Evidence map›Paper›PMID 42875464›Full record

ArticleNature communications2026

Global inequalities in weather forecasts.

Manuel Linsenmeier, Jeffrey G Shrader

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Global inequalities in weather forecasts.Nature communications · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Manuel LinsenmeierClimate School, Columbia University, New York, NY, USA. linsenmeier@c3s.uni-frankfurt.de.ORCID http://orcid.org/0000-0002-7790-4011
Jeffrey G ShraderSchool of International and Public Affairs, Columbia University, New York, NY, USA. jgs2103@columbia.edu.ORCID http://orcid.org/0000-0002-8981-0450

Funding

National Science Foundation (NSF) SES-2315555
6 · The paper itself

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.

Identifiers

PMID42875464
PMCPMC13669327

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.