Evidence map›Paper›PMID 42014750›Full record

ArticleScientific data2026

A global dataset of onshore wind turbines with site-specific historical (1989-2018) and future (2030-2059) wind resources across 89 countries.

Christopher Jung, Dirk Schindler

Abstract read
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Christopher JungEnvironmental Meteorology, University of Freiburg, Werthmannstrasse 10, D-79085, Freiburg, Germany. christopher.jung@mail.unr.uni-freiburg.de.
Dirk SchindlerEnvironmental Meteorology, University of Freiburg, Werthmannstrasse 10, D-79085, Freiburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The expansion of wind energy is a key strategy for mitigating global climate change. To support this goal, consistent global-scale datasets of existing wind turbines are essential for planning the future deployment of wind energy. Here, we introduce GOWIRES, a comprehensive global dataset of onshore wind turbines. GOWIRES provides detailed information on 416,417 horizontal-axis wind turbines (HAWT) across 89 countries. The dataset includes geographic coordinates, key technical specifications, and site-specific environmental characteristics for each wind turbine. In addition, GOWIRES provides historical (1989-2018) and future (2030-2059) site-specific wind resource data. Wind resources are characterized by mean wind speed, mean wind power density, Weibull parameters, power law exponents, and air density. Future Weibull parameters are based on simulations from 13 statistically downscaled global climate models under the SSP2-4.5 and SSP5-8.5 scenarios. GOWIRES is a valuable resource for energy and climate research, as well as for applications in wind energy development, grid and infrastructure planning, and policy-making.

Identifiers

PMID42014750
PMCPMC13100339

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.