Bad climate change may greatly increase the fragility of the country. How to evaluate the impact of climate change and mitigate the impact of climate change has become an urgent problem. With regard to task one, a data envelopment analysis (DEA) model is established to get the country's fragility. First of all, we selected 4 climate factors as input indicators and 5 output indicators. Then, we use the entropy method to determine the weight and then the national vulnerability is divided. At the same time, we get the conclusion that temperature affects GDP and the times of armed conflict directly and affects the fragility indirectly. In view of task two, we choose Somalia as an object of study. First, all the indexes are divided into 5 levels by the method of cluster analysis. Second, we select 10 countries including Somalia, to solve the decision unit matrix. Then, using the model of the problem one, it is found that the increase in temperature and rainfall will cause the national vulnerability to rise and decrease, respectively. Finally, we assign 4 climate indicators to 0 of the decision units, and draw the conclusion that national vulnerability will be reduced without the impact of climate factors. When it comes to task three, we use the rough set theory to reduce the output index to the number of armed conflicts. Then, we use the BP neural network model to predict the conclusion: There is a significant increase in fragility in cases of much more armed conflict and abnormal temperature. When the average annual armed conflict is certain, the national vulnerability index will face an increasing turning point at the temperature of 10.01 and the rainfall of 1823mm. As to task four, three policies on energy reduction and emission reduction issued by the government have been selected, and a model of carbon cycle is established. Taking China as an example, we calculate the extent of the change of the average temperature by reducing the carbon dioxide emiss

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