17 - 22 July, 2022 • Physical: Kuala Lumpur Convention Centre (KLCC), Kuala Lumpur, Malaysia • Hybrid: Online Platform

Preserving Our Heritage, Enabling Our Future Through Remote Sensing

17 - 22 July, 2022 • Physical: Kuala Lumpur Convention Centre (KLCC), Kuala Lumpur, Malaysia • Hybrid: Online Platform

TU5.V17.4

Study on cloud-rain evolution during precipitation based on multi-frequency and dual-polarization microwave observations

Jieying He, Kangwen Liu, National Space Science Center, Chinese Academy of Sciences, China; Xinxin Xie, School of Atmospheric Sciences, Sun Yat-Sen University, China; Yang Guo, Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center China Meteorological Administration, China
Session:
Artificial intelligence for radar and satellite remote sensing of precipitation Oral Virtual
Track:
Invited Sessions
Location:
Virtual Room 17
Presentation Time:
Tue, 19 Jul, 20:50 - 21:05 Malaysia Time (UTC +8)
Tue, 19 Jul, 14:50 - 15:05 Central European Time (UTC +1)
Tue, 19 Jul, 12:50 - 13:05 UTC
Tue, 19 Jul, 08:50 - 09:05 Eastern Time (UTC -5)
Session Co-Chairs:
V Chandrasekar, Colorado State University and Haonan Chen, Colorado State University
Session Manager:
Amirtha Sangeetha Ganesan
Presentation
Discussion
Resources
No resources available.
Session TU5.V17
TU5.V17.1: ENSEMBLE LEARNING FOR IMPROVING SATELLITE RETRIEVALS OF OROGRAPHIC PRECIPITATION
Liping Wang, WenWei (Tony) Liao, Colorado State University, United States; Haonan Chen, Colorado State University, National Oceanic and Atmospheric Administration (NOAA), United States
TU5.V17.2: An Improved Deep Learning-based Approach to Dual-polarization Radar Rainfall Estimation for Landfall Typhoon in South China
Tongxin Han, National Meteorological Information Centre, China; Ping Shen, Guangdong Emergency Early Warning Release Center, China; Yi Zhang, Yonghua Zhang, Guangdong Meteorological Public Service Center, China; Xiaozhi Zheng, Haizhu Bureau Of Meteorology, China
TU5.V17.3: MCT U-net: A Deep Learning Nowcasting Method Using Dual-polarization Radar Observations
Kexin Zhu, Lei Han, Ocean University of China, China; Haonan Chen, Colorado State University, United States
TU5.V17.4: Study on cloud-rain evolution during precipitation based on multi-frequency and dual-polarization microwave observations
Jieying He, Kangwen Liu, National Space Science Center, Chinese Academy of Sciences, China; Xinxin Xie, School of Atmospheric Sciences, Sun Yat-Sen University, China; Yang Guo, Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center China Meteorological Administration, China
TU5.V17.5: A Deep Learning Weather Model for Precipitation Nowcasting over China
Sheng Chen, Jinkai Tan, Sun Yat-sen University, China; Qiqiao Huang, Jing Tang, Nanning Normal University, China; Junjun Hu, Chinese Academy of Sciences, China