PROGRESS IN GEOGRAPHY

Previous Articles     Next Articles

Review on modeling of tropical cyclone rainfall

LI Ying1,2, FANG Weihua1,2,3   

  1. 1. Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Beijing Normal University, Beijing 100875, China;
    2. State Key Laboratory of Earth Surface Processes and Resources Ecology, Beijing Normal University, Beijing 100875, China;
    3. Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
  • Received:2012-09-01 Revised:2012-11-01 Online:2013-04-25 Published:2013-04-25

Abstract: China is one of the countries severely suffering from tropical cyclone (TC) disaster. Accurate rainfall modeling is of great significance for TC disaster risk assessment. From the perspective of TC disaster risk assessment, the methods of rainfall modeling can be classified into three categories, such as extreme rainfall modeling based on extreme value theory, stochastic space-time rainfall modeling based on ground station data, and TC rainfall event modeling based on stochastic TC tracks. This paper analyzes the demand of rainfall modeling for TC disaster risk assessment, and then reviews the principles, procedures, improvements and features of the three types of models. It is concluded that TC rainfall modeling for disaster risk assessment needs to integrate both the common features in rainfall modeling and the special requirements for TC rainfall simulation, in order to achieve a good balance among accuracy of TC rainfall, reliability of statistical results and computational costs. TC rainfall modeling should be based upon extreme value theory for long-term catastrophe risk analysis, and stochastic models are ideal for site-specific rainfall time series simulation, while stochastic TC rainfall event simulation, as the most advanced method, still needs further study in the areas such as rainfall mechanism and spatial structure, etc.

Key words: disaster, rainfall modeling, risk assessment, tropical cyclone