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| Analysis of TWP16 Wind Profile Radar Data during the Heavy Precipitation |
| Received:July 07, 2021 Revised:August 22, 2021 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7643/issn.1672-9242.2021.12.018 |
| KeyWord:wind profile radar heavy precipitation feature analysis |
| Author | Institution |
| ZHANG Shi |
Shenyang Institute of Atmospheric Environment, CMA, Shenyang , China;Liaoning Meteorological Equipment Support Center, Shenyang , China |
| WANG Guan |
Liaoning Branch, Training Institute for Meteorological Cadres, CMA, Shenyang , China |
| GUAN Jian-hua |
Liaoning Provincial Meteorological Service Center, Shenyang , China |
| KANG Bo-shi |
Liaoning Meteorological Equipment Support Center, Shenyang , China |
| HUANG Xing-you |
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing , China;Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing , China |
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| Abstract: |
| Based on TWP16 wind profile radar data, this paper diagnoses and analyzes the weather process of heavy precipitation caused by Typhoon Lekima landing in Panjin, Liaoning from August 10 to August 15 in 2019. The results show that the wind profile radar data can accurately and clearly monitor the weather system change process of this heavy rainfall continuously in time and space. The radial velocity in the middle and lower troposphere is greater than 9 m/s (the extreme value is 11.2 m/s), SNR is greater than 55 dB (the extreme value is 70 dB), Cn2 is greater than 1.0×10–10, and the velocity spectrum width is greater than 2.5 m/s. The vertical wind field movement in the whole atmosphere has a good correspondence with the precipitation process. The larger the value of vertical sinking velocity in the middle and lower layers of convection, the stronger the precipitation. SNR can well reveal the signal intensity of target scattering received by radar at the occurrence, development and end of heavy precipitation. The maximum detection height and duration with the maximum value 1.0×10–10 of Cn2 are closely related to precipitation. There is a significant linear relationship between the velocity spectrum width in different rainfall height layers and the rainfall, that is, the stronger the rainfall intensity, the larger the value of velocity spectrum width. On the contrary, the variation trend of rainfall intensity can be obtained through the variation trend of velocity spectrum width. The results reveal the internal relations among horizontal wind profile, radial velocity, SNR, velocity spectrum width and rainfall intensity of wind profile radar, and provide reference for the application of wind profile radar in rainfall weather monitoring. |
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