Residential relocation following extreme weather events is among the costliest individual-level measures of climate change adaptation. Consequently, they are fraught with inequalities, with disadvantaged groups most adversely impacted. As climate change continues to exacerbate extreme weather events, it is imperative that we better understand how existing socioeconomic inequalities affect climate migration and how they may be offset. In this study we use network regression models to look at how internal migration patterns in the United States vary by disaster-related property damage, household income, and local-level disaster resilience. Our results show that post-disaster migration patterns vary considerably by the income level of sending and receiving counties, which suggests that income-based inequality impacts both access to relocation for individuals and the ability to rebuild for disaster-afflicted areas. We further find evidence that these inequalities are attenuated in areas with higher disaster resilience. However, because existing resilience incentivizes in situ incremental adaptation which can be a long term drain on individual wellbeing and climate adaptation resources, they should be balanced with policies that encourage relocation where appropriate.
Impact of extreme weather events on urban human flow: A perspective from location-based service data