Advertisement

Journal of Meteorological Research

, Volume 32, Issue 4, pp 627–635 | Cite as

Characteristics of Spatiotemporal Distribution of Sea Surface Wind along the East Coast of Guangdong Province

  • Fei Liao
  • Hua Deng
  • Pak-wai Chan
Article
  • 28 Downloads

Abstract

We analyzed the frequency distribution characteristics of wind speeds occurring at different offshore sites within a range of 0–200 km based on the sea surface wind data captured via buoys and oil platforms located along the east coast of Guangdong Province. The results of the analysis showed that average wind speed measured for each station reached a maximum in winter while minima occurred in summer, corresponding to obvious seasonal variation, and average wind speed increased with offshore distance. The prevailing wind direction at the nearshore site is the easterly wind, and the frequency of winds within 6–10 m s–1 is considerable with that of winds at > 10 m s–1. With the increase of the offshore distance, the winds were less affected by the land, and the prevailing wind direction gradually became northerly winds, predominately those at > 10 m s–1. For areas of shorter offshore distance (< 100 km), surface wind speeds fundamentally conformed to a two-parameter Weibull distribution, but there was a significant difference between wind speed probability distributions and the Weibull distribution in areas more than 100 km offshore. The mean wind speeds and wind speed standard deviations increased with the offshore distance, indicating that with the increase of the wind speed, the pulsation of the winds increased obviously, resulting in an increase in the ratio of the mean wind speed to the standard deviation of wind speed. When the ratio was large, the skewness became negative. When a relatively great degree of dispersion was noted between the observed skewness and the skewness corresponding to the theoretical Weibull curve, the wind speed probability distribution could not be adequately described by a Weibull distribution. This study provides a basis for the verification of the adaptability of Weibull distribution in different sea areas.

Key words

sea surface wind probability distribution observation buoy oil platform 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bauer, E., 1996: Characteristic frequency distributions of remotely sensed in situ and modelled wind speeds. Int. J. Climatol., 16, 1087–1102, doi: 10.1002/(SICI)1097-0088(199610) 16:10<1087::AID-JOC68>3.3.CO;2-R.CrossRefGoogle Scholar
  2. Donelan, M. A., W. M. Drennan, E. S. Saltzman, et al., 2002: Gas Transfer at Water Surfaces. American Geophysical Union, Washington, 383 pp.CrossRefGoogle Scholar
  3. Erickson III, D. J., and J. A. Taylor, 1989: Non-Weibull behavior observed in a model-generated global surface wind field frequency distribution. J. Geophys. Res., 94, 12693–12698, doi: 10.1029/JC094iC09p12693.CrossRefGoogle Scholar
  4. Floors, R., C. L. Vincent, S. E. Gryning, et al., 2013: The wind profile in the coastal boundary layer: Wind lidar measurements and numerical modelling. Bound.-Layer Meteor., 147, 469–491, doi: 10.1007/s10546-012-9791-9.CrossRefGoogle Scholar
  5. Gryning S. E., E. Batchvarova, and R. Floors, 2013: A study on the effect of nudging on long-term boundary layer profiles of wind and Weibull distribution parameters in a rural coastal area. J. Appl. Meteor. Climatol., 52, 1201–1207, doi: 10.1175/JAMC-D-12-0319.1.CrossRefGoogle Scholar
  6. Ha, K. J., S. H. Shin, and L. Mahrt, 2009: Spatial variation of the regional wind field with land–sea contrasts and complex topography. J. Appl. Meteor. Climatol., 48, 1929–1939, doi: 10.1175/2009JAMC2105.1.CrossRefGoogle Scholar
  7. He, Y. P., A. H. Monahan, C. G. Jones, et al., 2010: Probability distributions of land surface wind speeds over North America. J. Geophys. Res., 115, D04103, doi: 10.1029/2008JD010708.Google Scholar
  8. He, Y. P., N. A. McFarlane, and A. H. Monahan, 2012: The influence of boundary layer processes on the diurnal variation of the climatological near-surface wind speed probability distribution over land. J. Climate, 25, 6441–6458, doi: 10.1175/JCLI-D-11-00321.1.CrossRefGoogle Scholar
  9. Isemer, H. J., and L. Hasse, 1991: The scientific Beaufort equivalent scale: Effects on wind statistics and climatological air–sea flux estimates in the North Atlantic Ocean. J. Climate, 4, 819–836, doi: 10.1175/1520-0442(1991)004<0819:TSBESE> 2.0.CO;2.CrossRefGoogle Scholar
  10. Justus, C. G., W. R. Hargraves, A. Mikhail, et al., 1978: Methods for estimating wind speed frequency distributions. J. Appl. Meteor., 17, 350–353, doi: 10.1175/1520-0450(1978)017<0350: MFEWSF>2.0.CO;2.CrossRefGoogle Scholar
  11. Monahan, A. H., 2006a: The probability distribution of sea surface wind speeds. Part I: Theory and sea winds observations. J. Climate, 19, 497–520, doi: 10.1175/JCLI3640.1.Google Scholar
  12. Monahan, A. H., 2006b: The probability distribution of sea surface wind speeds. Part II: Dataset intercomparison and seasonal variability. J. Climate, 19, 521–534, doi: 10.1175/JCLI3641.1.Google Scholar
  13. Monahan, A. H., 2007: Empirical models of the probability distribution of sea surface wind speeds. J. Climate, 20, 5798–5814, doi: 10.1175/2007JCLI1609.1.CrossRefGoogle Scholar
  14. Pang, W. K., J. J. Forster, and M. D. Troutt, 2001: Estimation of wind speed distribution using Markov chain Monte Carlo techniques. J. Appl. Meteor., 40, 1476–1484, doi: 10.1175/1520-0450(2001)040<1476:EOWSDU>2.0.CO;2.CrossRefGoogle Scholar
  15. Pavia, E. G., and J. J. O’Brien, 1986: Weibull statistics of wind speed over the ocean. J. Climate Appl. Meteor., 25, 1324–1332, doi: 10.1175/1520-0450(1986)025<1324:WSO WSO>2.0.CO;2.CrossRefGoogle Scholar
  16. Shi, R., X. Y. Guo, D. X. Wang, et al., 2015: Seasonal variability in coastal fronts and its influence on sea surface wind in the northern South China Sea. Deep Sea Res. Part II: Top. Stud. Oceanogr., 119, 30–39, doi: 10.1016/j.dsr2.2013.12.018.CrossRefGoogle Scholar
  17. Thompson, K. R., R. F. Marsden, and D. G. Wright, 1983: Estimation of low-frequency wind stress fluctuations over the open ocean. J. Phys. Oceanogr., 13, 1003–1011, doi: 10.1175/1520-0485(1983)013<1003:EOLFWS>2.0.CO;2.CrossRefGoogle Scholar
  18. Tye, M. R., D. B. Stephenson, G. J. Holland, et al., 2014: A Weibull approach for improving climate model projections of tropical cyclone wind-speed distributions. J. Climate, 27, 6119–6133, doi: 10.1175/JCLI-D-14-00121.1.CrossRefGoogle Scholar
  19. Wang, D. X., W. Zhou, X. L. Yu, et al., 2010: Marine atmospheric boundary layers associated with summer monsoon onset over the South China Sea in 1998. Atmos. Oceanic Sci. Lett., 3, 263–270, doi: 10.1080/16742834.2010.11446880.CrossRefGoogle Scholar
  20. Wang, D. X., L. L. Zeng, X. X. Li, et al., 2013: Validation of satellite-derived daily latent heat flux over the South China Sea, compared with observations and five products. J. Atmos. Oceanic Technol., 30, 1820–1832, doi: 10.1175/JTECH-D-12-00153.1.CrossRefGoogle Scholar
  21. Wanninkhof, R., and W. R. McGillis, 1999: A cubic relationship between air–sea CO2 exchange and wind speed. Geophys. Res. Lett., 26, 1889–1892, doi: 10.1029/1999GL900363.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Guangzhou Meteorological ObservatoryGuangzhouChina
  2. 2.Guangzhou Institute of Tropical and Marine Meteorology, China Meteorological AdministrationGuangzhouChina
  3. 3.Guangdong Ecological Meteorology CenterGuangzhouChina
  4. 4.Hong Kong ObservatoryHong KongChina

Personalised recommendations