Articles | Volume 22, issue 9
https://doi.org/10.5194/nhess-22-2943-2022
© Author(s) 2022. 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-22-2943-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Sep 2022
Research article |
| 06 Sep 2022
| 06 Sep 2022
A satellite lightning observation operator for storm-scale numerical weather prediction
Pauline Combarnous
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
LAERO, Université de Toulouse, UT3, CNRS, IRD, Toulouse, France
Felix Erdmann
Royal Meteorological Institute of Belgium, Brussels, Belgium
Olivier Caumont
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Météo-France, Direction des opérations pour la prévision, Toulouse, France
Éric Defer
LAERO, Université de Toulouse, UT3, CNRS, IRD, Toulouse, France
Maud Martet
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Related authors
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Pierre Brousseau, Valérie Vogt, Etienne Arbogast, Maud Martet, Guillaume Thomas, and Loïk Berre
EGUsphere, https://doi.org/10.5194/egusphere-2025-2642, https://doi.org/10.5194/egusphere-2025-2642, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Since October 2024, the Météo-France operational convective scale model AROME-France uses a three-dimensional ensemble-based variational data assimilation system. This allows observations to be spatialised in a flow-dependent way, leading to improved initial conditions. Numerous sensitivity studies allowed to configure this scheme in an operational context. Major positive impacts on the forecast quality have been demonstrated over a long period and on several severe meteorological situations.
Andrea Kolínská, Ivana Kolmašová, Eric Defer, Ondřej Santolík, and Stéphane Pédeboy
Atmos. Chem. Phys., 25, 1791–1803, https://doi.org/10.5194/acp-25-1791-2025, https://doi.org/10.5194/acp-25-1791-2025, 2025
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We contribute to understanding differences in lightning flashes of opposite polarity by explaining distinct in-cloud processes after return strokes. Using data from multiple sensors, including individual Lightning Mapping Array stations, we reveal that positive flashes sustain strong high-frequency radiation due to the recharging of their in-cloud leader; this is in contrast to negative flashes, for which this activity declines rapidly.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 25, 429–449, https://doi.org/10.5194/nhess-25-429-2025, https://doi.org/10.5194/nhess-25-429-2025, 2025
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The use of numerical weather prediction models enables the forecasting of hazardous weather situations. The incorporation of new temperature and relative humidity observations from personal weather stations into the French limited-area model is evaluated in this study. This leads to the improvement of the associated near-surface variables of the model during the first hours of the forecast. Examples are provided for a sea breeze case during a heatwave and a fog episode.
Vincent Forcadell, Clotilde Augros, Olivier Caumont, Kévin Dedieu, Maxandre Ouradou, Cloé David, Jordi Figueras i Ventura, Olivier Laurantin, and Hassan Al-Sakka
Atmos. Meas. Tech., 17, 6707–6734, https://doi.org/10.5194/amt-17-6707-2024, https://doi.org/10.5194/amt-17-6707-2024, 2024
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This study demonstrates the potential of enhancing severe-hail detection through the application of convolutional neural networks (CNNs) to dual-polarization radar data. It is shown that current methods can be calibrated to significantly enhance their performance for severe-hail detection. This study establishes the foundation for the solution of a more complex problem: the estimation of the maximum size of hailstones on the ground using deep learning applied to radar data.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 24, 907–927, https://doi.org/10.5194/nhess-24-907-2024, https://doi.org/10.5194/nhess-24-907-2024, 2024
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Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. The incorporation of new observations from personal weather stations into the French limited-area model is evaluated. It leads to a significant improvement in the modelling of the surface pressure field up to 9 h ahead. Their incorporation improves the location and intensity of the heavy precipitation event that occurred in the South of France in September 2021.
Felix Erdmann, Olivier Caumont, and Eric Defer
Nat. Hazards Earth Syst. Sci., 23, 2821–2840, https://doi.org/10.5194/nhess-23-2821-2023, https://doi.org/10.5194/nhess-23-2821-2023, 2023
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This work develops a novel lightning data assimilation (LDA) technique to make use of Meteosat Third Generation (MTG) Lightning Imager (LI) data in a regional, convection-permitting numerical weather prediction model. The approach combines statistical Bayesian and 3-dimensional variational methods. Our LDA can promote missing convection and suppress spurious convection in the initial state of the model, and it has similar skill to the operational radar data assimilation for rainfall forecasts.
Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger
Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, https://doi.org/10.5194/amt-15-5415-2022, 2022
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Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
Marc Mandement and Olivier Caumont
Weather Clim. Dynam., 2, 795–818, https://doi.org/10.5194/wcd-2-795-2021, https://doi.org/10.5194/wcd-2-795-2021, 2021
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On 14–15 October 2018, in the Aude department (France), a heavy-precipitation event produced up to about 300 mm of rain in 11 h. Simulations carried out show that the former Hurricane Leslie, while involved, was not the first supplier of moisture over the entire event. The location of the highest rainfall was primarily driven by the location of a quasi-stationary front and secondarily by the location of precipitation bands downwind of mountains bordering the Mediterranean Sea.
Alistair Bell, Pauline Martinet, Olivier Caumont, Benoît Vié, Julien Delanoë, Jean-Charles Dupont, and Mary Borderies
Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, https://doi.org/10.5194/amt-14-4929-2021, 2021
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This paper presents work towards making retrievals on the liquid water content in fog and low clouds. Future retrievals will rely on a radar simulator and high-resolution forecast. In this work, real observations are used to assess the errors associated with the simulator and forecast. A selection method to reduce errors associated with the forecast is proposed. It is concluded that the distribution of errors matches the requirements for future retrievals.
Olivier Caumont, Marc Mandement, François Bouttier, Judith Eeckman, Cindy Lebeaupin Brossier, Alexane Lovat, Olivier Nuissier, and Olivier Laurantin
Nat. Hazards Earth Syst. Sci., 21, 1135–1157, https://doi.org/10.5194/nhess-21-1135-2021, https://doi.org/10.5194/nhess-21-1135-2021, 2021
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This study focuses on the heavy precipitation event of 14 and 15 October 2018, which caused deadly flash floods in the Aude basin in south-western France.
The case is studied from a meteorological point of view using various operational numerical weather prediction systems, as well as a unique combination of observations from both standard and personal weather stations. The peculiarities of this case compared to other cases of Mediterranean heavy precipitation events are presented.
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 21, 463–480, https://doi.org/10.5194/nhess-21-463-2021, https://doi.org/10.5194/nhess-21-463-2021, 2021
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The assimilation impact of four observation data sets on forecasts is studied in a mesoscale weather model. The ground-based Global Navigation Satellite System (GNSS) zenithal total delay data set with information on humidity has the largest impact on analyses and forecasts, representing an evenly spread and frequent data set for each analysis time over the model domain. Moreover, the reprocessing of these data also improves the forecast quality, but this impact is not statistically significant.
Felix Erdmann, Eric Defer, Olivier Caumont, Richard J. Blakeslee, Stéphane Pédeboy, and Sylvain Coquillat
Atmos. Meas. Tech., 13, 853–875, https://doi.org/10.5194/amt-13-853-2020, https://doi.org/10.5194/amt-13-853-2020, 2020
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This article compares lightning observations from an optical sensor onboard the International Space Station to two ground-based networks using different radio frequencies. The location and timing of coincident flashes agree well for the three instruments. Differences exist for the detected number of flashes and the characteristics. Small flashes in particular are not always detected by all three instruments. About half of the flashes at altitudes below 10 km are not seen by the satellite sensor.
Marc Mandement and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 20, 299–322, https://doi.org/10.5194/nhess-20-299-2020, https://doi.org/10.5194/nhess-20-299-2020, 2020
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The number of connected personal weather stations has dramatically increased in the last years. These weather stations produce a high number of data that need a thorough quality control to unleash their potential. A novel quality-control algorithm now allows us to take full advantage of these data and observe thunderstorms with fine-scale details that cannot be caught by standard networks. These results pave the way for tremendous advances in both understanding and forecasting thunderstorms.
Sylvain Coquillat, Eric Defer, Pierre de Guibert, Dominique Lambert, Jean-Pierre Pinty, Véronique Pont, Serge Prieur, Ronald J. Thomas, Paul R. Krehbiel, and William Rison
Atmos. Meas. Tech., 12, 5765–5790, https://doi.org/10.5194/amt-12-5765-2019, https://doi.org/10.5194/amt-12-5765-2019, 2019
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Characteristics of SAETTA lightning imager installed in Corsica are presented, with original observations of lightning activity at regional and lightning scales. SAETTA monitors thunderstorms in a maritime and mountainous region, complex for weather forecasting and sensitive to global warming. A 3-year lightning climatology highlights frequent activity over a specific region due to relief. Uncommonly high discharge in stratiform thundercloud may support a recent model of charging processes.
Tony Le Bastard, Olivier Caumont, Nicolas Gaussiat, and Fatima Karbou
Atmos. Meas. Tech., 12, 5669–5684, https://doi.org/10.5194/amt-12-5669-2019, https://doi.org/10.5194/amt-12-5669-2019, 2019
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The estimation of surface rainfall from radars becomes less effective at long ranges or in mountainous regions where the radar beam is far from the ground. The method proposed in this paper investigates how vertical profiles simulated from high-resolution model can be used to predict the evolution of the precipitation below the radar beam. Our results show that this novel method leads to better results than the current operational methods that either use climatological or idealised profiles.
Stefano Federico, Rosa Claudia Torcasio, Elenio Avolio, Olivier Caumont, Mario Montopoli, Luca Baldini, Gianfranco Vulpiani, and Stefano Dietrich
Nat. Hazards Earth Syst. Sci., 19, 1839–1864, https://doi.org/10.5194/nhess-19-1839-2019, https://doi.org/10.5194/nhess-19-1839-2019, 2019
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This study shows the possibility to improve the weather forecast at the very short range (0–3 h) using lightning and/or radar reflectivity observations. We consider two challenging events that occurred over Italy, named Serrano and Livorno, characterized by moderate and exceptional rainfall, respectively.
The improvement given to the forecast by using the lightning and/or radar reflectivity observations is considerable. The best performance is obtained when using both data.
Nadia Fourrié, Mathieu Nuret, Pierre Brousseau, Olivier Caumont, Alexis Doerenbecher, Eric Wattrelot, Patrick Moll, Hervé Bénichou, Dominique Puech, Olivier Bock, Pierre Bosser, Patrick Chazette, Cyrille Flamant, Paolo Di Girolamo, Evelyne Richard, and Frédérique Saïd
Geosci. Model Dev., 12, 2657–2678, https://doi.org/10.5194/gmd-12-2657-2019, https://doi.org/10.5194/gmd-12-2657-2019, 2019
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The AROME-WMED (western Mediterranean) model is a dedicated version of the mesoscale Numerical Weather Prediction AROME-France model that ran in real time during the first special observation period of HyMeX. Two reanalyses were performed after the campaign. This paper depicts the main differences between the real-time version and the benefits brought by both HyMeX reanalyses. The second reanalysis is found to be closer to observations than the previous AROME-WMED analyses.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, Nadia Fourrié, and Pascal Marquet
Nat. Hazards Earth Syst. Sci., 19, 907–926, https://doi.org/10.5194/nhess-19-907-2019, https://doi.org/10.5194/nhess-19-907-2019, 2019
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The potential of W-band radar reflectivity to improve the quality of analyses and forecasts of heavy precipitation events in the Mediterranean area is investigated. The 1D + 3DVar assimilation method has been adapted to assimilate the W-band reflectivity in the Météo-France kilometre-scale NWP model AROME. The results suggest that the joint assimilation of W-band reflectivity and horizontal wind profiles lead to a slight improvement of moisture analyses and rainfall precipitation forecasts.
Mary Borderies, Olivier Caumont, Julien Delanoë, Véronique Ducrocq, and Nadia Fourrié
Nat. Hazards Earth Syst. Sci., 19, 821–835, https://doi.org/10.5194/nhess-19-821-2019, https://doi.org/10.5194/nhess-19-821-2019, 2019
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The study reports on the impact of the assimilation of wind data from airborne Doppler cloud-profiling radar in a kilometre-scale NWP model on predicting heavy precipitation events in the Mediterranean area. The positive impact of the assimilation of such data is particularly evidenced for a heavy precipitation event and results are slightly encouraging over a 45-day period. In addition, the impact of the length of the assimilation window in a 3h-3DVar assimilation system is investigated.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
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This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Francesco De Angelis, Domenico Cimini, Ulrich Löhnert, Olivier Caumont, Alexander Haefele, Bernhard Pospichal, Pauline Martinet, Francisco Navas-Guzmán, Henk Klein-Baltink, Jean-Charles Dupont, and James Hocking
Atmos. Meas. Tech., 10, 3947–3961, https://doi.org/10.5194/amt-10-3947-2017, https://doi.org/10.5194/amt-10-3947-2017, 2017
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Modern data assimilation systems require knowledge of the typical differences between observations and model background (O–B). This work illustrates a 1-year O–B analysis for ground-based microwave radiometer (MWR) observations in clear-sky conditions for a prototype network of six MWRs in Europe. Observations are MWR brightness temperatures (TB). Background profiles extracted from the output of a convective-scale model are used to simulate TB through the radiative transfer model RTTOV-gb.
Adrianus de Laat, Eric Defer, Julien Delanoë, Fabien Dezitter, Amanda Gounou, Alice Grandin, Anthony Guignard, Jan Fokke Meirink, Jean-Marc Moisselin, and Frédéric Parol
Atmos. Meas. Tech., 10, 1359–1371, https://doi.org/10.5194/amt-10-1359-2017, https://doi.org/10.5194/amt-10-1359-2017, 2017
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In-flight icing is an important aviation hazard which is still poorly understood, but consensus is that the presence of high ice water content is a necessary condition. For the European High Altitude Ice Crystals project a geostationary satellite remote-sensing mask has been developed for detection of atmospheric cloud environments where high ice water content is likely to occur. The mask performs satisfactory when compared against independent satellite ice water content measurements.
A. Hally, O. Caumont, L. Garrote, E. Richard, A. Weerts, F. Delogu, E. Fiori, N. Rebora, A. Parodi, A. Mihalović, M. Ivković, L. Dekić, W. van Verseveld, O. Nuissier, V. Ducrocq, D. D'Agostino, A. Galizia, E. Danovaro, and A. Clematis
Nat. Hazards Earth Syst. Sci., 15, 537–555, https://doi.org/10.5194/nhess-15-537-2015, https://doi.org/10.5194/nhess-15-537-2015, 2015
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Estimates of the risk posed by rare and catastrophic weather events are often derived from relatively short measurement records, which renders them highly uncertain. We investigate if (and by how much) this uncertainty can be reduced by making use of large datasets of simulated weather. More specifically, we focus on coastal flood hazard in the Netherlands and on the challenge of estimating the once in 10 million years coastal water level and wind stress as accurately as possible.
Felix Erdmann and Dieter Roel Poelman
Nat. Hazards Earth Syst. Sci., 25, 1751–1768, https://doi.org/10.5194/nhess-25-1751-2025, https://doi.org/10.5194/nhess-25-1751-2025, 2025
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This study provides detailed insight into the thunderstorm characteristics associated with abrupt changes in the lightning activity of a thunderstorm – lightning jumps (LJs) and lightning dives (LDs) – using geostationary satellite observations. Thunderstorms exhibiting one or multiple LJs or LDs feature characteristics similar to severe thunderstorms. Storms with multiple LJs contain strong convective updrafts and are prone to produce high rain rates, large hail, or tornadoes.
Jinfang Yin, Feng Li, Mingxin Li, Rudi Xia, Xinghua Bao, Jisong Sun, and Xudong Liang
Nat. Hazards Earth Syst. Sci., 25, 1719–1735, https://doi.org/10.5194/nhess-25-1719-2025, https://doi.org/10.5194/nhess-25-1719-2025, 2025
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A persistent severe rainfall event occurred over North China in July 2023, which was regarded as one of the most extreme episodes globally during that year. The extreme rainfall was significantly underestimated by forecasters at that time. Flooding from this event affected 1.3 million people, causing severe human casualties and economic losses. We examined the convective initiation and subsequent persistent heavy rainfall based on simulations with the Weather Research and Forecasting model.
Ilona Láng-Ritter, Terhi Kristiina Laurila, Antti Mäkelä, Hilppa Gregow, and Victoria Anne Sinclair
Nat. Hazards Earth Syst. Sci., 25, 1697–1717, https://doi.org/10.5194/nhess-25-1697-2025, https://doi.org/10.5194/nhess-25-1697-2025, 2025
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We present a classification method for extratropical cyclones and windstorms and show their impacts on Finland's electricity grid by analysing the 92 most damaging windstorms (2005–2018). The south-west- and north-west-arriving windstorms cause the most damage to the power grid. The most relevant parameters for damage are the wind gust speed and extent of wind gusts. Windstorms are more frequent and damaging in autumn and winter, but weaker wind speeds in summer also cause significant damage.
Joseph W. Gallear, Marcelo Valadares Galdos, Marcelo Zeri, and Andrew Hartley
Nat. Hazards Earth Syst. Sci., 25, 1521–1541, https://doi.org/10.5194/nhess-25-1521-2025, https://doi.org/10.5194/nhess-25-1521-2025, 2025
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In Brazil, drought is of national concern and can have major consequences for agriculture. Here, we determine how to develop forecasts for drought stress on vegetation health using machine learning. Results aim to inform future developments in operational drought monitoring at the National Centre for Monitoring and Early Warning of Natural Disasters (CEMADEN) in Brazil. This information is essential for disaster preparedness and planning of future actions to support areas affected by drought.
Thomas Schwitalla, Lisa Jach, Volker Wulfmeyer, and Kirsten Warrach-Sagi
Nat. Hazards Earth Syst. Sci., 25, 1405–1424, https://doi.org/10.5194/nhess-25-1405-2025, https://doi.org/10.5194/nhess-25-1405-2025, 2025
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During recent decades, Europe has experienced increasing periods of severe drought and heatwave. To provide an overview of how land-surface conditions shape land–atmosphere (LA) coupling, the interannual LA coupling strength variability for the summer seasons of 1991–2022 is investigated by means of ERA5 data. The results clearly reflect ongoing climate change by a shift in the coupling relationships towards reinforced heating and drying by the land surface.
Marcos Roberto Benso, Roberto Fray Silva, Gabriela Chiquito Gesualdo, Antonio Mauro Saraiva, Alexandre Cláudio Botazzo Delbem, Patricia Angélica Alves Marques, José Antonio Marengo, and Eduardo Mario Mendiondo
Nat. Hazards Earth Syst. Sci., 25, 1387–1404, https://doi.org/10.5194/nhess-25-1387-2025, https://doi.org/10.5194/nhess-25-1387-2025, 2025
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This study applies climate extreme indices to assess climate risks to food security. Using an explainable machine learning analysis, key climate indices affecting maize and soybean yields in Brazil were identified. Results reveal the temporal sensitivity of these indices and critical yield loss thresholds, informing policy and adaptation strategies.
Juan F. Dueñas, Edda Kunze, Huiying Li, and Matthias C. Rillig
Nat. Hazards Earth Syst. Sci., 25, 1377–1386, https://doi.org/10.5194/nhess-25-1377-2025, https://doi.org/10.5194/nhess-25-1377-2025, 2025
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We investigated the potential of adding mixtures composed of minimum dosages of several popular amendment types to soil. Our goal was to increase the resistance of agricultural soil to drought stress. We found that adding mixtures of three to five amendment types increased the capacity of soil to retain water, reduced soil erosion, and increased fungal abundance while buffering soil from drastic changes in pH. More research is encouraged to validate this approach.
Killian P. Brennan, Iris Thurnherr, Michael Sprenger, and Heini Wernli
EGUsphere, https://doi.org/10.5194/egusphere-2025-918, https://doi.org/10.5194/egusphere-2025-918, 2025
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Hailstorms can cause severe damage to homes, crops, and infrastructure. Using high-resolution climate simulations, we tracked thousands of hailstorms across Europe to study future changes. Large hail will become more frequent, hail-covered areas will expand, and extreme hail combined with heavy rain will double. These shifts could increase risks for communities and businesses, highlighting the need for better preparedness and adaptation.
Soledad Collazo, David Barriopedro, Ricardo García-Herrera, and Santiago Beguería
EGUsphere, https://doi.org/10.5194/egusphere-2025-792, https://doi.org/10.5194/egusphere-2025-792, 2025
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In the 2023/24 season, Rio de Janeiro experienced record-breaking heatwaves linked to climate change and El Niño. Our study shows global warming made these extreme temperatures at least 2°C hotter than in pre-industrial times. Heat-related deaths surged, with climate change contributing to 1 in 3 fatalities during the peak event. Without adaptation, future heatwaves will claim even more lives. This underscores the urgent need for policies to mitigate climate impacts from escalating heat threats.
François Collet, Margot Bador, Julien Boé, Laurent Dubus, and Bénédicte Jourdier
Nat. Hazards Earth Syst. Sci., 25, 843–856, https://doi.org/10.5194/nhess-25-843-2025, https://doi.org/10.5194/nhess-25-843-2025, 2025
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Our aim is to characterize the observed evolution of compound winter low-wind and cold events impacting the French electricity system. The frequency of compound events exhibits a decrease over the 1950–2022 period, which is likely due to a decrease in cold days. Large-scale atmospheric circulation is an important driver of compound event occurrence and has likely contributed to the decrease in cold days, while we cannot draw conclusions on its influence on the decrease in compound events.
Fabio Dioguardi, Giovanni Chiodini, and Antonio Costa
Nat. Hazards Earth Syst. Sci., 25, 657–674, https://doi.org/10.5194/nhess-25-657-2025, https://doi.org/10.5194/nhess-25-657-2025, 2025
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We present results of non-volcanic-gas (CO2) hazard assessment at the Mefite d’Ansanto area (Italy) where a cold-gas stream, which has already been lethal to humans and animals, forms in the valleys surrounding the emission zone. We took the uncertainty related to the gas emission and meteorological conditions into account. Results include maps of CO2 concentrations at defined probability levels and the probability of overcoming specified CO2 concentrations over specified time intervals.
Sonja Szymczak, Frederick Bott, Vigile Marie Fabella, and Katharina Fricke
Nat. Hazards Earth Syst. Sci., 25, 683–707, https://doi.org/10.5194/nhess-25-683-2025, https://doi.org/10.5194/nhess-25-683-2025, 2025
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We investigate the correlation between heavy-rainfall events and three associated natural hazards along the German rail network using GIS analyses and random-effects logistic models. The results show that 23 % of floods, 14 % of gravitational mass movements, and 2 % of tree fall events between 2017 and 2020 occurred after a heavy-rainfall event, and the probability of occurrence of flood and tree fall events significantly increased. This study contributes to more resilient rail transport.
Daniel G. Kingston, Liam Cooper, David A. Lavers, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 25, 675–682, https://doi.org/10.5194/nhess-25-675-2025, https://doi.org/10.5194/nhess-25-675-2025, 2025
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Extreme rainfall comprises a major hydrohazard for New Zealand and is commonly associated with atmospheric rivers – narrow plumes of very high atmospheric moisture transport. Here, we focus on improved forecasting of these events by testing a forecasting tool previously applied to similar situations in western Europe. However, our results for New Zealand suggest the performance of this forecasting tool may vary depending on geographical setting.
Tiago M. Ferreira, Ricardo M. Trigo, Tomás H. Gaspar, Joaquim G. Pinto, and Alexandre M. Ramos
Nat. Hazards Earth Syst. Sci., 25, 609–623, https://doi.org/10.5194/nhess-25-609-2025, https://doi.org/10.5194/nhess-25-609-2025, 2025
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We investigate the synoptic evolution associated with the occurrence of an atmospheric river that led to a 24 h record-breaking extreme precipitation event (120.3 mm) in Lisbon, Portugal, on 13 December 2022. The synoptic background allowed the formation, on 10 December, of an atmospheric river associated with a deep extratropical cyclone and with a high moisture content and an inflow of moisture, due to the warm conveyor belt, throughout its life cycle. The system made landfall on 12 December.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim G. Pinto, Markus Augenstein, Ting-Chen Chen, Hendrik Feldmann, Petra Friederichs, Daniel Gliksman, Laura Goulier, Karsten Haustein, Jens Heinke, Lisa Jach, Florian Knutzen, Stefan Kollet, Jürg Luterbacher, Niklas Luther, Susanna Mohr, Christoph Mudersbach, Christoph Müller, Efi Rousi, Felix Simon, Laura Suarez-Gutierrez, Svenja Szemkus, Sara M. Vallejo-Bernal, Odysseas Vlachopoulos, and Frederik Wolf
Nat. Hazards Earth Syst. Sci., 25, 541–564, https://doi.org/10.5194/nhess-25-541-2025, https://doi.org/10.5194/nhess-25-541-2025, 2025
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Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.
Lixin Song, Feifei Shen, Zhixin He, Dongmei Xu, Aiqing Shu, and Jiajun Chen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-203, https://doi.org/10.5194/nhess-2024-203, 2025
Revised manuscript accepted for NHESS
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When retrieving hydrometeors from reflectivity, there are two methods to allocate hydrometeor types: temperature-based and background hydrometer-dependent schemes. The temperature-based method divides hydrometeor proportions based on the background temperature, while the other scheme calculates average weights of each hydrometeor in various reflectivity intervals from background fields. The blending scheme adaptively combines these methods and is found to improve precipitation forecast accuracy.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 25, 429–449, https://doi.org/10.5194/nhess-25-429-2025, https://doi.org/10.5194/nhess-25-429-2025, 2025
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The use of numerical weather prediction models enables the forecasting of hazardous weather situations. The incorporation of new temperature and relative humidity observations from personal weather stations into the French limited-area model is evaluated in this study. This leads to the improvement of the associated near-surface variables of the model during the first hours of the forecast. Examples are provided for a sea breeze case during a heatwave and a fog episode.
Francisco Javier Acero, Manuel Antón, Alejandro Jesús Pérez Aparicio, Nieves Bravo-Paredes, Víctor Manuel Sánchez Carrasco, María Cruz Gallego, José Agustín García, Marcelino Núñez, Irene Tovar, Javier Vaquero-Martínez, and José Manuel Vaquero
Nat. Hazards Earth Syst. Sci., 25, 305–320, https://doi.org/10.5194/nhess-25-305-2025, https://doi.org/10.5194/nhess-25-305-2025, 2025
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The month of June 1925 was found to be exceptional in the southwest interior of the Iberian Peninsula due to the large number of thunderstorms and their significant impacts, with serious losses of human lives and material resources. We analyzed this event from different, complementary perspectives: reconstruction of the history of the events from newspapers, study of monthly meteorological variables of the longest series available, and the analysis of the meteorological synoptic situation.
Tiberiu-Eugen Antofie, Stefano Luoni, Aloïs Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci., 25, 287–304, https://doi.org/10.5194/nhess-25-287-2025, https://doi.org/10.5194/nhess-25-287-2025, 2025
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This is the first study that uses spatial patterns (clusters/hotspots) and meta-analysis in order to identify the regions at a European level at risk of multi-hazards. The findings point out the socioeconomic dimension as a determining factor in the potential risk of multi-hazards. The outcome provides valuable input for the disaster risk management policy support and will assist national authorities on the implementation of a multi-hazard approach in national risk assessment preparation.
Joona Cornér, Clément Bouvier, Benjamin Doiteau, Florian Pantillon, and Victoria A. Sinclair
Nat. Hazards Earth Syst. Sci., 25, 207–229, https://doi.org/10.5194/nhess-25-207-2025, https://doi.org/10.5194/nhess-25-207-2025, 2025
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Classification reduces the considerable variability between extratropical cyclones (ETCs) and thus simplifies studying their representation in climate models and changes in the future climate. In this paper we present an objective classification of ETCs using measures of ETC intensity. This is motivated by the aim of finding a set of ETC intensity measures which together comprehensively describe both the dynamical and impact-relevant nature of ETC intensity.
Cedric G. Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant
Nat. Hazards Earth Syst. Sci., 25, 147–168, https://doi.org/10.5194/nhess-25-147-2025, https://doi.org/10.5194/nhess-25-147-2025, 2025
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The present study addresses the predictability of heat waves at subseasonal timescales in West African cities over the period 2001–2020. Two models, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office models, were evaluated using two reanalyses: ERA5 and MERRA. The results suggest that at subseasonal timescales, the forecast models provide a better forecast than climatology, but the hit rate and false alarm rate are sub-optimal.
Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Mortimer M. Müller, Joni-Pekka Pietikäinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Sarah Veit, Julian Wendler, Elena Xoplaki, and Daniel Gliksman
Nat. Hazards Earth Syst. Sci., 25, 77–117, https://doi.org/10.5194/nhess-25-77-2025, https://doi.org/10.5194/nhess-25-77-2025, 2025
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Our research, involving 22 European scientists, investigated drought and heat impacts on forests in 2018–2022. Findings reveal that climate extremes are intensifying, with central Europe being most severely impacted. The southern region showed resilience due to historical drought exposure, while northern and Alpine areas experienced emerging or minimal impacts. The study highlights the need for region-specific strategies, improved data collection, and sustainable practices to safeguard forests.
Georgy Ayzel and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 25, 41–47, https://doi.org/10.5194/nhess-25-41-2025, https://doi.org/10.5194/nhess-25-41-2025, 2025
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Forecasting rainfall over the next hour is an essential feature of early warning systems. Deep learning (DL) has emerged as a powerful alternative to conventional nowcasting technologies, but it still struggles to adequately predict impact-relevant heavy rainfall. We think that DL could do much better if the training tasks were defined more specifically and that such specification presents an opportunity to better align the output of nowcasting models with actual user requirements.
Monica Ionita, Petru Vaideanu, Bogdan Antonescu, Catalin Roibu, Qiyun Ma, and Viorica Nagavciuc
Nat. Hazards Earth Syst. Sci., 24, 4683–4706, https://doi.org/10.5194/nhess-24-4683-2024, https://doi.org/10.5194/nhess-24-4683-2024, 2024
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Eastern Europe's heat wave history is explored from 1885 to 2023, with a focus on pre-1960 events. The study reveals two periods with more frequent and intense heat waves (HWs): 1920s–1960s and 1980s–present. The research highlights the importance of a long-term perspective, revealing that extreme heat events have occurred throughout the entire study period, and it emphasizes the combined influence of climate change and natural variations on increasing HW severity.
Tristan Shepherd, Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Nat. Hazards Earth Syst. Sci., 24, 4473–4505, https://doi.org/10.5194/nhess-24-4473-2024, https://doi.org/10.5194/nhess-24-4473-2024, 2024
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A historic derecho in the USA is presented. The 29 June 2012 derecho caused more than 20 deaths and millions of US dollars of damage. We use a regional climate model to understand how model fidelity changes under different initial conditions. We find changes drive different convective conditions, resulting in large variation in the simulated hazards. The variation using different reanalysis data shows that framing these results in the context of contemporary and future climate is a challenge.
Stephen Cusack and Tyler Cox
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-210, https://doi.org/10.5194/nhess-2024-210, 2024
Revised manuscript accepted for NHESS
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Warming seas have been driving greater hailstorm risk in Europe over the past few decades. Modern climate models indicate anthropogenic aerosols caused the observed cooling of seas from about 1900 to the 1970s, while the recent rapid warming is mostly explained by rising greenhouse gases. Current trends in anthropogenic forcing are likely to persist, suggesting seas will continue warming, and hailstorm risk over Europe will continue rising over the next couple of decades, at least.
Lena Wilhelm, Cornelia Schwierz, Katharina Schröer, Mateusz Taszarek, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 3869–3894, https://doi.org/10.5194/nhess-24-3869-2024, https://doi.org/10.5194/nhess-24-3869-2024, 2024
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In our study we used statistical models to reconstruct past hail days in Switzerland from 1959–2022. This new time series reveals a significant increase in hail day occurrences over the last 7 decades. We link this trend to increases in moisture and instability variables in the models. This time series can now be used to unravel the complexities of Swiss hail occurrence and to understand what drives its year-to-year variability.
Diego Saúl Carrió, Vincenzo Mazzarella, and Rossella Ferretti
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-177, https://doi.org/10.5194/nhess-2024-177, 2024
Revised manuscript accepted for NHESS
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Populated coastal regions in the Mediterranean are known to be severely affected by extreme weather events that are initiated over maritime regions. These weather events are known to pose a serious problem in terms of numerical predictability. Different Data Assimilation techniques are used in this study with the main aim of enhancing short-range forecasts of two challenging severe weather events.
Thomas Loridan and Nicolas Bruneau
EGUsphere, https://doi.org/10.5194/egusphere-2024-3253, https://doi.org/10.5194/egusphere-2024-3253, 2024
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Tropical Cyclone (TC) risk models have been used by the insurance industry to quantify occurrence and severity risk since the 90s. To date these models are mostly built from backward looking statistics and portray risk under a static view of the climate. We here introduce a novel approach, based on machine learning, that allows sampling of climate variability when assessing TC risk globally. This is of particular importance when computing forward looking views of TC risk.
Herijaona Hani-Roge Hundilida Randriatsara, Eva Holtanova, Karim Rizwan, Hassen Babaousmail, Mirindra Finaritra Tanteliniaina Rabezanahary, Kokou Romaric Posset, Donnata Alupot, and Brian Odhiambo Ayugi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-191, https://doi.org/10.5194/nhess-2024-191, 2024
Revised manuscript accepted for NHESS
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This study aims to analyze the spatiotemporal characteristics of drought (duration, frequency, severity, intensity) over Madagascar during 1981–2022 by using Standardized Precipitation Index (SPI-3, -6 and -12). Additionally, the impact of drought on vegetation over the studied area was assessed based on the relationship evaluation between SPI and the Normalized Difference Vegetation Index (NDVI) during 2000–2022.
Gwendoline Ducros, Timothy Tiggeloven, Lin Ma, Anne Sophie Daloz, Nina Schuhen, and Marleen C. de Ruiter
EGUsphere, https://doi.org/10.5194/egusphere-2024-3158, https://doi.org/10.5194/egusphere-2024-3158, 2024
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Our study finds that heatwave, drought and wildfire events occurring simultaneously in Scandinavia are pronounced in the summer months; and the heat-drought 2018 event led to a drop in gross domestic product, affecting agriculture and forestry imports, further impacting Europe’s trade balance. This research shows the importance of ripple effects of multi-hazard, and that forest management and adaptation measures are vital to reducing the risks of heat-related multi-hazards in vulnerable areas.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024, https://doi.org/10.5194/nhess-24-3479-2024, 2024
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To effectively track and identify droughts, we developed a novel integrated drought index that combines the effects of precipitation, temperature, and soil moisture on drought. After comparison and verification, the integrated drought index shows superior performance compared to a single meteorological drought index or agricultural drought index in terms of drought identification.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 24, 3445–3460, https://doi.org/10.5194/nhess-24-3445-2024, https://doi.org/10.5194/nhess-24-3445-2024, 2024
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European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological loss index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high-impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
Christopher J. White, Mohammed Sarfaraz Gani Adnan, Marcello Arosio, Stephanie Buller, YoungHwa Cha, Roxana Ciurean, Julia M. Crummy, Melanie Duncan, Joel Gill, Claire Kennedy, Elisa Nobile, Lara Smale, and Philip J. Ward
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-178, https://doi.org/10.5194/nhess-2024-178, 2024
Revised manuscript under review for NHESS
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Indicators contain observable and measurable characteristics to understand the state of a concept or phenomenon and/or monitor it over time. There have been limited efforts to understand how indicators are being used in multi-hazard and multi-risk contexts. We find most of existing indicators do not include the interactions between hazards or risks. We propose 12 recommendations to enable the development and uptake of multi-hazard and multi-risk indicators.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci., 24, 3267–3277, https://doi.org/10.5194/nhess-24-3267-2024, https://doi.org/10.5194/nhess-24-3267-2024, 2024
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The train effect is related to convective cells that pass over the same place. Trains produce heavy rainfall and sometimes floods and are reported in North America during spring and summer. In Israel, 17 trains associated with Cyprus lows were identified by radar images and were found within the cold sector south of the low center and in the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km; last 1–3 h; and yield 35 mm of rainfall up to 60 mm.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
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A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
Katharina Küpfer, Alexandre Tuel, and Michael Kunz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2803, https://doi.org/10.5194/egusphere-2024-2803, 2024
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Using loss data, we assess when and how single and multiple types of meteorological extremes (river floods and heavy rainfall events, windstorms and convective gusts, and hail). We find that the combination of several types of hazards clusters robustly on a seasonal scale, whereas only some single hazard types occur in clusters. This can be associated with higher losses compared to isolated events. We argue for the relevance of jointly considering multiple types of hazards.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024, https://doi.org/10.5194/nhess-24-3035-2024, 2024
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We have used the temperature and relative humidity sensors in smartphones to estimate the vapor pressure deficit (VPD), an important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal shows the potential for using smartphone data to compliment the regular weather station network while also providing high spatial resolution of the VPD index.
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, https://doi.org/10.5194/nhess-24-2939-2024, 2024
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High-impact river floods are often caused by extreme precipitation. Flood protection relies on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties in the return values can be substantially reduced compared to observational estimates.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
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Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024, https://doi.org/10.5194/nhess-24-2793-2024, 2024
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Weather prediction uncertainties can be described as sets of possible scenarios – a technique called ensemble prediction. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
Cited articles
Allen, B. J., Mansell, E. R., Dowell, D. C., and Deierling, W.: Assimilation
of pseudo-GLM data using the ensemble Kalman filter, Mon. Weather Rev., 144, 3465–3486, https://doi.org/10.1175/MWR-D-16-0117.1, 2016. a
Barthe, C. and Pinty, J.-P.: Simulation of a supercellular storm using a
three-dimensional mesoscale model with an explicit lightning flash scheme, J. Geophys. Res., 112, D06210, https://doi.org/10.1029/2006JD007484, 2007. a
Bateman, M., Mach, D., and Stock, M.: Further Investigation Into Detection
Efficiency and False Alarm Rate for the Geostationary Lightning Mappers Aboard GOES‐16 and GOES‐17, Earth Space Sci., 8, e2020EA001237, https://doi.org/10.1029/2020EA001237, 2021. a
Breiman, L.: Random Forest, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001. a
Brousseau, P., Seity, Y., Ricard, D., and Léger, J.: Improvement of the
forecast of convective activity from the AROME-France system, Q. J. Roy. Meteorol. Soc., 142, 2231–2243, https://doi.org/10.1002/qj.2822, 2016. a
Carey, L. D., Murphy, M. J., McCormick, T. L., and Demetriades, N. W.:
Lightning location relative to storm structure in a leading-line, trailing-stratiform mesoscale convective system, J. Geophys. Res., 110, D03105, https://doi.org/10.1029/2003JD004371, 2005. a
Chatterjee, S. and Hadi, A.: Regression analysis by example, John Wiley & Sons, Ltd, https://doi.org/10.1002/0470055464, 2006. a
Cohen, J., Patricia, C., West, S., and Aiken, L.: Applied multiple
regression, Correlation Analysis for the Behavioral Sciences, Lawrence Erlbaum Associates, Incorporated, https://doi.org/10.4324/9781410606266, 1983. a
Deierling, W. and Petersen, W. A.: Total lightning activity as an indicator of updraft characteristics, J. Geophys. Res.-Atmos., 113, D16210, https://doi.org/10.1029/2007JD009598, 2008. a, b, c, d
Deierling, W., Latham, J., Petersen, W. A., Ellis, S. M., and Christian, H. J.: On the relationship of thunderstorm ice hydrometeor characteristics and
total lightning measurements, Atmos. Res., 76, 114–126,
https://doi.org/10.1016/j.atmosres.2004.11.023, 2005. a, b
Efron, B. and Tibshirani, R. J.: An Introduction to the Bootstrap, Chapman & Hall, ISBN 978-0-412-04231-7, 1993. a
Erdmann, F.: Preparation for the use of Meteosat Third Generation Lightning
Imager observations in short-term numerical weather prediction, PhD thesis, Université de Toulouse, Université Toulouse III – Paul Sabatier, http://thesesups.ups-tlse.fr/4947/ (last access: 30 August 2022), 2020. a
Erdmann, F., Caumont, O., and Defer, E.: A Geostationary Lightning
Pseudo-Observation Generator Utilizing Low-Frequency Ground-Based Lightning
Observations, J. Atmos. Ocean. Tech., 39, 3–30,
https://doi.org/10.1175/JTECH-D-20-0160.1, 2022. a, b, c, d
Faggian, N., Roux, B., Steinle, P., and Ebert, B.: Fast calculation of the
fractions skill score, MAUSAM, 66, 457–466,
https://metnet.imd.gov.in/mausamdocs/166310_F.pdf (last access: 30 August 2022), 2015. a
Fierro, A. O., Mansell, E. R., Ziegler, C. L., and MacGorman, D. R.:
Application of a Lightning Data Assimilation Technique in the WRF-ARW Model
at Cloud-Resolving Scales for the Tornado Outbreak of 24 May 2011, Mon.
Weather Rev., 140, 2609–2627, https://doi.org/10.1175/MWR-D-11-00299.1, 2012. a, b
Fierro, A. O., Gao, J., Ziegler, C. L., Calhoun, K. M., Mansell, E. R., and
MacGorman, D. R.: Assimilation of Flash Extent Data in the Variational
Framework at Convection-Allowing Scales: Proof-of-Concept and Evaluation for
the Short-Term Forecast of the 24 May 2011 Tornado Outbreak, Mon. Weather Rev., 144, 4373–4393, https://doi.org/10.1175/MWR-D-16-0053.1, 2016. a, b
Fierro, A. O., Wang, Y., Gao, J., and Mansell, E. R.: Variational Assimilation of Radar Data and GLM Lightning-Derived Water Vapor for the Short-Term Forecasts of High-Impact Convective Events, Mon.Weather Rev., 147,
4045–4069, https://doi.org/10.1175/MWR-D-18-0421.1, 2019. a, b
Figueras i Ventura, J., Pineda, N., Besic, N., Grazioli, J., Hering, A., Van Der Velde, O. A., Romero, D., Sunjerga, A., Mostajabi, A., Azadifar, M.,
Rubinstein, M., Montanyà, J., Germann, U., and Rachidi, F.: Analysis of the lightning production of convective cells, Atmos. Meas. Tech., 12, 5573–5591, https://doi.org/10.5194/amt-12-5573-2019, 2019. a, b, c
Giannaros, T. M., Kotroni, V., and Lagouvardos, K.: Predicting lightning
activity in Greece with the Weather Research and Forecasting (WRF) model, Atmos. Res., 156, 1–13, https://doi.org/10.1016/j.atmosres.2014.12.009, 2015. a
Hu, J., Fierro, A. O., Wang, Y., Gao, J., and Mansell, E. R.: Exploring the
Assimilation of GLM-Derived Water Vapor Mass in a Cycled 3DVAR Framework for
the Short-Term Forecasts of High-Impact Convective Events, Mon. Weather Rev., 148, 1005–1028, https://doi.org/10.1175/MWR-D-19-0198.1, 2020. a, b
Jolliffe, I. T. and Cadima, J.: Principal component analysis: a review and
recent developments, Philos. T. Roy. Soc. A, 374, 20150202,
https://doi.org/10.1098/rsta.2015.0202, 2016. a, b
Karagiannidis, A., Lagouvardos, K., Lykoudis, S., Kotroni, V., Giannaros, T.,
and Betz, H. D.: Modeling lightning density using cloud top parameters, Atmos. Res., 222, 163–171, https://doi.org/10.1016/j.atmosres.2019.02.013, 2019. a
Kokou, P., Willemsen, P., Lekouara, M., Arioua, M., Mora, A., Van den
Braembussche, P., Neri, E., and Aminou, D. M. A.: Algorithmic Chain for
Lightning Detection and False Event Filtering Based on the MTG Lightning
Imager, IEEE T. Geosci. Remote, 56, 5115–5124, https://doi.org/10.1109/TGRS.2018.2808965, 2018. a
Lynn, B. H.: The Usefulness and Economic Value of Total Lightning Forecasts
Made with a Dynamic Lightning Scheme Coupled with Lightning Data Assimilation, Weather Forecast., 32, 645–663, https://doi.org/10.1175/WAF-D-16-0031.1, 2017. a
Mandement, M. and Caumont, O.: Contribution of personal weather stations to
the observation of deep-convection features near the ground, Nat. Hazards Earth Syst. Sci., 20, 299–322, https://doi.org/10.5194/nhess-20-299-2020, 2020. a
Mansell, E. R.: Storm-scale ensemble Kalman filter assimilation of total
lightning flash-extent data, Mon. Weather Rev., 142, 3683–3695, https://doi.org/10.1175/MWR-D-14-00061.1, 2014. a
Mansell, E. R., MacGorman, D. R., Ziegler, C. L., and Straka, J. M.: Simulated three-dimensional branched lightning in a numerical thunderstorm model, J. Geophys. Res.-Atmos., 107, 2–1, https://doi.org/10.1029/2000JD000244, 2002. a
Marchand, M. R. and Fuelberg, H. E.: Assimilation of Lightning Data Using a
Nudging Method Involving Low-Level Warming, Mon. Weather Rev., 142, 4850–4871, https://doi.org/10.1175/MWR-D-14-00076.1, 2014. a, b
METEO FRANCE: Données publiques, https://donneespubliques.meteofrance.fr/, last access: 31 August 2022. a
McCaul, E. W., Priftis, G., Case, J. L., Chronis, T., Gatlin, P. N., Goodman,
S. J., and Kong, F.: Sensitivities of the WRF Lightning Forecasting Algorithm to Parameterized Microphysics and Boundary Layer Schemes, Weather Forecast., 35, 1545–1560, https://doi.org/10.1175/WAF-D-19-0101.1, 2020. a
Mittermaier, M. and Roberts, N.: Intercomparison of Spatial Forecast
Verification Methods: Identifying Skillful Spatial Scales Using the Fractions
Skill Score, Weather Forecast., 25, 343–354, https://doi.org/10.1175/2009WAF2222260.1, 2010. a
Neter, J., Kutner, M., Nachtsheim, C., and Wasserman, W.: Applied Linear
Statistical Models, in: 4th Edn., McGraw-Hill, New York, ISBN 978-0-256-08601-0, 1996. a
Oshiro, T. M., Perez, P. S., and Baranauskas, J. A.: How Many Trees in a
Random Forest?, in: Machine Learning and Data Mining in Pattern Recognition, MLDM 2012, Lecture Notes in Computer Science, vol. 7376, edited by: Perner, P., Springer, Berlin, Heidelberg, 154–168, https://doi.org/10.1007/978-3-642-31537-4_13, 2012. a
Petersen, W. A., Christian, H. J., and Rutledge, S. A.: TRMM observations of
the global relationship between ice water content and lightning, Geophys. Res. Lett., 32, 1–4, https://doi.org/10.1029/2005GL023236, 2005. a, b, c, d
Peterson, M., Deierling, W., Liu, C., Mach, D., and Kalb, C.: The properties
of optical lightning flashes and the clouds they illuminate, J. Geophys. Res.-Atmos., 122, 423–442, https://doi.org/10.1002/2016JD025312, 2017. a
Price, C. and Rind, D.: A simple lightning parameterization for calculating
global lightning distributions, J. Geophys. Res., 97, 9919–9933, https://doi.org/10.1029/92JD00719, 1992.
a
Roberts, N. M. and Lean, H. W.: Scale-selective verification of rainfall
accumulations from high-resolution forecasts of convective events, Mon.
Weather Rev., 136, 78–97, https://doi.org/10.1175/2007MWR2123.1, 2008. a
Schultz, C. J., Petersen, W. A., and Carey, L. D.: Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather, J. Appl. Meteorol. Clim., 48, 2543–2563,
https://doi.org/10.1175/2009JAMC2237.1, 2009. a
Schultz, C. J., Petersen, W. A., and Carey, L. D.: Lightning and Severe
Weather: A Comparison between Total and Cloud-to-Ground Lightning Trends,
Weather Forecast., 26, 744–755, https://doi.org/10.1175/WAF-D-10-05026.1, 2011. a
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P., Bouttier,
F., Lac, C., and Masson, V.: The AROME-France Convective-Scale Operational
Model, Mon. Weather Rev., 139, 976–991, https://doi.org/10.1175/2010MWR3425.1, 2011. a
Skok, G. and Roberts, N.: Analysis of Fractions Skill Score properties for
random precipitation fields and ECMWF forecasts, Q. J. Roy. Meteorol. Soc., 142, 2599–2610, https://doi.org/10.1002/qj.2849, 2016. a
Weiss, S. A., MacGorman, D. R., and Calhoun, K. M.: Lightning in the Anvils of Supercell Thunderstorms, Mon. Weather Rev., 140, 2064–2079,
https://doi.org/10.1175/MWR-D-11-00312.1, 2012. a
Wong, J., Barth, M. C., and Noone, D.: Evaluating a lightning parameterization based on cloud-top height for mesoscale numerical model simulations, Geosci. Model Dev., 6, 429–443, https://doi.org/10.5194/gmd-6-429-2013,
2013. a
Xiao, X., Sun, J., Qie, X., Ying, Z., Ji, L., Chen, M., and Zhang, L.:
Lightning Data Assimilation Scheme in a 4DVAR System and Its Impact on Very
Short-Term Convective Forecasting, Mon. Weather Rev., 149, 353–373,
https://doi.org/10.1175/MWR-D-19-0396.1, 2021. a
Yair, Y., Lynn, B., Price, C., Kotroni, V., Lagouvardos, K., Morin, E., Mugnai, A., and Del Carmen Llasat, M.: Predicting the potential for lightning
activity in Mediterranean storms based on the Weather Research and
Forecasting (WRF) model dynamic and microphysical fields, J. Geophys. Res.-Atmos., 115, D04205, https://doi.org/10.1029/2008JD010868, 2010. a, b, c, d
Yoshida, S., Morimoto, T., Ushio, T., and Kawasaki, Z.: A fifth-power
relationship for lightning activity from Tropical Rainfall Measuring Mission
satellite observations, J.Geophys. Res., 114, D09104, https://doi.org/10.1029/2008JD010370, 2009. a
Zhang, R., Zhang, Y., Xu, L., Zheng, D., and Yao, W.: Assimilation of total
lightning data using the three-dimensional variational method at
convection-allowing resolution, J. Meteorol. Res., 31, 731–746, https://doi.org/10.1007/s13351-017-6133-3, 2017. a
Short summary
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.
The objective of this study is to prepare the assimilation of satellite lightning data in the...
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