文献类型：期刊文献

中文题名：Energy dissipation through wind-generated breaking waves

英文题名：Energy dissipation through wind-generated breaking waves

作者：Zhang Shuwen[1];Cao Ruixue[1];Xie Lingling[1]

机构：[1]Guangdong Ocean Univ, Coll Ocean & Meteorol, Guangdong Prov Key Lab Climate Resources & Enviro, Zhanjiang 524088, Peoples R China

年份：2012

卷号：30

期号：5

起止页码：822

中文期刊名：Chinese Journal of Oceanology and Limnology

外文期刊名：CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY

收录：SCI-EXPANDED(收录号：WOS:000308357800014)、CSTPCD、、Scopus(收录号：2-s2.0-84867413074)、CSCD2011_2012、WOS、CSCD

基金：Supported by the National Natural Science Foundation of China (Nos. 40876013, 40906008, 41176011, 41106012, and U0933001) and GDUPS (2010)

语种：英文

中文关键词：near-surface dynamics; energy dissipation; wave breaking

外文关键词：near-surface dynamics; energy dissipation; wave breaking

中文摘要：Wave breaking is an important process that controls turbulence properties and fluxes of heat and mass in the upper oceanic layer.A model is described for energy dissipation per unit area at the ocean surface attributed to wind-generated breaking waves,in terms of ratio of energy dissipation to energy input,windgenerated wave spectrum,and wave growth rate.Also advanced is a vertical distribution model of turbulent kinetic energy,based on an exponential distribution method.The result shows that energy dissipation rate depends heavily on wind speed and sea state.Our results agree well with predictions of previous works.

外文摘要：Wave breaking is an important process that controls turbulence properties and fluxes of heat and mass in the upper oceanic layer. A model is described for energy dissipation per unit area at the ocean surface attributed to wind-generated breaking waves, in terms of ratio of energy dissipation to energy input, wind-generated wave spectrum, and wave growth rate. Also advanced is a vertical distribution model of turbulent kinetic energy, based on an exponential distribution method. The result shows that energy dissipation rate depends heavily on wind speed and sea state. Our results agree well with predictions of previous works.