Front. Earth Sci. Frontiers in Earth Science Front. Earth Sci. 2296-6463 Frontiers Media S.A. 998491 10.3389/feart.2022.998491 Earth Science Correction Corrigendum: Quantitative precipitation estimation model integrating meteorological and geographical factors at multiple spatial scales Tian et al. 10.3389/feart.2022.998491 Tian Wei 1 2 * Shen Kailing 1 2 * Yi Lei 1 2 Zhang Lixia 3 Feng Yang 3 Chen Shiwei 4 1 School of Computer Science and Software, Nanjing University of Information Science and Technology, Nanjing, China 2 Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China 3 Shijiazhuang Meteorological Bureau, Shijiazhuang, China 4 School of Automation, Nanjing University of Information Science and Technology, Nanjing, China

Edited and reviewed by: Yuqing Wang, University of Hawaii at Manoa, United States

 *Correspondence: Wei Tian, tw@nuist.edu.cn; Kailing Shen, skling@nuist.edu.cn

This article was submitted to Atmospheric Science, a section of the journal Frontiers in Earth Science

 06 09 2022 2022 10 998491 20 07 2022 25 07 2022 Copyright © 2022 Tian, Shen, Yi, Zhang, Feng and Chen. 2022 Tian, Shen, Yi, Zhang, Feng and Chen

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 A Corrigendum on Quantitative precipitation estimation model integrating meteorological and geographical factors at multiple spatial scales by Tian W, Shen K, Yi L, Zhang L, Feng Y and Chen S (2022). Front. Earth Sci. 10:908869. doi:10.3389/feart.2022.908869 precipitation estimation weather radar deep learning multi-scale meteorological factors geographical factors

In the original article, there was an error in Figure 9C, page 13. The authors intended to use the root mean square error, relative error, and correlation coefficient as evaluation metrics when discussing the performance of their model and the comparison model at 17 different national weather stations. However, due to an oversight, the performance of the model under the correlation coefficient was not submitted, but instead there was a duplication of the performance of the model under the relative error. The corrected figure appears below.

MS-FCVNet scores for (A) RMSE, (B) MAE, (C) CC at 17 NWSs.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

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