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The past century, Earths climate is undergoing a significant change which is warming as the main feature and the warming trend will not reverse in the short term, climate warming may make different scales regional weather and climate extremes produce a significant change in the occurrence frequency. In China, Africa and the United States, many studies show that in large cities, deaths may lead to increase thousands of cases each year due to heat waves. According to 2020 and 2050 climate change projections, the mortality rate in summer there will be increased considerably, particularly the elderly is particularly difficult to adapt to high temperatures. Therefore, more and more governments and meteorologists increasingly concern of high temperatures and its variation and evaluation research is also very necessary.This paper attempts to study area high-temperature disaster events from the perspective of risk, proposed general procedures and methods to study high-temperature disaster for disaster risk analysis and evaluation of high temperature, but also enriched the theory of high-temperature system of disaster risk assessment. this article selects east China as a positive area, the findings have a certain significance for understanding the region high temperature hazard and vulnerability ,it can provide a reference to regional disaster risk management and disaster reduction.High Temperature disaster is a frequent type of natural disaster In East China. Based on 29 sites’daily maximum temperature monitoring data of 7 provinces in East China from 1951 to 2008, the days of high temperature (daily maximum temperature≥35℃) and summer (daily maximum temperature≥38℃) have been extracted and time series have been analysized using Excel and Spss. then based on basic ideas of high-temperature disaster risk analysis, and estimate high temperature strength - frequency using of Pearson-Ⅲtype probabilistic model; with ArcGIS statistical analysis and re-classification tools to carry out grid High-temperature hazard assessment and zoning in east China; then the case of Shanghai, with curve fitting tools it can draw the heat electricity, water, temperature outpatient increase emergency vulnerability curve, and finally ,it estimats water, electricity and staff costs of the value of rehabilitation ion, it reached the value of disaster losses and the loss of spatial distribution in Shanghai, then with the East China regional spatial distribution of the risk of superposition, calculate the loss distribution in east China.The results show that the heat intensity distributed in 0 d / a -73.25 d / a at 100-year scenario with the highest concentration of 35d/a-65d/. A "center - periphery diffusion" model of heat strength has been presented in the space. Nanping and Yongan in Fujian Province are the heat center followed the "low" area Jiangsu and Shandong province. The distribution of heat high-risk level is in the intersection region of Jiangxi, Fujian and Zhejiang province with low-risk level in Jiangsu, Anhui, Shandong and other province. With the reduction of return period, the risk levels and high-risk areas decreased progressively.Vulnerability of high temperature disaster can be measured with four indicators which is power consumption, water consumption, high capacity and integrated emergency, and is divided into six grades standards, through the GIS grid computing, respectively get each area of vulnerability levels in 6 typical scenario. for in 100 years scenario disaster in the electricity area of high vulnerability to 54,500 km2, area of no vulnerability is 513,000 km2; water area of high vulnerability is 33,500 km2, no Vulnerability area is 512,900 km2; the vulnerability of an area of high population 21,400 km2, the area of no vulnerability is135,300 km2; comprehensive high vulnerability area 1,700 km2, an area of vulnerability is 485 200 km2. ynthesis risk of high-temperature disaster losses includes electricity, water and population as three factors, according to low risk, low risk, medium risk, high risk and high risk levels were assigned 9,7,5,3 5 and 1, respectively calculate the space proportion of high-temperature for risk loss, get electricity, water, population, integrated risk loss space area, the whole, the overall risk is lower in the lower level of risk return period under the larger, higher weight in the smaller area under the current period, the higher the return period, the greater the value of high-risk area.
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