winter windstorm damages in Europe under climate change. We study the uncertainty and sensitivity factors related to the modelling of hazard, exposure and vulnerability. We emphasize high uncertainties in the damage projections, with climate models primarily driving the uncertainty. We find climate change reshapes future European windstorm risk by altering damage locations and intensity.
Daniel Krieger, Sebastian Brune, Johanna Baehr, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 1539–1554, https://doi.org/10.5194/nhess-24-1539-2024, https://doi.org/10.5194/nhess-24-1539-2024, 2024
Short summary
Short summary
Previous studies found that climate models can predict storm activity in the German Bight well for averages of 5–10 years but struggle in predicting the next winter season. Here, we improve winter storm activity predictions by linking them to physical phenomena that occur before the winter. We guess the winter storm activity from these phenomena and discard model solutions that stray too far from the guess. The remaining solutions then show much higher prediction skill for storm activity.
João P. A. Martins, Sara Caetano, Carlos Pereira, Emanuel Dutra, and Rita M. Cardoso
Nat. Hazards Earth Syst. Sci., 24, 1501–1520, https://doi.org/10.5194/nhess-24-1501-2024, https://doi.org/10.5194/nhess-24-1501-2024, 2024
Short summary
Short summary
Over Europe, 2022 was truly exceptional in terms of extreme heat conditions, both in terms of temperature anomalies and their temporal and spatial extent. The satellite all-sky land surface temperature (LST) is used to provide a climatological context to extreme heat events. Where drought conditions prevail, LST anomalies are higher than 2 m air temperature anomalies. ERA5-Land does not represent this effect correctly due to a misrepresentation of vegetation anomalies.
Rudolf Brázdil, Kateřina Chromá, and Pavel Zahradníček
Nat. Hazards Earth Syst. Sci., 24, 1437–1457, https://doi.org/10.5194/nhess-24-1437-2024, https://doi.org/10.5194/nhess-24-1437-2024, 2024
Short summary
Short summary
The official mortality data in the Czech Republic in 1919–2022 are used to show long-term fluctuations in the number of fatalities caused by excessive natural cold and heat, lightning, natural disasters, and falls on ice/snow, as well as the sex and age of the deceased, based on certain meteorological, historical, and socioeconomic factors that strongly influence changes in the number and structure of such fatalities. Knowledge obtained is usable in risk management for the preservation of lives.
Ben Maybee, Cathryn E. Birch, Steven J. Böing, Thomas Willis, Linda Speight, Aurore N. Porson, Charlie Pilling, Kay L. Shelton, and Mark A. Trigg
Nat. Hazards Earth Syst. Sci., 24, 1415–1436, https://doi.org/10.5194/nhess-24-1415-2024, https://doi.org/10.5194/nhess-24-1415-2024, 2024
Short summary
Short summary
This paper presents the development and verification of FOREWARNS, a novel method for regional-scale forecasting of surface water flooding. We detail outcomes from a workshop held with UK forecast users, who indicated they valued the forecasts and would use them to complement national guidance. We use results of objective forecast tests against flood observations over northern England to show that this confidence is justified and that FOREWARNS meets the needs of UK flood responders.
Ashbin Jaison, Asgeir Sorteberg, Clio Michel, and Øyvind Breivik
Nat. Hazards Earth Syst. Sci., 24, 1341–1355, https://doi.org/10.5194/nhess-24-1341-2024, https://doi.org/10.5194/nhess-24-1341-2024, 2024
Short summary
Short summary
The present study uses daily insurance losses and wind speeds to fit storm damage functions at the municipality level of Norway. The results show that the damage functions accurately estimate losses associated with extreme damaging events and can reconstruct their spatial patterns. However, there is no single damage function that performs better than another. A newly devised damage–no-damage classifier shows some skill in predicting extreme damaging events.
Madlen Peter, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 24, 1261–1285, https://doi.org/10.5194/nhess-24-1261-2024, https://doi.org/10.5194/nhess-24-1261-2024, 2024
Short summary
Short summary
The paper introduces a statistical modeling approach describing daily extreme precipitation in Germany more accurately by including changes within the year and between the years simultaneously. The changing seasonality over years is regionally divergent and mainly weak. However, some regions stand out with a more pronounced linear rise of summer intensities, indicating a possible climate change signal. Improved modeling of extreme precipitation is beneficial for risk assessment and adaptation.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
EGUsphere, https://doi.org/10.5194/egusphere-2024-322, https://doi.org/10.5194/egusphere-2024-322, 2024
Short summary
Short summary
A computer model that simulates the climate of south-eastern 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.
Faye Hulton and David M. Schultz
Nat. Hazards Earth Syst. Sci., 24, 1079–1098, https://doi.org/10.5194/nhess-24-1079-2024, https://doi.org/10.5194/nhess-24-1079-2024, 2024
Short summary
Short summary
Large hail devastates crops and property and can injure and kill people and livestock. Hail reports are collected by individual countries, so understanding where and when large hail occurs across Europe is an incomplete undertaking. We use the European Severe Weather Database to evaluate the quality of reports by year and by country since 2000. Despite its short record, the dataset appears to represent aspects of European large-hail climatology reliably.
Patrick Olschewski, Mame Diarra Bousso Dieng, Hassane Moutahir, Brian Böker, Edwin Haas, Harald Kunstmann, and Patrick Laux
Nat. Hazards Earth Syst. Sci., 24, 1099–1134, https://doi.org/10.5194/nhess-24-1099-2024, https://doi.org/10.5194/nhess-24-1099-2024, 2024
Short summary
Short summary
We applied a multivariate and dependency-preserving bias correction method to climate model output for the Greater Mediterranean Region and investigated potential changes in false-spring events (FSEs) and heat–drought compound events (HDCEs). Results project an increase in the frequency of FSEs in middle and late spring as well as increases in frequency, intensity, and duration for HDCEs. This will potentially aggravate the risk of crop loss and failure and negatively impact food security.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-45, https://doi.org/10.5194/nhess-2024-45, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
To effectively track and identify droughts, we developed a novel integrated drought index that combines the effects of precipitation, temperature, and soil moisture on drought. After comparison and verification, the integrated drought index shows superior performance to a single meteorological drought index or agricultural drought index in drought identification.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 24, 907–927, https://doi.org/10.5194/nhess-24-907-2024, https://doi.org/10.5194/nhess-24-907-2024, 2024
Short summary
Short summary
Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. The incorporation of new observations from personal weather stations into the French limited-area model is evaluated. It leads to a significant improvement in the modelling of the surface pressure field up to 9 h ahead. Their incorporation improves the location and intensity of the heavy precipitation event that occurred in the South of France in September 2021.
Timo Schmid, Raphael Portmann, Leonie Villiger, Katharina Schröer, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 847–872, https://doi.org/10.5194/nhess-24-847-2024, https://doi.org/10.5194/nhess-24-847-2024, 2024
Short summary
Short summary
Hailstorms cause severe damage to buildings and cars, which motivates a detailed risk assessment. Here, we present a new open-source hail damage model based on radar data in Switzerland. The model successfully estimates the correct order of magnitude of car and building damages for most large hail events over 20 years. However, large uncertainty remains in the geographical distribution of modelled damages, which can be improved for individual events by using crowdsourced hail reports.
Colin Raymond, Anamika Shreevastava, Emily Slinskey, and Duane Waliser
Nat. Hazards Earth Syst. Sci., 24, 791–801, https://doi.org/10.5194/nhess-24-791-2024, https://doi.org/10.5194/nhess-24-791-2024, 2024
Short summary
Short summary
How can we systematically understand what causes high levels of atmospheric humidity and thus heat stress? Here we argue that atmospheric rivers can be a useful tool, based on our finding that in several US regions, atmospheric rivers and humid heat occur close together in space and time. Most typically, an atmospheric river transports moisture which heightens heat stress, with precipitation following a day later. These effects tend to be larger for stronger and more extensive systems.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-16, https://doi.org/10.5194/nhess-2024-16, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological Loss Index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
Joseph Smith, Cathryn Birch, John Marsham, Simon Peatman, Massimo Bollasina, and George Pankiewicz
Nat. Hazards Earth Syst. Sci., 24, 567–582, https://doi.org/10.5194/nhess-24-567-2024, https://doi.org/10.5194/nhess-24-567-2024, 2024
Short summary
Short summary
Nowcasting uses observations to make predictions of the atmosphere on short timescales and is particularly applicable to the Maritime Continent, where storms rapidly develop and cause natural disasters. This paper evaluates probabilistic and deterministic satellite nowcasting algorithms over the Maritime Continent. We show that the probabilistic approach is most skilful at small scales (~ 60 km), whereas the deterministic approach is most skilful at larger scales (~ 200 km).
Julia Miller, Andrea Böhnisch, Ralf Ludwig, and Manuela I. Brunner
Nat. Hazards Earth Syst. Sci., 24, 411–428, https://doi.org/10.5194/nhess-24-411-2024, https://doi.org/10.5194/nhess-24-411-2024, 2024
Short summary
Short summary
We assess the impacts of climate change on fire danger for 1980–2099 in different landscapes of central Europe, using the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by 2099. High fire danger (FWI > 21.3) becomes the mean condition by 2099 under an RCP8.5 scenario. This study highlights the potential for severe fire events in central Europe from a meteorological perspective.
Clemens Schwingshackl, Anne Sophie Daloz, Carley Iles, Kristin Aunan, and Jana Sillmann
Nat. Hazards Earth Syst. Sci., 24, 331–354, https://doi.org/10.5194/nhess-24-331-2024, https://doi.org/10.5194/nhess-24-331-2024, 2024
Short summary
Short summary
Ambient heat in European cities will substantially increase under global warming, as projected by three heat metrics calculated from high-resolution climate model simulations. While the heat metrics consistently project high levels of ambient heat for several cities, in other cities the projected heat levels vary considerably across the three heat metrics. Using complementary heat metrics for projections of ambient heat is thus important for assessments of future risks from heat stress.
Dragan Petrovic, Benjamin Fersch, and Harald Kunstmann
Nat. Hazards Earth Syst. Sci., 24, 265–289, https://doi.org/10.5194/nhess-24-265-2024, https://doi.org/10.5194/nhess-24-265-2024, 2024
Short summary
Short summary
The influence of model resolution and settings on the reproduction of heat waves in Germany between 1980–2009 is analyzed. Outputs from a high-resolution model with settings tailored to the target region are compared to those from coarser-resolution models with more general settings. Neither the increased resolution nor the tailored model settings are found to add significant value to the heat wave simulation. The models exhibit a large spread, indicating that the choice of model can be crucial.
Josep Bonsoms, Juan I. López-Moreno, Esteban Alonso-González, César Deschamps-Berger, and Marc Oliva
Nat. Hazards Earth Syst. Sci., 24, 245–264, https://doi.org/10.5194/nhess-24-245-2024, https://doi.org/10.5194/nhess-24-245-2024, 2024
Short summary
Short summary
Climate warming is changing mountain snowpack patterns, leading in some cases to rain-on-snow (ROS) events. Here we analyzed near-present ROS and its sensitivity to climate warming across the Pyrenees. ROS increases during the coldest months of the year but decreases in the warmest months and areas under severe warming due to snow cover depletion. Faster snow ablation is anticipated in the coldest and northern slopes of the range. Relevant implications in mountain ecosystem are anticipated.
Tiberiu-Eugen Antofie, Stefano Luoni, Alois Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-220, https://doi.org/10.5194/nhess-2023-220, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
This is the first study that uses spatial patterns (clusters/hot-spots) and meta-analysis in order to identify the regions at European level at risk to multi-hazards. The findings point out the socio-economic dimension as determinant factor for the risk potential to multi-hazard. The outcome provides valuable input for the Disaster Risk Management policy support and will assist national authorities on the implementation of a multi-hazard approach in the National Risk Assessments preparation.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-215, https://doi.org/10.5194/nhess-2023-215, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
'Train effect' is related to convective cells that pass over the same place. Trains produce heavy rainfall, sometimes floods, and reported in N. America during spring and summer. In Israel, 17 trains were identified by radar images, associated with Cyprus Lows, sharing the following features: Found at the cold sector south of the low center, at the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km, last 1–3 hours and yield 35 mm rainfall, up to 60 mm.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-211, https://doi.org/10.5194/nhess-2023-211, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
We have used the temperature and relative humidity sensors in smartphones to estimate the Vapor Pressure Deficit (VPD), and important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal show the potential for using smartphone data to both compliment the regular weather station network, while also providing high spatial resolution of the VPD index.
Matthew D. K. Priestley, David B. Stephenson, Adam A. Scaife, Daniel Bannister, Christopher J. T. Allen, and David Wilkie
Nat. Hazards Earth Syst. Sci., 23, 3845–3861, https://doi.org/10.5194/nhess-23-3845-2023, https://doi.org/10.5194/nhess-23-3845-2023, 2023
Short summary
Short summary
This research presents a model for estimating extreme gusts associated with European windstorms. Using observed storm footprints we are able to calculate the return level of events at the 200-year return period. The largest gusts are found across NW Europe, and these are larger when the North Atlantic Oscillation is positive. Using theoretical future climate states we find that return levels are likely to increase across NW Europe to levels that are unprecedented compared to historical storms.
Tadeusz Chmielewski and Piotr A. Bońkowski
Nat. Hazards Earth Syst. Sci., 23, 3839–3844, https://doi.org/10.5194/nhess-23-3839-2023, https://doi.org/10.5194/nhess-23-3839-2023, 2023
Short summary
Short summary
The paper deals with wind speeds of extreme wind events in Poland and the descriptions of their effects. Two recent estimations developed by the Institute of Meteorology and Water Management in Warsaw and by Halina Lorenc are presented and briefly described. The 37 annual maximum gusts of wind speeds measured between 1971 and 2007 are analysed. Based on the measured and estimated wind speeds, the authors suggest new estimations for extreme winds that may occur in Poland.
Jingyu Wang, Jiwen Fan, and Zhe Feng
Nat. Hazards Earth Syst. Sci., 23, 3823–3838, https://doi.org/10.5194/nhess-23-3823-2023, https://doi.org/10.5194/nhess-23-3823-2023, 2023
Short summary
Short summary
Hail and tornadoes are devastating hazards responsible for significant property damage and economic losses in the United States. Quantifying the connection between hazard events and mesoscale convective systems (MCSs) is of great significance for improving predictability, as well as for better understanding the influence of the climate-scale perturbations. A 14-year statistical dataset of MCS-related hazard production is presented.
Ruijiao Jiang, Guoping Zhang, Shudong Wang, Bing Xue, Zhengshuai Xie, Tingzhao Yu, Kuoyin Wang, Jin Ding, and Xiaoxiang Zhu
Nat. Hazards Earth Syst. Sci., 23, 3747–3759, https://doi.org/10.5194/nhess-23-3747-2023, https://doi.org/10.5194/nhess-23-3747-2023, 2023
Short summary
Short summary
Lightning activity in China is analyzed. Low latitudes, undulating terrain, seaside, and humid surfaces are beneficial for lightning occurrence. Summer of the year or afternoon of the day is the high period. Large cloud-to-ground lightning frequency always corresponds to a small ratio and weak intensity of positive cloud-to-ground lightning on either a temporal or spatial scale. Interestingly, the discharge intensity difference between the two types of lightning shrinks on the Tibetan Plateau.
George Pacey, Stephan Pfahl, Lisa Schielicke, and Kathrin Wapler
Nat. Hazards Earth Syst. Sci., 23, 3703–3721, https://doi.org/10.5194/nhess-23-3703-2023, https://doi.org/10.5194/nhess-23-3703-2023, 2023
Short summary
Short summary
Cold fronts are often associated with areas of intense precipitation (cells) and sometimes with hazards such as flooding, hail and lightning. We find that cold-frontal cell days are associated with higher cell frequency and cells are typically more intense. We also show both spatially and temporally where cells are most frequent depending on their cell-front distance. These results are an important step towards a deeper understanding of cold-frontal storm climatology and improved forecasting.
Francesco Battaglioli, Pieter Groenemeijer, Ivan Tsonevsky, and Tomàš Púčik
Nat. Hazards Earth Syst. Sci., 23, 3651–3669, https://doi.org/10.5194/nhess-23-3651-2023, https://doi.org/10.5194/nhess-23-3651-2023, 2023
Short summary
Short summary
Probabilistic models for lightning and large hail were developed across Europe using lightning observations and hail reports. These models accurately predict the occurrence of lightning and large hail several days in advance. In addition, the hail model was shown to perform significantly better than the state-of-the-art forecasting methods. These results suggest that the models developed in this study may help improve forecasting of convective hazards and eventually limit the associated risks.
Rosa Claudia Torcasio, Alessandra Mascitelli, Eugenio Realini, Stefano Barindelli, Giulio Tagliaferro, Silvia Puca, Stefano Dietrich, and Stefano Federico
Nat. Hazards Earth Syst. Sci., 23, 3319–3336, https://doi.org/10.5194/nhess-23-3319-2023, https://doi.org/10.5194/nhess-23-3319-2023, 2023
Short summary
Short summary
This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.
Gerd Bürger and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 3065–3077, https://doi.org/10.5194/nhess-23-3065-2023, https://doi.org/10.5194/nhess-23-3065-2023, 2023
Short summary
Short summary
Our subject is a new catalogue of radar-based heavy rainfall events (CatRaRE) over Germany and how it relates to the concurrent atmospheric circulation. We classify reanalyzed daily atmospheric fields of convective indices according to CatRaRE, using conventional statistical and more recent machine learning algorithms, and apply them to present and future atmospheres. Increasing trends are projected for CatRaRE-type probabilities, from reanalyzed as well as from simulated atmospheric fields.
Marleen R. Lam, Alessia Matanó, Anne F. Van Loon, Rhoda A. Odongo, Aklilu D. Teklesadik, Charles N. Wamucii, Marc J. C. van den Homberg, Shamton Waruru, and Adriaan J. Teuling
Nat. Hazards Earth Syst. Sci., 23, 2915–2936, https://doi.org/10.5194/nhess-23-2915-2023, https://doi.org/10.5194/nhess-23-2915-2023, 2023
Short summary
Short summary
There is still no full understanding of the relation between drought impacts and drought indices in the Horn of Africa where water scarcity and arid regions are also present. This study assesses their relation in Kenya. A random forest model reveals that each region, aggregated by aridity, has its own set of predictors for every impact category. Water scarcity was not found to be related to aridity. Understanding these relations contributes to the development of drought early warning systems.
Marie Hundhausen, Hendrik Feldmann, Natalie Laube, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 23, 2873–2893, https://doi.org/10.5194/nhess-23-2873-2023, https://doi.org/10.5194/nhess-23-2873-2023, 2023
Short summary
Short summary
Using a convection-permitting regional climate ensemble, the magnitude of heat waves (HWs) over Germany is projected to increase by 26 % (100 %) in a 2 °C (3 °C) warmer world. The increase is strongest in late summer, relatively homogeneous in space, and accompanied by increasing variance in HW length. Tailored parameters to climate adaptation to heat revealed dependency on major landscapes, and a nonlinear, exponential increase for parameters characterizing strong heat stress is expected.
Pauline Rivoire, Olivia Martius, Philippe Naveau, and Alexandre Tuel
Nat. Hazards Earth Syst. Sci., 23, 2857–2871, https://doi.org/10.5194/nhess-23-2857-2023, https://doi.org/10.5194/nhess-23-2857-2023, 2023
Short summary
Short summary
Heavy precipitation can lead to floods and landslides, resulting in widespread damage and significant casualties. Some of its impacts can be mitigated if reliable forecasts and warnings are available. In this article, we assess the capacity of the precipitation forecast provided by ECMWF to predict heavy precipitation events on a subseasonal-to-seasonal (S2S) timescale over Europe. We find that the forecast skill of such events is generally higher in winter than in summer.
Stephen Cusack
Nat. Hazards Earth Syst. Sci., 23, 2841–2856, https://doi.org/10.5194/nhess-23-2841-2023, https://doi.org/10.5194/nhess-23-2841-2023, 2023
Short summary
Short summary
The link from European windstorm research findings to insurance applications is strengthened by a new storm loss history spanning 1950 to 2022. It is based on ERA5 winds, together with long-term trends from observed gusts for improved validation. Correlations between losses and climate indices are around 0.4 for interannual variations, rising to 0.7 for decadal variations. A significant divergence between standard climate indices and storm losses over the past 20 years needs further research.
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...
Altmetrics
Final-revised paper
Preprint