Detection of deterministic and probabilistic convection initiation using Himawari-8 Advanced Himawari Imager data

Lee, Sanggyun; Han, Hyangsun; Im, Jungho; Jang, Eunna; Lee, Myong-In

doi:https://doi.org/10.5194/amt-10-1859-2017

Articles | Volume 10, issue 5

https://doi.org/10.5194/amt-10-1859-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/amt-10-1859-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 10, issue 5

Research article

|

24 May 2017

Research article |

| 24 May 2017

Detection of deterministic and probabilistic convection initiation using Himawari-8 Advanced Himawari Imager data

Sanggyun Lee, Hyangsun Han, Jungho Im, Eunna Jang, and Myong-In Lee

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Final revised paper (published on 24 May 2017)
Preprint (discussion started on 01 Nov 2016)
Supplement to the preprint

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Reviewer comment', Anonymous Referee #1, 16 Dec 2016
- AC1: 'Authors' Response to Reviewer#1 and Revised Manuscript', Jungho Im, 19 Mar 2017
RC2: 'Detection of deterministic and probabilistic convective initiation using Himawari-8', Anonymous Referee #2, 02 Feb 2017
- AC2: 'Authors' Response to Reviewer#2 and Revised Manuscript', Jungho Im, 19 Mar 2017

Short summary

Deterministic and probabilistic CI detection models based on decision trees (DT), random forest (RF), and logistic regression (LR) were developed using Himawari-8 AHI data obtained over the Korean Peninsula. We used a total of 12 interest fields including time trends to develop the models. We identified contributing variables for CI detection. DT showed a higher hit rate, while RF produced a higher critical success index. The mean lead times by the four models were in the range of 20–40 min.