Research Of Tropical Cyclone Damage Forecasting Technology And Development Of Its Decision Support System

Meteorological service of decision-making makes a tremendous role on major disaster prevention and mitigation of meteorological disasters in our country, people’s life and property is protected, since meteorology decision-making has been raised. Benefit is obvious. With advances in technology, continuous improvement of people’s living standards and rapid development of society, people and government put forward higher requirements in decision-making meteorological service. Tropical cyclones, especially typhoons is one of the most serious meteorological disasters that affect Chinese coastal areas, there’re important application value and practical significance in the research.Now the forecasting and monitoring of typhoon has already reached a very high level in china, what play an important part in typhoon disaster protecting. Typhoon disaster protecting and mitigation is system engineering, the work only to forecast and monitor tropical cyclone is not enough, we must evaluation person, society and disaster as a whole. If we can forecast the damage and influence according to the weather report, and establish typhoon decision support system, meteorology decision-making will be more effective.We want to forecast damage such as submergence farmland area and direct economic losses, according to weather report, provincial characteristics and historical typhoon data, then make decisions according to forecasting result. To evaluate the combined effect of the region’s social situation, and help the government decision-making and directive masses to resist disasters. Through the search, statistics, research the relevant historical data, regional characteristic data and some current methods, we identify the evaluation index, apply fuzzy mathematics method to evaluate typhoon’s causing capacity, to be equivalent to TNT bomb, not involved in region difference. Based on the method of Artificial Neural Network, we use causing capacity index, regional feature and meteorological forecast level as input, use disaster losses like natural economy loss as output to forecast the damage. We evaluate social comprehensive effect by analytic hierarchy process and forecast the influence in one region caused by one typhoon at the crowd. Finally, we build the decision support system which can forecast the damage, the system is B/S structure, and works with GIS.