This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcast...This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform （CCMP） reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.展开更多
Studies on climate change typically consider temperature and precipitation over extended periods but less so the wind. We used the Cross-Calibrated Multi-Platform (CCMP) 24-year wind fi eld data set to investigate the...Studies on climate change typically consider temperature and precipitation over extended periods but less so the wind. We used the Cross-Calibrated Multi-Platform (CCMP) 24-year wind fi eld data set to investigate the trends of wind energy over the South China Sea during 1988-2011. The results reveal a clear trend of increase in wind power density for each of three base statistics (i.e., mean, 90 th percentile and 99 th percentile) in all seasons and for annual means. The trends of wind power density showed obvious temporal and spatial variations. The magnitude of the trends was greatest in winter, intermediate in spring, and smallest in summer and autumn. A greater trend of increase was found in the northern areas of the South China Sea than in southern parts. The magnitude of the annual and seasonal trends over the South China Sea was larger in extreme high events (i.e., 90 th and 99 th percentiles) compared to the mean conditions. Sea surface temperature showed a negative correlation with the variability of wind power density over the majority of the South China Sea in all seasons and annual means, except for winter (41.7%).展开更多
利用目前国际先进的第三代海浪模式WAVEWATCH-Ⅲ(WW3),以CCMP(Cross-Calibrated,Multi-Platform)风场为驱动场,对近22年南海的波浪能资源进行模拟研究。综合能流密度大小、能级频率、有效波高(significantwave height,SWH)和能流密度的...利用目前国际先进的第三代海浪模式WAVEWATCH-Ⅲ(WW3),以CCMP(Cross-Calibrated,Multi-Platform)风场为驱动场,对近22年南海的波浪能资源进行模拟研究。综合能流密度大小、能级频率、有效波高(significantwave height,SWH)和能流密度的长期变化趋势以及能流密度的稳定性等各方面,发现我国南海尤其是南海北部海域蕴藏着较为丰富、适宜开发的波浪能资源;并探索性地构建了一套资源评估系统,对南海的波浪能资源进行综合分析,寻找资源的相对优势区域,为海浪发电、海水淡化等波浪能资源开发工作提供科学依据。结果表明:1)南海大部分海域的能流密度在2—16kW m 1,大值区分布于吕宋海峡—中南半岛东南海域一线。2)近22年期间,南海大部分海域的SWH以0.005—0.025m a 1的速度显著性逐年线性递增,大部分海域的波浪能流密度以0.05—0.55kW m 1 a 1的速度显著性逐年线性递增。3)南海大部分海域2W m 1以上能流密度出现频率在60%以上。4)南海大部分海域波浪能流密度各月的变异系数Cv基本都在0.9以内,稳定性较好,大部分海域的月变化指数Mv指数在6以内,季节变化指数Sv指数在4以内。5)南海北部为波浪能资源的相对优势区域。展开更多
基金supported by the National Natural Science Foundation of China(Grants No.51309092 and 51379072)the Special Fund for Public Welfare Industry of the Ministry of Water Resources of China(Grant No.201201045)+1 种基金the Natural Science Fund for Colleges and Universities in Jiangsu Province(Grant No.BK20130833)the Fundamental Research Funds for the Central Universities(Grants No.2015B16014 and 2013B03414)
文摘This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform （CCMP） reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.
基金Supported by the National Natural Science Foundation of China(Nos.5171101175,41606196)the Tianjin Natural Science Foundation(No.16JCYBJC20600)+1 种基金the National Marine Renewable Energy Programs of China(No.GHME2016ZC04)the National Marine Function-Oriented Zone Planning
文摘Studies on climate change typically consider temperature and precipitation over extended periods but less so the wind. We used the Cross-Calibrated Multi-Platform (CCMP) 24-year wind fi eld data set to investigate the trends of wind energy over the South China Sea during 1988-2011. The results reveal a clear trend of increase in wind power density for each of three base statistics (i.e., mean, 90 th percentile and 99 th percentile) in all seasons and for annual means. The trends of wind power density showed obvious temporal and spatial variations. The magnitude of the trends was greatest in winter, intermediate in spring, and smallest in summer and autumn. A greater trend of increase was found in the northern areas of the South China Sea than in southern parts. The magnitude of the annual and seasonal trends over the South China Sea was larger in extreme high events (i.e., 90 th and 99 th percentiles) compared to the mean conditions. Sea surface temperature showed a negative correlation with the variability of wind power density over the majority of the South China Sea in all seasons and annual means, except for winter (41.7%).
文摘利用目前国际先进的第三代海浪模式WAVEWATCH-Ⅲ(WW3),以CCMP(Cross-Calibrated,Multi-Platform)风场为驱动场,对近22年南海的波浪能资源进行模拟研究。综合能流密度大小、能级频率、有效波高(significantwave height,SWH)和能流密度的长期变化趋势以及能流密度的稳定性等各方面,发现我国南海尤其是南海北部海域蕴藏着较为丰富、适宜开发的波浪能资源;并探索性地构建了一套资源评估系统,对南海的波浪能资源进行综合分析,寻找资源的相对优势区域,为海浪发电、海水淡化等波浪能资源开发工作提供科学依据。结果表明:1)南海大部分海域的能流密度在2—16kW m 1,大值区分布于吕宋海峡—中南半岛东南海域一线。2)近22年期间,南海大部分海域的SWH以0.005—0.025m a 1的速度显著性逐年线性递增,大部分海域的波浪能流密度以0.05—0.55kW m 1 a 1的速度显著性逐年线性递增。3)南海大部分海域2W m 1以上能流密度出现频率在60%以上。4)南海大部分海域波浪能流密度各月的变异系数Cv基本都在0.9以内,稳定性较好,大部分海域的月变化指数Mv指数在6以内,季节变化指数Sv指数在4以内。5)南海北部为波浪能资源的相对优势区域。
