Adverse weather events
Adverse weather events research encompass severe atmospheric phenomena such as hurricanes, tornadoes, floods, and droughts that significantly impact ecosystems and human communities. This research field focuses on understanding the causes, patterns, and consequences of these events, often framed within the broader atmospheric sciences category. Researchers and students benefit from JoVE Visualize by accessing peer-reviewed articles paired with JoVE’s experiment videos, offering a comprehensive view of the latest methodologies and findings related to extreme weather events around the world.
Established research methods in the study of adverse weather events include remote sensing techniques, climate modeling, and atmospheric data analysis. Satellite imagery and radar are widely used to monitor and track extreme weather events in the last 10 years, providing valuable spatial and temporal information. Numerical weather prediction models simulate severe weather patterns, supporting forecasts and retrospective analyses of extreme weather examples. Field observations and climatological records also play an essential role in identifying trends and validating models within this evolving research domain.
Innovative approaches are enhancing the understanding of adverse weather events today by integrating machine learning, high-resolution climate simulations, and advanced sensor technology. Data-driven techniques help identify subtle patterns in complex atmospheric data, improving forecasts of extreme weather events in history and future scenarios. Additionally, interdisciplinary integration with socioeconomic impact studies is growing, aiding in the development of better mitigation and adaptation strategies. These emerging methods reflect the field’s expanding scope and the importance of comprehensive data interpretation.
Yanyan Liu, Gai Zhou, Jie Ying, Daoming Yan, Jianxin Ge, Zonghang Liu, Rongjia Zhang, Jianming Sun
Sangkyu Shin, Jaehan Joo, Hunyoul Lee, Suk Chan Kim
Zi Lu, Shangyue Zhang, Yuming Wang, Junting Xiong, Rui Zhao
Martin Chiari, Thomas Jagdhuber, Rainer Speck, Madhu Chandra
F Alemanno, Q An, P Azzarello, F C T Barbato, P Bernardini, X J Bi, H Boutin, I Cagnoli, M S Cai, E Casilli, J Chang, D Y Chen, J L Chen, Z F Chen, Z X Chen, P Coppin, M Y Cui, T S Cui, I De Mitri, F de Palma, A Di Giovanni, T K Dong, Z X Dong, G Donvito, J L Duan, K K Duan, R R Fan, Y Z Fan, F Fang, K Fang, C Q Feng, L Feng, S Fogliacco, J M Frieden, P Fusco, M Gao, F Gargano, E Ghose, K Gong, Y Z Gong, D Y Guo, J H Guo, S X Han, Y M Hu, G S Huang, X Y Huang, Y Y Huang, M Ionica, L Y Jiang, W Jiang, Y Z Jiang, J Kong, A Kotenko, D Kyratzis, S J Lei, B Li, W L Li, W H Li, X Li, X Q Li, Y M Liang, C M Liu, H Liu, J Liu, S B Liu, Y Liu, F Loparco, M Ma, P X Ma, T Ma, X Y Ma, G Marsella, M N Mazziotta, D Mo, Y Nie, X Y Niu, A Parenti, W X Peng, X Y Peng, C Perrina, E Putti-Garcia, R Qiao, J N Rao, Y Rong, A Ruina, R Sarkar, P Savina, Z Shangguan, W H Shen, Z Q Shen, Z T Shen, L Silveri, J X Song, M Stolpovskiy, H Su, M Su, H R Sun, Z Y Sun, A Surdo, X J Teng, A Tykhonov, G F Wang, J Z Wang, L G Wang, S Wang, X L Wang, Y F Wang, D M Wei, J J Wei, Y F Wei, D Wu, J Wu, S S Wu, X Wu, Z Q Xia, Z Xiong, E H Xu, H T Xu, J Xu, Z H Xu, Z Z Xu, Z L Xu, G F Xue, M Y Yan, H B Yang, P Yang, Y Q Yang, H J Yao, Y H Yu, Q Yuan, C Yue, J J Zang, S X Zhang, W Z Zhang, Yan Zhang, Y P Zhang, Yi Zhang, Y J Zhang, Y Q Zhang, Y L Zhang, Z Zhang, Z Y Zhang, C Zhao, H Y Zhao, X F Zhao, C Y Zhou, X Zhu, Y Zhu, X Luo
Anna G Goncharova, Ludmila H Pastushkova, Elena S Luchitskaya, Daria N Kashirina, Andrey M Nosovsky, Igor N Goncharov, Kirill S Kireev, Irina M Larina
Lei Wang, Jian Lu, Melissa L Breeden, Gang Chen, Stephanie A Henderson, Veeshan Narinesingh, Isla R Simpson, Tim Woollings, Yanjun Hu, Sandro W Lubis