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"Hail"
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When hail hits
\"Full-color photographs emphasize just how big hailstones can be and how much damage they can cause.\"--Provided by publisher.
Book
Hail: Mechanisms, Monitoring, Forecasting, Damages, Financial Compensation Systems, and Prevention
Hail has long caused extensive damage and economic loss in places inhabited by humans. Climate change is expected to lead to different types of damage due to the geographic characteristics of each continent. Under changing environment, hail is becoming increasingly unstable and is causing damage that is difficult to repair, making it essential to study the occurrence of hail and hail-damage. Hail formation has been studied at the micro- and macrophysical scales as well as thermal and dynamical scales. Hail forms in various sizes, and the scale of damage varies with size. Hail precipitation occurs suddenly and is localized, making it is difficult to observe and predict. Nonetheless, techniques to measure and forecast hail precipitation are improving in accuracy. Hail-damage management and financial compensation systems are used to mitigate the severe economic losses caused by hail fallen in rural and urban areas. This review most comprehensively considers hail research, focusing on the mechanisms, observation and prediction methods, damage, social compensation systems for hail damage, and hail-disaster prevention, suggesting future study directions briefly.
Journal Article
Raindrops on a roller coaster : hail
Bel and her cousin, Dylan, explore hail, learning about when and how hail forms.
Book
Classification of Hailstone Trajectories in a Hail Cloud over a Semi-Arid Region in China
The growth trajectory of hailstones in clouds determines the ground intensity and spatial distribution of hailfall. A systematic study of hail trajectories can help improve the current scientific understanding of the mechanisms by which hail forms in semi-arid regions of China and, in doing so, improve the quality of hail forecasts and warnings and help to prevent and mitigate disasters. In this study, the WRFv3.7.1 model was employed to provide the background field to drive the hailstone trajectory model. Cluster analysis was then used to classify hail trajectories to investigate the characteristics of different types of hail trajectories and the microphysical characteristics of hail formation. The differences in hail trajectories might be mainly due to differences in the background flow fields and microphysical fields of hail clouds in different regions. Comparative analysis revealed that as the maximum particle size of ground hailfall increased, the maximum supercooled cloud water content and the maximum updraft velocity for the formation and growth of hailstone increased. The larger the size when the hailstone reaches its maximum height, the larger the ground hailstone formed. Overall, the formation and growth of hailstone are caused by the joint action of the dynamical flow field and cloud microphysical processes. The physical processes of hailstone growth and main growth regions differ for different types of hail trajectories. Therefore, different catalytic schemes should be adopted in artificial hail prevention operations for different hail clouds and trajectories due to differences in hail formation processes and ground hailfall characteristics.
Journal Article
Hail to spring!
\"Introduces hail through fun, poetic text and colorful illustrations\"-- Provided by publisher.
Book
An open-source radar-based hail damage model for buildings and cars
Severe hailstorms result in substantial damage to buildings and vehicles, necessitating the quantification of associated risks. Here, we present a novel open-source hail damage model for buildings and cars based on single-polarization radar data and 250 000 geolocated hail damage reports in Switzerland from 2002 to 2021. To this end, we conduct a detailed evaluation of different radar-based hail intensity measures at 1 km resolution and find that the maximum expected severe hail size (MESHS) outperforms the other measures, despite a considerable false-alarm ratio. Asset-specific hail damage impact functions for buildings and cars are calibrated based on MESHS and incorporated into the open-source risk modelling platform CLIMADA. The model successfully estimates the correct order of magnitude for the number of damaged building in 91 %, their total cost in 77 %, the number of damaged vehicles in 74 %, and their total cost in 60 % of over 100 considered large hail events. We found considerable uncertainties in hail damage estimates, which are largely attributable to limitations of radar-based hail detection. Therefore, we explore the usage of crowdsourced hail reports and find substantially improved spatial representation of severe hail for individual events. By highlighting the potential and limitations of radar-based hail size estimates, particularly MESHS, and the utilization of an open-source risk modelling platform, this study represents a significant step towards addressing the gap in risk quantification associated with severe hail events in Switzerland.
Journal Article
How are rain, snow, and hail alike?
Discusses the similarities and differences between the forms of precipitation: rain, snow, and hail.
Book
Advances and challenges in hail research: report from the 4th European hail workshop 2024
Hailstorms cause substantial damage to buildings, crops, vehicles, and infrastructure in many regions worldwide. Despite notable progress in recent years, hail remains insufficiently understood and poorly represented in numerical weather prediction models and risk assessments. The 4th European Hail Workshop (2024) showcased advances in detection, forecasting, climatology, and impact assessment of hail, while highlighting key challenges that remain. Progress in remote sensing, weather prediction, and seamless forecasting has improved early detection of hail events, extended forecast lead times, and enhanced warning capabilities. Field campaigns and laboratory experiments are yielding new insights into hailstone characteristics, hail formation processes, and impacts. Studies of storm dynamics and microphysics emphasized the complex interactions of processes involved across a wide range of temporal and spatial scales. Finally, artificial intelligence and machine learning are opening new avenues for hail detection, prediction, and risk modeling, marking a shift toward more integrated and innovative approaches in hail research.
Journal Article
Extreme earth
Towering Mount Everest is famous for its height, but the lowest point on Earth, Challenger Deep, is deeper than Everest is high. The Cave of Crystals in Mexico contains formations of gypsum that look like giant swords. Not only does Earth contain some extreme land formations such as these, but it's constantly changing. The world's largest desert, the Sahara, was once a swamp, and volcanoes are still building islands. These facts and many more, as well as quizzes, diagrams, and fun information boxes, create a book that will make readers truly appreciate Earth's awesome natural history.
Book
Conference Committee
Conference Chair Prof. Mário S. Ming Kong, University Lisbon, Portugal Program Chair Dr. Andrea Deaconescu, Transilvania University of Brasov, Romania Dr. İlhan Asiltürk, Selcuk University, Turkey Dr. Serhat İkizoğlu, Istanbul Technical University, Turkey Dr. Osman Adiguzel, Firat University, Department of Physics, Turkey Dr. Wen. Z. Cui, Chongqing University, China Technical Committee Prof. João C. O. Matias, University of Aveiro, Portugal Dr. Emin Taner ELMAS, Forent Energy Co., İzmir / TURKEY Dr. Mehdi Jafari Vardanjani, University of Tehran, Iran Dr. Ahmed Maher Mohammed, University of Portsmouth, UK Dr. Wan Ahmad Yusmawiza Wan Yusoff, Hail University, Kingdom of Saudi Arabia Dr. Ergin Kilic, Suleyman Demirel University, Turkey Dr. Alireza Araee, University of Tehran, Iran Dr. Erik Prada, Slovak joint stock research company, Slovak Dr. Eng. Ivan Virgala, Technical University of Košice, Slovak Dr. Chien-Chih Wang, Ming Chi University of Technology, Taiwan Dr. Kuentai Chen, Ming Chi University of Technology, Taiwan Dr. K. K. Soundrapandian, Pdpm-Indian Institute Of Information Technology Design And Manufacturing, Jabalpur, India Dr. Tzu-An Chiang, National Taipei University of Business, Taiwan Dr. Mohd Omar bin Ab Kadir, Universiti Sains Malaysia (Usm), Malaysia Dr. Noor Aziah Serri, Universiti Sains Malaysia (Usm), Malaysia
Journal Article