Global inequalities in weather forecasts
Abstract Weather forecasts provide substantial economic value for society, but differences in forecast accuracy across regions can potentially exacerbate existing—and create new—economic inequalities. These differences are particularly important given the role of weather forecasts in helping prevent damage from climate change. In this paper, we provide a global analysis of the accuracy of predictions of temperature and relate our findings to existing economic inequalities. We report two stylized facts: First, temperature forecasts are much more accurate in high-income countries compared to low-income countries. A seven-day-ahead forecast in a high-income country is, on average, approximately as accurate as a one-day-ahead forecast in a low-income country. Second, while forecast accuracy has improved steadily since 1985, a persistent gap remains between high- and low-income countries. These disparities result both from differences in the inherent scientific challenge of weather predictability across regions and from unequal weather observing infrastructure. Countries with lower income have fewer land-based weather stations and radiosondes as well as lower reporting rates from existing infrastructure. Low-income countries also appear to have lower institutional capacity to issue official, local weather forecasts. Remedying the differences in monitoring infrastructure could help reduce the gap in forecast accuracy between higher-income and lower-income countries.
Authors
- Jeffrey Shrader (ORCID: https://orcid.org/0000-0002-8981-0450)
- Manuel Linsenmeier (ORCID: https://orcid.org/0000-0002-7790-4011)
Institutions
- Goethe University Frankfurt (DE)
- Princeton University (US)
- Frankfurt Institute for Advanced Studies (DE)
- Luxembourg Institute of Socio-Economic Research (LU)
- High Meadows Environmental Institute (US)
- Columbia University (US)
Publication Details
- Journal
- Nature Communications
- Published
- 2026-09-14
- DOI
- https://doi.org/10.1038/s41467-026-77630-w
- Primary Topic
- Climate variability and models
- Type
- article
- Field-Weighted Citation Impact
- 0.00