Evidence map›Paper›PMID 39971936›Full record

ArticleScientific data2025

Global Future Drought Layers Based on Downscaled CMIP6 Models and Multiple Socioeconomic Pathways.

Diogo S A Araujo, Brian J Enquist, Amy E Frazier, Cory Merow, Patrick R Roehrdanz, Gabriel M Moulatlet, Alex Zvoleff, Lei Song, Brian Maitner, Efthymios I Nikolopoulos

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

10 authors.

Diogo S A AraujoDepartment of Civil and Environmental Engineering, Rutgers University, Piscataway, NJ, 08854, USA.ORCID http://orcid.org/0000-0002-4492-8578
Brian J EnquistDepartment of Ecology and Evolutionary Biology, University of Arizona, Tucson, 85721, USA.
Amy E FrazierDepartment of Geography, University of California, Santa Barbara, CA, 93106, USA.ORCID http://orcid.org/0000-0003-4552-4935
Cory MerowDepartment of Ecology and Evolutionary Biology and Eversource Energy Center, University of Connecticut, Storrs, CT, USA.
Patrick R RoehrdanzMoore Center for Science, Conservation International, Arlington, VA, USA.ORCID http://orcid.org/0000-0003-4047-5011
Gabriel M MoulatletDepartment of Ecology and Evolutionary Biology, University of Arizona, Tucson, 85721, USA.
Alex ZvoleffMoore Center for Science, Conservation International, Arlington, VA, USA.ORCID http://orcid.org/0000-0002-6008-4918
Lei SongDepartment of Geography, University of California, Santa Barbara, CA, 93106, USA.
Brian MaitnerDepartment of Integrative Biology, University of South Florida, St. Petersburg, FL, 33701, USA.ORCID http://orcid.org/0000-0002-2118-9880
Efthymios I NikolopoulosDepartment of Civil and Environmental Engineering, Rutgers University, Piscataway, NJ, 08854, USA. efthymios.nikolopoulos@rutgers.edu.ORCID http://orcid.org/0000-0002-5206-1249

Funding

National Science Foundation (NSF) 2243809National Science Foundation (NSF) 2416164
6 · The paper itself

Abstract

Droughts are a natural hazard of growing concern as they are projected to increase in frequency and severity for many regions of the world. The identification of droughts and their future characteristics is essential to building an understanding of the geography and magnitude of potential drought change trajectories, which in turn is critical information to manage drought resilience across multiple sectors and disciplines. Adding to this effort, we developed a dataset of global historical and projected future drought indices over the 1980-2100 period based on downscaled CMIP6 models across multiple shared socioeconomic pathways (SSP). The dataset is composed of two indices: the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) for 23 downscaled global climate models (GCMs) (0.25-degree resolution), including historical (1980-2014) and future projections (2015-2100) under four climate scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The drought indices were calculated for 3-, 6- and 12-month accumulation timescales and are available as gridded spatial datasets in a regular latitude-longitude format at monthly time resolution.

Identifiers

PMID39971936
PMCPMC11840089

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Registered trials

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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.