Tsunami arrival time detection system applicable to discontinuous time series data with outliers

Lee, Jun-Whan; Park, Sun-Cheon; Lee, Duk Kee; Lee, Jong Ho

doi:https://doi.org/10.5194/nhess-16-2603-2016

Articles | Volume 16, issue 12

https://doi.org/10.5194/nhess-16-2603-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/nhess-16-2603-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 16, issue 12

Research article

|

09 Dec 2016

Research article |

| 09 Dec 2016

Tsunami arrival time detection system applicable to discontinuous time series data with outliers

Jun-Whan Lee, Sun-Cheon Park, Duk Kee Lee, and Jong Ho Lee

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Views and downloads (calculated since 07 Jun 2016)

Month	HTML	PDF	XML	Total
Jun 2016	41	21	2	64
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Sep 2016	4	2	0	6
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Nov 2016	5	2	1	8
Dec 2016	74	13	2	89
Jan 2017	49	14	1	64
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Mar 2017	19	12	0	31
Apr 2017	12	4	0	16
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Aug 2017	8	12	2	22
Sep 2017	15	10	0	25
Oct 2017	4	5	1	10
Nov 2017	10	7	0	17
Dec 2017	14	14	5	33
Jan 2018	9	9	1	19
Feb 2018	5	6	0	11
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Jun 2018	11	16	1	28
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Aug 2018	17	16	1	34
Sep 2018	13	9	1	23
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Nov 2018	17	21	0	38
Dec 2018	9	16	0	25
Jan 2019	7	11	1	19
Feb 2019	8	11	2	21
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Apr 2019	8	13	1	22
May 2019	6	11	1	18
Jun 2019	6	19	0	25
Jul 2019	7	16	1	24
Aug 2019	4	17	0	21
Sep 2019	5	13	0	18
Oct 2019	8	8	2	18
Nov 2019	9	8	0	17
Dec 2019	3	3	0	6
Jan 2020	9	5	3	17
Feb 2020	5	3	0	8
Mar 2020	6	9	0	15
Apr 2020	5	1	1	7
May 2020	4	8	1	13
Jun 2020	16	10	1	27
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Jan 2021	14	7	0	21
Feb 2021	11	8	0	19
Mar 2021	8	3	0	11
Apr 2021	6	3	1	10
May 2021	3	6	1	10
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Jan 2023	8	7	0	15
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Jun 2023	27	9	0	36
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May 2024	11	9	6	26
Jun 2024	17	11	3	31
Jul 2024	13	9	3	25
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Sep 2024	9	11	1	21
Oct 2024	10	16	1	27
Nov 2024	3	6	0	9
Dec 2024	9	7	1	17
Jan 2025	10	5	0	15
Feb 2025	15	5	1	21
Mar 2025	8	9	0	17
Apr 2025	7	12	0	19
May 2025	13	14	0	27
Jun 2025	27	18	3	48
Jul 2025	8	14	1	23

Cumulative views and downloads (calculated since 07 Jun 2016)

Month	HTML	PDF	XML	Total
Jun 2016	41	21	2	64
Jul 2016	11	3	1	15
Aug 2016	21	1	0	22
Sep 2016	4	2	0	6
Oct 2016	9	2	1	12
Nov 2016	5	2	1	8
Dec 2016	74	13	2	89
Jan 2017	49	14	1	64
Feb 2017	17	5	5	27
Mar 2017	19	12	0	31
Apr 2017	12	4	0	16
May 2017	18	5	0	23
Jun 2017	16	6	0	22
Jul 2017	14	10	0	24
Aug 2017	8	12	2	22
Sep 2017	15	10	0	25
Oct 2017	4	5	1	10
Nov 2017	10	7	0	17
Dec 2017	14	14	5	33
Jan 2018	9	9	1	19
Feb 2018	5	6	0	11
Mar 2018	9	5	1	15
Apr 2018	7	6	0	13
May 2018	7	6	0	13
Jun 2018	11	16	1	28
Jul 2018	8	15	2	25
Aug 2018	17	16	1	34
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Oct 2018	8	18	0	26
Nov 2018	17	21	0	38
Dec 2018	9	16	0	25
Jan 2019	7	11	1	19
Feb 2019	8	11	2	21
Mar 2019	6	14	1	21
Apr 2019	8	13	1	22
May 2019	6	11	1	18
Jun 2019	6	19	0	25
Jul 2019	7	16	1	24
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Nov 2019	9	8	0	17
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Feb 2024	6	9	1	16
Mar 2024	6	4	0	10
Apr 2024	18	9	2	29
May 2024	11	9	6	26
Jun 2024	17	11	3	31
Jul 2024	13	9	3	25
Aug 2024	19	4	5	28
Sep 2024	9	11	1	21
Oct 2024	10	16	1	27
Nov 2024	3	6	0	9
Dec 2024	9	7	1	17
Jan 2025	10	5	0	15
Feb 2025	15	5	1	21
Mar 2025	8	9	0	17
Apr 2025	7	12	0	19
May 2025	13	14	0	27
Jun 2025	27	18	3	48
Jul 2025	8	14	1	23

Cited

Latest update: 13 Jul 2025

Short summary

Water level sensors often experience unexpected gaps and outliers that cause major difficulties in detecting tsunamis. Thus, we propose a tsunami arrival time detection system applicable to discontinuous time-series data with outliers. We want to stress that the efficiency and simplicity of the system enable its wide application in tsunami monitoring areas.

Tsunami arrival time detection system applicable to discontinuous time series data with outliers

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Cited

6 citations as recorded by crossref.

6 citations as recorded by crossref.