Individuals living in every region of the world are increasingly vulnerable to negative health outcomes due to extreme heat exposure. Children, in particular, may face long-term consequences associated with heat stress that affect their educational attainment and later life health and well-being. Retrospective individual-level analyses are useful for determining the effects of extreme heat exposure on health outcomes. Typically, future risk is inferred by extrapolating these effects using future warming scenarios that are applied uniformly over space and time without consideration of topographical or climatological gradients. We propose an alternative approach using a stochastic weather generator. This approach employs a 1 °C warming scenario to produce an ensemble of plausible future weather scenarios, and subsequently a distribution of future health risks. We focus on the effect of global warming on fetal development as measured by birth weight in Ethiopia. We demonstrate that predicted changes in birth weight are sensitive to the evolution of temperatures not quantified in a uniform warming scenario. Distributions of predicted changes in birth weight vary in magnitude and variability depending on geographic and socioeconomic region. We present these distributions alongside results from the uniform warming scenario and discuss the spatiotemporal variability of these predicted changes.
Bibliographical noteFunding Information:
This work was supported by the National Science Foundation Award Abstract #1639214.
INFEWS/T1: Understanding multi-scale resilience options for vulnerable regions. Additional funding was provided via NASA Award 80NSSC19K0686: Ag Out - An Enhanced IMERG-Based Agricultural Outlook System.
© 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
- Birth weight
- Climate change
- Extreme heat
- Health surveys
- Weather generator