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This research estimates the climate change in mainland China between 1951 and 2010, and empirically analyzes the mechanism of climate change’s impact on population migration in mainland China using individual micro-data from China’s 2010 census. The study found that temperature has a significant positive effect on population migration, as the higher the temperature increases, the more likely people are to make the decision to migrate; on the contrary, rainfall has a significant negative impact on population migration, as the more the rainfall decreases, the more likely people are to make the decision to migrate. Conversely, the interaction term results show that when facing increasing temperature, females, ethnic minorities, married individuals and rural residents are more likely to migrate, while highly educated people will tend not to move out. In terms of rainfall, females, highly educated people and ethnic minorities are more likely to make migration decisions; while married individuals and rural residents are less likely to make migration decisions. The couple-matching model found that the migration decisions between couples are significantly influenced upon climate change. With the continuous rise of the Chinese government’s rural revitalization strategy, how to maintain rural residents becomes a focal issue. Rural residents are more vulnerable to climate change than urban residents, so how to effectively reduce the impact of climate change and stabilize rural residents’ production and life have become a policy-challenging issue.

Researches on the human mobility have made great progress in many aspects, but the long-term and long-distance migration behavior is lack of in-depth and extensive research because of the difficulty in accessing to household data. In this paper, we use the resume data to discover the human migration behavior on the large-scale scope. It is found that the asymmetry in the flow structure which reflects the influence of population competition is caused by the difference of attractiveness among cities. This flow structure can be approximately described by the gravity model of spatial economics. Besides, the value of scaling exponent of distance function in the gravity model is less than the value of short-term travel behavior. It means that, compared with the short-term travel behavior, the long-term human migration behavior is less sensitive. Moreover, the scaling coefficients of each variable in the gravity model are investigated. The result shows that the economic level is the main factor of migration.