EGU25-8958, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-8958
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Reconstruction of Radar Composite Reflectivity Based on Satellite Observations and Deep Learning
4,- 1Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China (chensheng@nieer.ac.cn)
- 2University of Chinese Academy of Sciences, Beijing, China (zhaojianyu24@mails.ucas.ac.cn)
- 3Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China (huangqiqiao23@mails.ucas.ac.cn)
- 4Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, China (indicator@sina.cn)
- 5State Key Laboratory of Internet of Things for Smart City, and Department of Civil and Environmental Engineering, University of Macau, Macau, China (gaoliang@um.edu.mo)
- 6Guangxi Meteorological Information Center, Nanning, China (liyanpinggx@163.com)
- 7Guangxi Institute of Meteorological Sciences, Nanning, China (wcx_hc@163.com)
How to cite: Zhao, J., Chen, S., Tan, J., Huang, Q., Gao, L., Li, Y., and Wei, C.: Reconstruction of Radar Composite Reflectivity Based on Satellite Observations and Deep Learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8958, https://doi.org/10.5194/egusphere-egu25-8958, 2025.