Earticle

초록

영어

Accurate storm tracking and forecasting are essential parts of severe weather warning operations. The main problem of existing tracking and forecasting algorithms is unphysical split and merger of cloud clusters within the life cycle of Mesoscale Convective System (MCS). To address this issue, an automatic algorithm called TFCC (Tracking and Forecasting Convective Cells) is proposed for tracking and forecasting convective cells using infrared (IR) image sequences from geostationary meteorology satellite. In this paper, convective cells are utilized for tracking and forecasting instead of MCS because convective cells are stable portion in MCS. TFCC algorithm utilizes overlapping technique and uses a dynamic constraint technique based combinatorial optimization method. Moreover, displacement of the geometrical centroid is utilized to forecast the movement of convective cells. Case studies show that convective cells are tracked and forecasted efficiently in different phases of MCS lifecycle including genesis, maturity and dissipation using TFCC algorithm. Categorical statistics and contingency tables method applied to various case studies over China show that TFCC algorithm efficiently and accurately.

목차

Abstract
 1. Introduction
 2. Methods
  2.1 Mathematical Morphology Descriptions
  2.2 The Details of TFCC Algorithm
 3. Satellite Data and Case Studies
  3.1 Satellite Data
  3.2 Case Studies
 4. Validation Method
  4.1 Contingency Tables Method
  4.2 Categorical Statistics
 5. Summary and Conclusions
 References

키워드

저자

• Jia Liu [ Nanjing University of Science and Technology, School of Computer Science and Engineering, 200 Xiaolingwei Street, Nanjing, China, 210094 ]
• Chuancai Liu [ Nanjing University of Science and Technology, School of Computer Science and Engineering, 200 Xiaolingwei Street, Nanjing, China, 210094 ]
• Chao Ma [ Nanjing University of Science and Technology, School of Computer Science and Engineering, 200 Xiaolingwei Street, Nanjing, China, 210094 ]
• Danyu Qin [ China Meteorological Administration, National Satellite Meteorological Center, 46 Zhongguancun South Street, Beijing, China, 100081 ]
• Furong Peng [ Nanjing University of Science and Technology, School of Computer Science and Engineering, 200 Xiaolingwei Street, Nanjing, China, 210094 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605