A Deep Learning Approach to Radar‐Based QPE

A Deep Learning Approach to Radar‐Based QPE

Abstract In this study, we propose a volume‐to‐point framework for quantitative precipitation estimation (QPE) based on the Quantitative Precipitation Estimation and Segregation Using Multiple Sensor (QPESUMS) Mosaic Radar data set. With a data volume consisting of the time series of gridded radar r...

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Bibliographic Details
Main Authors: Ting‐Shuo Yo, Shih‐Hao Su, Jung‐Lien Chu, Chiao‐Wei Chang, Hung‐Chi Kuo
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2021-03-01
Series:Earth and Space Science
Subjects:
convolutional neural networks
machine learning
QPESUMS
quantitative precipitation estimation
radar
volume‐to‐point
Online Access:https://doi.org/10.1029/2020EA001340

Internet

https://doi.org/10.1029/2020EA001340

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