摘要
研究介绍了一种基于ASCAT散射计风场数据计算热带气旋风速达到34节和50节时风圈半径(R34和R50)大小的方法,根据美国国家海洋和大气管理局提供的最佳路径数据,分析了2013—2022年发生在西北太平洋和北大西洋的热带气旋(TC)。结果表明:ASCAT估算的R34比最佳路径记录大4.5%左右,标准误差、均方根误差和相关系数分别为8.6 km、52.4 km和0.88;R50比最佳路径记录小约4.0%,标准误差、均方根误差和相关系数分别为-15.4 km、39.6 km和0.74,说明本方法能够较好地估计TC风圈半径。两个海盆中TC强度(最大持续风速)与R34的相关性较强(相关系数为0.62~0.66),比R50(与TC强度的相关系数为0.36~0.48)能够更好地表征TC的影响强度和尺度大小,也说明了从ASCAT风场得到的风半径信息对于监测和预报TC强度是有参考价值的。用R34定义TC大小和分类统计,发现两个海盆上平均尺度的峰值出现在9月和10月,中型TC的总数量最多,3种类型TC的变化趋势总体均呈现单峰分布,小型和中型TC的峰值出现在9月,大型TC的峰值滞后1个月。
This paper introduces a method for calculating the wind radius(34-knot and 50-knot wind radii,R34 and R50)when the wind speed of a tropical cyclone reaches 34 knots and 50 knots based on the ASCAT scatterometer wind field data.Tropical cyclones(TC)occurred in the Northwest Pacific and North Atlantic from 2013 to 2022 are analyzed using Best Track dataset provided by NOAA,the results show that:The R34 estimated by ASCAT is about 4.5%larger than the Best Track record,and the standard error,root mean square error and correlation coefficient are 8.6 km,52.4 km and 0.88,respectively;The R50 is about 4.0%smaller than the Best Track record,and the corresponding values are-15.4 km,39.6 km and 0.74,respectively;The correlation coefficient between TC intensity(maximum sustained wind speed)and R34 in two basins is 0.62~0.66,while that of R50 is 0.36~0.48,suggesting that R34 has a better performance in characterizing TC's influence intensity and scale.It also indicates that the wind radius obtained from ASCAT wind field is valuable in monitoring and predicting TC's intensity.Using R34 to define the size of TC and categorical statistics,we find that the peak value of mean TC size occurs in September and October in both basins,and the total number of medium TC is the largest.The trend of the three types(small,medium,large)of TC shows unimodal distribution,the peak values of small and medium TC occur in September,and that of large TC lag by one month.
作者
董海啸
冯佳俊
张渊智
DONG Haixiao;FENG Jiajun;ZHANG Yuanzhi(School of Marine Sciences,Nanjing University of Information Science and Technology,Nanjing 210044,China)
出处
《海洋预报》
CSCD
北大核心
2023年第6期67-77,共11页
Marine Forecasts
基金
国家自然科学基金-广东联合基金重点项目(U1901215)。
