Temperature and precipitation projections from: Heat disproportionately kills young people: evidence from wet-bulb temperature in Mexico

Recent studies project that temperature-related mortality will be the largest source of future damage from climate change, with particular concern for the elderly (whom it is believed bear the largest heat-related mortality risk) and humid heat extremes (which physiology suggests may have dire consequences for human health). Here, we study heat and mortality in Mexico, a country that exhibits a unique combination of universal mortality microdata and among the most extreme humid heat exposures. By combining detailed measurements of wet-bulb temperature with granular, age-specific outcome data, we find that younger people are particularly vulnerable to heat while older people are particularly vulnerable to cold: those under 35 years old account for 75% of recent heat-related deaths and 87% of heat-related lost life years while those 50 and older account for 96% of cold-related deaths and 80% of cold-related lost life years. We develop high-resolution projections of humid heat and associat..., , , **Climate projections for** *Heat disproportionately kills young people: evidence from wet-bulb temperature in Mexico *([https://doi.org/10.1126/sciadv.adq3367](https://doi.org/10.1126/sciadv.adq3367))

This repo contains climate projections produced for the paper \"Heat disproportionately kills young people: evidence from wet-bulb temperature in Mexico.\" Scripts and other data needed for replication can be found at [https://doi.org/10.5281/zenodo.14182718](https://doi.org/10.5281/zenodo.14182718).

The structure of the files in this repo follows the pattern:

\_.pq

All files are parquet format, written using arrow v17.

Each file represents a time series of weather variables for each of Mexico's second-order administrative units (municipalities). Projections are made at the level of weather stations active during the study's historical data period and mapped to municipalities according to the methods described in the paper. The variables in each file are: date, scenario (GHG emissions ...