This paper presents a distribution free method for predicting the extreme wind velocity from wind monitoring data at the site of the Runyang Suspension Bridge (RSB), China using the maximum entropy theory. The maximum...This paper presents a distribution free method for predicting the extreme wind velocity from wind monitoring data at the site of the Runyang Suspension Bridge (RSB), China using the maximum entropy theory. The maximum entropy theory is a rational approach for choosing the most unbiased probability distribution from a small sample, which is consistent with available data and contains a minimum of spurious information. In this paper, the theory is used for estimating a joint probability density function considering the combined action of wind speed and direction based on statistical analysis of wind monitoring data at the site of the RSB. The joint probability distribution model is further used to estimate the extreme wind velocity at the deck level of the RSB. The results of the analysis reveal that the probability density function of the maximum entropy method achieves a result that fits well with the monitoring data. Hypothesis testing shows that the distributions of the wind velocity data collected during the past three years do not obey the Gumbel distribution. Finally, our comparison shows that the wind predictions of the maximum entropy method are higher than that of the Gumbel distribution, but much lower than the design wind speed.展开更多
Based on sorting out the data, this paper makes statistics and analysis for the basic features of sea surface wind of each season in the shore and offshore areas of Qingdao and calculates the maximum wind velocity onc...Based on sorting out the data, this paper makes statistics and analysis for the basic features of sea surface wind of each season in the shore and offshore areas of Qingdao and calculates the maximum wind velocity once in a century.展开更多
针对台风数值预报中由于采用对称模型而导致预报误差的现实,通过引入非对称分布的台风最大风速、最大风速半径等因子,在得到台风报告中7级风和10级风的半径的基础上,利用最佳权系数方案来得到非对称的台风外围风速分布因子,从而对Chan a...针对台风数值预报中由于采用对称模型而导致预报误差的现实,通过引入非对称分布的台风最大风速、最大风速半径等因子,在得到台风报告中7级风和10级风的半径的基础上,利用最佳权系数方案来得到非对称的台风外围风速分布因子,从而对Chan and Williams 1987年提出的切向风廓线方案进行改造,进而得到了台风海面非对称风场的计算式。检验表明,该方法能够描述台风海面风场的非对称分布,具有较好的应用前景。展开更多
Preliminary results of the wind velocity estimation using the Maximum Entropy Method (MEM) to MU radar observation data sets are presented. The comparison of the results from the periodogram method and the MEM shows t...Preliminary results of the wind velocity estimation using the Maximum Entropy Method (MEM) to MU radar observation data sets are presented. The comparison of the results from the periodogram method and the MEM shows that the MEM estimation is reliable, and has higher accuracy, resolution and detectability than the estimation from periodogram method. The high accuracy power spectrum obtained by the MEM is very useful to studying the atmospheric turbulence structure. However. the MEM needs the longer computing time for obtaining the high accuracy spectrum. Particularly, the estimation of MEM will bring serious devia- tion at lower signal-to-noise ratio.展开更多
Based on gradient wind equations, including frictional force, and considering the effect of the movement of a tropical cyclone on wind speed, the Fujita Formula is improved and further simplified, and the numerical sc...Based on gradient wind equations, including frictional force, and considering the effect of the movement of a tropical cyclone on wind speed, the Fujita Formula is improved and further simplified, and the numerical scheme for calculating the maximum wind speed radius and wind velocity distribution of a moving tropical cyclone is derived. In addition, the effect of frictional force on the internal structure of the tropical cyclone is discussed. By comparison with observational data, this numerical scheme demonstrates great advantages, i.e. it can not only describe the asymmetrical wind speed distribution of a tropical cyclone reasonably, but can also calculate the maximum wind speed in each direction within the typhoon domain much more accurately. Furthermore, the combination of calculated and analyzed wind speed distributions by the scheme is perfectly consistent with observations.展开更多
基金Project supported by the National Natural Science Foundation of China (Nos. 50725828 and 50808041)Scientific Research Foundation of Graduate School of Southeast University (No. YBJJ0923)the Teaching and Research Foundation for Excellent Young Teacher of Southeast University,China
文摘This paper presents a distribution free method for predicting the extreme wind velocity from wind monitoring data at the site of the Runyang Suspension Bridge (RSB), China using the maximum entropy theory. The maximum entropy theory is a rational approach for choosing the most unbiased probability distribution from a small sample, which is consistent with available data and contains a minimum of spurious information. In this paper, the theory is used for estimating a joint probability density function considering the combined action of wind speed and direction based on statistical analysis of wind monitoring data at the site of the RSB. The joint probability distribution model is further used to estimate the extreme wind velocity at the deck level of the RSB. The results of the analysis reveal that the probability density function of the maximum entropy method achieves a result that fits well with the monitoring data. Hypothesis testing shows that the distributions of the wind velocity data collected during the past three years do not obey the Gumbel distribution. Finally, our comparison shows that the wind predictions of the maximum entropy method are higher than that of the Gumbel distribution, but much lower than the design wind speed.
文摘Based on sorting out the data, this paper makes statistics and analysis for the basic features of sea surface wind of each season in the shore and offshore areas of Qingdao and calculates the maximum wind velocity once in a century.
文摘针对台风数值预报中由于采用对称模型而导致预报误差的现实,通过引入非对称分布的台风最大风速、最大风速半径等因子,在得到台风报告中7级风和10级风的半径的基础上,利用最佳权系数方案来得到非对称的台风外围风速分布因子,从而对Chan and Williams 1987年提出的切向风廓线方案进行改造,进而得到了台风海面非对称风场的计算式。检验表明,该方法能够描述台风海面风场的非对称分布,具有较好的应用前景。
文摘Preliminary results of the wind velocity estimation using the Maximum Entropy Method (MEM) to MU radar observation data sets are presented. The comparison of the results from the periodogram method and the MEM shows that the MEM estimation is reliable, and has higher accuracy, resolution and detectability than the estimation from periodogram method. The high accuracy power spectrum obtained by the MEM is very useful to studying the atmospheric turbulence structure. However. the MEM needs the longer computing time for obtaining the high accuracy spectrum. Particularly, the estimation of MEM will bring serious devia- tion at lower signal-to-noise ratio.
基金supported by the National Natural Science Foundation of China (NSFC) under Grant Nos. 40425009 and 40730953
文摘Based on gradient wind equations, including frictional force, and considering the effect of the movement of a tropical cyclone on wind speed, the Fujita Formula is improved and further simplified, and the numerical scheme for calculating the maximum wind speed radius and wind velocity distribution of a moving tropical cyclone is derived. In addition, the effect of frictional force on the internal structure of the tropical cyclone is discussed. By comparison with observational data, this numerical scheme demonstrates great advantages, i.e. it can not only describe the asymmetrical wind speed distribution of a tropical cyclone reasonably, but can also calculate the maximum wind speed in each direction within the typhoon domain much more accurately. Furthermore, the combination of calculated and analyzed wind speed distributions by the scheme is perfectly consistent with observations.