2014年两类南海生成台风组织化特征对比分析
Organization Features Comparison of Different Typhoons in the South China Sea in 2014
DOI: 10.12677/AG.2019.97065, PDF,    国家自然科学基金支持
作者: 秦南南:南京信息工程大学,大气科学学院,江苏 南京;尹枢楷:金陵中学,江苏 南京;李云鹤:南京外国语学校,江苏 南京
关键词: 南海台风偏角方程技术深对流云团Typhoon South China Sea Deviation Angle Variation Deep Convections
摘要: 本文选取了2014年两个具有相似生成和移动过程的南海生成命名和南海生成未命名的典型台风个例,对其生成,成熟、消亡三个阶段的组织化特征进行分析,通过比较偏差角方差(Deviation Angle Variation, DAV)技术计算结果与最佳路径资料信息以及风云云图分布特点,揭示了南海台风生命史全过程的精细化结构分布及其与路径强度变化的关系。研究表明,DAV表征的是系统内具有一定范围的深对流云团的轴对称程度,是台风内深对流组织化的量化体现。DAV极小值(Map Minimum Value, MMV)则表征系统内深对流云团轴对称化的最高程度及其中心位置。因此,当深对流云团呈环状或螺旋状分布时,MMV位置能够较好地指示环流中心所在。同时MMV量值大小与强度变化呈现明显反比关系,尤其滤去高频变化后的MMV变化与系统强度变化趋势匹配度更高。然而当深对流云团出现明显非闭合特征时,MMV所在位置总是趋向于局地对流最旺盛的区域,这使得在MMV位置与台风路径产生较大偏差,同时量值与强度的联系也不紧密。此外,地面摩擦和斜压环境场会使得系统内深对流云团的非对称结构明显,从而影响其结构与强度之间的关系。
Abstract: In this paper, two typhoons in the South China Sea, one named case and one unnamed case, with similar evolution process have been chosen to analyze their organization features in genesis, development and dissipation stages. By comparing the deviation angle variation (DAV) with the best track data from China Meteorology Administration (CMA-BST) and satellite images from Fengyun, it shows the distribution and value of DAV can quantize the symmetry of deep convections (DCs) in typhoon. The map minimum value (MMV) of DAV can identify the degree of DCs’ organization and the center of organized DCs. When DCs appear to be ring-shape or spiral-shape, the locations of MMV can be the marker of typhoon center and their values appear to be inversely related to the typhoon intensity. The relation becomes significant if filtering the high frequency signal of MMV value in time series. However, when the DCs obviously appear non-closed shape, the locations of MMV always accord to the region where the DCs are strongest in typhoon system, which may result in the deviation between MMV location trajectory and typhoon path. Then the relation of MMV value and typhoon intensity is reduced. In addition, land friction and baroclinic environment may reinforce the asymmetric distribution of DCs, which also reduce the relation of its structure to typhoon intensity.
文章引用:秦南南, 尹枢楷, 李云鹤. 2014年两类南海生成台风组织化特征对比分析[J]. 地球科学前沿, 2019, 9(7): 606-616. https://doi.org/10.12677/AG.2019.97065

参考文献

[1] 陈国民, 张喜平, 白莉娜, 等. 2016年西北太平洋和南海热带气旋预报精度评定[J]. 气象, 2018, 44(4): 116-123.
[2] Spencer, R. and Braswell, W.D. (2001) Atlantic Tropical Cyclone Monitoring with AMSU-A: Estimation of Maximum Sustained Wind Speeds. Monthly Weather Review, 129, 1518-1532. [Google Scholar] [CrossRef
[3] Dvorak, V.F. (1975) Tropical Cyclone Intensity Analysis and Forecasting from Satellite Imagery. Monthly Weather Review, 103, 420-430. [Google Scholar] [CrossRef
[4] Dvorak, V.F. (1984) Tropical Cyclone Intensity Analysis Using Satellite Data. NOAA Technical Report, 11, 6-25.
[5] Velden, C.S., Olander, T.L. and Zehr, R.M. (1998) Development of an Objective Scheme to Estimate Tropical Cyclone Intensity from Digital Geostationary Satellite Infrared Imagery. Weather Forecasting, 13, 172-186. [Google Scholar] [CrossRef
[6] Olander, T.L. and Velden, C.S. (2007) The Advanced Dvorak Technique: Continued Development of an Objective Scheme to Estimate Tropical Cyclone Intensity Using Geostationary Infrared Satellite Imagery. Weather Forecasting, 22, 287-298. [Google Scholar] [CrossRef
[7] Pineros, M.F., Ritchie, E.A. and Tyo, J.S. (2008) Objective Measures of Tropical Cyclone Structure and Intensity Change from Remotely Sensed Infrared Image Data. IEEE Transactions on Geoscience Remote Sensing, 46, 3574-3580. [Google Scholar] [CrossRef
[8] Ritchie, E.A. (1999) Large-Scale Patterns Associated with Tropical Cyclogenesis in the Western Pacific. Monthly Weather Review, 127, 2027-2043. [Google Scholar] [CrossRef
[9] 鲁小琴, 雷小途, 余晖, 等. 基于卫星资料进行热带气旋强度客观估算[J]. 应用气象学报, 2014, 25(1): 52-58.
[10] Yuan, M. and Zhong, W. (2019) Detecting Intensity Evolution of the Western North Pacific Super Typhoons in 2016 Using the Deviation Angle Variance Technique with FY Data. Journal of Meteorological Research, 33, 104-114. [Google Scholar] [CrossRef