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Wind and Structures Volume 40, Number 1, January 2025 , pages 47-59 DOI: https://doi.org/10.12989/was.2025.40.1.047 |
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PINN-based mesoscale wind field reconstruction of radar measured convective storm in Nanchang |
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Zidong Xu, Hao Wang, Kaiyong Zhao, Shulin Zhi, Ruliang Wang, Rui Zhou, Yuxuan Lin and Han Zhang
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| Abstract | ||
| Radar echo data, which include surface meteorological information, are frequently required for various types of weather predictions. However, the spatial resolution of meteorological radar data is typically on the order of kilometers. Additionally, various environmental factors can interfere with radar data acquisition, leading to instability and frequent data gaps. To solve this problem, the physics informed neural network (PINN) is utilized to reconstruct the radar measured convective storm in Nanchang, so as to supplement the missing radar echo data. Navier-Stokes equation is encoded in PINN as the prior physical knowledge. The reconstruction errors are also statistically analyzed. What' s more, the evolutionary mesoscale features of the convective storm are briefly described. The field survey is conducted to evaluate the wind disaster losses in Nanchang. Results show that the severe convective weather in Nanchang on March 30, 2024, was a typical squall line event. The reconstruction method based on PINN effectively compensates for missing radar wind data. The reconstruction errors approximately follow a Weibull distribution, with most significant errors occurring near the boundaries of the missing data regions, which has a limited impact on analyzing mesoscale features of convective storm. | ||
| Key Words | ||
| convective storm; physics-informed neural network; radar echo data; wind disaster survey; wind field reconstruction | ||
| Address | ||
| Zidong Xu: Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China Hao Wang: Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China Kaiyong Zhao: Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China Shulin Zhi: Jiangxi Meteorological Observatory, Nanchang 330096, China Ruliang Wang: Jiangxi Meteorological Observatory, Nanchang 330096, China Rui Zhou: Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China Yuxuan Lin: Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China Han Zhang: Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China | ||