Articles | Volume 19, issue 8
https://doi.org/10.5194/nhess-19-1839-2019
© Author(s) 2019. 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-19-1839-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Aug 2019
Research article |
| 23 Aug 2019
| 23 Aug 2019
The impact of lightning and radar reflectivity factor data assimilation on the very short-term rainfall forecasts of RAMS@ISAC: application to two case studies in Italy
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Rosa Claudia Torcasio
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Elenio Avolio
ISAC-CNR, zona Industriale comparto 15, 88046, Lamezia Terme, Italy
Olivier Caumont
CNRM UMR 3589, University of Toulouse, Météo-France, CNRS, 42 avenue G. Coriolis, 31057 Toulouse, France
Mario Montopoli
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Luca Baldini
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Gianfranco Vulpiani
Dipartimento Protezione Civile Nazionale Ufficio III – Attività Tecnico Scientifiche per la Previsione e Prevenzione dei Rischi, 00189, Rome, Italy
Stefano Dietrich
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Related authors
Stefano Federico, Rosa Claudia Torcasio, Claudio Transerici, Mario Montopoli, Cinzia Cambiotti, Francesco Manconi, Alessandro Battaglia, and Maryam Pourshamsi
EGUsphere, https://doi.org/10.5194/egusphere-2025-2095, https://doi.org/10.5194/egusphere-2025-2095, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
The Wind Velocity Radar Nephoscope (WIVERN) mission will be the first space-based mission to provide global in-cloud wind, cloud and precipitation measurements. The mission is proposed as a candidate for the ESA Earth Explorer 11. Its data could be beneficial to several sectors, including numerical weather prediction performance enhancement. This paper aims to contribute to the last point by analyzing the impact that WIVERN would have in the case of a Tropical-like cyclone event.
Rosa Claudia Torcasio, Alessandra Mascitelli, Eugenio Realini, Stefano Barindelli, Giulio Tagliaferro, Silvia Puca, Stefano Dietrich, and Stefano Federico
Nat. Hazards Earth Syst. Sci., 23, 3319–3336, https://doi.org/10.5194/nhess-23-3319-2023, https://doi.org/10.5194/nhess-23-3319-2023, 2023
Short summary
Short summary
This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.
Monica Campanelli, Alessandra Mascitelli, Paolo Sanò, Henri Diémoz, Victor Estellés, Stefano Federico, Anna Maria Iannarelli, Francesca Fratarcangeli, Augusto Mazzoni, Eugenio Realini, Mattia Crespi, Olivier Bock, Jose A. Martínez-Lozano, and Stefano Dietrich
Atmos. Meas. Tech., 11, 81–94, https://doi.org/10.5194/amt-11-81-2018, https://doi.org/10.5194/amt-11-81-2018, 2018
Short summary
Short summary
The estimation of precipitable water vapour (W) content is of great interest in both meteorological and climatological studies. Sun photometers allowed the development of W automatic estimations with high temporal resolution. A new methodology, based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site, has been presented providing good results.
Stefano Federico, Marco Petracca, Giulia Panegrossi, Claudio Transerici, and Stefano Dietrich
Adv. Sci. Res., 14, 187–194, https://doi.org/10.5194/asr-14-187-2017, https://doi.org/10.5194/asr-14-187-2017, 2017
Short summary
Short summary
This study investigates the impact of using lightning data on the precipitation forecast at different forecast ranges (3–24 h). Twenty case studies, occurred over Italy in fall 2012, are selected to show the impact.
Results show the important and positive impact of using lightning data to improve the precipitation forecast. The time range, however, is very important because the performance decreases steadily and substantially with forecasting time.
Stefano Federico, Rosa Claudia Torcasio, Paolo Sanò, Daniele Casella, Monica Campanelli, Jan Fokke Meirink, Ping Wang, Stefania Vergari, Henri Diémoz, and Stefano Dietrich
Atmos. Meas. Tech., 10, 2337–2352, https://doi.org/10.5194/amt-10-2337-2017, https://doi.org/10.5194/amt-10-2337-2017, 2017
Short summary
Short summary
In this paper we evaluate the performance of two estimates of the global horizontal irradiance (GHI), one derived from the Meteosat Second Generation and one from a meteorological model (Regional Atmospheric Modeling System) forecast. The focus area is Italy, and the performance is evaluated for 12 pyranometers spanning a range of climate conditions, from Mediterranean maritime to Alpine.
Stefano Federico, Marco Petracca, Giulia Panegrossi, and Stefano Dietrich
Nat. Hazards Earth Syst. Sci., 17, 61–76, https://doi.org/10.5194/nhess-17-61-2017, https://doi.org/10.5194/nhess-17-61-2017, 2017
Short summary
Short summary
The motivation of this study is to use lightning observations to improve the precipitation forecast at the short range (3 h). For this purpose 20 case studies, occurring in fall 2012, were analyzed using a meteorological model, whose set-up is applicable in real-time weather forecasting. Lightning observations were provided by the LINET network. Results show a systematic improvement of the 3 h precipitation forecast when lightning observations are used.
Elenio Avolio, Rosa Claudia Torcasio, Teresa Lo Feudo, Claudia Roberta Calidonna, Daniele Contini, and Stefano Federico
Adv. Sci. Res., 13, 69–73, https://doi.org/10.5194/asr-13-69-2016, https://doi.org/10.5194/asr-13-69-2016, 2016
Short summary
Short summary
The improvement of the Solar and Wind short-term forecasting represents a critical goal for the weather prediction community and is of great importance for a better estimation of power production from solar and wind farms.
In this work we analyze the performance of two deterministic models operational at ISAC-CNR for the prediction of short-wave irradiance and wind speed, at two experimental sites in southern Italy.
Rosa Claudia Torcasio, Stefano Federico, Claudia Roberta Calidonna, Elenio Avolio, Oxana Drofa, Tony Christian Landi, Piero Malguzzi, Andrea Buzzi, and Paolo Bonasoni
Ann. Geophys., 34, 347–356, https://doi.org/10.5194/angeo-34-347-2016, https://doi.org/10.5194/angeo-34-347-2016, 2016
Short summary
Short summary
Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market.
This work shows the application of a technique to improve wind forecasting. The study area is southern Italy.
L. Tiriolo, R. C. Torcasio, S. Montesanti, A. M. Sempreviva, C. R. Calidonna, C. Transerici, and S. Federico
Adv. Sci. Res., 12, 37–44, https://doi.org/10.5194/asr-12-37-2015, https://doi.org/10.5194/asr-12-37-2015, 2015
Short summary
Short summary
We show a study of the prediction of power production of a wind farm located in Central Italy using RAMS model for wind speed forecast.
S. Federico, E. Avolio, M. Petracca, G. Panegrossi, P. Sanò, D. Casella, and S. Dietrich
Nat. Hazards Earth Syst. Sci., 14, 2933–2950, https://doi.org/10.5194/nhess-14-2933-2014, https://doi.org/10.5194/nhess-14-2933-2014, 2014
Short summary
Short summary
This paper shows the implementation of a simple model for simulating lightning into the RAMS model.
The methodology is applied to six case studies that occurred in central Italy and the results are verified against LINET observations.
Advantages and weaknesses of the methodology are discussed.
S. Federico
Atmos. Meas. Tech., 6, 3563–3576, https://doi.org/10.5194/amt-6-3563-2013, https://doi.org/10.5194/amt-6-3563-2013, 2013
Stefano Federico, Rosa Claudia Torcasio, Claudio Transerici, Mario Montopoli, Cinzia Cambiotti, Francesco Manconi, Alessandro Battaglia, and Maryam Pourshamsi
EGUsphere, https://doi.org/10.5194/egusphere-2025-2095, https://doi.org/10.5194/egusphere-2025-2095, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
The Wind Velocity Radar Nephoscope (WIVERN) mission will be the first space-based mission to provide global in-cloud wind, cloud and precipitation measurements. The mission is proposed as a candidate for the ESA Earth Explorer 11. Its data could be beneficial to several sectors, including numerical weather prediction performance enhancement. This paper aims to contribute to the last point by analyzing the impact that WIVERN would have in the case of a Tropical-like cyclone event.
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
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.
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.
Florian Pantillon, Silvio Davolio, Elenio Avolio, Carlos Calvo-Sancho, Diego Saul Carrió, Stavros Dafis, Emanuele Silvio Gentile, Juan Jesus Gonzalez-Aleman, Suzanne Gray, Mario Marcello Miglietta, Platon Patlakas, Ioannis Pytharoulis, Didier Ricard, Antonio Ricchi, Claudio Sanchez, and Emmanouil Flaounas
Weather Clim. Dynam., 5, 1187–1205, https://doi.org/10.5194/wcd-5-1187-2024, https://doi.org/10.5194/wcd-5-1187-2024, 2024
Short summary
Short summary
Cyclone Ianos of September 2020 was a high-impact but poorly predicted medicane (Mediterranean hurricane). A community effort of numerical modelling provides robust results to improve prediction. It is found that the representation of local thunderstorms controlled the interaction of Ianos with a jet stream at larger scales and its subsequent evolution. The results help us understand the peculiar dynamics of medicanes and provide guidance for the next generation of weather and climate models.
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.
Rosa Claudia Torcasio, Alessandra Mascitelli, Eugenio Realini, Stefano Barindelli, Giulio Tagliaferro, Silvia Puca, Stefano Dietrich, and Stefano Federico
Nat. Hazards Earth Syst. Sci., 23, 3319–3336, https://doi.org/10.5194/nhess-23-3319-2023, https://doi.org/10.5194/nhess-23-3319-2023, 2023
Short summary
Short summary
This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.
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
Short summary
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.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
Short summary
Short summary
The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
Short summary
Short summary
The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
Gianluca Di Natale, David D. Turner, Giovanni Bianchini, Massimo Del Guasta, Luca Palchetti, Alessandro Bracci, Luca Baldini, Tiziano Maestri, William Cossich, Michele Martinazzo, and Luca Facheris
Atmos. Meas. Tech., 15, 7235–7258, https://doi.org/10.5194/amt-15-7235-2022, https://doi.org/10.5194/amt-15-7235-2022, 2022
Short summary
Short summary
In this paper, we describe a new approach to test the consistency of the precipitating ice cloud optical and microphysical properties in Antarctica, Dome C, retrieved from hyperspectral measurements in the far-infrared, with the reflectivity detected by a co-located micro rain radar operating at 24 GHz. The retrieved ice crystal sizes were found in accordance with the direct measurements of an optical imager, also installed at Dome C, which can collect the falling ice particles.
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.
Monica Campanelli, Henri Diémoz, Anna Maria Siani, Alcide di Sarra, Anna Maria Iannarelli, Rei Kudo, Gabriele Fasano, Giampietro Casasanta, Luca Tofful, Marco Cacciani, Paolo Sanò, and Stefano Dietrich
Atmos. Meas. Tech., 15, 1171–1183, https://doi.org/10.5194/amt-15-1171-2022, https://doi.org/10.5194/amt-15-1171-2022, 2022
Short summary
Short summary
The aerosol optical depth (AOD) characteristics in an urban area of Rome were retrieved over a period of 11 years (2010–2020) to determine, for the first time, their effect on the incoming ultraviolet (UV) solar radiation. The surface forcing efficiency shows that the AOD is the primary parameter affecting the surface irradiance in Rome, and it is found to be greater for smaller zenith angles and for larger and more absorbing particles in the UV range (such as, e.g., mineral dust).
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.
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.
Elenio Avolio, Ottavio Cavalcanti, Luca Furnari, Alfonso Senatore, and Giuseppe Mendicino
Nat. Hazards Earth Syst. Sci., 19, 1619–1627, https://doi.org/10.5194/nhess-19-1619-2019, https://doi.org/10.5194/nhess-19-1619-2019, 2019
Short summary
Short summary
This is the first scientific report of the flash flood of 20 August 2018 on “Raganello Gorge” (Southern Italy), an extreme event with rather specific features (very localized in space and time), which unfortunately caused 10 victims. The meteo-hydrological dynamics were reasonably reconstructed and the forecasting skills were evaluated using an innovative modelling approach, including fully coupled atmospheric-hydrological modelling and improved representation of Sea Surface Temperature.
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.
Matthieu Poret, Stefano Corradini, Luca Merucci, Antonio Costa, Daniele Andronico, Mario Montopoli, Gianfranco Vulpiani, and Valentin Freret-Lorgeril
Atmos. Chem. Phys., 18, 4695–4714, https://doi.org/10.5194/acp-18-4695-2018, https://doi.org/10.5194/acp-18-4695-2018, 2018
Short summary
Short summary
This study aims at proposing a method to better assess the initial magma fragmentation produced during explosive volcanic eruptions. We worked on merging field, radar, and satellite data to estimate the total grain-size distribution, which is used within simulations to reconstruct the tephra loading and far-travelling airborne ash dispersal. This approach is applied to 23 November 2013, giving the very fine ash fraction related to volcanic hazards (e.g. air traffic safety).
Monica Campanelli, Alessandra Mascitelli, Paolo Sanò, Henri Diémoz, Victor Estellés, Stefano Federico, Anna Maria Iannarelli, Francesca Fratarcangeli, Augusto Mazzoni, Eugenio Realini, Mattia Crespi, Olivier Bock, Jose A. Martínez-Lozano, and Stefano Dietrich
Atmos. Meas. Tech., 11, 81–94, https://doi.org/10.5194/amt-11-81-2018, https://doi.org/10.5194/amt-11-81-2018, 2018
Short summary
Short summary
The estimation of precipitable water vapour (W) content is of great interest in both meteorological and climatological studies. Sun photometers allowed the development of W automatic estimations with high temporal resolution. A new methodology, based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site, has been presented providing good results.
Ida Maiello, Sabrina Gentile, Rossella Ferretti, Luca Baldini, Nicoletta Roberto, Errico Picciotti, Pier Paolo Alberoni, and Frank Silvio Marzano
Hydrol. Earth Syst. Sci., 21, 5459–5476, https://doi.org/10.5194/hess-21-5459-2017, https://doi.org/10.5194/hess-21-5459-2017, 2017
Short summary
Short summary
In this paper the impact of multiple radar reflectivity data assimilation on a flash flood event occurred during SOP1 of the HyMeX campaign has been evaluated: the aim is to build a regionally tuned numerical prediction model and decision-support system for environmental civil protection services within the central Italian regions. The results are encouraging, but a significant number of flash flood cases and a deeper analysis of the meteorology of the region are necessary.
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.
Stefano Federico, Marco Petracca, Giulia Panegrossi, Claudio Transerici, and Stefano Dietrich
Adv. Sci. Res., 14, 187–194, https://doi.org/10.5194/asr-14-187-2017, https://doi.org/10.5194/asr-14-187-2017, 2017
Short summary
Short summary
This study investigates the impact of using lightning data on the precipitation forecast at different forecast ranges (3–24 h). Twenty case studies, occurred over Italy in fall 2012, are selected to show the impact.
Results show the important and positive impact of using lightning data to improve the precipitation forecast. The time range, however, is very important because the performance decreases steadily and substantially with forecasting time.
Stefano Federico, Rosa Claudia Torcasio, Paolo Sanò, Daniele Casella, Monica Campanelli, Jan Fokke Meirink, Ping Wang, Stefania Vergari, Henri Diémoz, and Stefano Dietrich
Atmos. Meas. Tech., 10, 2337–2352, https://doi.org/10.5194/amt-10-2337-2017, https://doi.org/10.5194/amt-10-2337-2017, 2017
Short summary
Short summary
In this paper we evaluate the performance of two estimates of the global horizontal irradiance (GHI), one derived from the Meteosat Second Generation and one from a meteorological model (Regional Atmospheric Modeling System) forecast. The focus area is Italy, and the performance is evaluated for 12 pyranometers spanning a range of climate conditions, from Mediterranean maritime to Alpine.
Stefano Federico, Marco Petracca, Giulia Panegrossi, and Stefano Dietrich
Nat. Hazards Earth Syst. Sci., 17, 61–76, https://doi.org/10.5194/nhess-17-61-2017, https://doi.org/10.5194/nhess-17-61-2017, 2017
Short summary
Short summary
The motivation of this study is to use lightning observations to improve the precipitation forecast at the short range (3 h). For this purpose 20 case studies, occurring in fall 2012, were analyzed using a meteorological model, whose set-up is applicable in real-time weather forecasting. Lightning observations were provided by the LINET network. Results show a systematic improvement of the 3 h precipitation forecast when lightning observations are used.
Martina Buiat, Federico Porcù, and Stefano Dietrich
Atmos. Meas. Tech., 10, 221–230, https://doi.org/10.5194/amt-10-221-2017, https://doi.org/10.5194/amt-10-221-2017, 2017
Short summary
Short summary
The cloud radar on board the NASA CloudSat mission provides information on the vertical structure of the cloud that, in the present study, is matched to ground-based measurements of lightning occurrences. The aim of this research was to study the relationship between the ice content of the cloud and its capability to produce lightning. Results show the importance of high ice content, especially close to the cloud top, for producing lightning.
Paolo Sanò, Giulia Panegrossi, Daniele Casella, Anna C. Marra, Francesco Di Paola, and Stefano Dietrich
Atmos. Meas. Tech., 9, 5441–5460, https://doi.org/10.5194/amt-9-5441-2016, https://doi.org/10.5194/amt-9-5441-2016, 2016
Short summary
Short summary
The objective of this paper is to describe the development and evaluate the performance of a totally new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2), an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track ATMS radiometer measurements.
Elenio Avolio, Rosa Claudia Torcasio, Teresa Lo Feudo, Claudia Roberta Calidonna, Daniele Contini, and Stefano Federico
Adv. Sci. Res., 13, 69–73, https://doi.org/10.5194/asr-13-69-2016, https://doi.org/10.5194/asr-13-69-2016, 2016
Short summary
Short summary
The improvement of the Solar and Wind short-term forecasting represents a critical goal for the weather prediction community and is of great importance for a better estimation of power production from solar and wind farms.
In this work we analyze the performance of two deterministic models operational at ISAC-CNR for the prediction of short-wave irradiance and wind speed, at two experimental sites in southern Italy.
Rosa Claudia Torcasio, Stefano Federico, Claudia Roberta Calidonna, Elenio Avolio, Oxana Drofa, Tony Christian Landi, Piero Malguzzi, Andrea Buzzi, and Paolo Bonasoni
Ann. Geophys., 34, 347–356, https://doi.org/10.5194/angeo-34-347-2016, https://doi.org/10.5194/angeo-34-347-2016, 2016
Short summary
Short summary
Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market.
This work shows the application of a technique to improve wind forecasting. The study area is southern Italy.
N. Roberto, E. Adirosi, L. Baldini, D. Casella, S. Dietrich, P. Gatlin, G. Panegrossi, M. Petracca, P. Sanò, and A. Tokay
Atmos. Meas. Tech., 9, 535–552, https://doi.org/10.5194/amt-9-535-2016, https://doi.org/10.5194/amt-9-535-2016, 2016
Short summary
Short summary
This study examines various microphysical properties of liquid and solid hydrometeors to investigate their relationship with lightning activity. Measurements were collected from the Polar 55C dual-polarization radar, a 2-DVD, and LINET. From the analysis of three significant case studies, linear relations between the total mass of graupel and the number of strokes were found. Results point out the key role of ice mass in determining the electrical charging of convective clouds.
G. Vulpiani, L. Baldini, and N. Roberto
Atmos. Meas. Tech., 8, 4681–4698, https://doi.org/10.5194/amt-8-4681-2015, https://doi.org/10.5194/amt-8-4681-2015, 2015
Short summary
Short summary
This work shows the effective monitoring of intense precipitation events in the Mediterranean area by an operational X-band dual-polarization radar operated in south Italy by the Department of Civil Protection. Two severe hail-bearing storms, causing high attenuation, have been described in terms of the polarimetric radar signatures and estimated rainfall fields. The comparative analysis of the radar observations enabled the triggering hail formation and precipitation process to be inferred.
L. Tiriolo, R. C. Torcasio, S. Montesanti, A. M. Sempreviva, C. R. Calidonna, C. Transerici, and S. Federico
Adv. Sci. Res., 12, 37–44, https://doi.org/10.5194/asr-12-37-2015, https://doi.org/10.5194/asr-12-37-2015, 2015
Short summary
Short summary
We show a study of the prediction of power production of a wind farm located in Central Italy using RAMS model for wind speed forecast.
D. Casella, G. Panegrossi, P. Sanò, L. Milani, M. Petracca, and S. Dietrich
Atmos. Meas. Tech., 8, 1217–1232, https://doi.org/10.5194/amt-8-1217-2015, https://doi.org/10.5194/amt-8-1217-2015, 2015
Short summary
Short summary
The CCA algorithm is applicable to any modern passive microwave radiometer on board polar orbiting satellites; it has been developed using a data set of co-located SSMIS and TRMM-PR measurements and AMSU-MHS and TRMM-PR measurements. The algorithm shows a small rate of false alarms and superior detection capability and can efficiently detect (POD between 0.55 and 0.71) minimum rain rate varying from 0.14 mm/h (AMSU over ocean) to 0.41 (SSMIS over coast).
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
P. Sanò, G. Panegrossi, D. Casella, F. Di Paola, L. Milani, A. Mugnai, M. Petracca, and S. Dietrich
Atmos. Meas. Tech., 8, 837–857, https://doi.org/10.5194/amt-8-837-2015, https://doi.org/10.5194/amt-8-837-2015, 2015
L. Milani, F. Porcù, D. Casella, S. Dietrich, G. Panegrossi, M. Petracca, and P. Sanò
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-141-2015, https://doi.org/10.5194/tcd-9-141-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
The aim of this work is to show that the CloudSat Cloud Profiling Radar (CPR) can be a valuable source of snowfall rate data in Antarctica that can be used at different temporal scales. Two years of CloudSat data over Antarctica are analyzed and two different approaches for precipitation estimates are considered. The results show that CPR can provide valuable support to the sparse network of ground-based instruments both for numerical model validation and climatological studies.
S. Federico, E. Avolio, M. Petracca, G. Panegrossi, P. Sanò, D. Casella, and S. Dietrich
Nat. Hazards Earth Syst. Sci., 14, 2933–2950, https://doi.org/10.5194/nhess-14-2933-2014, https://doi.org/10.5194/nhess-14-2933-2014, 2014
Short summary
Short summary
This paper shows the implementation of a simple model for simulating lightning into the RAMS model.
The methodology is applied to six case studies that occurred in central Italy and the results are verified against LINET observations.
Advantages and weaknesses of the methodology are discussed.
I. Maiello, R. Ferretti, S. Gentile, M. Montopoli, E. Picciotti, F. S. Marzano, and C. Faccani
Atmos. Meas. Tech., 7, 2919–2935, https://doi.org/10.5194/amt-7-2919-2014, https://doi.org/10.5194/amt-7-2919-2014, 2014
R. Ferretti, E. Pichelli, S. Gentile, I. Maiello, D. Cimini, S. Davolio, M. M. Miglietta, G. Panegrossi, L. Baldini, F. Pasi, F. S. Marzano, A. Zinzi, S. Mariani, M. Casaioli, G. Bartolini, N. Loglisci, A. Montani, C. Marsigli, A. Manzato, A. Pucillo, M. E. Ferrario, V. Colaiuda, and R. Rotunno
Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, https://doi.org/10.5194/hess-18-1953-2014, 2014
S. Puca, F. Porcu, A. Rinollo, G. Vulpiani, P. Baguis, S. Balabanova, E. Campione, A. Ertürk, S. Gabellani, R. Iwanski, M. Jurašek, J. Kaňák, J. Kerényi, G. Koshinchanov, G. Kozinarova, P. Krahe, B. Lapeta, E. Lábó, L. Milani, L'. Okon, A. Öztopal, P. Pagliara, F. Pignone, C. Rachimow, N. Rebora, E. Roulin, I. Sönmez, A. Toniazzo, D. Biron, D. Casella, E. Cattani, S. Dietrich, F. Di Paola, S. Laviola, V. Levizzani, D. Melfi, A. Mugnai, G. Panegrossi, M. Petracca, P. Sanò, F. Zauli, P. Rosci, L. De Leonibus, E. Agosta, and F. Gattari
Nat. Hazards Earth Syst. Sci., 14, 871–889, https://doi.org/10.5194/nhess-14-871-2014, https://doi.org/10.5194/nhess-14-871-2014, 2014
M. Montopoli, G. Vulpiani, D. Cimini, E. Picciotti, and F. S. Marzano
Atmos. Meas. Tech., 7, 537–552, https://doi.org/10.5194/amt-7-537-2014, https://doi.org/10.5194/amt-7-537-2014, 2014
S. Federico
Atmos. Meas. Tech., 6, 3563–3576, https://doi.org/10.5194/amt-6-3563-2013, https://doi.org/10.5194/amt-6-3563-2013, 2013
D. Cimini, F. Romano, E. Ricciardelli, F. Di Paola, M. Viggiano, F. S. Marzano, V. Colaiuda, E. Picciotti, G. Vulpiani, and V. Cuomo
Atmos. Meas. Tech., 6, 3181–3196, https://doi.org/10.5194/amt-6-3181-2013, https://doi.org/10.5194/amt-6-3181-2013, 2013
A. Rinollo, G. Vulpiani, S. Puca, P. Pagliara, J. Kaňák, E. Lábó, L'. Okon, E. Roulin, P. Baguis, E. Cattani, S. Laviola, and V. Levizzani
Nat. Hazards Earth Syst. Sci., 13, 2695–2705, https://doi.org/10.5194/nhess-13-2695-2013, https://doi.org/10.5194/nhess-13-2695-2013, 2013
E. Picciotti, F. S. Marzano, E. N. Anagnostou, J. Kalogiros, Y. Fessas, A. Volpi, V. Cazac, R. Pace, G. Cinque, L. Bernardini, K. De Sanctis, S. Di Fabio, M. Montopoli, M. N. Anagnostou, A. Telleschi, E. Dimitriou, and J. Stella
Nat. Hazards Earth Syst. Sci., 13, 1229–1241, https://doi.org/10.5194/nhess-13-1229-2013, https://doi.org/10.5194/nhess-13-1229-2013, 2013
M. Formenton, G. Panegrossi, D. Casella, S. Dietrich, A. Mugnai, P. Sanò, F. Di Paola, H.-D. Betz, C. Price, and Y. Yair
Nat. Hazards Earth Syst. Sci., 13, 1085–1104, https://doi.org/10.5194/nhess-13-1085-2013, https://doi.org/10.5194/nhess-13-1085-2013, 2013
Related subject area
Atmospheric, Meteorological and Climatological Hazards
Temporal dynamic vulnerability – impact of antecedent events on residential building losses to wind storm events in Germany
Verifying the relationships among the variabilities of summer rainfall extremes over Japan in the d4PDF climate ensemble, Pacific sea surface temperature, and monsoon activity
Tree fall along railway lines: modelling the impact of wind and other meteorological factors
The probabilistic skill of extended-range heat wave forecasts over Europe
An appraisal of the value of simulated weather data for quantifying coastal flood hazard in the Netherlands
Insights into thunderstorm characteristics from geostationary lightning jump and dive observations
The unique features in the 4 d widespread extreme rainfall event over North China in July 2023
Classifying extratropical cyclones and their impact on Finland's electricity grid: insights from 92 damaging windstorms
Evaluation of machine learning approaches for large-scale agricultural drought forecasts to improve monitoring and preparedness in Brazil
Soil moisture–atmosphere coupling strength over central Europe in the recent warming climate
A data-driven framework for assessing climatic impact drivers in the context of food security
Soil conditioner mixtures as an agricultural management alternative to mitigate drought impacts: a proof of concept
Insights from hailstorm track analysis in European climate change simulations
Extreme heat and mortality in the State of Rio de Janeiro in the 2023/24 season: attribution to climate change and ENSO
Compound winter low-wind and cold events impacting the French electricity system: observed evolution and role of large-scale circulation
Probabilistic hazard analysis of the gas emission of Mefite d'Ansanto, southern Italy
Are heavy-rainfall events a major trigger of associated natural hazards along the German rail network?
Brief communication: Forecasting extreme precipitation from atmospheric rivers in New Zealand
The record-breaking precipitation event of December 2022 in Portugal
Compound events in Germany in 2018: drivers and case studies
Indirect assimilation of radar reflectivity data with an adaptive hydrometer retrieval scheme for the short-term severe weather forecasts
Assimilation of temperature and relative humidity observations from personal weather stations in AROME-France
The anomalously thundery month of June 1925 in southwest Spain: description and synoptic analysis
Spatial identification of regions exposed to multi-hazards at the pan-European level
Classification of North Atlantic and European extratropical cyclones using multiple measures of intensity
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?
Is considering runs (in)consistency so useless for weather forecasting?
Reconstructing hail days in Switzerland with statistical models (1959–2022)
Exploring the interplay between observed warming, atmospheric circulation, and soil-atmosphere feedbacks on heatwaves in a temperate mountain region
High-Resolution Data Assimilation for Two Maritime Extreme Weather Events: A comparison between 3DVar and EnKF
Reask UTC: a machine learning modeling framework to generate climate connected tropical cyclone event sets globally
Historical changes in drought characteristics and its impact on vegetation cover over Madagascar
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?
Invited perspectives: Thunderstorm Intensification from Mountains to Plains
Intense rains in Israel associated with the train effect
Review article: The growth in compound weather events research in the decade since SREX
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
Impact-based temporal clustering of multiple meteorological hazard types in southwestern Germany
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
The ability of a stochastic regional weather generator to reproduce heavy precipitation events across scales
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
Andreas Trojand, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 25, 2331–2350, https://doi.org/10.5194/nhess-25-2331-2025, https://doi.org/10.5194/nhess-25-2331-2025, 2025
Short summary
Short summary
The study investigates how the intensity of previous windstorm events and the time between two events affect the vulnerability of residential buildings in Germany. By analyzing 23 years of data, it was found that higher intensity of previous events generally reduces vulnerability in subsequent storms, while shorter intervals between events increase vulnerability. The results emphasize the approach of considering vulnerability in risk assessments as temporally dynamic.
Shao-Yi Lee, Sicheng He, and Tetsuya Takemi
Nat. Hazards Earth Syst. Sci., 25, 2225–2253, https://doi.org/10.5194/nhess-25-2225-2025, https://doi.org/10.5194/nhess-25-2225-2025, 2025
Short summary
Short summary
The authors performed verification on the relationships between extreme monsoon rainfall over Japan and Pacific sea surface temperature variability in the “database for Policy Decision-making for Future climate changes” (d4PDF). Observations showed widespread weak relationships between hourly extremes and the warming mode but reversed relationships between daily extremes and the decadal variability mode. Biases in d4PDF could be explained by the monsoon's slower movement over Japan in the model.
Rike Lorenz, Nico Becker, Barry Gardiner, Uwe Ulbrich, Marc Hanewinkel, and Benjamin Schmitz
Nat. Hazards Earth Syst. Sci., 25, 2179–2196, https://doi.org/10.5194/nhess-25-2179-2025, https://doi.org/10.5194/nhess-25-2179-2025, 2025
Short summary
Short summary
Tree fall events have an impact on forests and transport systems. Our study explored tree fall in relation to wind and other weather conditions. We used tree fall data along railway lines and ERA5 and radar meteorological data to build a logistic regression model. We found that high and prolonged wind speeds, wet conditions, and high air density increase tree fall risk. These factors might change in the changing climate, which in return will change risks for trees, forests and transport.
Natalia Korhonen, Otto Hyvärinen, Virpi Kollanus, Timo Lanki, Juha Jokisalo, Risto Kosonen, David S. Richardson, and Kirsti Jylhä
Nat. Hazards Earth Syst. Sci., 25, 1865–1879, https://doi.org/10.5194/nhess-25-1865-2025, https://doi.org/10.5194/nhess-25-1865-2025, 2025
Short summary
Short summary
The skill of hindcasts from the European Centre for Medium-Range Weather Forecasts in forecasting heat wave days, defined as periods with the 5 d moving average temperature exceeding its local summer 90th percentile over Europe 1 to 4 weeks ahead, is examined. Forecasts of heat wave days show potential for warning of heat risk 1 to 2 weeks in advance and enhanced accuracy in forecasting prolonged heat waves up to 3 weeks ahead, when the heat wave had already begun before forecast issuance.
Cees de Valk and Henk van den Brink
Nat. Hazards Earth Syst. Sci., 25, 1769–1788, https://doi.org/10.5194/nhess-25-1769-2025, https://doi.org/10.5194/nhess-25-1769-2025, 2025
Short summary
Short summary
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
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 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
Short summary
Short summary
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
Short summary
Short summary
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
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 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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
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.
Hugo Marchal, François Bouttier, and Olivier Nuissier
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-208, https://doi.org/10.5194/nhess-2024-208, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This paper investigates the relationship between changes in weather forecasts and predictability, which has so far been considered weak. By focusing on the persistence of weather scenarios over successive forecasts, we found that it significantly affects the reliability of forecasts.
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.
Marc Lemus-Canovas, Sergi Gonzalez-Herrero, Laura Trapero, Anna Albalat, Damian Insua-Costa, Martin Senande-Rivera, and Gonzalo Miguez-Macho
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-192, https://doi.org/10.5194/nhess-2024-192, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
This study explores the 2022 heatwaves in the Pyrenees, examining the factors that contributed to their intensity and distribution. The June event was driven by strong winds that created uneven temperature patterns, while the July heatwave featured calmer conditions and more uniform temperatures. Human-driven climate change has made these heatwaves more severe compared to the past. This research helps us better understand how climate change affects extreme weather in mountainous regions.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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.
Jannick Fischer, Pieter Groenemeijer, Alois Holzer, Monika Feldmann, Katharina Schröer, Francesco Battaglioli, Lisa Schielicke, Tomáš Púčik, Christoph Gatzen, Bogdan Antonescu, and the TIM Partners
EGUsphere, https://doi.org/10.5194/egusphere-2024-2798, https://doi.org/10.5194/egusphere-2024-2798, 2024
Short summary
Short summary
Strong thunderstorms have been studied mainly over flat terrain and in computer simulations in the past. However, they are particularly frequent near mountain ranges, which emphasizes the need to study storms near mountains. This article gives an overview about our existing knowledge on this topic and presents plans for a large European field campaign with the goals to fill these knowledge gaps, validate tools for thunderstorm warnings, and improve numerical weather prediction near mountains.
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.
Lou Brett, Christopher J. White, Daniela I.V. Domeisen, Bart van den Hurk, Philip Ward, and Jakob Zscheischler
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-182, https://doi.org/10.5194/nhess-2024-182, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Compound events, where multiple weather or climate hazards occur together, pose significant risks to both society and the environment. These events, like simultaneous wind and rain, can have more severe impacts than single hazards. Our review of compound event research from 2012–2022 reveals a rise in studies, especially on events that occur concurrently, hot and dry events and compounding flooding. The review also highlights opportunities for research in the coming years.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
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.
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
Short summary
Short summary
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
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.
Xiaoxiang Guan, Dung Viet Nguyen, Paul Voit, Bruno Merz, Maik Heistermann, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-143, https://doi.org/10.5194/nhess-2024-143, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
We evaluated a multi-site stochastic regional weather generator (nsRWG) for its ability to capture the cross-scale extremity of high precipitation events (HPEs) in Germany. We generated 100 realizations of 72 years of daily synthetic precipitation data. The performance was assessed using WEI and xWEI indices, which measure event extremity across spatio-temporal scales. Results show nsRWG simulates well the extremity patterns of HPEs, though it overestimates short-duration, small-extent events.
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.
Cited articles
Alexander, G. D., Weinman, J. A., Karyampoudi, V. M., Olson, W. S., and Lee,
A. C. L.: The effect of assimilating rain rates derived from satellites and
lightning on forecasts of the 1993 superstorm, Mon. Weather Rev., 127,
1433–1457, 1999.
Barker, D. M., Huang, W., Guo, Y.-R., and Xiao, Q. N.: A Three-Dimensional
Variational Data Assimilation System for MM5: Implementation And Initial
Results, Mon. Weather Rev., 132, 897–914, 2004.
Barker, D. M., Huang, X.-Y., Liu, Z., Aulignè, T., Zhang, X., Rugg ,S.,
Ajjaji, R., Bourgeois, A., Bray, J., Chen ,Y., Demirtas, M.,. Guo, Y.-R,
Henderson, T., Huang, W, Lin, H. C., Michalakes, J., Rizvi, S., and Zhang,
X.: The Weather Research and Forecasting (WRF) Model's Community
Variational/Ensemble Data Assimilation System: WRFDA, B. Am. Meteorol.
Soc., 93, 831–843, 2012.
Betz, H.-D., Schmidt, K., Oettinger, P., and Wirz, M.: Lightning detection with
3D-discrimination of intracloudandcloud-to-grounddischarges, J. Geophys. Res.
Lett., 31, L11108, https://doi.org/10.1029/2004GL019821, 2004.
Betz, H. D., Schmidt, K., Laroche, P., Blanchet, P., Oettinger, P., Defer,
E., Dziewit, Z., and Konarski, J.: LINET-an international lightning
detection network in Europe, Atmos. Res., 91, 564–573, 2009.
Buzzi, A. and Tibaldi, S.: Cyclogenesis in the lee of the Alps: A case
study, Q. J. Roy. Meteor. Soc., 104, 271–287, https://doi.org/10.1002/qj.49710444004, 1978.
Carey, L. D. and Rutledge, S. A.: Electrical and multiparameter radar
observations of a severe hailstorm, J. Geophys. Res., 103, 13979–14000,
https://doi.org/10.1029/97JD02626, 1998.
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.
Chang, D. E., Weinman, J. A., Morales, C. A., and Olson, W. S.: The effect
of spaceborn microwave and ground-based continuous lightning measurements on
forecasts of the 1998 Groundhog Day storm, Mon. Weather Rev., 129,
1809–1833, 2001.
Chen, C. and Cotton, W. R.: A One-Dimensional Simulation of the
Stratocumulus-Capped Mixed Layer, Bound.-Lay. Meteorol., 25, 289–321,
1983.
Cotton, W. R., Pielke Sr., R. A., Walko, R. L., Liston, G. E., Tremback, C. J.,
Jiang, H., McAnelly, R. L., Harrington, J. Y., Nicholls, M. E., Carrio, G. G.,
and McFadden, J. P.: RAMS 2001: Current status and future directions,
Meteorol. Atmos. Phys., 82, 5–29, 2003.
Courtier, P., Thépaut, J. N., and Hollingsworth, A.: A strategy for
operational implementation of 4D-Var, using an incremental approach, Q. J.
Roy. Meteor. Soc., 120, 1367–1387, 1994.
Dahl, J. M. L., Höller, H., and Schumann, U.: Modeling the Flash Rate of
Thunderstorms. Part II: Implementation, Mon. Weather Rev., 139,
3112–3124, 2011.
Deierling, W. and Peterse, W. A.: Total lightning activity as an indicator
of updraft characteristics, J. Geophys. Res., 113, D16210,
https://doi.org/10.1029/2007JD009598, 2008.
Ducrocq, V., Braud, I., Davolio, S., Ferretti, R., Flamant, C., Jansa, A.,
Kalthoff, N., Richard, E., Taupier-Letage, I., Ayral, P.-A., Belamari, S.,
Berne, A., Borga, M., Boudevillain, B., Bock, O., Boichard, J.-L., Bouin,
M.-N., Bousquet, O., Bouvier, C., Chiggiato, J., Cimini, D., Corsmeier, U.,
Coppola, L., Cocquerez, P., Defer, E., Delanoë, J., Di Girolamo, P.,
Doerenbecher, A., Drobinski, P., Dufournet, Y., Fourrié, N., Gourley,
J.J., Labatut, L., Lambert, D., Le Coz, J., Marzano, F.S., Molinié, G.,
Montani, A., Nord, G., Nuret, M., Ramage, K., Rison, W., Roussot, O., Said,
F., Schwarzenboeck, A., Testor, P., Van Baelen, J., Vincendon, B., Aran, M.,
and Tamayo, J.: HYMEX-SOP1 The Field Campaign Dedicated to Heavy
Precipitation and Flash Flooding in the Northwestern Mediterranean, B.
Am. Meteorol. Soc., 95, 1083–1100,
https://doi.org/10.1175/BAMS-D-12-00244.1, 2014.
Emersic, C., and Saunders, C. P. R.: Further laboratory investigations
into the relative diffusional growth rate theory of thunderstorm
electrification, Atmos. Res., 98, 327–340,
https://doi.org/10.1016/j.atmosres.2010.07.011, 2010.
Fabry, F. and Sun, J.: For how long should what data be assimilated for the
mesoscale forecasting of convection and why? Part I: On the propagation of
initial condition errors and their implications for data
assimilation, Mon. Weather Rev., 138, 242–255, 2010.
Federico, S.: Implementation of a 3D-Var system for atmospheric profiling data assimilation into the RAMS model: initial results, Atmos. Meas. Tech., 6, 3563–3576, https://doi.org/10.5194/amt-6-3563-2013, 2013.
Federico, S.: Implementation of the WSM5 and WSM6 Single Moment Microphysics
Scheme into the RAMS Model: Verification for the HyMeX-SOP1, Adv.
Meteorol., 2016, 17 pp., https://doi.org/10.1155/2016/5094126, 2016.
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.
Federico, S., Petracca, M., Panegrossi, G., and Dietrich, S.: Improvement of RAMS precipitation forecast at the short-range through lightning data assimilation, Nat. Hazards Earth Syst. Sci., 17, 61–76, https://doi.org/10.5194/nhess-17-61-2017, 2017a.
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, 2017b.
Federico, S., Torcasio, R. C., Avolio, E., Caumont, O., Montopoli, M., Baldini, L., Vulpiani, G., and Dietrich, S.: The impact of lightning and radar data assimilation on the performance of very short term rainfall forecast for two case studies in Italy, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2018-319, in review, 2018.
Ferretti, R., Pichelli, E., Gentile, S., Maiello, I., Cimini, D., Davolio, S., Miglietta, M. M., Panegrossi, G., Baldini, L., Pasi, F., Marzano, F. S., Zinzi, A., Mariani, S., Casaioli, M., Bartolini, G., Loglisci, N., Montani, A., Marsigli, C., Manzato, A., Pucillo, A., Ferrario, M. E., Colaiuda, V., and Rotunno, R.: Overview of the first HyMeX Special Observation Period over Italy: observations and model results, Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, 2014.
Fierro, A. O., Gilmore, M. S., Mansell, E. R., Wicker, L. J., and Straka, J. M.: Electrification and lightning in an idealized boundary-crossing supercell
simulation of 2 June 1995, Mon. Weather Rev., 134, 3149–3172,
https://doi.org/10.1175/MWR3231.1, 2006.
Fierro, A. O., Mansell, E., Ziegler, C., and MacGorman, D.: Application of a
lightning data assimilation technique in the WRFARW model at cloud-resolving
scales for the tornado outbreak of 24 May 2011, Mon. Weather Rev., 140,
2609–2627, 2012.
Fierro, A. O., Gao, J., Ziegler, C., Mansell, E. R., MacGorman, D. R., and
Dembek, S.: 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.
Fierro, A. O., A. J. Clark, E. R. Mansell, D. R. MacGorman, S. Dembek, and
C. Ziegler: Impact of storm-scale lightning data assimilation on WRF-ARW
precipitation forecasts during the 2013 warm season over the contiguous
United States, Mon. Weather Rev., 143, 757–777,
https://doi.org/10.1175/MWR-D-14-00183.1, 2015.
Fierro, A. O., Gao, L., 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.
Giannaros, T. M., Kotroni, V., and Lagouvardos, K.: WRFLTNGDA: 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.
Hong, S. Y. and Lim, J. J. O.: The WRF single-moment 6-class microphysics scheme
(WSM6), J. Korean Meteorol. Soc., 42, 129–151, 2006.
Hu, M., Xue, M., and Brewster, K.: 3DVAR and cloud analysis with WSR-88D
level-II data for the prediction of the Fort Worth, Texas, tornadic
thunderstorms. Part I: Cloud analysis and its impact, Mon. Weather Rev., 134,
675–698, https://doi.org/10.1175/MWR3092.1, 2006.
Ikuta, Y. and Honda, Y.: Development of 1D+4DVAR data assimilation of
radar reflectivity in JNoVA. Tech, Report, 01.09–01.10, available at:
http://www.wcrp-climate.org/WGNE/BlueBook/2011/individual-articles/01_Ikuta_Yasutaka_WGNE2011_1D4DVAR.pdf (last access: 8 August 2019), 2011.
Jones, C. D. and Macpherson, B.: A latent heat nudging scheme for the
assimilation of precipitation into an operational mesoscale model, Meteorol.
Appl., 4, 269–277, 1997.
Jones, T. A., Otkin, J. A., Stensrud, D. J., and Knopfmeier, K.: Forecast
evaluation of an observing system simulation experiment assimilating both
radar and satellite data, Mon. Weather Rev., 142, 107–124,
https://doi.org/10.1175/MWR-D-13-00151.1, 2014.
Kain, J. S. and Fritsch, J. M.: Convective parameterization for mesoscale
models: the Kain-Fritsch scheme. The representation of cumulus convection in
numerical models, Meteor. Monogr. No. 46, Am. Meteor. Soc., Boston,
165–170, 1993.
Kuhlman, K. M., Zielger, C. L., Mansell, E. R., MacGorman, D. R., and
Straka, J. M.: Numerically simulated electrification and lightning of the 29 June
2000 STEPS supercell storm, Mon. Weather Rev., 134, 2734–2757,
https://doi.org/10.1175/MWR3217.1, 2006.
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, 2001.
Lagouvardos, K., Kotroni, V., Betz, H.-D., and Schmidt, K.: A comparison of lightning data provided by ZEUS and LINET networks over Western Europe, Nat. Hazards Earth Syst. Sci., 9, 1713–1717, https://doi.org/10.5194/nhess-9-1713-2009, 2009.
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.
Lynn, B. H., Kelman, G., and Ellrod, G.: An evaluation of the ef?cacy 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.
MacGorman, D. R. and Nielsen, K. E.: Cloud-to-Ground Lightning in a Tornadic
Storm on 8 May 1986, Mon. Weather Rev., 119, 1557–1574,
https://doi.org/10.1175/1520-0493(1991)119<1557:CTGLIA>2.0.CO;2, 1991.
MacGorman, D. R., Burgess, D. W., Mazur, V., Rust, W. D., Taylor, W. L., and Johnson, B. C.: Lightning rates relative to tornadic storm evolution on 22
May 1981, J. Atmos. Sci., 46, 221–251, https://doi.org/10.1175/1520-0469(1989)046<0221:LRRTTS>2.0.CO;2, 1989.
MacGorman, D. R., Apostolakopoulos, I. R., Lund, N. R., Demetriades, N. W. S., Murphy, M. J., and Krehbiel, P. R.: The timing of cloud-to-ground lightning relative
to total lightning activity, Mon. Weather Rev., 139, 3871–3886,
https://doi.org/10.1175/MWR-D-11-00047.1, 2011.
MacGorman, D. R., Apostolakopoulos, I. R., Lund, N. R., Demetriades, N. W. S., Murphy, M. J., and Krehbiel, P. R.: The
electrical structure of two supercell storms during STEPS, Mon. Weather Rev.,
133, 2583–2607, https://doi.org/10.1175/MWR2994.1, 2005.
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, 2007.
Marchand, M. and Fuelberg, H.: 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.
Mass, C. F., Ovens, D., Westrick, K., and Colle, B. A.: Does increasing
horizontal resolution produce more skilful forecasts?, B. Am. Meteorol.
Soc., 83, 407–430, 2002.
Mellor, G. and Yamada, T.: Development of a Turbulence Closure Model for
Geophysical Fluid Problems, Review of Geophysics and Space Physics, 20,
851–875, 1982.
Mittermaier, M., Roberts, N., and Thompson, S. A.: A long-term assessment of
precipitation forecast skill using the Fractions Skill Score, Meteor. Appl.,
20, 176–186, https://doi.org/10.1002/met.296, 2013.
Molinari, J. and Corsetti, T.: Incorporation of cloud-scale and mesoscale
down-drafts into a cumulus parametrization: results of one and
three-dimensional integrations, Mon. Weather Rev., 113, 485–501, 1985.
nowcast: available at:
https://www.nowcast.de, last access: 8 August 2019.
Olson, W. S., Kummerow, C. D., Heymsfield, G. M., and Giglio, L.: A method
for combined passive-active microwave retrievals of cloud and precipitation
profiles, J. Appl. Meteorol., 35, 1763–1789, 1996.
Papadopoulos, A., Chronis, T. G., and Anagnostou, E. N.: Improving convective
precipitation forecasting through assimilation of regional lightning
measurements in a mesoscale model, Mon. Weather Rev., 133, 1961–1977, 2005.
Parrish, D. F. and Derber, J. C.: The National Meteorological Center's
Spectral Statistical Interpolation analysis system, Mon. Weather Rev.,
120, 1747–1763, 1992.
Pessi, A. T. and Businger, S.: Relationships among Lightning,
Precipitation, and Hydrometeor Characteristics over the North Pacific
Ocean, J. Appl. Meteor. Clim., 48, 833–848,
https://doi.org/10.1175/2008JAMC1817.1, 2009.
Petracca, M., Casella, D., Dietrich, S., Milani, L., Panegrossi, G., Sanò, P., Möhrlein, M., Riso, S., and Betz, H. D.: Lightning strokes frequency
homogenization for climatological analysis: application to LINET data
records over Europe, 2nd TEA – IS Summer School, 23–27 June,
Collioure, France, 2014.
Petracca, M., D'Adderio, L. P., Porcù, F., Vulpiani, G., Sebastianelli, S.,
and Puca, S.: Validation of GPM Dual-Frequency Precipitation Radar (DPR)
rainfall products over Italy, J.
Hydrometeorol., 19, 907–925, https://doi.org/10.1175/JHM-D-17-0144.1, 2018.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.:
Numerical recipes in Fortran 77, second ed., Cambridge University Press,
Cambridge, 992 pp., 1992.
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, 2014.
Ricciardelli, E., Di Paola, F., Gentile, S., Cersosimo, A., Cimini, D.,
Gallucci, D., Geraldi, E., Larosa, S., Nilo, S. T., Ripepi, E., Romano, F.,
and Viggiano, M.: Analysis of Livorno Heavy Rainfall Event: Examples of
Satellite-Based Observation Techniques in Support of Numerical Weather
Prediction, Remote Sensing, 2018, 1549, https://doi.org/10.3390/rs10101549, 2018.
Ridal, M. and Dahlbom, M.: Assimilation of multinational radar reflectivity
data in a mesoscale model: a proof of concept, J. Appl.
Meteorol. Clim., 56, 1739–1751,
https://doi.org/10.1175/jamc-d-16-0247.1, 2017.
Roebber, P. J.: Visualizing multiple measures of forecast quality, Weather Forecast., 24, 601–608, 2009.
Rohn, M., Kelly, G., and Saunders, R. W.: Impact of a New Cloud Motion Wind
Product from Meteosat on NWP Analyses and Forecasts, Mon. Weather Rev.,
129, 2392–2403, 2001.
Smagorinsky, J.: General circulation experiments with the primitive
equations. Part I, The basic experiment, Mon. Weather Rev., 91, 99–164,
1963.
Stensrud, D. J. and Fritsch, J. M.: Mesoscale convective systems in weakly
forced large-scale environments. Part II: Generation of a mesoscale initial
condition, Mon. Weather Rev., 122, 2068–2083, 1994.
Stensrud, D. J., Xue, M., Wicker, L. J., Kelleher, K. E., Foster, M. P.,
Schaefer, J. T., Schneider, R. S., Benjamin, S. G., Weygandt, S. S., Ferree, J. T., and
Tuell, J. P.: Convective-Scale Warn-on-Forecast System, B. Am. Meteorol.
Soc., 90, 1487–1500, https://doi.org/10.1175/2009BAMS2795.1,
2009.
Stewart, L. M., Dance, S. L., and Nichols, N. K.: Data assimilation with
correlated observation errors: experiments with a 1-D shallow water
model, Tellus A, 65, 19546, https://doi.org/10.3402/tellusa.v65i0.19546, 2013.
Sun, J. and Crook, N. A.: Dynamical and Microphysical Retrieval from
Doppler RADAR Observations Using a Cloud Model and Its Adjoint, Part I:
Model Development and Simulated Data Experiments, J. Atmos. Sci., 54,
1642–1661, 1997.
Sun, J. and Crook, N. A.: Dynamical and Microphysical Retrieval from
Doppler RADAR Observations Using a Cloud Model and Its Adjoint, Part II:
Retrieval Experiments of an Observed Florida Convective Storm, J. Atmos.
Sci., 55, 835–852, 1998.
Takahashi, T.: Riming electrification as a charge generation mechanism in
thunderstorms, J. Atmos. Sci., 35, 1536–1548,
https://doi.org/10.1175/1520-0469(1978)035<1536:REAACG>2.0.CO;2, 1978.
Vulpiani, G., Rinollo, A., Puca, S., and Montopoli, M.: A quality-based
approach for radar rain field reconstruction and the H-SAF precipitation
products validation. Proc. Eighth European Radar Conf.,
Garmish-Partenkirchen, Germany, ERAD, Abstract 220, 6 pp., available at:
http://www.pa.op.dlr.de/erad2014/programme/ExtendedAbstracts/220_Vulpiani.pdf (last access: 8 August 2019), 2014.
Walko, R. L., Band, L. E., Baron, J., Kittel, T. G., Lammers, R., Lee, T. J.,
Ojima, D., Pielke Sr., R. A., Taylor, C., Tague, C., Tremback, C. J., and
Vidale, P. L.: Coupled Atmosphere-Biosphere-Hydrology Models for
environmental prediction, J. Appl. Meteorol., 39, 931–944, 2000.
Wattrelot, É., 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.
Weisman, M. L., Skamarock, W. C., and Klemp, J. B.: The resolution
dependence of explicitly modeled convective systems, Mon. Weather Rev., 125,
527–548, 1997.
Weygandt, S. S., Benjamin, S. G., Hu, M., Smirnova, T. G., and Brown, J. M.:
Use of lightning data to enhance radar assimilation within the RUC and Rapid
Refresh models. Third Conf. on Meteorological Applications of Lightning
Data, 20–24 January 2008, New Orleans, LA, Amer. Meteor. Soc., 8.4,
available at: https://ams.confex.com/ams/88Annual/webprogram/Paper134112.html (last
access: 3 October 2018), 2008.
Wiens, K. C., Rutledge, S. A., and Tessendorf, S. A.: The 29 June 2000
supercell observed during STEPS. Part II: Lightning and charge structure, J.
Atmos. Sci., 62, 4151–4177, https://doi.org/10.1175/JAS3615.1, 2005.
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, Academic Press, London, 627 pp., 2006.
Xu, Q., Wei, L., Gu, W., Gong, J., and Zhao, Q.: A 3.5-dimensional
variational method for Doppler radar data assimilation and its application
to phased array radar observations, Adv. Meteorol., 2010,
797265, https://doi.org/10.1155/2010/797265, 2010.
Xue, M., Wang, D., Gao, J., Brewster, K., and Droegemeier, K. K.: The
Advanced Regional Prediction System (ARPS), storm scale numerical weather
prediction and data assimilation, Meteorol. Atmos. Phys., 82, 139–170, 2003.
Zhao, Q., Cook, J., Xu, Q., and Harasti, P. R.: Using radar wind
observations to improve mesoscale numerical weather prediction, Weather
Forecast., 21, 502–522, 2006.
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.
This study shows the possibility to improve the weather forecast at the very short range (0–3 h)...
Altmetrics
Final-revised paper
Preprint