西北太平洋迅速加強熱帶氣旋的統計特征和識別預報試驗
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國家自然科學基金項目(41365005)、國家科技支撐項目(重大自然災害預報預警及信息共享關鍵技術研究與示范2013BAK05B03)、中國氣象局行業專項(201406014,201406006)資助


Characteristics and Identification of Rapidly Intensifying Tropical Cyclones in Western North Pacific Basin
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    摘要:

    利用2000—2014年熱帶氣旋(TC)最佳路徑、最終分析資料和靜止衛星紅外云頂亮溫(TBB)資料,對比分析了西北太平洋(WNP),以及南海(SCS)的迅速加強(RI),與非迅速加強(nonRI)TC樣本的環境背景和TBB統計特征,其中nonRI樣本細分為不同的強度變化率即:緩慢加強(SI),強度穩定、緩慢減弱和迅速減弱等。結果表明,相對于SI,WNP海域的RI樣本處于海表溫度較高、海洋上層熱容量較大、最大可能強度較大、高層輻散較強、風垂直切變(VWS)較弱和高層緯向風(U200)偏東分量較大等環境背景條件下;SCS海域的RI樣本較易發生在VWS較弱的環境背景條件下。此外,相對于nonRI,支持RI發展的有利條件還包括中低層相對濕度較大、高層環境溫度較低等。RI樣本通常具備的TBB特征為TC內核的對流云覆蓋率較大、TBB平均值相對較小。采用K最近鄰分類算法進行RI預報試驗,交叉檢驗結果表明,該方法對RI樣本有一定的識別預報能力,RI樣本概括率達到742%,技巧評分達到0.717。

    Abstract:

    The best tracks and satellitesborne infrared cloud top temperatures (TBB) observations of the National Centers for Environmental Prediction Final Analysis are employed to examine the largescale and innercore convection and characteristics of tropical cyclones (TCs) undergoing different intensity changes in the western North Pacific (WNP) and South China Sea (SCS) ocean basins from 2000 to 2014. The mean conditions of TCs cases that undergo rapid intensification (RI) are compared to those of the nonRI cases. In addition, the nonRI cases are defined in four other intensity change bins: slow intensification (SI), intensification stable (IS), slow weakness (SW) and rapid weakness (RW). For the environmental variables, statistically significant differences are found between RI cases and nonRI samples, especially in IS, SW and RW groups. In both basins, RI events tend to form in environments with weaker environmental vertical wind shear than SI cases. In the WNP, RI events occurred in high maximum potential intensity environments characterized by warmer sea surface temperature, greater upperoceanic heat content, and stronger upperlevel divergence. RI events tend to occur in favorable environments with higher lowerlevel relative humidity, and cooler upperlevel temperatures than nonRI cases. For TBB observations, RI cases have larger cold TBB covering areas in the innercore regions, and lower average symmetry TBB within the eyewalls of the storms. The KNearest Neighbor (KNN) rule is employed to identify the RI cases using leaveoneout cross validation. The results show that the verification of forecasts is generally skillful.

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李勛,趙聲蓉,王勇,吳俞,李玉梅.西北太平洋迅速加強熱帶氣旋的統計特征和識別預報試驗[J].氣象科技,2016,44(4):585~595

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  • 收稿日期:2015-07-20
  • 定稿日期:2016-04-06
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  • 在線發布日期: 2016-08-29
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