Articles | Volume 23, issue 8
https://doi.org/10.5194/nhess-23-2821-2023
© Author(s) 2023. 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-23-2821-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Aug 2023
Research article |
| 18 Aug 2023
| 18 Aug 2023
Assimilation of Meteosat Third Generation (MTG) Lightning Imager (LI) pseudo-observations in AROME-France – proof of concept
CNRM, Université de Toulouse, Météo-France, CNRS, 42 Av. Gaspard Coriolis, Toulouse, France
Royal Meteorological Institute, 3 Av. Circulaire, Brussels, Belgium
Olivier Caumont
CNRM, Université de Toulouse, Météo-France, CNRS, 42 Av. Gaspard Coriolis, Toulouse, France
Météo-France, Direction des opérations pour la prévision, 42 Av. Gaspard Coriolis, Toulouse, France
Eric Defer
LAERO, Université de Toulouse, CNRS, UT3, IRD, 14 Av. Edouard Belin, Toulouse, France
Related authors
Felix Erdmann and Dieter Roel Poelman
EGUsphere, https://doi.org/10.5194/egusphere-2024-174, https://doi.org/10.5194/egusphere-2024-174, 2024
Short summary
Short summary
This study provides detailed insight into the thunderstorm characteristics associated with abrupt changes in the lightning activity of a thunderstorm – lightning jump (LJ) and lightning dive (LD) – using geostationary satellite observations. Thunderstorms exhibiting one or multiple LJs or LDs feature similar characteristics as severe thunderstorms. Storms with multiple LJs contain strong convective updrafts, and are prone to produce high rain rates, large hail or tornadoes.
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
Short summary
Short summary
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.
Andrea Kolínská, Ivana Kolmašová, Eric Defer, Ondřej Santolík, and Stéphane Pédeboy
EGUsphere, https://doi.org/10.5194/egusphere-2024-2489, https://doi.org/10.5194/egusphere-2024-2489, 2024
Short summary
Short summary
We contribute to the knowledge about the differences in lightning flashes of opposite polarity. We found and explained a distinct behaviour of in-cloud processes happening immediately after return strokes of cloud-to-ground lightning flashes, considering a recharging of in-cloud part of bidirectional leader.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
EGUsphere, https://doi.org/10.5194/egusphere-2024-1673, https://doi.org/10.5194/egusphere-2024-1673, 2024
Short summary
Short summary
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.
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.
Felix Erdmann and Dieter Roel Poelman
EGUsphere, https://doi.org/10.5194/egusphere-2024-174, https://doi.org/10.5194/egusphere-2024-174, 2024
Short summary
Short summary
This study provides detailed insight into the thunderstorm characteristics associated with abrupt changes in the lightning activity of a thunderstorm – lightning jump (LJ) and lightning dive (LD) – using geostationary satellite observations. Thunderstorms exhibiting one or multiple LJs or LDs feature similar characteristics as severe thunderstorms. Storms with multiple LJs contain strong convective updrafts, and are prone to produce high rain rates, large hail or tornadoes.
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
Short summary
Short summary
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.
Pauline Combarnous, Felix Erdmann, Olivier Caumont, Éric Defer, and Maud Martet
Nat. Hazards Earth Syst. Sci., 22, 2943–2962, https://doi.org/10.5194/nhess-22-2943-2022, https://doi.org/10.5194/nhess-22-2943-2022, 2022
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Related subject area
Atmospheric, Meteorological and Climatological Hazards
Classification of North Atlantic and European extratropical cyclones using multiple measures of intensity
Subseasonal forecasts of heat waves in West African cities
Impacts on and damage to European forests from the 2018–2022 heat and drought events
Brief communication: Training of AI-based nowcasting models for rainfall early warning should take into account user requirements
Examining the Eastern European extreme summer temperatures of 2023 from a long-term perspective: the role of natural variability vs. anthropogenic factors
How well are hazards associated with derechos reproduced in regional climate simulations?
Reconstructing hail days in Switzerland with statistical models (1959–2022)
GTDI: a game-theory-based integrated drought index implying hazard-causing and hazard-bearing impact change
Insurance loss model vs. meteorological loss index – how comparable are their loss estimates for European windstorms?
Intense rains in Israel associated with the train effect
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
On the potential of using smartphone sensors for wildfire hazard estimation through citizen science
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations
Probabilistic short-range forecasts of high-precipitation events: optimal decision thresholds and predictability limits
Surprise floods: the role of our imagination in preparing for disasters
Modelling crop hail damage footprints with single-polarization radar: the roles of spatial resolution, hail intensity, and cropland density
Insights into ground strike point properties in Europe through the EUCLID lightning location system
The role of citizen science in assessing the spatiotemporal pattern of rainfall events in urban areas: a case study in the city of Genoa, Italy
The Record-Breaking Precipitation Event of December 2022 in Portugal
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
Assimilation of temperature and relative humidity observations from personal weather stations in AROME-France
Catchment-scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan
The risk of synoptic-scale Arctic cyclones to shipping
Brief communication: Forecasting extreme precipitation from atmospheric rivers in New Zealand
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
Application of machine learning to forecast agricultural drought impacts for large scale sub-seasonal drought monitoring in Brazil
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
Compound winter low wind and cold events impacting the French electricity system: observed evolution and role of large-scale circulation
Interannual variations in the seasonal cycle of extreme precipitation in Germany and the response to climate change
Climatology of large hail in Europe: characteristics of the European Severe Weather Database
Amplified potential for vegetation stress under climate-change-induced intensifying compound extreme events in the Greater Mediterranean Region
Assimilation of surface pressure observations from personal weather stations in AROME-France
An open-source radar-based hail damage model for buildings and cars
Linkages between atmospheric rivers and humid heat across the United States
A data-driven framework for assessing climatic impact-drivers in the context of food security
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
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
A historic derecho in the USA is presented. The 29 June 2012 derecho caused more than 20 deaths and millions of US dollars of damage. We use a regional climate model to understand how model fidelity changes under different initial conditions. We find changes drive different convective conditions, resulting in large variation in the simulated hazards. The variation using different reanalysis data shows that framing these results in the context of contemporary and future climate is a challenge.
Lena Wilhelm, Cornelia Schwierz, Katharina Schröer, Mateusz Taszarek, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 3869–3894, https://doi.org/10.5194/nhess-24-3869-2024, https://doi.org/10.5194/nhess-24-3869-2024, 2024
Short summary
Short summary
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.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024, https://doi.org/10.5194/nhess-24-3479-2024, 2024
Short summary
Short summary
To effectively track and identify droughts, we developed a novel integrated drought index that combines the effects of precipitation, temperature, and soil moisture on drought. After comparison and verification, the integrated drought index shows superior performance compared to a single meteorological drought index or agricultural drought index in terms of drought identification.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 24, 3445–3460, https://doi.org/10.5194/nhess-24-3445-2024, https://doi.org/10.5194/nhess-24-3445-2024, 2024
Short summary
Short summary
European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological loss index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high-impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci., 24, 3267–3277, https://doi.org/10.5194/nhess-24-3267-2024, https://doi.org/10.5194/nhess-24-3267-2024, 2024
Short summary
Short summary
The train effect is related to convective cells that pass over the same place. Trains produce heavy rainfall and sometimes floods and are reported in North America during spring and summer. In Israel, 17 trains associated with Cyprus lows were identified by radar images and were found within the cold sector south of the low center and in the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km; last 1–3 h; and yield 35 mm of rainfall up to 60 mm.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
Short summary
Short summary
A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024, https://doi.org/10.5194/nhess-24-3035-2024, 2024
Short summary
Short summary
We have used the temperature and relative humidity sensors in smartphones to estimate the vapor pressure deficit (VPD), an important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal shows the potential for using smartphone data to compliment the regular weather station network while also providing high spatial resolution of the VPD index.
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, https://doi.org/10.5194/nhess-24-2939-2024, 2024
Short summary
Short summary
High-impact river floods are often caused by extreme precipitation. Flood protection relies on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties in the return values can be substantially reduced compared to observational estimates.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
Short summary
Short summary
Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024, https://doi.org/10.5194/nhess-24-2793-2024, 2024
Short summary
Short summary
Weather prediction uncertainties can be described as sets of possible scenarios – a technique called ensemble prediction. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024, https://doi.org/10.5194/nhess-24-2633-2024, 2024
Short summary
Short summary
What’s the worst that could happen? Recent floods are often claimed to be beyond our imagination. Imagination is the picturing of a situation in our mind and the emotions that we connect with this situation. But why is this important for disasters? This survey found that when we cannot imagine a devastating flood, we are not preparing in advance. Severe-weather forecasts and warnings need to advance in order to trigger our imagination of what might happen and enable us to start preparing.
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024, https://doi.org/10.5194/nhess-24-2541-2024, 2024
Short summary
Short summary
The study presents an open-source model to determine the occurrence of hail damage to field crops and grapevines after hailstorms in Switzerland based on radar, agricultural land use data, and insurance damage reports. The model performs best at 8 km resolution for field crops and 1 km for grapevine and in the main production areas. Highlighting performance trade-offs and the relevance of user needs, the study is a first step towards the assessment of risk and damage for crops in Switzerland.
Dieter Roel Poelman, Hannes Kohlmann, and Wolfgang Schulz
Nat. Hazards Earth Syst. Sci., 24, 2511–2522, https://doi.org/10.5194/nhess-24-2511-2024, https://doi.org/10.5194/nhess-24-2511-2024, 2024
Short summary
Short summary
EUCLID's lightning data unveil distinctive ground strike point (GSP) patterns in Europe. Over seas, GSPs per flash surpass inland, reaching a minimum in the Alps. Mountainous areas like the Alps and Pyrenees have the closest GSP separation, highlighting terrain elevation's impact. The daily peak current correlates with average GSPs per flash. These findings could significantly influence lightning protection measures, urging a focus on GSP density rather than flash density for risk assessment.
Nicola Loglisci, Giorgio Boni, Arianna Cauteruccio, Francesco Faccini, Massimo Milelli, Guido Paliaga, and Antonio Parodi
Nat. Hazards Earth Syst. Sci., 24, 2495–2510, https://doi.org/10.5194/nhess-24-2495-2024, https://doi.org/10.5194/nhess-24-2495-2024, 2024
Short summary
Short summary
We analyse the meteo-hydrological features of the 27 and 28 August 2023 event that occurred in Genoa. Rainfall observations were made using rain gauge networks based on either official networks or citizen science networks. The merged analysis stresses the spatial variability in the precipitation, which cannot be captured by the current spatial density of authoritative stations. Results show that at minimal distances the variations in cumulated rainfall over a sub-hourly duration are significant.
Tiago M. Ferreira, Ricardo M. Trigo, Tomás H. Gaspar, Joaquim G. Pinto, and Alexandre M. Ramos
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-130, https://doi.org/10.5194/nhess-2024-130, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Here we investigate the synoptic evolution associated with the occurrence of an atmospheric river leading 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 day 12.
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.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
EGUsphere, https://doi.org/10.5194/egusphere-2024-1673, https://doi.org/10.5194/egusphere-2024-1673, 2024
Short summary
Short summary
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.
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.
Daniel G. Kingston, Liam Cooper, David A. Lavers, and David M. Hannah
EGUsphere, https://doi.org/10.5194/egusphere-2024-1742, https://doi.org/10.5194/egusphere-2024-1742, 2024
Short summary
Short summary
Extreme rainfall comprises a major hydro-hazard 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 geographic setting.
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.
Joseph William Gallear, Marcelo Valadares Galdos, Marcelo Zeri, and Andrew Hartley
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-60, https://doi.org/10.5194/nhess-2024-60, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
In Brazil, drought is of national concern and can have major consequences for agriculture. Here, we determine how to develop forecasts for drought impacts on vegetation health using machine learning. Results aim to inform future developments in operational drought monitoring at the National Center for Monitoring and Early Warning of Natural Disasters in Brazil (CEMADEN). This information is essential for disaster preparedness and planning of future actions to support areas affected by drought.
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.
François Collet, Margot Bador, Julien Boé, Laurent Dubus, and Bénédicte Jourdier
EGUsphere, https://doi.org/10.5194/egusphere-2024-903, https://doi.org/10.5194/egusphere-2024-903, 2024
Short summary
Short summary
The objective of this study 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 high interannual variability and a decrease over the 1950–2022 period. We further show that the regional atmospheric circulation is an important driver of compound events occurence, but do not strongly contributes to the observed decrease.
Madlen Peter, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 24, 1261–1285, https://doi.org/10.5194/nhess-24-1261-2024, https://doi.org/10.5194/nhess-24-1261-2024, 2024
Short summary
Short summary
The paper introduces a statistical modeling approach describing daily extreme precipitation in Germany more accurately by including changes within the year and between the years simultaneously. The changing seasonality over years is regionally divergent and mainly weak. However, some regions stand out with a more pronounced linear rise of summer intensities, indicating a possible climate change signal. Improved modeling of extreme precipitation is beneficial for risk assessment and adaptation.
Faye Hulton and David M. Schultz
Nat. Hazards Earth Syst. Sci., 24, 1079–1098, https://doi.org/10.5194/nhess-24-1079-2024, https://doi.org/10.5194/nhess-24-1079-2024, 2024
Short summary
Short summary
Large hail devastates crops and property and can injure and kill people and livestock. Hail reports are collected by individual countries, so understanding where and when large hail occurs across Europe is an incomplete undertaking. We use the European Severe Weather Database to evaluate the quality of reports by year and by country since 2000. Despite its short record, the dataset appears to represent aspects of European large-hail climatology reliably.
Patrick Olschewski, Mame Diarra Bousso Dieng, Hassane Moutahir, Brian Böker, Edwin Haas, Harald Kunstmann, and Patrick Laux
Nat. Hazards Earth Syst. Sci., 24, 1099–1134, https://doi.org/10.5194/nhess-24-1099-2024, https://doi.org/10.5194/nhess-24-1099-2024, 2024
Short summary
Short summary
We applied a multivariate and dependency-preserving bias correction method to climate model output for the Greater Mediterranean Region and investigated potential changes in false-spring events (FSEs) and heat–drought compound events (HDCEs). Results project an increase in the frequency of FSEs in middle and late spring as well as increases in frequency, intensity, and duration for HDCEs. This will potentially aggravate the risk of crop loss and failure and negatively impact food security.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 24, 907–927, https://doi.org/10.5194/nhess-24-907-2024, https://doi.org/10.5194/nhess-24-907-2024, 2024
Short summary
Short summary
Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. The incorporation of new observations from personal weather stations into the French limited-area model is evaluated. It leads to a significant improvement in the modelling of the surface pressure field up to 9 h ahead. Their incorporation improves the location and intensity of the heavy precipitation event that occurred in the South of France in September 2021.
Timo Schmid, Raphael Portmann, Leonie Villiger, Katharina Schröer, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 847–872, https://doi.org/10.5194/nhess-24-847-2024, https://doi.org/10.5194/nhess-24-847-2024, 2024
Short summary
Short summary
Hailstorms cause severe damage to buildings and cars, which motivates a detailed risk assessment. Here, we present a new open-source hail damage model based on radar data in Switzerland. The model successfully estimates the correct order of magnitude of car and building damages for most large hail events over 20 years. However, large uncertainty remains in the geographical distribution of modelled damages, which can be improved for individual events by using crowdsourced hail reports.
Colin Raymond, Anamika Shreevastava, Emily Slinskey, and Duane Waliser
Nat. Hazards Earth Syst. Sci., 24, 791–801, https://doi.org/10.5194/nhess-24-791-2024, https://doi.org/10.5194/nhess-24-791-2024, 2024
Short summary
Short summary
How can we systematically understand what causes high levels of atmospheric humidity and thus heat stress? Here we argue that atmospheric rivers can be a useful tool, based on our finding that in several US regions, atmospheric rivers and humid heat occur close together in space and time. Most typically, an atmospheric river transports moisture which heightens heat stress, with precipitation following a day later. These effects tend to be larger for stronger and more extensive systems.
Marcos Roberto Benso, Roberto Fray Silva, Gabriela Gesualdo Chiquito, Antonio Mauro Saraiva, Alexandre Cláudio Botazzo Delbem, Patricia Angélica Alves Marques, and Eduardo Mario Mendiondo
EGUsphere, https://doi.org/10.5194/egusphere-2023-3002, https://doi.org/10.5194/egusphere-2023-3002, 2024
Short summary
Short summary
The production of food is susceptible to several climate hazards such as droughts, excessive rainfall, and heat waves. In this paper, we present a methodology that uses artificial intelligence for assessing the impact of climate risks on food production. Our methodology helps us to automatically select the most relevant indices and critical thresholds of these indices that when surpassed can increase the danger of crop yield loss.
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.
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, b
Allen, D. J. and Pickering, K. E.: Evaluation of lightning flash rate parameterizations for use in a global chemical transport model, J. Geophys. Res.-Atmos., 107, ACH 15-1–ACH 15-21,
https://doi.org/10.1029/2002JD002066, 2002. a
Apodaca, K., Zupanski, M., DeMaria, M., Knaff, J. A., and Grasso, L. D.: Development of a hybrid variational-ensemble data assimilation technique for observed lightning tested in a mesoscale model, Nonlin. Processes Geophys., 21, 1027–1041, https://doi.org/10.5194/npg-21-1027-2014, 2014. a
Barthe, C., Deierling, W., and Barth, M. C.: Estimation of total lightning from various storm parameters: A cloud-resolving model study, J. Geophys. Res.-Atmos., 115, D24202, https://doi.org/10.1029/2010JD014405, 2010. a, b
Betz, H. D., Schmidt, K., Laroche, P., Blanchet, P., Oettinger, W. P., Defer,
E., Dziewit, Z., and Konarski, J.: LINET – An international lightning
detection network in Europe, Atmos. Res., 91, 564–573,
https://doi.org/10.1016/j.atmosres.2008.06.012, 2009. a
Borderies, M., Caumont, O., Augros, C., Bresson, E., Delanoë, J., Ducrocq, V., Fourrié, N., Bastard, T. L., and Nuret, M.: Simulation of W-band radar reflectivity for model validation and data assimilation, Q. J. Roy. Meteor. Soc., 144, 391–403, https://doi.org/10.1002/qj.3210, 2018. a
Borderies, M., Caumont, O., Delanoë, J., Ducrocq, V., Fourrié, N., and Marquet, P.: Impact of airborne cloud radar reflectivity data assimilation on kilometre-scale numerical weather prediction analyses and forecasts of heavy precipitation events, Nat. Hazards Earth Syst. Sci., 19, 907–926, https://doi.org/10.5194/nhess-19-907-2019, 2019. a, b, c, d
Bouyssel, F., Berre, L., Bénichou, H., Chambon, P., Girardot, N., Guidard, V., Loo, C., Mahfouf, J.-F., Moll, P., Payan, C., and Raspaud, D.: The 2020
Global Operational NWP Data Assimilation System at Météo-France, in: Data
Assimilation for Atmospheric, Oceanic and Hydrologic Applications, edited by: Park, S. K. and Xu, L., IV,
645–664, https://doi.org/10.1007/978-3-030-77722-7_25, Springer, Cham, 2022. a
Bovalo, C., Barthe, C., and Pinty, J.-P.: Examining relationships between cloud-resolving model parameters and total flash rates to generate lightning density maps, Q. J. Roy. Meteor. Soc., 145, 1250–1266, https://doi.org/10.1002/qj.3494, 2019. a
Brousseau, P., Desroziers, G., Bouttier, F., and Chapnik, B.: A posteriori
diagnostics of the impact of observations on the AROME-France
convective-scale data assimilation system, Q. J. Roy. Meteor. Soc., 140, 982–994, https://doi.org/10.1002/qj.2179, 2014. 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. Meteor. Soc., 142, 2231–2243, https://doi.org/10.1002/qj.2822, 2016. a, b, c, d
Buiat, M., Porcù, F., and Dietrich, S.: Observing relationships between lightning and cloud profiles by means of a satellite-borne cloud radar, Atmos. Meas. Tech., 10, 221–230, https://doi.org/10.5194/amt-10-221-2017, 2017. a
Caumont, O., Ducrocq, V., Wattrelot, E., Jaubert, G., and Pradier-Vabre, S.: 1D+3DVar assimilation of radar reflectivity data: a proof of concept, Tellus
A, 62, 173–187, https://doi.org/10.1111/j.1600-0870.2009.00430.x, 2010. a, b, c, d
Chen, Y., Yu, Z., Han, W., He, J., and Chen, M.: Case Study of a Retrieval Method of 3D Proxy Reflectivity from FY-4A Lightning Data and Its Impact on the Assimilation and Forecasting for Severe Rainfall Storms, Remote Sens.,
12, 1165, https://doi.org/10.3390/rs12071165, 2020. a
Combarnous, P., Erdmann, F., Caumont, O., Defer, É., and Martet, M.: A satellite lightning observation operator for storm-scale numerical weather prediction, Nat. Hazards Earth Syst. Sci., 22, 2943–2962, https://doi.org/10.5194/nhess-22-2943-2022, 2022. a, b
Davies, H. C.: A lateral boundary formulation for multi-level prediction
models, Q. J. Roy. Meteor. Soc., 102, 405–418,
https://doi.org/10.1002/qj.49710243210, 1976. a
Deierling, W. and Petersen, W. A.: Total lightning activity as an indicator of updraft characteristics, J. Geophys. Res., 113, D16210,
https://doi.org/10.1029/2007JD009598, 2008. a, b
Deierling, W., Petersen, W. A., Lathman, J., Ellis, S., and Christian, H. J.: The relationship between lightning activity and ice fluxes in thunderstorms,
J. Geophys. Res., 113, D15210, https://doi.org/10.1029/2007JD009700, 2008. a, b, c, d
Dixon, K., Mass, C., Hakim, G., and Holzworth, R.: The Impact of Lightning Data Assimilation on Deterministic and Ensemble Forecasts of Convective Events, J. Atmos. Ocean. Tech., 33, 1801–1823, https://doi.org/10.1175/JTECH-D-15-0188.1, 2016. a
Do, P.-N., Chung, K.-S., Lin, P.-L., Ke, C.-Y., and Ellis, S. M.: Assimilating Retrieved Water Vapor and Radar Data from NCAR S-PolKa: Performance and Validation Using Real Cases, Mon. Weather Rev., 150, 1177–1199, https://doi.org/10.1175/MWR-D-21-0292.1, 2022. a
Dobber, M. and Grandell, J.: Meteosat Third Generation (MTG) Lightning Imager (LI) Instrument Performance and Calibration from User Perspective, in: Proceedings of the 23rd Conference on Characterization and Radiometric Calibration for Remote Sensing (CALCON), 11–14 August 2014,
Utah State University, Logan, Utah, USA, 13 pp., 2014. a
Duruisseau, F., Chambon, P., Wattrelot, E., Barreyat, M., and Mahfouf, J.-F.: Assimilating cloudy and rainy microwave observations from SAPHIR on board Megha Tropiques within the ARPEGE global model, Q. J. Roy. Meteor. Soc., 145, 620–641, https://doi.org/10.1002/qj.3456, 2019. a
Erdmann, F.: Préparation à l'utilisation des observations de l'imageur d'éclairs de Météosat Troisième Génération pour la prévision numérique à courte échéance (Preparation for the use of Meteosat Third Generation Lightning Imager observations in short-term numerical weather prediction), PhD thesis, Université Toulouse 3 – Paul Sabatier, Toulouse, France,
http://thesesups.ups-tlse.fr/4947/ (last access: 27 September 2022), 2020. a
Erdmann, F., Defer, E., Caumont, O., Blakeslee, R. J., Pédeboy, S., and Coquillat, S.: Concurrent satellite and ground-based lightning observations from the Optical Lightning Imaging Sensor (ISS-LIS), the low-frequency network Meteorage and the SAETTA Lightning Mapping Array (LMA) in the northwestern Mediterranean region, Atmos. Meas. Tech., 13, 853–875, https://doi.org/10.5194/amt-13-853-2020, 2020. a, b
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
Federico, S., Avolio, E., Petracca, M., Panegrossi, G., Sanò, P., Casella, D., and Dietrich, S.: Simulating lightning into the RAMS model: implementation and preliminary results, Nat. Hazards Earth Syst. Sci., 14, 2933–2950, https://doi.org/10.5194/nhess-14-2933-2014, 2014. a
Federico, S., Petracca, M., Panegrossi, G., Transerici, C., and Dietrich, S.: Impact of the assimilation of lightning data on the precipitation forecast at different forecast ranges, Adv. Sci. Res., 14, 187–194, https://doi.org/10.5194/asr-14-187-2017, 2017. 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, c, d
Fierro, A. O., Gao, J., Ziegler, C. L., Mansell, E. R., MacGorman, D. R., and Dembrek, S. R.: Evaluation of a Cloud-Scale Lightning Data Assimilation Technique and a 3DVAR Method for the Analysis and Short-Term Forecast of the
29 June 2012 Derecho Event, Mon. Weather Rev., 142, 183–202,
https://doi.org/10.1175/MWR-D-13-00142.1, 2014. a
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, c
Fischer, C., Bouyssel, F., Brousseau, P., El Khatib, R., Pottier, P., Seity,
Y., Wattrelot, E., and Joly, A.: Les modèles opérationnels de prévision
numérique à aire limitée de Météo-France, La Météorologie, 100,
18–28, https://doi.org/10.4267/2042/65139, 2018. a
Formenton, M., Panegrossi, G., Casella, D., Dietrich, S., Mugnai, A., Sanò, P., Di Paola, F., Betz, H.-D., Price, C., and Yair, Y.: Using a cloud electrification model to study relationships between lightning activity and cloud microphysical structure, Nat. Hazards Earth Syst. Sci., 13, 1085–1104, https://doi.org/10.5194/nhess-13-1085-2013, 2013. a
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
Giannaros, T. M., Kotroni, V., and Lagouvardos, K.: WRF-LTNGDA: A lightning
data assimilation technique implemented in the WRF model for improving
precipitation forecasts, Environ. Model. Softw., 76, 54–68,
https://doi.org/10.1016/j.envsoft.2015.11.017, 2016. a
Goodman, S. J., Blakeslee, R. J., Koshak, W. J., Mach, D., Bailey, J., Buechler, D., Carey, L., Schultz, C., Bateman, M., McCaul, E., and Stano, G.: The GOES-R Geostationary Lightning Mapper (GLM), Atmos. Res., 125–126, 34–49, https://doi.org/10.1016/j.atmosres.2013.01.006, 2013. 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, c, d, e, f
Janisková, M. and Lopez, P.: Linearized Physics for Data Assimilation at ECMWF, in: Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications, edited by: Park, S. and Xu, L., Springer, Berlin, Heidelberg, vol. 2, https://doi.org/10.1007/978-3-642-35088-7_11, 2013. a
Järvinen, H. and Undén, P.: Observation screening and background quality control in the ECMWF 3D-Var data assimilation system, Tech. rep. ECMWF,
https://doi.org/10.21957/lyd3q81, 1997. a
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
Kong, R., Xue, M., Fierro, A. O., Jung, Y., Liu, C., Mansell, E. R., and MacGorman, D. R.: Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI EnKF for the Analysis and Short-Term Forecast of a Mesoscale Convective System, Mon. Weather Rev., 148, 2111–2133, https://doi.org/10.1175/MWR-D-19-0192.1, 2020. a
Kummerow, C., Hong, Y., Olson, W. S., Yang, S., Adler, R. F., McCollum, J., Ferraro, R., Petty, G., Shin, D.-B., and Wilheit, T. T.: The Evolution of the Goddard Profiling Algorithm (GPROF) for Rainfall Estimation from Passive Microwave Sensors, J. Appl. Meteorol., 40, 1801–1820, https://doi.org/10.1175/1520-0450(2001)040<1801:TEOTGP>2.0.CO;2, 2001. a
Lagouvardos, K., Kotroni, V., Defer, E., and Bousquet, O.: Study of a heavy precipitation event over southern France, in the frame of HYMEX project: Observational analysis and model results using assimilation of lightning, Atmos. Res., 134, 45–55, https://doi.org/10.1016/j.atmosres.2013.07.003, 2013. a
Lascaux, F., Richard, E., and Pinty, J.-P.: Numerical simulations of three different MAP IOPs and the associated microphysical processes, Q. J. Roy. Meteor. Soc., 132, 1907–1926, https://doi.org/10.1256/qj.05.197, 2006. a
Laurantin, O.: ANTILOPE: hourly rainfall analysis merging radar and rain
gauge data, in: Int. Symp. Weather Radar and Hydrology (WRaH2008), Grenoble and Autrans, France, 10–15 March 2008, 2008. a
Laurantin, O.: ANTILOPE: hourly rainfall analysis over France merging radar
and rain gauges data, in: Proceedings of the 11th International Precipitation Conference, edited by: Leijnse, H. and Uijlenhoet, R.,
KNMI, Ede-Wageningen, the Netherlands, 30 June to 3 July 2013,
2013. a
Liu, P., Yang, Y., Gao, J., Wang, Y., and Wang, C.: An Approach for
Assimilating FY4 Lightning and Cloud Top Height Data Using 3DVAR,
Front. Earth Sci., 8, 288, https://doi.org/10.3389/feart.2020.00288, 2020. a
Lynn, B. H., Kelman, G., and Ellrod, G.: An Evaluation of the Efficacy of Using Observed Lightning to Improve Convective Lightning Forecasts, Weather Forecast., 30, 405–423, https://doi.org/10.1175/WAF-D-13-00028.1, 2015. a, b
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, b
Mansell, E. R., Ziegler, C. L., and MacGorman, D. R.: A Lightning Data
Assimilation Technique for Mesoscale Forecast Models, Mon. Weather Rev.,
135, 1732–1748, https://doi.org/10.1175/MWR3387.1, 2007. 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
McCaul, Eugene W., J., Goodman, S. J., LaCasse, K. M., and Cecil, D. J.: Forecasting Lightning Threat Using Cloud-Resolving Model Simulations, Weather Forecast., 24, 709–729, https://doi.org/10.1175/2008WAF2222152.1, 2009. a, b, c
Michel, Y.: Revisiting Fisher's approach to the handling of horizontal spatial correlations of observation errors in a variational framework, Q. J. Roy. Meteor. Soc., 144, 2011–2025, https://doi.org/10.1002/qj.3249, 2018. a
Olson, W. S., Kummerow, C. D., Heymsfield, G. M., and Giglio, L.: A Method for Combined PassiveActive Microwave Retrievals of Cloud and Precipitation Profiles, J. Appl. Meteorol., 35, 1763–1789,
https://doi.org/10.1175/1520-0450(1996)035<1763:AMFCPM>2.0.CO;2, 1996. a
Papadopoulos, A., Chronis, T., and Anagnostou, E.: Improving Convective
Precipitation Forecasting through Assimilation of Regional Lightning
Measurements in a Mesoscale Model, Mon. Weather Rev., 133, 1961–1977,
https://doi.org/10.1175/MWR2957.1, 2005. a
Pédeboy, S.: Analysis of the French lightning locating system location accuracy, 2015 International Symposium on Lightning Protection (XIII SIPDA), Balneário Camboriú, Brazil, 28 September–2 October 2015, 337–341, https://doi.org/10.1109/SIPDA.2015.7339299, 2015. a
Pergaud, J., Masson, V., Malardel, S., and Couvreux, F.: A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction, Bound.-Lay. Meteorol., 132, 83–106, https://doi.org/10.1007/s10546-009-9388-0, 2009. a
Pessi, A. T. and Businger, S.: The Impact of Lightning Data Assimilation on a Winter Storm Simulation over the North Pacific Ocean, Mon. Weather Rev., 137, 3177–3195, https://doi.org/10.1175/2009MWR2765.1, 2009. 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
Price, C. and Rind, D.: What determines the cloud-to-ground lightning fraction in thunderstorms?, Geophys. Res. Lett., 20, 463–466,
https://doi.org/10.1029/93GL00226, 1993.
a
Qie, X., Zhu, R., Yuan, T., Wu, X., Li, W., and Liu, D.: Application of total-lightning data assimilation in a mesoscale convective system based on the WRF model, Atmos. Res., 145–146, 255–266, https://doi.org/10.1016/j.atmosres.2014.04.012, 2014. a
Rabier, F.: Importance of Data: A Meteorological Perspective, in: Ocean Weather Forecasting, edited by: Chassignet, E. and Verron, J., Chap. 12, Springer, Dordrecht, 343–360, https://doi.org/10.1007/1-4020-4028-8_12,
2006. a
Roberts, N. and Lean, H.: 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
Schulz, W., Diendorfer, G., Pedeboy, S., and Poelman, D. R.: The European lightning location system EUCLID – Part 1: Performance analysis and validation, Nat. Hazards Earth Syst. Sci., 16, 595–605, https://doi.org/10.5194/nhess-16-595-2016, 2016. a
Vié, B., Nuissier, O., and Ducrocq, V.: Cloud-Resolving Ensemble Simulations of Mediterranean Heavy Precipitating Events: Uncertainty on Initial Conditions and Lateral Boundary Conditions, Mon. Weather Rev., 139, 403–423, https://doi.org/10.1175/2010MWR3487.1, 2011. a
Wang, H., Sun, J., Fan, S., and Huang, X.-Y.: Indirect Assimilation of Radar Reflectivity with WRF 3D-Var and Its Impact on Prediction of Four Summertime Convective Events, J. Appl. Meteorol. Clim., 52, 889–902,
https://doi.org/10.1175/JAMC-D-12-0120.1, 2013. a
Wang, H., Liu, Y., Cheng, W. Y. Y., Zhao, T., Xu, M., Liu, Y., Shen, S., Calhoun, K. M., and Fierro, A. O.: Improving Lightning and Precipitation Prediction of Severe Convection Using Lightning Data Assimilation With NCAR
WRF-RTFDDA, J. Geophys. Res.-Atmos., 122, 12,296–12,316, https://doi.org/10.1002/2017JD027340, 2017. a
Wang, H., Liu, Y., Zhao, T., Liu, Y., Xu, M., Shen, S., Jiang, Y., Yang, H., and Feng, S.: Continuous Assimilation of Lightning Data Using Time-Lagged Ensembles for a Convection-Allowing Numerical Weather Prediction Model, J. Geophys. Res.-Atmos., 123, 9652–9673, https://doi.org/10.1029/2018JD028494, 2018. a
Wang, Y., Yang, Y., and Wang, C.: Improving forecasting of strong convection by assimilating cloud-to-ground lightning data using the physical initialization method, Atmos. Res., 150, 31–41,
https://doi.org/10.1016/j.atmosres.2014.06.017, 2014. a
Wang, Y., Yang, Y., Liu, D., Zhang, D., Yao, W., and Wang, C.: A Case Study of Assimilating Lightning-Proxy Relative Humidity with WRF-3DVAR, Atmosphere, 8, 20, https://doi.org/10.3390/atmos8030055, 2017. a, b
Wattrelot, E., Caumont, O., and Mahfouf, J.-F.: Operational Implementation of the 1D+3D-Var Assimilation Method of Radar Reflectivity Data in the AROME Model, Mon. Weather Rev., 142, 1852–1873,
https://doi.org/10.1175/MWR-D-13-00230.1, 2014. a, b
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
Yair, Y., Lynn, B., Price, C., Kotroni, V., Lagouvardos, K., Morin, E., Mugnai, A., and Llasat, M. d. C.: 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
Zhang, D., Cummins, K. L., Bitzer, P. M., and Koshak, W. J.: Evaluation of the Performance Characteristics of the Lightning Imaging Sensor, J. Atmos. Ocean. Tech., 36, 1015–1030, https://doi.org/10.1175/JTECH-D-18-0173.1, 2019. a
Short summary
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.
This work develops a novel lightning data assimilation (LDA) technique to make use of Meteosat...
Altmetrics
Final-revised paper
Preprint