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SCIENCE CHINA Earth Sciences, Volume 61, Issue 7: 980-994(2018) https://doi.org/10.1007/s11430-017-9156-7

Climate and extrema of ocean waves in the East China Sea

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  • ReceivedAug 7, 2017
  • AcceptedDec 4, 2017
  • PublishedJan 31, 2018

Abstract

Wave climate plays an important role in the air-sea interaction over marginal seas. Extreme wave height provides fundamental information for various ocean engineering practices, such as hazard mitigation, coastal structure design, and risk assessment. In this paper, we implement a third generation wave model and conduct a high-resolution wave hindcast over the East China Sea to reconstruct a 15-year wave field from 1988 to 2002 for derivation of monthly mean wave parameters and analysis of extreme wave conditions. The numerical results of the wave field are validated through comparison with satellite altimetry measurements, low-resolution reanalysis, and the ocean wave buoy record. The monthly averaged wave height and wave period show seasonal variation and refined spatial patterns of surface waves in the East China Sea. The climatological significant wave height and mean wave period decrease from the open ocean in the southeast toward the continental area in the northwest, with the pattern generally following the bathymetry. Extreme analysis on the significant wave height at the buoy station indicates the hindcast data underestimate the extreme values relative to the observations. The spatial pattern of extreme wave height shows single peak emerges at the southwest of Ryukyu Island although a wind forcing with multi-core structure at the extreme is applied.


Funded by

the National High Technology Research and Development Program of China(Grant)

and National Program on Global Change and Air-Sea Interaction(Grant)

the National Natural Science Foundation of China(Grant)


Acknowledgment

The authors would like to thank the SOED HPCC for their computational support, and WAFO group for supplying the code (http://www.maths.lth.se/matstat/wafo/). The CCMP wind product was provided by Earth Science Enterprise (ESE) of National Aeronautics and Space Administration (NASA). TP satellite significant wave height was downloaded from Jet Propulsion Laboratory of NASA (https://www.jpl.nasa.gov/). Comments and suggestions provided by anonymous reviewers are greatly appreciated. This work was supported by the National Natural Science Foundation of China (Grant Nos. 41476021, 41576013 & 41321004), the National High Technology Research and Development Program of China (Grant No. 2013AA122803), and National Program on Global Change and Air-Sea Interaction (Grant No. GASI-IPOVAI-04).


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  • Figure 1

    Computational domain and research area.

  • Figure 2

    Bathymetry (units: m, blue) and satellite tracks of TP (red) over the East China Sea. The buoy location of the Japan Meteorology Agency B22001 is also marked with an inverted red triangle.

  • Figure 3

    Climatological monthly mean wind vectors (units: m s−1) over the East China Sea. (a), (c), (e), (g) are from the ERA data set and (b), (d), (f), (h) are from the CCMP data.

  • Figure 4

    N-year return extreme value analysis of wind speed (units: m s−1) over the East China Sea. (a), (c), (e), (g) are from the ERA data set and (b), (d), (f), (h) are from the CCMP data.

  • Figure 5

    Time-latitude Hovmöller plot of the monthly mean Hs (units: m) from TP altimeter (a), ERA reanalysis (b) and WW3 modeling (c).

  • Figure 6

    Scatter plot of monthly mean Hs (units: m) of the along-track TP (Track 138) result versus (a) the ERA reanalysis data and (b) the WW3 hindcast result. Diagonal line represents the perfect fit where the TP result matches the result from the ERA or WW3. The contours show the number of data points in each increment square, where the increments are 0.2 m in both axes. The cross markers show the outliers where the number of data points less than 10.

  • Figure 7

    Climatological monthly mean Hs (units: m). (a), (d), (g), (j) are the TP satellite data, (b), (e), (h), (k) show the ERA reanalysis data, and the (c), (f), (i), (l) are the WW3 model hindcast.

  • Figure 8

    Climatological monthly mean Tm (units: s). (a), (c), (e), (g) are the ERA reanalysis data and the (b), (d), (f), (h) show the WW3 model hindcast.

  • Figure 9

    Extreme value analysis of Hs at buoy station (126.33°E, 28.17°N). (a)–(d) are the cumulative distribution of Hs from the buoy measurements, satellite data, reanalysis data and model hindcast, respectively. The circles are the cumulative density computed from the sampling data, and the lines are the cumulative densities estimated by the Gumbel function. (e) is the time series of yearly maximum Hs. (f) is the N-year return Hs.

  • Figure 10

    Time-latitude Hovmöller plot of the monthly maximum Hs (units: m) from TP altimeter (a), ERA reanalysis (b) and WW3 model hindcast (c).

  • Figure 11

    Scatter plot of the monthly maximum Hs of the along-track TP (Track 138) result versus (a) the ERA reanalysis data and (b) the WW3 hindcast result. Diagonal line represents the perfect fit where the TP result matches the result from ERA or WW3. The contours show the number of data points in each increment square, where the increments are 0.5 m in both axes. The cross markers show the outliers where the number of data points less than 25.

  • Figure 12

    10-year return Hs from TP satellite (Track 138), ERA reanalysis, and WW3 model hindcast.

  • Figure 13

    N-year return Hs in the East China Sea. (a), (d), (g), (j) are results computed from the TP satellite data, (b), (e), (h), (k) are from ERA reanalysis data, and (c), (f), (i), (l) are computed from the WW3 model hindcast.

  • Table 1   Climatological monthly mean Hs at Japan meteorology agency buoy B22001 (126.33°E, 28.17°N)a)

    Month

    Hs (m)

    Hs (m)

    Bias (m)

    RE

    Hs (m)

    Bias (m)

    RE

    Hs (m)

    Bias (m)

    RE

    Buoy

    TP

    TP

    TP

    ERA

    ERA

    ERA

    WW3

    WW3

    WW3

    1

    1.70

    2.46

    0.76

    30.9%

    2.04

    0.34

    20.0%

    1.96

    0.25

    14.7%

    2

    1.78

    2.15

    0.37

    20.8%

    1.97

    0.19

    10.7%

    1.88

    0.11

    6.2%

    3

    1.62

    1.86

    0.24

    14.8%

    1.71

    0.09

    5.6%

    1.68

    0.06

    3.7%

    4

    1.28

    1.78

    0.50

    39.1%

    1.39

    0.11

    8.6%

    1.40

    0.12

    9.4%

    5

    1.09

    1.33

    0.24

    22.0%

    1.22

    0.13

    11.9%

    1.20

    0.11

    10.1%

    6

    1.17

    1.70

    0.53

    45.3%

    1.27

    0.09

    7.7%

    1.27

    0.09

    7.7%

    7

    1.20

    1.54

    0.34

    28.3%

    1.25

    0.05

    4.2%

    1.33

    0.14

    11.7%

    8

    1.49

    1.83

    0.34

    22.8%

    1.55

    0.06

    4.0%

    1.65

    0.16

    10.7%

    9

    1.62

    2.02

    0.40

    24.7%

    1.63

    0.01

    0.6%

    1.67

    0.05

    3.1%

    10

    1.71

    1.70

    −0.01

    −0.6%

    1.82

    0.11

    6.4%

    1.89

    0.18

    10.5%

    11

    1.74

    2.29

    0.55

    31.6%

    1.94

    0.20

    11.5%

    2.05

    0.30

    17.2%

    12

    1.66

    1.97

    0.31

    18.7%

    1.92

    0.26

    15.7%

    1.96

    0.30

    18.1%

    Mean

    1.51

    1.89

    0.38

    25.2%

    1.64

    0.14

    9.3%

    1.66

    0.16

    10.6%

    a)The integral time period is from year 1988 to 1999 for buoy, ERA and WW3, but from year 1993 to 2001 for TP. RE denotes relative error.

  • Table 2   Climatological monthly mean Tm at Japan meteorology agency buoy B22001 (126.33°E, 28.17°N)a)

    Month

    Tm (s)

    Tm (s)

    Bias (m)

    RE

    Tm (s)

    Bias (m)

    RE

    Buoy

    ERA

    ERA

    ERA

    WW3

    WW3

    WW3

    1

    7.82

    6.79

    −1.03

    −13.2%

    6.35

    −1.48

    −18.9%

    2

    7.98

    6.76

    −1.22

    −15.3%

    6.32

    −1.65

    −20.7%

    3

    8.18

    6.65

    −1.53

    −18.7%

    6.58

    −1.59

    −19.4%

    4

    8.36

    6.34

    −2.01

    −24.0%

    6.51

    −1.85

    −22.1%

    5

    8.60

    6.17

    −2.42

    −28.1%

    6.41

    −2.19

    −25.5%

    6

    8.47

    6.15

    −2.32

    −27.4%

    6.12

    −2.36

    −27.9%

    7

    8.58

    6.32

    −2.26

    −26.3%

    6.54

    −2.04

    −23.8%

    8

    9.13

    7.00

    −2.14

    −23.4%

    7.11

    −2.02

    −22.1%

    9

    8.91

    7.03

    −1.88

    −21.1%

    6.86

    −2.05

    −23.0%

    10

    8.33

    6.98

    −1.35

    −16.2%

    6.76

    −1.57

    −18.9%

    11

    8.32

    7.13

    −1.19

    −14.3%

    7.01

    −1.31

    −15.8%

    12

    8.26

    6.99

    −1.28

    −15.5%

    6.92

    −1.34

    −16.2%

    Mean

    8.41

    6.69

    −1.72

    −20.5%

    6.62

    −1.79

    −21.3%

    a)RE denotes relative error.

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