Mass migration is one of the most concerning potential outcomes of global climate change. Recent research into environmentally induced migration suggests that relationship is much more complicated than originally posited by the βenvironmental refugeeβ hypothesis. Climate change is likely to increase migration in some cases and reduce it in others, and these movements will more often be temporary and short term than permanent and long term. However, few large-sample studies have examined the evolution of temporary migration under changing environmental conditions. To address this gap, we measure the extent to which temperature, precipitation, and flooding can predict temporary migration in Matlab, Bangladesh. Our analysis incorporates high-frequency demographic surveillance data, a discrete time event history approach, and a range of sociodemographic and contextual controls. This approach reveals that migration declines immediately after flooding but quickly returns to normal. In contrast, optimal precipitation and high temperatures have sustained positive effects on temporary migration that persist over one to two year periods. Building on previous studies of long-term migration, these results challenge the common assumption that flooding, precipitation extremes and high temperatures will consistently increase temporary migration. Instead, our results are consistent with a livelihoods interpretation of environmental migration in which households draw on a range of strategies to cope with environmental variability
