globalchange  > 影响、适应和脆弱性
DOI: 10.1007/s00382-018-4071-0
Scopus记录号: 2-s2.0-85040860619
论文题名:
A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm
作者: Huang X.; Hu C.; Huang X.; Chu Y.; Tseng Y.-H.; Zhang G.J.; Lin Y.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2018
卷: 51, 期:2018-07-08
起始页码: 3145
结束页码: 3159
语种: 英语
英文关键词: Area-overlapping ; Kalman filter ; Mesoscale convective systems ; Objective tracking
英文摘要: Mesoscale convective systems (MCSs) are important components of tropical weather systems and the climate system. Long-term data of MCS are of great significance in weather and climate research. Using long-term (1985–2008) global satellite infrared (IR) data, we developed a novel objective automatic tracking algorithm, which combines a Kalman filter (KF) with the conventional area-overlapping method, to generate a comprehensive MCS dataset. The new algorithm can effectively track small and fast-moving MCSs and thus obtain more realistic and complete tracking results than previous studies. A few examples are provided to illustrate the potential application of the dataset with a focus on the diurnal variations of MCSs over land and ocean regions. We find that the MCSs occurring over land tend to initiate in the afternoon with greater intensity, but the oceanic MCSs are more likely to initiate in the early morning with weaker intensity. A double peak in the maximum spatial coverage is noted over the western Pacific, especially over the southwestern Pacific during the austral summer. Oceanic MCSs also persist for approximately 1 h longer than their continental counterparts. © 2018, The Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/109090
Appears in Collections:影响、适应和脆弱性
气候变化事实与影响

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作者单位: Ministry of Education Key Laboratory for Earth System Modeling, and Department for Earth System Science, Tsinghua University, Beijing, 100084, China; Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China; National Supercomputing Center in Wuxi, Wuxi, 214072, China; Department of Electrical and Electronic Engineering, Imperial College, London, United Kingdom; Institute of Oceanography, National Taiwan University, Taipei, Taiwan; Scripps Institution of Oceanography, La Jolla, CA, United States

Recommended Citation:
Huang X.,Hu C.,Huang X.,et al. A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm[J]. Climate Dynamics,2018-01-01,51(2018-07-08)
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