Journal of Oceanology and Limnology

, Volume 37, Issue 2, pp 486–497 | Cite as

Coastal sea level variability in the Bohai Bay: influence of atmospheric forcing and prediction

  • Xianqing Lü
  • Daosheng WangEmail author
  • Bing Yan
  • Hua Yang


The sea level variabilities, especially the atmosphere-driven sea level variabilities, which are different in studies on diverse areas and timescales, need to be further documented in the Bohai Bay. Coastal sea level data and coincident meteorological data collected hourly at two observation stations (E1 and E2) in the Bohai Bay, which is a typical semi-enclosed coastal sea in China, are analyzed for the period from 19 August 2014 to 18 November 2014. The sub-sampled low-pass (<0.8 cpd) sea levels (SLSLs) at E1 and E2 are almost the same as each other, while the winds are not. On the whole, SLSLs at E1 and E2 are dominantly influenced by the across-shore wind; in detail, the dominant wind orientation at E1 is 65° measured clockwise from north, and SLSL at E2 is significantly influenced by the sub-sampled wind (SW) at 55°. Regression of SLSL onto the corresponding SW in dominant orientation and the atmospheric pressure is used to predict SLSL, which make the frequency of occurrences when the predicted total sea level is within 0.15 m from the observed values increase to 66.03% and 58.08% at E1 and E2 from original 36.71% and 34.80% without using it, respectively. The results indicate that for the prediction of the total sea level variability in the coastal shallow waters, the SLSL influenced by the atmospheric forcing, including local wind and atmospheric pressure, can be predicted using the multivariable linear regression model.


coastal sea level atmospheric forcing Bohai Bay prediction 


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  1. Andres M, Gawarkiewicz G G, Toole J M. 2013. Interannual sea level variability in the western North Atlantic: regional forcing and remote response. Geophysical Research Letters, 40 (22): 5 915–5 919, Scholar
  2. Cao A Z, Guo Z, Lü X Q. 2012. Inversion of two–dimensional tidal open boundary conditions of M 2 constituent in the Bohai and Yellow Seas. Chinese Journal of Oceanology and Limnology, 30 (5): 868–875,–012–1185–9.CrossRefGoogle Scholar
  3. Carrere L, Faugère Y, Ablain M. 2016. Major improvement of altimetry sea level estimations using pressure–derived corrections based on ERA–Interim atmospheric reanalysis. Ocean Science, 12 (3): 825–842.CrossRefGoogle Scholar
  4. Carrère L, Lyard F. 2003. Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing–comparisons with observations. Geophysical Research Letters, 30 (6): 1275.CrossRefGoogle Scholar
  5. Castro B M, Lee T N. 1995. Wind–forced sea level variability on the southeast Brazilian shelf. Journal of Geophysical Research: Oceans, 100 (C8): 16 045–16 056, https://doi. org/10.1029/95jc01499.CrossRefGoogle Scholar
  6. Chen X Y, Zhang X B, Church J A, Watson C S, King M A, Monselesan D, Legresy B, Harig C. 2017. The increasing rate of global mean sea–level rise during 1993–2014. Nature Climate Change, 7 (7): 492–497, Scholar
  7. Cheng Y C, Andersen O B. 2011. Multimission empirical ocean tide modeling for shallow waters and polar seas. Journal of Geophysical Research: Oceans, 116 (C11): C11001, Scholar
  8. Egbert G D, Erofeeva S Y. 2002. Efficient inverse modeling of barotropic ocean tides. Journal of Atmospheric and Oceanic Technology, 19 (2): 183–204,–0426(2002)019<0183:eimobo>;2.CrossRefGoogle Scholar
  9. Garrett C. 2001. What is the “near–inertial” band and why is it different from the rest of the internal wave spectrum? Journal of Physical Oceanography, 31 (4): 962–971,–0485(2001)031<0962:witni b>;2.CrossRefGoogle Scholar
  10. Grinsted A, Moore J C, Jevrejeva S. 2004. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11 (5–6): 561–566,–11–561–2004.CrossRefGoogle Scholar
  11. He Y J, Lu X Q, Qiu Z F, Zhao J P. 2004. Shallow water tidal constituents in the Bohai Sea and the Yellow Sea from a numerical adjoint model with TOPEX/POSEIDON altimeter data. Continental Shelf Research, 24 (13–14): 1 521–1 529, Scholar
  12. Hsueh Y, Romea R D. 1983. Wintertime winds and coastal sealevel fluctuations in the northeast China Sea. Part I: observations. Journal of Physical Oceanography, 13 (11): 2 091–2 106,–0485(1983) 013<2091:wwacsl>;2.Google Scholar
  13. Kurapov A L, Erofeeva S Y, Myers E. 2017. Coastal sea level variability in the US West Coast Ocean Forecast System (WCOFS). Ocean Dynamics, 67 (1): 23–36, https://doi. org/10.1007/s10236–016–1013–4.CrossRefGoogle Scholar
  14. Le Provost C, Lyard F, Molines J M, Genco M L, Rabilloud F. 1998. A hydrodynamic ocean tide model improved by assimilating a satellite altimeter–derived data set. Journal of Geophysical Research: Oceans, 103 (C3): 5 513–5 529, Scholar
  15. Li K P, Yang K Q. 1983. The non–periodic sea level variation in relation to wind and pressure at the Bohai Bay. Marine Sciences, (2): 12–15. (in Chinese with English abstract)Google Scholar
  16. Liu K X, Wang H, Fu S J, Gao Z G, Dong J X, Feng J L, Gao T. 2017. Evaluation of sea level rise in Bohai Bay and associated responses. Advances in Climate Change Research, 8 (1): 48–56, 2017.03.006.CrossRefGoogle Scholar
  17. Matsumoto K, Takanezawa T, Ooe M. 2000. Ocean tide models developed by assimilating TOPEX/POSEIDON altimeter data into hydrodynamical model: a global model and a regional model around Japan. Journal of Oceanography, 56 (5): 567–581, Scholar
  18. Mellor G L, Ezer T. 1995. Sea level variations induced by heating and cooling: an evaluation of the Boussinesq approximation in ocean models. Journal of Geophysical Research: Oceans, 100 (C10): 20 565–20 577, https://doi. org/10.1029/95jc02442.Google Scholar
  19. Meng W, Qin Y W, Zheng B H, Zhang L. 2008. Heavy metal pollution in Tianjin Bohai bay, China. Journal of Environmental Sciences, 20 (7): 814–819,–0742(08)62131–2.CrossRefGoogle Scholar
  20. Paraso M C, Valle–Levinson A. 1996. Meteorological influences on sea level and water temperature in the lower Chesapeake bay: 1992. Estuaries, 19 (3): 548–561, Scholar
  21. Piecuch C G, Dangendorf S, Ponte R M, Marcos M. 2016. Annual sea level changes on the North American Northeast Coast: influence of local winds and barotropic motions. Journal of Climate, 29 (13): 4 801–4 816,–d–16–0048.1.CrossRefGoogle Scholar
  22. Quartly G D, Legeais J F, Ablain M, Zawadzki L, Fernandes M J, Rudenko S, Carrère L, García P N, Cipollini P, Andersen O B, Poisson J C, Njiche S M, Cazenave A, Benveniste J. 2017. A new phase in the production of quality–controlled sea level data. Earth System Science Data, 9 (2): 557–572.CrossRefGoogle Scholar
  23. Sandstrom H. 1980. On the wind–induced sea level changes on the Scotian shelf. Journal of Geophysical Research: Oceans, 85 (C1): 461–468, Scholar
  24. Shum C K, Woodworth P L, Andersen O B, Egbert G D, Francis O, King C, Klosko S M, Le Provost C, Li X, Molines J M, Parke M E, Ray R D, Schlax M G, Stammer D, Tierney C C, Vincent P, Wunsch C I. 1997. Accuracy assessment of recent ocean tide models. Journal of Geophysical Research: Oceans, 102 (C11): 25 173–25 194, Scholar
  25. Sun P, Yu G, Chen Z Z, Hu J Y, Liu G X, Xu D H. 2015. Diagnostic model construction and example analysis of habitat degradation in enclosed bay: III. Sansha Bay habitat restoration strategy. Chinese Journal of Oceanology and Limnology, 33 (2): 477–489, https://doi. org/10.1007/s00343–015–4169–8.CrossRefGoogle Scholar
  26. Thompson P R, Merrifield M A, Wells J R, Chang C M. 2014. Wind–driven coastal sea level variability in the northeast pacific. Journal of Climate, 27 (12): 4 733–4 751,–d–13–00225.1.CrossRefGoogle Scholar
  27. Wang Y H, Fang G H, Wei Z X, Wang Y G, Wang X Y. 2010. Accuracy assessment of global ocean tide models base on satellite altimetry. Advances in Earth Science, 25 (4): 353–359. (in Chinese with English abstract)Google Scholar
  28. Xu Z H, Yin B S, Hou Y J, Xu Y S. 2013. Variability of internal tides and near–inertial waves on the continental slope of the northwestern South China Sea. Journal of Geophysical Research: Oceans, 118 (1): 197–211, 1029/2012jc008212.Google Scholar
  29. Zhang A J, Hess K W, Wei E, Myers E. 2006. Implementation of Model Skill Assessment Software for Water Level and Current in Tidal Regions. NOAA Technical Report NOS CS 24. NOAA, Silver Spring, MD. (2006–03). Accessed on 2018–6–21.Google Scholar
  30. Zhang J C, Lu X Q. 2010. Inversion of three–dimensional tidal currents in marginal seas by assimilating satellite altimetry. Computer Methods in Applied Mechanics and Engineering, 199 (49–52): 3 125–3 136, 1016/j.cma.2010.06.014.Google Scholar
  31. Zhao B R, Cao D M. 1987. Wintertime low frequency fluctuations of Chinese coastal sea–level in the Huanghai Sea and the East China Sea. Oceanologia et Limnologia Sinica, 18 (6): 563–574. (in Chinese with English abstract)Google Scholar

Copyright information

© Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xianqing Lü
    • 1
    • 2
  • Daosheng Wang
    • 2
    • 3
    • 4
    Email author
  • Bing Yan
    • 1
  • Hua Yang
    • 1
  1. 1.Key Laboratory of Engineering Sediment of the Ministry of Transport / National Engineering Laboratory for Port Hydraulic Construction TechnologyTianjin Research Institute for Water Transport Engineering, M.O.T.TianjinChina
  2. 2.Physical Oceanography Laboratory/CIMSTOcean University of China and Qingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.College of Marine Science and TechnologyChina University of GeosciencesWuhanChina
  4. 4.Shenzhen Research InstituteChina University of GeosciencesShenzhenChina

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