Significant wave height is an important criterion in designing coastal and offshore structures.Based on the orthogonality principle, the linear mean square estimation method is applied to calculate significant wave he...Significant wave height is an important criterion in designing coastal and offshore structures.Based on the orthogonality principle, the linear mean square estimation method is applied to calculate significant wave height in this paper.Twenty-eight-year time series of wave data collected from three ocean buoys near San Francisco along the California coast are analyzed.It is proved theoretically that the computation error will be reduced by using as many measured data as possible for the calculation of significant wave height.Measured significant wave height at one buoy location is compared with the calculated value based on the data from two other adjacent buoys.The results indicate that the linear mean square estimation method can be well applied to the calculation and prediction of significant wave height in coastal regions.展开更多
Based on global solar radiation and related meteorological data from 57 stations in China between 1961 and 2009, we analyze the variation of surface global solar radiation (G) and its relationship to meteorological el...Based on global solar radiation and related meteorological data from 57 stations in China between 1961 and 2009, we analyze the variation of surface global solar radiation (G) and its relationship to meteorological elements using linear-trend estimation, wavelet analysis, and the Mann-Kendall test. The results show that of the 33 stations with time series longer than 45 years, G is significant at the 95% confidence level. G has a decreasing trend at many stations, but results vary across different areas. The decadal departure percentage of G increased from the 1960s to 1970s, declined gradually after the 1970s, and decreased significantly in the 1980s. In the 1990s, the trend at a few sites slightly increased. The trend of cumulative variance is of four types, i.e. rise-fall, rise-fall-slight rise, rise-fall-rise, and not obvious. For changes within a year, the most obvious decline was in winter, and the rest of the year had a slight decrease. The major cycles of annual G were 6-9, 10-13, and 29-33 a. The inflection points were mostly in the 1970s. The reasons for greater changes were complex. Relevant meteorological elements were selected and analyzed by statistical methods. Trends in climatic parameters, such as annual average percentage of sunshine, annual average wind speed, and annual average of low cloud cover, were closely related to G. Thus, this indicated the potential causes of the observed trends in G. The long-term trend for annual G in some regions was also influenced by anthro- pogenic activities. Annual average percentage of sunshine and annual average wind speed were positively correlated with annual G, respectively.展开更多
基金support for this study was provided by the National Natural Science Foundation of China (No.40776006)Research Fund for the Doctoral Program of Higher Education of China (Grant No.20060423009)the Science and Technology Development Program of Shandong Province (Grant No.2008GGB01099)
文摘Significant wave height is an important criterion in designing coastal and offshore structures.Based on the orthogonality principle, the linear mean square estimation method is applied to calculate significant wave height in this paper.Twenty-eight-year time series of wave data collected from three ocean buoys near San Francisco along the California coast are analyzed.It is proved theoretically that the computation error will be reduced by using as many measured data as possible for the calculation of significant wave height.Measured significant wave height at one buoy location is compared with the calculated value based on the data from two other adjacent buoys.The results indicate that the linear mean square estimation method can be well applied to the calculation and prediction of significant wave height in coastal regions.
基金supported by the Special Scientific Research Fund of the Meteorological Public Welfare Profession of China (Grant No.GYHY201006036)the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No.IAP09303)the Major State Basic Research Development Program of China (Grant No.2010CB428401)
文摘Based on global solar radiation and related meteorological data from 57 stations in China between 1961 and 2009, we analyze the variation of surface global solar radiation (G) and its relationship to meteorological elements using linear-trend estimation, wavelet analysis, and the Mann-Kendall test. The results show that of the 33 stations with time series longer than 45 years, G is significant at the 95% confidence level. G has a decreasing trend at many stations, but results vary across different areas. The decadal departure percentage of G increased from the 1960s to 1970s, declined gradually after the 1970s, and decreased significantly in the 1980s. In the 1990s, the trend at a few sites slightly increased. The trend of cumulative variance is of four types, i.e. rise-fall, rise-fall-slight rise, rise-fall-rise, and not obvious. For changes within a year, the most obvious decline was in winter, and the rest of the year had a slight decrease. The major cycles of annual G were 6-9, 10-13, and 29-33 a. The inflection points were mostly in the 1970s. The reasons for greater changes were complex. Relevant meteorological elements were selected and analyzed by statistical methods. Trends in climatic parameters, such as annual average percentage of sunshine, annual average wind speed, and annual average of low cloud cover, were closely related to G. Thus, this indicated the potential causes of the observed trends in G. The long-term trend for annual G in some regions was also influenced by anthro- pogenic activities. Annual average percentage of sunshine and annual average wind speed were positively correlated with annual G, respectively.
