Wind waves in the North Atlantic from ship navigational radar: SeaVision development and its validation with the Spotter wave buoy and WaveWatch III

Tilinina, Natalia; Ivonin, Dmitry; Gavrikov, Alexander; Sharmar, Vitali; Gulev, Sergey; Suslov, Alexander; Fadeev, Vladimir; Trofimov, Boris; Bargman, Sergey; Salavatova, Leysan; Koshkina, Vasilisa; Shishkova, Polina; Ezhova, Elizaveta; Krinitsky, Mikhail; Razorenova, Olga; Koltermann, Klaus Peter; Tereschenkov, Vladimir; Sokov, Alexey

doi:https://doi.org/10.5194/essd-14-3615-2022

Articles | Volume 14, issue 8

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Articles | Volume 14, issue 8

https://doi.org/10.5194/essd-14-3615-2022

Articles | Volume 14, issue 8

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Peer review
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Data description paper

11 Aug 2022

Data description paper |

| 11 Aug 2022

Wind waves in the North Atlantic from ship navigational radar: SeaVision development and its validation with the Spotter wave buoy and WaveWatch III

Natalia Tilinina, Dmitry Ivonin, Alexander Gavrikov, Vitali Sharmar, Sergey Gulev, Alexander Suslov, Vladimir Fadeev, Boris Trofimov, Sergey Bargman, Leysan Salavatova, Vasilisa Koshkina, Polina Shishkova, Elizaveta Ezhova, Mikhail Krinitsky, Olga Razorenova, Klaus Peter Koltermann, Vladimir Tereschenkov, and Alexey Sokov

Natalia Tilinina

CORRESPONDING AUTHOR

natalia.tilinina@univ-grenoble-alpes.fr

Université Grenoble Alpes, CNRS, IRD, Grenoble-INP, Institut des Géosciences de l'Environnement, 70 rue de la Physique, 38400, Grenoble, France

Dmitry Ivonin

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

Alexander Gavrikov

https://orcid.org/0000-0002-4198-4400

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

Vitali Sharmar

https://orcid.org/0000-0001-9841-4954

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

Sergey Gulev

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

A. M. Obukhov Institute of Atmospheric Physics, RAS, Pyzhevskiy Lane 3, 109017, Moscow, Russia

Alexander Suslov

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

Vladimir Fadeev

Joint stock company “Marine Complexes and Systems”, Aleksandrovskoy Fermy ave. 2 office 2H, 192174, Saint Petersburg, Russia

Boris Trofimov

Joint stock company “Marine Complexes and Systems”, Aleksandrovskoy Fermy ave. 2 office 2H, 192174, Saint Petersburg, Russia

Sergey Bargman

Joint stock company “Marine Complexes and Systems”, Aleksandrovskoy Fermy ave. 2 office 2H, 192174, Saint Petersburg, Russia

Leysan Salavatova

Moscow Institute of Physics and Technology, Institutskiy Pereulok 9, 141701, Dolgoprudny, Moscow Region, Russia

Vasilisa Koshkina

https://orcid.org/0000-0003-1027-1835

Moscow Institute of Physics and Technology, Institutskiy Pereulok 9, 141701, Dolgoprudny, Moscow Region, Russia

Polina Shishkova

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

Elizaveta Ezhova

Moscow Institute of Physics and Technology, Institutskiy Pereulok 9, 141701, Dolgoprudny, Moscow Region, Russia

Mikhail Krinitsky

https://orcid.org/0000-0001-5943-0695

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

Olga Razorenova

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

Klaus Peter Koltermann

Faculty of Geography, Lomonosov Moscow State University, Moscow, 119991, Russia

Vladimir Tereschenkov

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

Alexey Sokov

Shirshov Institute of Oceanology, RAS, Nakhimovsky ave. 36, 117997, Moscow, Russia

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PDF: 904
XML: 104
Total: 3,676
BibTeX: 103
EndNote: 84

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Total article views: 2,386 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
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HTML: 1,829
PDF: 493
XML: 64
Total: 2,386
BibTeX: 88
EndNote: 67

Views and downloads (calculated since 11 Aug 2022)

Month	HTML	PDF	XML	Total
Aug 2022	192	46	5	243
Sep 2022	110	25	1	136
Oct 2022	110	16	1	127
Nov 2022	45	18	0	63
Dec 2022	54	16	2	72
Jan 2023	39	12	1	52
Feb 2023	37	24	0	61
Mar 2023	46	26	0	72
Apr 2023	29	11	0	40
May 2023	24	7	1	32
Jun 2023	72	21	1	94
Jul 2023	55	12	2	69
Aug 2023	34	10	3	47
Sep 2023	70	13	1	84
Oct 2023	36	14	0	50
Nov 2023	25	8	0	33
Dec 2023	36	9	2	47
Jan 2024	58	13	1	72
Feb 2024	34	21	2	57
Mar 2024	43	24	3	70
Apr 2024	50	9	11	70
May 2024	60	9	10	79
Jun 2024	58	15	2	75
Jul 2024	70	11	5	86
Aug 2024	50	16	3	69
Sep 2024	55	11	1	67
Oct 2024	53	10	2	65
Nov 2024	25	4	0	29
Dec 2024	47	11	1	59
Jan 2025	89	18	0	107
Feb 2025	51	16	1	68
Mar 2025	72	17	2	91

Cumulative views and downloads (calculated since 11 Aug 2022)

Month	HTML	PDF	XML	Total
Aug 2022	192	46	5	243
Sep 2022	110	25	1	136
Oct 2022	110	16	1	127
Nov 2022	45	18	0	63
Dec 2022	54	16	2	72
Jan 2023	39	12	1	52
Feb 2023	37	24	0	61
Mar 2023	46	26	0	72
Apr 2023	29	11	0	40
May 2023	24	7	1	32
Jun 2023	72	21	1	94
Jul 2023	55	12	2	69
Aug 2023	34	10	3	47
Sep 2023	70	13	1	84
Oct 2023	36	14	0	50
Nov 2023	25	8	0	33
Dec 2023	36	9	2	47
Jan 2024	58	13	1	72
Feb 2024	34	21	2	57
Mar 2024	43	24	3	70
Apr 2024	50	9	11	70
May 2024	60	9	10	79
Jun 2024	58	15	2	75
Jul 2024	70	11	5	86
Aug 2024	50	16	3	69
Sep 2024	55	11	1	67
Oct 2024	53	10	2	65
Nov 2024	25	4	0	29
Dec 2024	47	11	1	59
Jan 2025	89	18	0	107
Feb 2025	51	16	1	68
Mar 2025	72	17	2	91

Total article views: 1,290 (including HTML, PDF, and XML)

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839	411	40	1,290	15	17

HTML: 839
PDF: 411
XML: 40
Total: 1,290
BibTeX: 15
EndNote: 17

Views and downloads (calculated since 16 Dec 2021)

Month	HTML	PDF	XML	Total
Aug 2022	192	46	5	243
Sep 2022	110	25	1	136
Oct 2022	110	16	1	127
Nov 2022	45	18	0	63
Dec 2022	54	16	2	72
Jan 2023	39	12	1	52
Feb 2023	37	24	0	61
Mar 2023	46	26	0	72
Apr 2023	29	11	0	40
May 2023	24	7	1	32
Jun 2023	72	21	1	94
Jul 2023	55	12	2	69
Aug 2023	34	10	3	47
Sep 2023	70	13	1	84
Oct 2023	36	14	0	50
Nov 2023	25	8	0	33
Dec 2023	36	9	2	47
Jan 2024	58	13	1	72
Feb 2024	34	21	2	57
Mar 2024	43	24	3	70
Apr 2024	50	9	11	70
May 2024	60	9	10	79
Jun 2024	58	15	2	75
Jul 2024	70	11	5	86
Aug 2024	50	16	3	69
Sep 2024	55	11	1	67
Oct 2024	53	10	2	65
Nov 2024	25	4	0	29
Dec 2024	47	11	1	59
Jan 2025	89	18	0	107
Feb 2025	51	16	1	68
Mar 2025	72	17	2	91

Cumulative views and downloads (calculated since 16 Dec 2021)

Month	HTML	PDF	XML	Total
Aug 2022	192	46	5	243
Sep 2022	110	25	1	136
Oct 2022	110	16	1	127
Nov 2022	45	18	0	63
Dec 2022	54	16	2	72
Jan 2023	39	12	1	52
Feb 2023	37	24	0	61
Mar 2023	46	26	0	72
Apr 2023	29	11	0	40
May 2023	24	7	1	32
Jun 2023	72	21	1	94
Jul 2023	55	12	2	69
Aug 2023	34	10	3	47
Sep 2023	70	13	1	84
Oct 2023	36	14	0	50
Nov 2023	25	8	0	33
Dec 2023	36	9	2	47
Jan 2024	58	13	1	72
Feb 2024	34	21	2	57
Mar 2024	43	24	3	70
Apr 2024	50	9	11	70
May 2024	60	9	10	79
Jun 2024	58	15	2	75
Jul 2024	70	11	5	86
Aug 2024	50	16	3	69
Sep 2024	55	11	1	67
Oct 2024	53	10	2	65
Nov 2024	25	4	0	29
Dec 2024	47	11	1	59
Jan 2025	89	18	0	107
Feb 2025	51	16	1	68
Mar 2025	72	17	2	91

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Total article views: 2,386 (including HTML, PDF, and XML) Thereof 2,308 with geography defined and 78 with unknown origin.

Total article views: 1,290 (including HTML, PDF, and XML) Thereof 1,225 with geography defined and 65 with unknown origin.

Country	#	Views	%
United States of America	1	1048	28
Russia	2	660	17
China	3	378	10
Germany	4	164	4
Netherlands	5	149	4

Country	#	Views	%
United States of America	1	603	25
Russia	2	477	19
China	3	328	13
Germany	4	98	4
Netherlands	5	65	2

Country	#	Views	%
United States of America	1	445	34
Russia	2	183	14
Netherlands	3	84	6
Germany	4	66	5
France	5	65	5


Total:	0
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1
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1048


Total:	0
HTML:	0
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603


Total:	0
HTML:	0
PDF:	0
XML:	0

445

Cited

Show all Final revised paper only Preprint only

12 citations as recorded by crossref.

Improvement of the AI-Based Estimation of Significant Wave Height Based on Preliminary Training on Synthetic X-Band Radar Sea Clutter Images V. Rezvov et al. 10.3103/S0027134923070275
Determination of the Significant Wave Height from Doppler Radar Images of the Sea Surface A. Ermoshkin et al. 10.1134/S000143702470084X
Dispersion relation for wind waves with account for the drift current Y. Plaksina et al. 10.31857/S0002351524030024
Dispersion Relation for Wind Waves with Account for the Drift Current Y. Plaksina et al. 10.1134/S0001433824700300
THE VALIDITY DOMAIN OF SATELLITE ALTIMETRY DATA FOR VALIDATION OF ALGORITHMS FOR ESTIMATION WIND WAVE HEIGHT E. Ezhova et al. 10.29006/1564-2291.JOR-2024.52(4).3
Estimating Significant Wave Height from X-Band Navigation Radar Using Convolutional Neural Networks M. Krinitskiy et al. 10.3103/S0027134923070159
Verifying Measurements of Surface Current Velocities by X-Band Coherent Radar Using Drifter Data I. Gorbunov et al. 10.32603/1993-8985-2023-26-3-99-110
MEAN WIND WAVE PERIOD ESTIMATION FROM INDIVIDUAL SHIP NAVIGATION RADAR IMAGES USING DEEP LEARNING METHODS V. Golikov et al. 10.29006/1564-2291.JOR-2024.52(4).2
Improving data-driven estimation of significant wave height through preliminary training on synthetic X-band radar sea clutter imagery V. Rezvov et al. 10.3389/fmars.2024.1363135
Measurement of Sea Surface Characteristics from Radar Images Using Gradient Methods K. Laptev et al. 10.32603/1993-8985-2024-27-5-41-53
MEAN WIND WAVE PERIOD ESTIMATION FROM INDIVIDUAL SHIP NAVIGATION RADAR IMAGES USING DEEP LEARNING METHODS V. Golikov et al. 10.29006/1564-2291.JOR-2024.52(4).2
Improvement of the AI-Based Estimation of Significant Wave Height Based on Preliminary Training on Synthetic X-Band Radar Sea Clutter Images V. Rezvov et al. 10.3103/S0027134923070275

10 citations as recorded by crossref.

Improvement of the AI-Based Estimation of Significant Wave Height Based on Preliminary Training on Synthetic X-Band Radar Sea Clutter Images V. Rezvov et al. 10.3103/S0027134923070275
Determination of the Significant Wave Height from Doppler Radar Images of the Sea Surface A. Ermoshkin et al. 10.1134/S000143702470084X
Dispersion relation for wind waves with account for the drift current Y. Plaksina et al. 10.31857/S0002351524030024
Dispersion Relation for Wind Waves with Account for the Drift Current Y. Plaksina et al. 10.1134/S0001433824700300
THE VALIDITY DOMAIN OF SATELLITE ALTIMETRY DATA FOR VALIDATION OF ALGORITHMS FOR ESTIMATION WIND WAVE HEIGHT E. Ezhova et al. 10.29006/1564-2291.JOR-2024.52(4).3
Estimating Significant Wave Height from X-Band Navigation Radar Using Convolutional Neural Networks M. Krinitskiy et al. 10.3103/S0027134923070159
Verifying Measurements of Surface Current Velocities by X-Band Coherent Radar Using Drifter Data I. Gorbunov et al. 10.32603/1993-8985-2023-26-3-99-110
MEAN WIND WAVE PERIOD ESTIMATION FROM INDIVIDUAL SHIP NAVIGATION RADAR IMAGES USING DEEP LEARNING METHODS V. Golikov et al. 10.29006/1564-2291.JOR-2024.52(4).2
Improving data-driven estimation of significant wave height through preliminary training on synthetic X-band radar sea clutter imagery V. Rezvov et al. 10.3389/fmars.2024.1363135
Measurement of Sea Surface Characteristics from Radar Images Using Gradient Methods K. Laptev et al. 10.32603/1993-8985-2024-27-5-41-53

2 citations as recorded by crossref.

MEAN WIND WAVE PERIOD ESTIMATION FROM INDIVIDUAL SHIP NAVIGATION RADAR IMAGES USING DEEP LEARNING METHODS V. Golikov et al. 10.29006/1564-2291.JOR-2024.52(4).2
Improvement of the AI-Based Estimation of Significant Wave Height Based on Preliminary Training on Synthetic X-Band Radar Sea Clutter Images V. Rezvov et al. 10.3103/S0027134923070275

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Short summary

We present wind wave parameter data from research cruises in the North Atlantic in 2020 and 2021 and the SeaVision system for measuring wind wave characteristics with a standard marine navigation X-band radar. We promote the potential of ship navigation X-band radars (when assembled with SeaVision or similar systems) for the development of a new near-global observational network, providing a much larger number of wind wave observations.

We present wind wave parameter data from research cruises in the North Atlantic in 2020 and 2021...

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