西北太平洋TC移动速度异常及预报误差特征的分析
发布时间：2019-05-22 12:43
【摘要】：利用国家气象局和上海台风研究所(CMA-STI)整编的西北太平洋1970—2009年热带气旋(TC,Tropical Cyclone)及TC最佳路径数据集和2005—2010年的TC路径预报误差资料,应用百分位法,确定TC移动速度异常指标,分析了40 a来西北太平洋TC移动速度及其变化异常发生的时空分布特征,研究了TC速度预报误差对路径预报误差的影响及其与大尺度引导气流之间的关系。结果显示:1)西北太平洋TC移速及移速变化累积概率达95%(5%)分位数的阈值分别为10.8 m·s~(-1)(1.43 m·s~(-1))和2.42m·s~(-1)(-1.72 m·s~(-1))。2)快速移动及加速的TC大都出现在日本海地区,而缓慢的和减速移动TC主要出现在南海区域。3)TC移动速度异常的季节变化表现为,快速移动的TC在5月出现的频率达到最高,缓慢移动的TC在10月频率达到最高,加速移动的TC在6月频率达到最高。4)近6 a的TC移速预报误差对TC路径预报误差的贡献平均约为41.6%。5)对TC路径预报误差偏大,且移速预报误差贡献大的个例分析显示,该个例大尺度环境引导气流偏弱使TC移动速度偏慢。而如果预报的大尺度环境引导气流偏强,使预报的TC移速偏快,那么就容易导致大的路径预报误差。
[Abstract]:Based on the data set of tropical cyclone (TC,Tropical Cyclone) and TC in the northwest Pacific Ocean compiled by the National Meteorological Administration and the Shanghai Typhoon Research Institute (CMA-STI), and the TC path prediction error data from 2005 to 2010, the percentile method is applied. The abnormal index of TC movement velocity is determined, and the temporal and spatial distribution characteristics of TC movement velocity and its variation anomalies in the northwest Pacific in the past 40 years are analyzed. The influence of TC velocity prediction error on path prediction error and its relationship with large scale guided air flow are studied. The results show that: 1) the threshold of 95% (5%) quantile of TC migration velocity and its cumulative probability of velocity variation in the northwest Pacific is 10.8 m 路s ~ (- 1) (1.43 m 路s ~ (- 1) and 2.42 m 路s ~ (- 1), respectively. 1) (- 1.72 m 路s ~ (- 1). 2) most of the fast moving and accelerated TC occurred in the Sea of Japan. The slow and deceleration TC mainly appeared in the South China Sea. 3) the seasonal variation of TC movement speed anomaly showed that the frequency of fast moving TC reached the highest in May, and the frequency of slow moving TC reached the highest in October. The frequency of accelerated TC is the highest in June. 4) the contribution of TC velocity prediction error in recent 6 years to TC path prediction error is about 41.6%. 5) the prediction error of TC path is too large. The analysis of an example with great contribution to the prediction error of moving velocity shows that the weak guided air flow in the large scale environment slows the movement speed of TC. If the predicted large-scale environment leads the airflow to be stronger and the predicted TC shift speed is faster, then it is easy to lead to large path prediction errors.
【作者单位】： 南京信息工程大学气象灾害教育部重点实验室;南京信息工程大学太平洋台风研究中心;
【基金】：国家自然科学基金资助项目(41575083;41575108)
【分类号】：P732
本文编号：2482948
[Abstract]:Based on the data set of tropical cyclone (TC,Tropical Cyclone) and TC in the northwest Pacific Ocean compiled by the National Meteorological Administration and the Shanghai Typhoon Research Institute (CMA-STI), and the TC path prediction error data from 2005 to 2010, the percentile method is applied. The abnormal index of TC movement velocity is determined, and the temporal and spatial distribution characteristics of TC movement velocity and its variation anomalies in the northwest Pacific in the past 40 years are analyzed. The influence of TC velocity prediction error on path prediction error and its relationship with large scale guided air flow are studied. The results show that: 1) the threshold of 95% (5%) quantile of TC migration velocity and its cumulative probability of velocity variation in the northwest Pacific is 10.8 m 路s ~ (- 1) (1.43 m 路s ~ (- 1) and 2.42 m 路s ~ (- 1), respectively. 1) (- 1.72 m 路s ~ (- 1). 2) most of the fast moving and accelerated TC occurred in the Sea of Japan. The slow and deceleration TC mainly appeared in the South China Sea. 3) the seasonal variation of TC movement speed anomaly showed that the frequency of fast moving TC reached the highest in May, and the frequency of slow moving TC reached the highest in October. The frequency of accelerated TC is the highest in June. 4) the contribution of TC velocity prediction error in recent 6 years to TC path prediction error is about 41.6%. 5) the prediction error of TC path is too large. The analysis of an example with great contribution to the prediction error of moving velocity shows that the weak guided air flow in the large scale environment slows the movement speed of TC. If the predicted large-scale environment leads the airflow to be stronger and the predicted TC shift speed is faster, then it is easy to lead to large path prediction errors.
【作者单位】： 南京信息工程大学气象灾害教育部重点实验室;南京信息工程大学太平洋台风研究中心;
【基金】：国家自然科学基金资助项目(41575083;41575108)
【分类号】：P732
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