Articles | Volume 25, issue 1
https://doi.org/10.5194/nhess-25-429-2025
© Author(s) 2025. 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-25-429-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Jan 2025
Research article |
| 29 Jan 2025
| 29 Jan 2025
Assimilation of temperature and relative humidity observations from personal weather stations in AROME-France
Alan Demortier
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Marc Mandement
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Vivien Pourret
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Olivier Caumont
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Direction des opérations pour la prévision, Météo-France, Toulouse, France
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Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. The incorporation of new observations from personal weather stations into the French limited-area model is evaluated. It leads to a significant improvement in the modelling of the surface pressure field up to 9 h ahead. Their incorporation improves the location and intensity of the heavy precipitation event that occurred in the South of France in September 2021.
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On 14–15 October 2018, in the Aude department (France), a heavy-precipitation event produced up to about 300 mm of rain in 11 h. Simulations carried out show that the former Hurricane Leslie, while involved, was not the first supplier of moisture over the entire event. The location of the highest rainfall was primarily driven by the location of a quasi-stationary front and secondarily by the location of precipitation bands downwind of mountains bordering the Mediterranean Sea.
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Marc Mandement and Olivier Caumont
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François Collet, Margot Bador, Julien Boé, Laurent Dubus, and Bénédicte Jourdier
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Our aim is to characterize the observed evolution of compound winter low-wind and cold events impacting the French electricity system. The frequency of compound events exhibits a decrease over the 1950–2022 period, which is likely due to a decrease in cold days. Large-scale atmospheric circulation is an important driver of compound event occurrence and has likely contributed to the decrease in cold days, while we cannot draw conclusions on its influence on the decrease in compound events.
Fabio Dioguardi, Giovanni Chiodini, and Antonio Costa
Nat. Hazards Earth Syst. Sci., 25, 657–674, https://doi.org/10.5194/nhess-25-657-2025, https://doi.org/10.5194/nhess-25-657-2025, 2025
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We present results of non-volcanic-gas (CO2) hazard assessment at the Mefite d’Ansanto area (Italy) where a cold-gas stream, which has already been lethal to humans and animals, forms in the valleys surrounding the emission zone. We took the uncertainty related to the gas emission and meteorological conditions into account. Results include maps of CO2 concentrations at defined probability levels and the probability of overcoming specified CO2 concentrations over specified time intervals.
Sonja Szymczak, Frederick Bott, Vigile Marie Fabella, and Katharina Fricke
Nat. Hazards Earth Syst. Sci., 25, 683–707, https://doi.org/10.5194/nhess-25-683-2025, https://doi.org/10.5194/nhess-25-683-2025, 2025
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We investigate the correlation between heavy-rainfall events and three associated natural hazards along the German rail network using GIS analyses and random-effects logistic models. The results show that 23 % of floods, 14 % of gravitational mass movements, and 2 % of tree fall events between 2017 and 2020 occurred after a heavy-rainfall event, and the probability of occurrence of flood and tree fall events significantly increased. This study contributes to more resilient rail transport.
Daniel G. Kingston, Liam Cooper, David A. Lavers, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 25, 675–682, https://doi.org/10.5194/nhess-25-675-2025, https://doi.org/10.5194/nhess-25-675-2025, 2025
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Extreme rainfall comprises a major hydrohazard for New Zealand and is commonly associated with atmospheric rivers – narrow plumes of very high atmospheric moisture transport. Here, we focus on improved forecasting of these events by testing a forecasting tool previously applied to similar situations in western Europe. However, our results for New Zealand suggest the performance of this forecasting tool may vary depending on geographical setting.
Tiago M. Ferreira, Ricardo M. Trigo, Tomás H. Gaspar, Joaquim G. Pinto, and Alexandre M. Ramos
Nat. Hazards Earth Syst. Sci., 25, 609–623, https://doi.org/10.5194/nhess-25-609-2025, https://doi.org/10.5194/nhess-25-609-2025, 2025
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We investigate the synoptic evolution associated with the occurrence of an atmospheric river that led to a 24 h record-breaking extreme precipitation event (120.3 mm) in Lisbon, Portugal, on 13 December 2022. The synoptic background allowed the formation, on 10 December, of an atmospheric river associated with a deep extratropical cyclone and with a high moisture content and an inflow of moisture, due to the warm conveyor belt, throughout its life cycle. The system made landfall on 12 December.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim G. Pinto, Markus Augenstein, Ting-Chen Chen, Hendrik Feldmann, Petra Friederichs, Daniel Gliksman, Laura Goulier, Karsten Haustein, Jens Heinke, Lisa Jach, Florian Knutzen, Stefan Kollet, Jürg Luterbacher, Niklas Luther, Susanna Mohr, Christoph Mudersbach, Christoph Müller, Efi Rousi, Felix Simon, Laura Suarez-Gutierrez, Svenja Szemkus, Sara M. Vallejo-Bernal, Odysseas Vlachopoulos, and Frederik Wolf
Nat. Hazards Earth Syst. Sci., 25, 541–564, https://doi.org/10.5194/nhess-25-541-2025, https://doi.org/10.5194/nhess-25-541-2025, 2025
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Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.
Francisco Javier Acero, Manuel Antón, Alejandro Jesús Pérez Aparicio, Nieves Bravo-Paredes, Víctor Manuel Sánchez Carrasco, María Cruz Gallego, José Agustín García, Marcelino Núñez, Irene Tovar, Javier Vaquero-Martínez, and José Manuel Vaquero
Nat. Hazards Earth Syst. Sci., 25, 305–320, https://doi.org/10.5194/nhess-25-305-2025, https://doi.org/10.5194/nhess-25-305-2025, 2025
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The month of June 1925 was found to be exceptional in the southwest interior of the Iberian Peninsula due to the large number of thunderstorms and their significant impacts, with serious losses of human lives and material resources. We analyzed this event from different, complementary perspectives: reconstruction of the history of the events from newspapers, study of monthly meteorological variables of the longest series available, and the analysis of the meteorological synoptic situation.
Tiberiu-Eugen Antofie, Stefano Luoni, Aloïs Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci., 25, 287–304, https://doi.org/10.5194/nhess-25-287-2025, https://doi.org/10.5194/nhess-25-287-2025, 2025
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This is the first study that uses spatial patterns (clusters/hotspots) and meta-analysis in order to identify the regions at a European level at risk of multi-hazards. The findings point out the socioeconomic dimension as a determining factor in the potential risk of multi-hazards. The outcome provides valuable input for the disaster risk management policy support and will assist national authorities on the implementation of a multi-hazard approach in national risk assessment preparation.
Joona Cornér, Clément Bouvier, Benjamin Doiteau, Florian Pantillon, and Victoria A. Sinclair
Nat. Hazards Earth Syst. Sci., 25, 207–229, https://doi.org/10.5194/nhess-25-207-2025, https://doi.org/10.5194/nhess-25-207-2025, 2025
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Classification reduces the considerable variability between extratropical cyclones (ETCs) and thus simplifies studying their representation in climate models and changes in the future climate. In this paper we present an objective classification of ETCs using measures of ETC intensity. This is motivated by the aim of finding a set of ETC intensity measures which together comprehensively describe both the dynamical and impact-relevant nature of ETC intensity.
Cedric G. Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant
Nat. Hazards Earth Syst. Sci., 25, 147–168, https://doi.org/10.5194/nhess-25-147-2025, https://doi.org/10.5194/nhess-25-147-2025, 2025
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The present study addresses the predictability of heat waves at subseasonal timescales in West African cities over the period 2001–2020. Two models, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office models, were evaluated using two reanalyses: ERA5 and MERRA. The results suggest that at subseasonal timescales, the forecast models provide a better forecast than climatology, but the hit rate and false alarm rate are sub-optimal.
Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Mortimer M. Müller, Joni-Pekka Pietikäinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Sarah Veit, Julian Wendler, Elena Xoplaki, and Daniel Gliksman
Nat. Hazards Earth Syst. Sci., 25, 77–117, https://doi.org/10.5194/nhess-25-77-2025, https://doi.org/10.5194/nhess-25-77-2025, 2025
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Our research, involving 22 European scientists, investigated drought and heat impacts on forests in 2018–2022. Findings reveal that climate extremes are intensifying, with central Europe being most severely impacted. The southern region showed resilience due to historical drought exposure, while northern and Alpine areas experienced emerging or minimal impacts. The study highlights the need for region-specific strategies, improved data collection, and sustainable practices to safeguard forests.
Georgy Ayzel and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 25, 41–47, https://doi.org/10.5194/nhess-25-41-2025, https://doi.org/10.5194/nhess-25-41-2025, 2025
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Forecasting rainfall over the next hour is an essential feature of early warning systems. Deep learning (DL) has emerged as a powerful alternative to conventional nowcasting technologies, but it still struggles to adequately predict impact-relevant heavy rainfall. We think that DL could do much better if the training tasks were defined more specifically and that such specification presents an opportunity to better align the output of nowcasting models with actual user requirements.
Monica Ionita, Petru Vaideanu, Bogdan Antonescu, Catalin Roibu, Qiyun Ma, and Viorica Nagavciuc
Nat. Hazards Earth Syst. Sci., 24, 4683–4706, https://doi.org/10.5194/nhess-24-4683-2024, https://doi.org/10.5194/nhess-24-4683-2024, 2024
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Eastern Europe's heat wave history is explored from 1885 to 2023, with a focus on pre-1960 events. The study reveals two periods with more frequent and intense heat waves (HWs): 1920s–1960s and 1980s–present. The research highlights the importance of a long-term perspective, revealing that extreme heat events have occurred throughout the entire study period, and it emphasizes the combined influence of climate change and natural variations on increasing HW severity.
Tristan Shepherd, Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Nat. Hazards Earth Syst. Sci., 24, 4473–4505, https://doi.org/10.5194/nhess-24-4473-2024, https://doi.org/10.5194/nhess-24-4473-2024, 2024
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A historic derecho in the USA is presented. The 29 June 2012 derecho caused more than 20 deaths and millions of US dollars of damage. We use a regional climate model to understand how model fidelity changes under different initial conditions. We find changes drive different convective conditions, resulting in large variation in the simulated hazards. The variation using different reanalysis data shows that framing these results in the context of contemporary and future climate is a challenge.
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
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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
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In our study we used statistical models to reconstruct past hail days in Switzerland from 1959–2022. This new time series reveals a significant increase in hail day occurrences over the last 7 decades. We link this trend to increases in moisture and instability variables in the models. This time series can now be used to unravel the complexities of Swiss hail occurrence and to understand what drives its year-to-year variability.
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
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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
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Populated coastal regions in the Mediterranean are known to be severely affected by extreme weather events that are initiated over maritime regions. These weather events are known to pose a serious problem in terms of numerical predictability. Different Data Assimilation techniques are used in this study with the main aim of enhancing short-range forecasts of two challenging severe weather events.
Thomas Loridan and Nicolas Bruneau
EGUsphere, https://doi.org/10.5194/egusphere-2024-3253, https://doi.org/10.5194/egusphere-2024-3253, 2024
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Tropical Cyclone (TC) risk models have been used by the insurance industry to quantify occurrence and severity risk since the 90s. To date these models are mostly built from backward looking statistics and portray risk under a static view of the climate. We here introduce a novel approach, based on machine learning, that allows sampling of climate variability when assessing TC risk globally. This is of particular importance when computing forward looking views of TC risk.
Herijaona Hani-Roge Hundilida Randriatsara, Eva Holtanova, Karim Rizwan, Hassen Babaousmail, Mirindra Finaritra Tanteliniaina Rabezanahary, Kokou Romaric Posset, Donnata Alupot, and Brian Odhiambo Ayugi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-191, https://doi.org/10.5194/nhess-2024-191, 2024
Revised manuscript accepted for NHESS
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This study aims to analyze the spatiotemporal characteristics of drought (duration, frequency, severity, intensity) over Madagascar during 1981–2022 by using Standardized Precipitation Index (SPI-3, -6 and -12). Additionally, the impact of drought on vegetation over the studied area was assessed based on the relationship evaluation between SPI and the Normalized Difference Vegetation Index (NDVI) during 2000–2022.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024, https://doi.org/10.5194/nhess-24-3479-2024, 2024
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To effectively track and identify droughts, we developed a novel integrated drought index that combines the effects of precipitation, temperature, and soil moisture on drought. After comparison and verification, the integrated drought index shows superior performance compared to a single meteorological drought index or agricultural drought index in terms of drought identification.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 24, 3445–3460, https://doi.org/10.5194/nhess-24-3445-2024, https://doi.org/10.5194/nhess-24-3445-2024, 2024
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European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological loss index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high-impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
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
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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
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The train effect is related to convective cells that pass over the same place. Trains produce heavy rainfall and sometimes floods and are reported in North America during spring and summer. In Israel, 17 trains associated with Cyprus lows were identified by radar images and were found within the cold sector south of the low center and in the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km; last 1–3 h; and yield 35 mm of rainfall up to 60 mm.
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
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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
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A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
Katharina Küpfer, Alexandre Tuel, and Michael Kunz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2803, https://doi.org/10.5194/egusphere-2024-2803, 2024
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Using loss data, we assess when and how single and multiple types of meteorological extremes (river floods and heavy rainfall events, windstorms and convective gusts, and hail). We find that the combination of several types of hazards clusters robustly on a seasonal scale, whereas only some single hazard types occur in clusters. This can be associated with higher losses compared to isolated events. We argue for the relevance of jointly considering multiple types of hazards.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024, https://doi.org/10.5194/nhess-24-3035-2024, 2024
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We have used the temperature and relative humidity sensors in smartphones to estimate the vapor pressure deficit (VPD), an important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal shows the potential for using smartphone data to compliment the regular weather station network while also providing high spatial resolution of the VPD index.
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, https://doi.org/10.5194/nhess-24-2939-2024, 2024
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High-impact river floods are often caused by extreme precipitation. Flood protection relies on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties in the return values can be substantially reduced compared to observational estimates.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
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Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024, https://doi.org/10.5194/nhess-24-2793-2024, 2024
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Weather prediction uncertainties can be described as sets of possible scenarios – a technique called ensemble prediction. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
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
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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
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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
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The study presents an open-source model to determine the occurrence of hail damage to field crops and grapevines after hailstorms in Switzerland based on radar, agricultural land use data, and insurance damage reports. The model performs best at 8 km resolution for field crops and 1 km for grapevine and in the main production areas. Highlighting performance trade-offs and the relevance of user needs, the study is a first step towards the assessment of risk and damage for crops in Switzerland.
Dieter Roel Poelman, Hannes Kohlmann, and Wolfgang Schulz
Nat. Hazards Earth Syst. Sci., 24, 2511–2522, https://doi.org/10.5194/nhess-24-2511-2024, https://doi.org/10.5194/nhess-24-2511-2024, 2024
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EUCLID's lightning data unveil distinctive ground strike point (GSP) patterns in Europe. Over seas, GSPs per flash surpass inland, reaching a minimum in the Alps. Mountainous areas like the Alps and Pyrenees have the closest GSP separation, highlighting terrain elevation's impact. The daily peak current correlates with average GSPs per flash. These findings could significantly influence lightning protection measures, urging a focus on GSP density rather than flash density for risk assessment.
Nicola Loglisci, Giorgio Boni, Arianna Cauteruccio, Francesco Faccini, Massimo Milelli, Guido Paliaga, and Antonio Parodi
Nat. Hazards Earth Syst. Sci., 24, 2495–2510, https://doi.org/10.5194/nhess-24-2495-2024, https://doi.org/10.5194/nhess-24-2495-2024, 2024
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We analyse the meteo-hydrological features of the 27 and 28 August 2023 event that occurred in Genoa. Rainfall observations were made using rain gauge networks based on either official networks or citizen science networks. The merged analysis stresses the spatial variability in the precipitation, which cannot be captured by the current spatial density of authoritative stations. Results show that at minimal distances the variations in cumulated rainfall over a sub-hourly duration are significant.
Ellina Agayar, Franziska Aemisegger, Moshe Armon, Alexander Scherrmann, and Heini Wernli
Nat. Hazards Earth Syst. Sci., 24, 2441–2459, https://doi.org/10.5194/nhess-24-2441-2024, https://doi.org/10.5194/nhess-24-2441-2024, 2024
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This study presents the results of a climatological investigation of extreme precipitation events (EPEs) in Ukraine for the period 1979–2019. During all seasons EPEs are associated with pronounced upper-level potential vorticity (PV) anomalies. In addition, we find distinct seasonal and regional differences in moisture sources. Several extreme precipitation cases demonstrate the importance of these processes, complemented by a detailed synoptic analysis.
Antonio Giordani, Michael Kunz, Kristopher M. Bedka, Heinz Jürgen Punge, Tiziana Paccagnella, Valentina Pavan, Ines M. L. Cerenzia, and Silvana Di Sabatino
Nat. Hazards Earth Syst. Sci., 24, 2331–2357, https://doi.org/10.5194/nhess-24-2331-2024, https://doi.org/10.5194/nhess-24-2331-2024, 2024
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To improve the challenging representation of hazardous hailstorms, a proxy for hail frequency based on satellite detections, convective parameters from high-resolution reanalysis, and crowd-sourced reports is tested and presented. Hail likelihood peaks in mid-summer at 15:00 UTC over northern Italy and shows improved agreement with observations compared to previous estimates. By separating ambient signatures based on hail severity, enhanced appropriateness for large-hail occurrence is found.
Claire L. Ryder, Clément Bézier, Helen F. Dacre, Rory Clarkson, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Zak Kipling, Angela Benedetti, Mark Parrington, Samuel Rémy, and Mark Vaughan
Nat. Hazards Earth Syst. Sci., 24, 2263–2284, https://doi.org/10.5194/nhess-24-2263-2024, https://doi.org/10.5194/nhess-24-2263-2024, 2024
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Desert dust poses a hazard to aircraft via degradation of engine components. This has financial implications for the aviation industry and results in increased fuel burn with climate impacts. Here we quantify dust ingestion by aircraft engines at airports worldwide. We find Dubai and Delhi in summer are among the dustiest airports, where substantial engine degradation would occur after 1000 flights. Dust ingestion can be reduced by changing take-off times and the altitude of holding patterns.
Cited articles
Båserud, L., Lussana, C., Nipen, T. N., Seierstad, I. A., Oram, L., and Aspelien, T.: TITAN automatic spatial quality control of meteorological in-situ observations, Adv. Sci. Res., 17, 153–163, https://doi.org/10.5194/asr-17-153-2020, 2020. a, b, c
Beele, E., Reyniers, M., Aerts, R., and Somers, B.: Quality control and correction method for air temperature data from a citizen science weather station network in Leuven, Belgium, Earth Syst. Sci. Data, 14, 4681–4717, https://doi.org/10.5194/essd-14-4681-2022, 2022. a, b
Bell, A., Martinet, P., Caumont, O., Burnet, F., Delanoë, J., Jorquera, S., Seity, Y., and Unger, V.: An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties, Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, 2022. a
Bell, S., Cornford, D., and Bastin, L.: How good are citizen weather stations? Addressing a biased opinion, Weather, 70, 75–84, https://doi.org/10.1002/wea.2316, 2015. a, b
Brousseau, P., Desroziers, G., Bouttier, F., and Chapnik, B.: A posteriori diagnostics of the impact of observations on the AROME-France convective-scale data assimilation system, Q. J. Roy. Meteor. Soc., 140, 982–994, https://doi.org/10.1002/qj.2179, 2014. a
Brousseau, P., Seity, Y., Ricard, D., and Léger, J.: Improvement of the forecast of convective activity from the AROME-France system, Q. J. Roy. Meteor. Soc., 142, 2231–2243, https://doi.org/10.1002/qj.2822, 2016. a, b
Büchau, Y. G.: Modelling Shielded Temperature Sensors: an Assessment of the Netatmo Citizen Weather Station, MSc Thesis, University of Hamburg, https://bis-erdsystem.de/fileadmin/user_upload/bise/Texte/MSC_Met_61-20180313.pdf (last access: 15 April 2024), 2018. a
Cardinali, C., Andersson, E., Viterbo, P., Thépaut, J.-N., and Vasiljevic, D.: Use of conventional surface observations in three-dimensional variational assimilation, ECMWF Technical Memoranda, p. 31, https://doi.org/10.21957/p6p470k5x, 1994. a
Caumont, O., Cimini, D., Löhnert, U., Alados-Arboledas, L., Bleisch, R., Buffa, F., Ferrario, M. E., Haefele, A., Huet, T., Madonna, F., and Pace, G.: Assimilation of humidity and temperature observations retrieved from ground-based microwave radiometers into a convective-scale NWP model, Q. J. Roy. Meteor. Soc., 142, 2692–2704, https://doi.org/10.1002/qj.2860, 2016. a
Clark, M. R., Webb, J. D. C., and Kirk, P. J.: Fine-scale analysis of a severe hailstorm using crowd-sourced and conventional observations, Meteorol. Appl., 25, 472–492, https://doi.org/10.1002/met.1715, 2018. a, b
Coney, J., Pickering, B., Dufton, D., Lukach, M., Brooks, B., and Neely III, R. R.: How useful are crowdsourced air temperature observations? An assessment of Netatmo stations and quality control schemes over the United Kingdom, Meteorol. Appl., 29, e2075, https://doi.org/10.1002/met.2075, 2022. a
Cornes, R. C., Dirksen, M., and Sluiter, R.: Correcting citizen-science air temperature measurements across the Netherlands for short wave radiation bias, Meteorol. Appl., 27, e1814, https://doi.org/10.1002/met.1814, 2019. a
Courtier, P., Andersson, E., Heckley, W., Vasiljevic, D., Hamrud, M., Hollingsworth, A., Rabier, F., Fisher, M., and Pailleux, J.: The ECMWF implementation of three-dimensional variational assimilation (3D-Var). I: Formulation, Q. J. Roy. Meteor. Soc., 124, 1783–1807, https://doi.org/10.1002/qj.49712455002, 1998. a
Demortier, A., Mandement, M., Pourret, V., and Caumont, O.: Assimilation of surface pressure observations from personal weather stations in AROME-France, Nat. Hazards Earth Syst. Sci., 24, 907–927, https://doi.org/10.5194/nhess-24-907-2024, 2024. a
Derrien, M. and Le Gléau, H.: Improvement of cloud detection near sunrise and sunset by temporal-differencing and region-growing techniques with real-time SEVIRI, Int. J. Remote Sens., 31, 1765–1780, https://doi.org/10.1080/01431160902926632, 2010. a
Desroziers, G., Berre, L., Chapnik, B., and Poli, P.: Diagnosis of observation, background and analysis-error statistics in observation space, Q. J. Roy. Meteor. Soc., 131, 3385–3396, https://doi.org/10.1256/qj.05.108, 2005. a
Dumas, G., Masson, V., Hidalgo, J., Edouart, V., Hanna, A., and Poujol, G.: Co-construction of climate services based on a weather stations network: Application in Toulouse agglomeration local authority, Climate Services, 24, 100274, https://doi.org/10.1016/j.cliser.2021.100274, 2021. a
ECMWF: IFS Documentation CY48R1 – Part I: Observations, chap. 1, ECMWF, https://www.ecmwf.int/en/elibrary/81367-ifs-documentation-cy48r1-part-i-observations (last access: 17 January 2025), 2023. a
EUMETSAT: Hourly Surface Solar Irradiance (netCDF) – MSG, https://user.eumetsat.int/catalogue/EO:EUM:DAT:MSG:OSI-304-H/overview (last access: 31 March 2024), 2017. a
EUMETSAT: EUMETSAT Data Services: Rapid Scan High Rate SEVIRI Level 1.5 Image Data – MSG, https://data.eumetsat.int/data/map/EO:EUM:DAT:MSG:MSG15-RSS (last access: 15 April 2024), 2024. a
Feichtinger, M., de Wit, R., Goldenits, G., Kolejka, T., Hollósi, B., Žuvela-Aloise, M., and Feigl, J.: Case-study of neighborhood-scale summertime urban air temperature for the City of Vienna using crowd-sourced data, Urban Climate, 32, 100597, https://doi.org/10.1016/j.uclim.2020.100597, 2020. a
Fenner, D., Bechtel, B., Demuzere, M., Kittner, J., and Meier, F.: CrowdQC+ – A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications, Frontiers in Environmental Science, 9, 720747, https://doi.org/10.3389/fenvs.2021.720747, 2021. a, b, c
Flamant, C., Chazette, P., Caumont, O., Di Girolamo, P., Behrendt, A., Sicard, M., Totems, J., Lange, D., Fourrié, N., Brousseau, P., Augros, C., Baron, A., Cacciani, M., Comerón, A., De Rosa, B., Ducrocq, V., Genau, P., Labatut, L., Muñoz-Porcar, C., Rodríguez-Gómez, A., Summa, D., Thundathil, R., and Wulfmeyer, V.: A network of water vapor Raman lidars for improving heavy precipitation forecasting in southern France: introducing the WaLiNeAs initiative, Bulletin of Atmospheric Science and Technology, 2, 1–10, https://doi.org/10.1007/s42865-021-00037-6, 2021. a
Garcelon, L., Brana, S., Didez, J., and Ameye, F.: StatIC : un réseau d'observation au service d'une information de proximité et de vulgarisation scientifique, La Météorologie, 122, 37–46, https://doi.org/10.37053/lameteorologie-2023-0071, 2023. a, b
Giard, D. and Bazile, E.: Implementation of a New Assimilation Scheme for Soil and Surface Variables in a Global NWP Model, Mon. Weather Rev., 128, 997–1015, https://doi.org/10.1175/1520-0493(2000)128<0997:IOANAS>2.0.CO;2, 2000. a
Gouttevin, I., Vionnet, V., Seity, Y., Boone, A., Lafaysse, M., Deliot, Y., and Merzisen, H.: To the Origin of a Wintertime Screen-Level Temperature Bias at High Altitude in a Kilometric NWP Model, J. Hydrometeorol., 24, 53–71, https://doi.org/10.1175/JHM-D-21-0200.1, 2023. a
Guillet, O., Weaver, A. T., Vasseur, X., Michel, Y., Gratton, S., and Gürol, S.: Modelling spatially correlated observation errors in variational data assimilation using a diffusion operator on an unstructured mesh, Q. J. Roy. Meteor. Soc., 145, 1947–1967, 2019. a
Gustafsson, N., Janjić, T., Schraff, C., Leuenberger, D., Weissmann, M., Reich, H., Brousseau, P., Montmerle, T., Wattrelot, E., Bučánek, A., Mile, M., Hamdi, R., Lindskog, M., Barkmeijer, J., Dahlbom, M., Macpherson, B., Ballard, S., Inverarity, G., Carley, J., Alexander, C., Dowell, D., Liu, S., Ikuta, Y., and Fujita, T.: Survey of data assimilation methods for convective-scale numerical weather prediction at operational centres, Q. J. Roy. Meteor. Soc., 144, 1218–1256, https://doi.org/10.1002/qj.3179, 2018. a
Hintz, K. S., Vedel, H., and Kaas, E.: Collecting and processing of barometric data from smartphones for potential use in numerical weather prediction data assimilation, Meteorol. Appl., 26, 733–746, https://doi.org/10.1002/met.1805, 2019. a
Infoclimat: Open data – données météo – Infoclimat, https://www.infoclimat.fr/opendata/ (last access: 16 April 2024), 2024. a
Leroy, M.: Note technique N° 35B : Classification d’un site, https://www.infoclimat.fr/stations/DSO_35B.pdf (last access: 17 January 2025), 2014. a
Li, J. and Shibata, K.: On the Effective Solar Pathlength, J. Atmos. Sci., 63, 1365–1373, https://doi.org/10.1175/JAS3682.1, 2006. a
Marquès, E.: Étude à fine échelle de l'îlot de chaleur urbain par modélisation bayésienne à partir de données opportunes, PhD thesis, Institut National Polytechnique de Toulouse, http://www.theses.fr/2023INPT0016 (last access: 17 January 2025), 2023. a
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, 2013. a
Meier, F., Fenner, D., Grassmann, T., Otto, M., and Scherer, D.: Crowdsourcing air temperature from citizen weather stations for urban climate research, Urban Climate, 19, 170–191, https://doi.org/10.1016/j.uclim.2017.01.006, 2017. a
Michel, Y. and Brousseau, P.: A Square-Root, Dual-Resolution 3DEnVar for the AROME Model: Formulation and Evaluation on a Summertime Convective Period, Mon. Weather Rev., 149, 3135–3153, https://doi.org/10.1175/MWR-D-21-0026.1, 2021. a
Montmerle, T., Michel, Y., Arbogast, E., Ménétrier, B., and Brousseau, P.: A 3D ensemble variational data assimilation scheme for the limited-area AROME model: Formulation and preliminary results, Q. J. Roy. Meteor. Soc., 144, 2196–2215, https://doi.org/10.1002/qj.3334, 2018. a
Météo-France: Données de modèle AROME, https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=131&id_rubrique=51 (last access: 5 April 2024), 2024a. a
Météo-France: Observations du réseau sol de France, https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=93&id_rubrique=32 (last access: 5 April 2024), 2024b. a
Météo-France: Observations en mer (messages SHIP, BUOY), https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=95&id_rubrique=32 (last access: 5 April 2024), 2024c. a
Météo-France: Données SYNOP essentielles OMM, https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=90&id_rubrique=32 (last access: 5 April 2024), 2024d. a
Netatmo: Weather API Documentation, https://dev.netatmo.com/apidocumentation/weather (last access: 5 April 2024), 2024. a
Netatmo: Netatmo Connect APIs Terms of Use!, https://dev.netatmo.com/legal (last access: 17 January 2025), 2025. a
Nipen, T. N., Seierstad, I. A., Lussana, C., Kristiansen, J., and Hov, Ø.: Adopting Citizen Observations in Operational Weather Prediction, B. Am. Meteorol. Soc., 101, E43–E57, https://doi.org/10.1175/BAMS-D-18-0237.1, 2020. a, b, c
Orlanski, I.: A Rational Subdivision of Scales for Atmospheric Processes, B. Am. Meteorol. Soc., 56, 527–530, https://doi.org/10.1175/1520-0477-56.5.527, 1975. a
Pergaud, J., Masson, V., Malardel, S., and Couvreux, F.: A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction., Bound.-Lay. Meteorol., 132, 83–106, https://doi.org/10.1007/s10546-009-9388-0, 2009. a
Potgieter, J., Nazarian, N., Lipson, M. J., Hart, M. A., Ulpiani, G., Morrison, W., and Benjamin, K.: Combining High-Resolution Land Use Data With Crowdsourced Air Temperature to Investigate Intra-Urban Microclimate, Frontiers in Environmental Science, 9, 720323, https://doi.org/10.3389/fenvs.2021.720323, 2021. a
Pourret, V., Šavli, M., Mahfouf, J.-F., Raspaud, D., Doerenbecher, A., Bénichou, H., and Payan, C.: Operational assimilation of Aeolus winds in the Météo-France global NWP model ARPEGE, Q. J. Roy. Meteor. Soc., 148, 2652–2671, https://doi.org/10.1002/qj.4329, 2022. a, b
Sassi, M. Z., Fourrié, N., Guidard, V., and Birman, C.: Use of Infrared Satellite Observations for the Surface Temperature Retrieval over Land in a NWP Context, Remote Sensing, 11, 2371, https://doi.org/10.3390/rs11202371, 2019. a, b
Schmetz, J., Pili, P., Tjemkes, S., Just, D., Kerkmann, J., Rota, S., and Ratier, A.: An Introduction to Meteosat Second Generation (MSG), B. Am. Meteor. Soc., 83, 977–992, https://doi.org/10.1175/1520-0477(2002)083<0977:AITMSG>2.3.CO;2, 2002. a
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P., Bouttier, F., Lac, C., and Masson, V.: The AROME-France Convective-Scale Operational Model, Mon. Weather Rev., 139, 976–991, https://doi.org/10.1175/2010MWR3425.1, 2011. a, b
Sgoff, C., Acevedo, W., Paschalidi, Z., Ulbrich, S., Bauernschubert, E., Kratzsch, T., and Potthast, R.: Assimilation of crowd-sourced surface observations over Germany in a regional weather prediction system, Q. J. Roy. Meteor. Soc., 148, 1752–1767, https://doi.org/10.1002/qj.4276, 2022. a, b, c, d, e, f, g, h, i, j
Stoffelen, A.: Toward the true near-surface wind speed: Error modeling and calibration using triple collocation, J. Geophys. Res.-Oceans, 103, 7755–7766, https://doi.org/10.1029/97JC03180, 1998. a
Stull, R. B.: Mean Boundary Layer Characteristics, Springer Netherlands, Dordrecht, 1–27, ISBN 978-94-009-3027-8, https://doi.org/10.1007/978-94-009-3027-8_1, 1988. a
Toulouse Métropole: Portail d'ouverture des données publiques de Toulouse Métropole – Open Data Toulouse Métropole, https://data.toulouse-metropole.fr/explore/?sort=modified&refine.keyword=m% C3% A9t% C3% A9o (last access: 16 April 2024), 2024. a
Varentsov, M. I., Konstantinov, P. I., Shartova, N. V., Samsonov, T. E., Kargashin, P. E., Varentsov, A. I., Fenner, D., and Meier, F.: Urban heat island of the Moscow megacity: the long-term trends and new approaches for monitoring and research based on crowdsourcing data, IOP Conf. Ser. Earth Environ., 606, 012063, https://doi.org/10.1088/1755-1315/606/1/012063, 2020. a, b
Vasiljevic, D., Cardinali, C., and Undén, P.: ECMWF 3D variational data assimilation of conventional observations, in: Workshop on variational assimilation, with special emphasis on three-dimensional Aspects, 9–12 November 1992, ECMWF, Shinfield Park, Reading, 389–436, https://www.ecmwf.int/sites/default/files/elibrary/1992/76806-ecmwf-3d-variational-data-assimilation-conventional-observations_0.pdf (last access: 17 January 2025), 1992. a
Venter, Z. S., Brousse, O., Esau, I., and Meier, F.: Hyperlocal mapping of urban air temperature using remote sensing and crowdsourced weather data, Remote Sens. Environ., 242, 111791, https://doi.org/10.1016/j.rse.2020.111791, 2020. a
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C. J., Polat, İ., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F., van Mulbregt, P., and SciPy 1.0 Contributors: SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python, Nat. Meth., 17, 261–272, https://doi.org/10.1038/s41592-019-0686-2, 2020. a
Vural, J., Merker, C., Löffler, M., Leuenberger, D., Schraff, C., Stiller, O., Schomburg, A., Knist, C., Haefele, A., and Hervo, M.: Improving the representation of the atmospheric boundary layer by direct assimilation of ground-based microwave radiometer observations, Q. J. Roy. Meteor. Soc., 150, 1012–1028, https://doi.org/10.1002/qj.4634, 2024. a
World Meteorological Organization: Guide to Instruments and Methods of Observation, Volume I – Measurement of Meteorological Variables (WMO-No. 8), World Meteorological Organization, ISBN 9789263100085, https://library.wmo.int/idurl/4/68695 (last access: 17 January 2025), 2023. a
Zumwald, M., Knüsel, B., Bresch, D. N., and Knutti, R.: Mapping urban temperature using crowd-sensing data and machine learning, Urban Climate, 35, 100739, https://doi.org/10.1016/j.uclim.2020.100739, 2021. a
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.
The use of numerical weather prediction models enables the forecasting of hazardous weather...
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