Regional analysis of wave characteristics is crucial for ocean engineering planning and marine disaster protection. However, current wave observation methods have limitations in capturing sufficient coverage and resolution of wave field data, specifically significant wave height (SWH). Thus, we fuse multi-source satellite altimeter data using four fusion methods to generate daily SWH fields with a spatial resolution of 0.125° × 0.125° over the North Pacific Ocean (NPO). The results show that the fused SWHs exhibit a consistent spatial distribution pattern similar to the product provided by Archiving, Validation, and Interpretation of Satellite Oceanographic Data. Considering the spatial and temporal variation characteristics of the along-track data, the inverse distance weighting-based spatiotemporal fusion (IDW-ST) method outperforms other fusion methods compared to buoy measurements. Building upon the IDW-ST method, we fuse multi-source satellite altimetry data from 2016 to 2020 and analyze the regional spatial patterns and variations of waves in the NPO. Waves in this region are primarily influenced by monsoons and significantly regulated by extreme weather systems, such as tropical cyclones (TCs). Seasonal variations in wave characteristics may be linked to the frequency and tracks of TCs, with distinctive local features observed in representative zones. For example, the probability distribution of SWHs in the NPO exhibits a trailing pattern with significant deviations from the main SWHs, particularly during winter. Additionally, a heavy-tailed distribution is observed in the central high-latitude zone, except during summer. These patterns indicate the frequency and severity of extreme wave events in these zones.

1.
T. A. A.
Adcock
and
P. H.
Taylor
, “
Fast and local non-linear evolution of steep wave-groups on deep water: A comparison of approximate models to fully non-linear simulations
,”
Phys. Fluids
28
(
1
),
016601
(
2016
).
2.
S.
Støle-Hentschel
,
K.
Trulsen
,
L. B.
Rye
, and
A.
Raustøl
, “
Extreme wave statistics of counter-propagating, irregular, long-crested sea states
,”
Phys. Fluids
30
(
6
),
067102
(
2018
).
3.
H.
Gao
,
Z.
Shao
,
G.
Wu
, and
P.
Li
, “
Study of directional declustering for estimating extreme wave heights in the Yellow Sea
,”
J. Mar. Sci. Eng.
8
(
4
),
236
(
2020
).
4.
A. F.
Haselsteiner
and
K. D.
Thoben
, “
Predicting wave heights for marine design by prioritizing extreme events in a global model
,”
Renewable Energy
156
,
1146
1157
(
2020
).
5.
H.
Yang
,
Z.
Shao
,
B.
Liang
,
Z.
Wang
, and
D.
Lee
, “
Performance of different input and dissipation packages in WAVEWATCH III model during tropical cyclones
,”
Phys. Fluids
34
(
10
),
107102
(
2022
).
6.
H.
He
,
J.
Song
,
Y.
Bai
,
Y.
Xu
,
J.
Wang
, and
F.
Bi
, “
Climate and extrema of ocean waves in the East China Sea
,”
Sci. China Earth Sci.
61
(
7
),
980
994
(
2018
).
7.
J.
Shi
,
J.
Zheng
,
C.
Zhang
,
A.
Joly
,
W.
Zhang
,
P.
Xu
,
T.
Sui
, and
T.
Chen
, “
A 39-year high resolution wave hindcast for the Chinese coast: Model validation and wave climate analysis
,”
Ocean Eng.
183
,
224
235
(
2019
).
8.
G.
Dodet
,
S.
Abdalla
,
M.
Alday
,
M.
Accensi
,
J.
Bidlot
, and
F.
Ardhuin
, “
Error characterization of significant wave heights in multidecadal satellite altimeter product, model hindcast, and in situ measurements using the triple collocation technique
,”
J. Atmos. Ocean. Technol.
39
(
7
),
887
901
(
2022
).
9.
Z.
Sun
,
H.
Zhang
,
D.
Xu
,
X.
Liu
, and
J.
Ding
, “
Assessment of wave power in the South China Sea based on 26-year high-resolution hindcast data
,”
Energy
197
,
117218
(
2020
).
10.
M. N.
Uti
,
A. H.
Md Din
, and
O.
Yaakob
, “
Significant wave height assessment using multi mission satellite altimeter over Malaysian seas
,”
IOP Conf. Ser.: Earth Environ. Sci.
169
(
1
),
012025
(
2018
).
11.
I. R.
Young
, “
Global ocean wave statistics obtained from satellite observations
,”
Appl. Ocean Res.
16
(
4
),
235
248
(
1994
).
12.
H.
Jiang
,
G.
Fu
, and
L.
Ren
, “
Evaluation of coastal altimeter wave height observations using dynamic collocation
,”
IEEE Trans. Geosci. Remote Sens.
60
,
4209008
(
2022
).
13.
K.
Amarouche
,
A.
Akpınar
,
M. B.
Soran
,
S.
Myslenkov
,
A. G.
Majidi
,
M.
Kankal
, and
V.
Arkhipkin
, “
Spatial calibration of an unstructured SWAN model forced with CFSR and ERA5 winds for the Black and Azov Seas
,”
Appl. Ocean Res.
117
,
102962
(
2021
).
14.
S.
Myslenkov
and
A.
Chernyshova
, “
Comparing wave heights simulated in the Black Sea by the SWAN model with satellite data and direct wave measurements
,”
Russ. J. Earth Sci.
16
(
5
),
1
12
(
2016
).
15.
G.
Marechal
and
F.
Ardhuin
, “
Surface currents and significant wave height gradients: Matching numerical models and high-resolution altimeter wave heights in the Agulhas Current Region
,”
J. Geophys. Res. Ocean
126
(
2
),
e2020JC016564
, https://doi.org/10.1029/2020JC016564 (
2021
).
16.
M.
Yurovskaya
,
V.
Kudryavtsev
,
A.
Mironov
,
A.
Mouche
,
F.
Collard
, and
B.
Chapron
, “
Surface wave developments under tropical Cyclone Goni (2020): Multi-satellite observations and parametric model comparisons
,”
Remote Sens.
14
(
9
),
2032
(
2022
).
17.
M.
Seemanth
,
P. G.
Remya
,
S. A.
Bhowmick
,
R.
Sharma
,
T. M.
Balakrishnan Nair
,
R.
Kumar
, and
A.
Chakraborty
, “
Implementation of altimeter data assimilation on a regional wave forecasting system and its impact on wave and swell surge forecast in the Indian Ocean
,”
Ocean Eng.
237
,
109585
(
2021
).
18.
C.
Skandrani
,
J. M.
Lefevre
, and
P.
Queffeulou
, “
Impact of multisatellite altimeter data assimilation on wave analysis and forecast
,”
Mar. Geod.
27
(
3–4
),
511
533
(
2004
).
19.
L.
Rusu
and
C.
Guedes Soares
, “
Impact of assimilating altimeter data on wave predictions in the western Iberian coast
,”
Ocean Model.
96
,
126
135
(
2015
).
20.
F.
Nelli
,
M. H.
Derkani
,
A.
Alberello
, and
A.
Toffoli
, “
A satellite altimetry data assimilation approach to optimise sea state estimates from vessel motion
,”
Appl. Ocean Res.
132
,
103479
(
2023
).
21.
Y.
Sun
,
K.
Wang
,
X.
Zhong
,
Z.
Zhou
,
Z.
Ren
, and
J.
Zhang
, “
Assess the typhoon-driven extreme wave conditions in manila bay through numerical simulation and statistical analysis
,”
Appl. Ocean Res.
109
,
102565
(
2021
).
22.
B. W.
Timmermans
,
C. P.
Gommenginger
,
G.
Dodet
, and
J. R.
Bidlot
, “
Global wave height trends and variability from new multimission satellite altimeter products, reanalyses, and wave Buoys
,”
Geophys. Res. Lett.
47
(
9
),
e2019GL086880
, https://doi.org/10.1029/2019GL086880 (
2020
).
23.
N. K.
Hithin
,
V. S.
Kumar
, and
P. R.
Shanas
, “
Trends of wave height and period in the Central Arabian Sea from 1996 to 2012: A study based on satellite altimeter data
,”
Ocean Eng.
108
,
416
425
(
2015
).
24.
H.-J.
Woo
and
K.-A.
Park
, “
Estimation of extreme significant wave height in the northwest pacific using satellite altimeter data focused on typhoons (1992–2016)
,”
Remote Sens.
13
(
6
),
1063
(
2021
).
25.
R.
Kalra
,
M. C.
Deo
,
R.
Kumar
, and
V. K.
Agarwal
, “
RBF network for spatial mapping of wave heights
,”
Mar. Struct.
18
(
3
),
289
300
(
2005
).
26.
C. M.
Appendini
,
A.
Torres-Freyermuth
,
P.
Salles
,
J.
López-González
, and
E. T.
Mendoza
, “
Wave climate and trends for the Gulf of Mexico: A 30-yr wave hindcast
,”
J. Clim.
27
(
4
),
1619
1632
(
2014
).
27.
O.
Yaakob
,
F. E.
Hashim
,
K.
Mohd Omar
,
A. H.
Md Din
, and
K. K.
Koh
, “
Satellite-based wave data and wave energy resource assessment for South China Sea
,”
Renewable Energy
88
,
359
371
(
2016
).
28.
T. H.
Durrant
,
D. J. M.
Greenslade
, and
I.
Simmonds
, “
Validation of Jason-1 and Envisat remotely sensed wave heights
,”
J. Atmos. Ocean. Technol.
26
(
1
),
123
134
(
2009
).
29.
P.
Queffeulou
, “
Long-term validation of wave height measurements from altimeters
,”
Mar. Geod.
27
(
3–4
),
495
510
(
2004
).
30.
S.
Zieger
,
J.
Vinoth
, and
I. R.
Young
, “
Joint calibration of multiplatform altimeter measurements of wind speed and wave height over the past 20 years
,”
J. Atmos. Ocean. Technol.
26
(
12
),
2549
2564
(
2009
).
31.
I. R.
Young
and
A.
Ribal
, “
Multiplatform evaluation of global trends in wind speed and wave height
,”
Science
364
(
6440
),
548
552
(
2019
).
32.
A.
Pascual
,
M. I.
Pujol
,
G.
Larnicol
,
P. Y.
Le Traon
, and
M. H.
Rio
, “
Mesoscale mapping capabilities of multisatellite altimeter missions: First results with real data in the Mediterranean Sea
,”
J. Mar. Syst.
65
(
1–4
),
190
211
(
2007
).
33.
M.
Kaselimi
and
D.
Delikaraoglou
, “
Estimating the prospects of wave energy potential in Eastern Mediterranean using multi-mission satellite altimeter data
,” Quod Erat Demonstrandum–In Quest of the Ultimate Geodetic Insight, Honorary volume dedicated to Professor Emeritus A. Dermanis (School of Rural and Surveying Engineering, 2018), pp.
221
238
.
34.
V. G.
Polnikov
,
F. A.
Pogarskii
,
N. S.
Zilitinkevich
, and
A. A.
Kubryakov
, “
Use of along-track altimeter data to verify numerical wave models
,”
Izv. Atmos. Ocean. Phys.
55
(
9
),
1089
1097
(
2019
).
35.
Y.
Wan
,
J.
Zhang
,
J.
Meng
, and
J.
Wang
, “
A wave energy resource assessment in the China's seas based on multi-satellite merged radar altimeter data
,”
Acta Oceanol. Sin.
34
,
115
124
(
2015
).
36.
R.
Kurniawan
and
M. K.
Khotimah
, “
Ocean wave characteristics in Indonesian waters for sea transportation safety and planning
,”
IPTEK J. Technol. Sci.
26
(
1
),
19
27
(
2015
).
37.
F.
Onea
,
E.
Rusu
, and
M.
Bernardino
, “Overview of wave and wind climate in the Romanian nearshore using satellite data,” Ann. Univ. “Dunarea de Jos” of Galati, Fascicle X Appl. Math. 28(2) (
2010
).
38.
A. M.
Rizal
and
N. S.
Ningsih
, “
Ocean wave energy potential along the west coast of the Sumatra Island, Indonesia
,”
J. Ocean Eng. Mar. Energy
6
(
2
),
137
154
(
2020
).
39.
E.
Toualy
,
A.
Aman
,
P.
Koffi
,
F.
Marin
, and
T. E.
Wango
, “
Ocean swell variability along the northern coast of the Gulf of Guinea
,”
Afr. J. Mar. Sci.
37
(
3
),
353
361
(
2015
).
40.
F.
Onea
,
A.
Raileanu
, and
E.
Rusu
, “
Analysis of the extreme wind and wave conditions in the Black Sea as reflected by the altimeter measurements
,”
Mech. Test. Diagn.
6
(
1
),
5
12
(
2016
).
41.
F.
Onea
and
L.
Rusu
, “
A long-term assessment of the Black Sea wave climate
,”
Sustainability
9
(
10
),
1875
(
2017
).
42.
B. A.
Oliveira
,
F.
Sobral
,
A.
Fetter
, and
F. J.
Mendez
, “
A high-resolution wave hindcast off Santa Catarina (Brazil) for identifying wave climate variability
,”
Reg. Stud. Mar. Sci.
32
,
100834
(
2019
).
43.
H.
Su
,
C.
Wei
,
S.
Jiang
,
P.
Li
, and
F.
Zhai
, “
Revisiting the seasonal wave height variability in the South China Sea with merged satellite altimetry observations
,”
Acta Oceanol. Sin.
36
(
11
),
38
50
(
2017
).
44.
J.
Yang
,
X.
Chen
,
J.
Wang
,
R.
Zhang
, and
W.
Huang
, “
Data fusion of significant wave height from multiple satellite altimeters
,”
Proc. SPIE
7154
,
715408
(
2008
).
45.
J.
Yang
,
G.
Xu
,
L.
Yin
,
Q.
Xiao
, and
Y.
Xu
, “
Data fusion of significant wave height from HY-2A and other satellite altimeters
,”
Proc. SPIE
8532
,
85320K
(
2012
).
46.
M. R.
Badriana
,
H. S.
Lee
,
H.
Diastomo
,
Avrionesti
,
M. Y.
Surya
,
U.
Abdurrahman
,
T.
Suprijo
, and
H.
Park
, “
Multi-data ensemble estimation of wave energy potential in Indonesian Seas
,”
J. Coast. Res.
114
,
271
275
(
2021
).
47.
X.
Chen
,
J.
Yang
,
W.
Huang
,
J.
Wang
,
H.
Wang
, and
R.
Zhang
, “
Research on the fusion methods of significant wave height data from multisatellite altimeters
,”
Acta Oceanlog. Sin.
31
(
4
),
51
57
(
2009
).
48.
W.
Han
and
J.
Yang
, “
Wave height possibility distribution characteristics of significant wave height in China Sea based on multi-satellite grid data
,”
IOP Conf. Ser.: Earth Environ. Sci.
46
(
1
),
012033
(
2016
).
49.
J.
Yang
,
X.
Chen
,
R.
Zhang
,
J.
Wang
, and
W.
Huang
, “
Characteristics of significant wave height in china seas and their adjacent waters from merged altimetry data
,” in
IEEE International Symposium on Geoscience and Remote Sensing
(
IEEE
,
2009
), p.
II-499
.
50.
R.
Scharroo
,
E. W.
Leuliette
,
J. L.
Lillibridge
,
D.
Byrne
,
M. C.
Naeije
, and
G. T.
Mitchum
, “
RADS: Consistent multi-mission products
,” in
Proceedings of the Symposium on 20 Years of Progress in Radar Altimetry,
Venice, 20–28 September 2012, ESA SP-710, 66 (Eur. Space Agency Spec. Publ., 2013).
51.
H. J.
Woo
and
K. A.
Park
, “
Long-term trend of satellite-observed significant wave height and impact on ecosystem in the East/Japan Sea
,”
Deep. Res. Part II
143
,
1
14
(
2017
).
52.
C.
Aguirre
,
J. A.
Rutllant
, and
M.
Falvey
, “
Wind waves climatology of the Southeast Pacific Ocean
,”
Int. J. Climatol.
37
(
12
),
4288
4301
(
2017
).
53.
J.
Kang
,
R.
Mao
,
Y.
Chang
, and
H.
Fu
, “
Comparative analysis of significant wave height between a new Southern Ocean buoy and satellite altimeter
,”
Atmos. Ocean. Sci. Lett.
14
(
5
),
100044
(
2021
).
54.
Q.
Peng
and
S.
Jin
, “
Significant wave height estimation from space-borne cyclone-GNSS reflectometry
,”
Remote Sens.
11
(
5
),
584
(
2019
).
55.
P. R.
Shanas
,
V.
Sanil Kumar
, and
N. K.
Hithin
, “
Comparison of gridded multi-mission and along-track mono-mission satellite altimetry wave heights with in situ near-shore buoy data
,”
Ocean Eng.
83
,
24
35
(
2014
).
56.
A.
Setianto
and
T.
Triandini
, “
Comparison of kriging and inverse distance weighted (IDW) interpolation methods in lineament extraction and analysis
,”
J. Appl. Geol.
5
(
1
),
21
29
(
2013
).
57.
G. P.
Cressman
, “
An operational objective analysis system
,”
Mon. Weather Rev.
87
(
10
),
367
374
(
1959
).
58.
L.
Li
,
X.
Zhou
,
M.
Kalo
, and
R.
Piltner
, “
Spatiotemporal interpolation methods for the application of estimating population exposure to fine particulate matter in the contiguous U.S. and a real-time web application
,”
Int. J. Environ. Res. Public Health
13
(
8
),
749
(
2016
).
59.
C.
Leys
,
C.
Ley
,
O.
Klein
,
P.
Bernard
, and
L.
Licata
, “
Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median
,”
J. Exp. Soc. Psychol.
49
(
4
),
764
766
(
2013
).
60.
J.
Miller
, “
Short report: Reaction time analysis with outlier exclusion: Bias varies with sample size
,”
Q. J. Exp. Psychol. Sect. A
43
(
4
),
907
912
(
1991
).
61.
A.
Ribal
and
I. R.
Young
, “
33 years of globally calibrated wave height and wind speed data based on altimeter observations
,”
Sci. Data
6
(
1
),
77
(
2019
).
62.
K.-A.
Park
,
H.-J.
Woo
,
E.-Y.
Lee
,
S.
Hong
, and
K.-L.
Kim
, “
Validation of significant wave height from satellite altimeter in the Seas around Korea and error characteristics
,”
Korean J. Remote Sens.
29
(
6
),
631
644
(
2013
).
63.
F.
Monaldo
, “
Expected differences between buoy and radar altimeter estimates of wind speed and significant wave height and their implications on Buoy-altimeter comparisons
,”
J. Geophys. Res.
93
(
C3
),
2285
2302
, https://doi.org/10.1029/JC093iC03p02285 (
1988
).
64.
W. S.
Kessler
and
J. P.
McCreary
, “
The annual wind-driven Rossby wave in the subthermocline equatorial Pacific
,”
J. Phys. Oceanogr.
23
(
6
),
1192
1207
(
1993
).
65.
F.
Bi
,
J.
Song
,
K.
Wu
, and
Y.
Xu
, “
Evaluation of the simulation capability of the Wavewatch III model for Pacific Ocean wave
,”
Acta Oceanol. Sin.
34
(
9
),
43
57
(
2015
).
66.
J. L.
Hanson
,
B. A.
Tracy
,
H. L.
Tolman
, and
R. D.
Scott
, “
Pacific hindcast performance of three numerical wave models
,”
J. Atmos. Ocean. Technol.
26
(
8
),
1614
1633
(
2009
).
67.
R. J.
Smith
, “
Use and misuse of the reduced major axis for line-fitting
,”
Am. J. Phys. Anthropol.
140
(
3
),
476
486
(
2009
).
68.
Y.
Xu
,
F.
Bi
,
J.
Song
, and
H.
He
, “
The temporal and spatial variations in the Pacific wind and wave fields for the period 2002–2011
,”
Acta Oceanol. Sin.
36
(
3
),
26
36
(
2017
).
69.
B.
Liang
,
H.
Gao
, and
Z.
Shao
, “
Characteristics of global waves based on the third-generation wave model SWAN
,”
Mar. Struct.
64
,
35
53
(
2019
).
70.
J.-R.
Bidlot
,
G.
Lemos
, and
A.
Semedo
, “
ERA5 reanalysis and ERA5-based ocean wave hindcast
,” in
2nd International Workshop on Waves, Storm Surges and Coastal Hazards
,
The University of Melbourne, Australia
(
2019
).
71.
Q.
Liu
,
I. R.
Young
,
S.
Zieger
,
A.
Ribal
,
S. M.
Long
,
X.
Dong
,
Z.
Song
,
C.
Guan
, and
A. V.
Babanin
, “
On global wave height climatology and trends from multiplatform altimeter measurements and wave hindcast
,”
Ocean Model.
186
,
102264
(
2023
).
72.
M. M.
Amrutha
,
V. S.
Kumar
, and
J.
George
, “
Observations of long-period waves in the nearshore waters of central west coast of India during the fall inter-monsoon period
,”
Ocean Eng.
131
,
244
262
(
2017
).
73.
E. R.
Echevarria
,
M. A.
Hemer
, and
N. J.
Holbrook
, “
Seasonal variability of the global spectral wind wave climate
,”
JGR Oceans
124
(
4
),
2924
2939
(
2019
).
74.
P. D.
Bromirski
,
D. R.
Cayan
,
J.
Helly
, and
P.
Wittmann
, “
Wave power variability and trends across the North Pacific
,”
JGR Oceans
118
(
12
),
6329
6348
(
2013
).
75.
C. Q.
Lin
,
L. L.
Fan
,
X. Z.
Chen
,
J. H.
Li
, and
J. J.
Xu
, “
Modulation of the Madden–Julian oscillation center stagnation on typhoon genesis over the Western North Pacific
,”
Atmosphere
15
(
3
),
373
(
2024
).
76.
H.
Wang
and
C.
Wang
, “
What caused the increase of tropical cyclones in the western North Pacific during the period of 2011–2020?
Clim. Dyn.
60
(
1–2
),
165
177
(
2023
).
77.
J.
Wang
,
S.
Zhu
,
J.
Liu
,
X.
Wang
,
J.
Wang
,
J.
Xu
,
P.
Yao
, and
Y.
Yang
, “
Frequency, intensity and influences of tropical cyclones in the Northwest Pacific and China, 1977–2018
,”
Sustainability
15
(
5
),
3933
(
2023
).
78.
J. E.
Stopa
,
K. F.
Cheung
,
H. L.
Tolman
, and
A.
Chawla
, “
Patterns and cycles in the Climate Forecast System Reanalysis wind and wave data
,”
Ocean Model.
70
,
207
220
(
2013
).
79.
Z.
Wang
,
L.
Zhou
,
S.
Dong
,
L.
Wu
,
Z.
Li
,
L.
Mou
, and
A.
Wang
, “
Wind wave characteristics and engineering environment of the South China Sea
,”
J. Ocean Univ. China
13
(
6
),
893
900
(
2014
).
80.
H. S.
Kim
,
J. H.
Kim
,
C. H.
Ho
, and
P. S.
Chu
, “
Pattern classification of typhoon tracks using the fuzzy c-means clustering method
,”
J. Clim.
24
(
2
),
488
508
(
2011
).
81.
F.
Zhai
,
W.
Wu
,
Y.
Gu
,
P.
Li
, and
Z.
Liu
, “
Dynamics of the seasonal wave height variability in the South China Sea
,”
Int. J. Climatol.
41
(
2
),
934
951
(
2021
).
82.
G.
Wang
,
J.
Su
,
Y.
Ding
, and
D.
Chen
, “
Tropical cyclone genesis over the south China sea
,”
J. Mar. Syst.
68
(
3–4
),
318
326
(
2007
).
83.
J.
Sun
,
F.
Xu
,
L. Y.
Oey
, and
Y.
Lin
, “
Monthly variability of Luzon Strait tropical cyclone intensification over the Northern South China Sea in recent decades
,”
Clim. Dyn.
52
(
5–6
),
3631
3642
(
2019
).
84.
J.
Li
,
Y.
Chen
,
S.
Pan
,
Y.
Pan
,
J.
Fang
, and
D. M. A.
Sowa
, “
Estimation of mean and extreme waves in the East China Seas
,”
Appl. Ocean Res.
56
,
35
47
(
2016
).
You do not currently have access to this content.