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Can we advance individual-level heat-health research through the application of stochastic weather generators?

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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.

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Data availability

The authors choose to defer the responsibility of data dissemination to the agencies that develop these data. The temperature data were obtained from the Terrestrial Hydrology Research Group at Princeton University. The Demographic and Health Survey data are available with registration and justification, with approval from the United States Agency for International Development.


  1. That is, we do not specify a spatial component of the SWG, though this is possible, e.g., Verdin et al. (2018).



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Code availability

The authors will provide the custom R scripts used in this research, upon request.


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.

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Authors and Affiliations



Andrew Verdin contributed to all sections of the manuscript, including literature review, data preparation, method development and execution, post-processing of the weather generation simulations, and figure creation. He wrote the initial manuscript draft and contributed to the final manuscript draft.

Kathryn Grace contributed to the health model definition and execution and contributed to the final manuscript draft.

Frank Davenport contributed to the scenarios and model development and contributed to the final manuscript draft.

Chris Funk contributed to the scenarios and model development and contributed to the final manuscript draft.

Greg Husak contributed to discussion and interpretation of the scenarios and model output and contributed to the final manuscript draft.

Corresponding author

Correspondence to Andrew Verdin.

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Verdin, A., Grace, K., Davenport, F. et al. Can we advance individual-level heat-health research through the application of stochastic weather generators?. Climatic Change 164, 7 (2021).

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