An Improved Deep Learning-based Approach to Dual-Polarization Radar Rainfall Estimation for Landfall Typhoon in South China-Reference-Cited by-同舟云学术

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An Improved Deep Learning-based Approach to Dual-Polarization Radar Rainfall Estimation for Landfall Typhoon in South China

Published:2022-07-17 Issue: Volume: Page:
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Container-title:IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Han Tongxin¹,Shen Ping²,Zhang Yi³,Zhang Yonghua³,Zheng Xiaozhi⁴

Affiliation:

1. National Meteorological Information Centre,Beijing,China,100081

2. Guangdong Emergency Early Warning Release Center,Guangzhou,Guangdong,China,510641

3. Guangdong Meteorological Public Service Center,Guangzhou,Guangdong,China,510641

4. Haizhu Bureau Of Meteorology,Guangzhou,Guangdong,China,510240

Funder

Nation Key R&D Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9883023/9883024/09884962.pdf?arnumber=9884962

Reference17 articles.

1. An Adaptive Neural Network Scheme for Radar Rainfall Estimation from WSR-88D Observations

2. Rainfall estimation from spaceborne and ground based radars using neural networks

3. Artificial neural network estimation of rainfall intensity from radar observations

4. Operational Feasibility of Neural-Network-Based Radar Rainfall Estimation

5. Improving weather radar estimates of rainfall using feed-forward neural networks

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