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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

TU1.O-13.3

A Multi-channel 3D Convolutional-Recurrent Neural Network for Convective Storm Nowcasting

Wei Zhang, Rui Zhang, Ocean University of China, China; Haonan Chen, Colorado State University, United States; Guangxin He, Nanjing University of Information Science and Technology, China; Yurong Ge, Lei Han, Ocean University of China, China
Session:
AI for Weather Radars
Track:
Invited Sessions
Presentation Time:
Tue, 13 Jul, 09:00-09:15 (UTC)
Tue, 13 Jul, 11:00-11:15 Central Europe Summer Time (UTC +2)
Tue, 13 Jul, 17:00-17:15 China Standard Time (UTC +8)
Tue, 13 Jul, 05:00-05:15 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Haonan Chen, Colorado State University and Chandra V Chandrasekar, Colorado State University
Session Manager:
Javiera Castillo-Navarro
Presentation
Discussion
Resources
Session TU1.O-13
TU1.O-13.1: Deep learning for surface precipitation estimation using multidimensional polarimetric radar measurements
Haonan Chen, V. Chandrasekar, Colorado State University, United States
TU1.O-13.3: A Multi-channel 3D Convolutional-Recurrent Neural Network for Convective Storm Nowcasting
Wei Zhang, Rui Zhang, Ocean University of China, China; Haonan Chen, Colorado State University, United States; Guangxin He, Nanjing University of Information Science and Technology, China; Yurong Ge, Lei Han, Ocean University of China, China
TU1.O-13.4: HIGH EFFICIENCY WEATHER RADAR MOSAIC IMAGE GENERATION FRAMEWORK
Jingyin Tang, Citadel LLC, United States; Corene Matyas, University of Florida, United States
TU1.O-13.5: IDENTIFICATION OF CONVECTIVE PRECIPITATION FEATURE OBSERVED BY TRMM/GPM PR USING A REVISED UNSUPERVISED CLUSTERING PROPOSAL
Lei Ji, Weixin Xu, Sun Yat-Sen University, China; Haonan Chen, Colorado State University, United States; Hao Chen, Sun Yat-Sen University, China

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