Prediction and variation of the auroral oval boundary based on a deep learning model and space physical parameters

Han, Yiyuan; Han, Bing; Hu, Zejun; Gao, Xinbo; Zhang, Lixia; Yang, Huigen; Li, Bin

doi:https://doi.org/10.5194/npg-27-11-2020

Articles | Volume 27, issue 1

https://doi.org/10.5194/npg-27-11-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/npg-27-11-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 27, issue 1

Research article

|

03 Feb 2020

Research article |

| 03 Feb 2020

Prediction and variation of the auroral oval boundary based on a deep learning model and space physical parameters

Yiyuan Han, Bing Han, Zejun Hu, Xinbo Gao, Lixia Zhang, Huigen Yang, and Bin Li

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Final revised paper (published on 03 Feb 2020)
Supplement to the final revised paper
Preprint (discussion started on 05 Jun 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'lack of physics', Anonymous Referee #1, 02 Jul 2019
- AC1: 'Reply the review comments', Bing Han, 27 Jul 2019
- AC2: 'Reply the review comments', Bing Han, 27 Jul 2019
- AC3: 'Reply the reviewer comments', Bing Han, 28 Sep 2019
SC1: 'Comments of npg-2019-28', Zanyang Xing, 05 Aug 2019
- AC4: 'Reply the reviewer comments', Bing Han, 28 Sep 2019
RC2: 'Optimum choice of input parameters for Modelling of Auroral Oval Boundary', Unnikrishnan Kaleekkal, 21 Sep 2019
- AC5: 'Reply the reviewer comments', Bing Han, 28 Sep 2019
- AC6: 'Experiments results in the supplementary material', Bing Han, 28 Sep 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Bing Han on behalf of the Authors (29 Sep 2019) Author's response Manuscript

ED: Publish as is (17 Dec 2019) by Jörg Büchner

AR by Bing Han on behalf of the Authors (24 Dec 2019) Author's response Manuscript

Short summary

We design a new non-linear model to construct an accurate relationship between auroral oval boundaries and 18 space physical parameters, and explore the influence of every single space physical parameter on auroral oval boundary in this paper. As a result, we found the combination of some space physical parameters can strengthen each other's influence on aurora oval boundary prediction, and this model can achieve the best performance when only partial space physical parameters are used as input.