Evidence map›Paper›PMID 40064907›Full record

ArticleScientific data2025

GLEAM4: global land evaporation and soil moisture dataset at 0.1 resolution from 1980 to near present.

Diego G Miralles, Olivier Bonte, Akash Koppa, Oscar M Baez-Villanueva, Emma Tronquo, Feng Zhong, Hylke E Beck, Petra Hulsman, Wouter Dorigo, Niko E C Verhoest and 1 more

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 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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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

11 authors.

Diego G MirallesHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium. diego.miralles@ugent.be.ORCID http://orcid.org/0000-0001-6186-5751
Olivier BonteHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium.
Akash KoppaHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium.
Oscar M Baez-VillanuevaHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium.
Emma TronquoHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium.ORCID http://orcid.org/0000-0001-7528-8289
Feng ZhongHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium.
Hylke E BeckPhysical Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
Petra HulsmanHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium.
Wouter DorigoDepartment of Geodesy and Geoinformation, TU Wien, Vienna, Austria.
Niko E C VerhoestHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium.ORCID http://orcid.org/0000-0003-4116-8881
Shekoofeh HaghdoostHydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Terrestrial evaporation plays a crucial role in modulating climate and water resources. Here, we present a continuous, daily dataset covering 1980-2023 with a 0.1°spatial resolution, produced using the fourth generation of the Global Land Evaporation Amsterdam Model (GLEAM). GLEAM4 embraces developments in hybrid modelling, learning evaporative stress from eddy-covariance and sapflow data. It features improved representation of key factors such as interception, atmospheric water demand, soil moisture, and plant access to groundwater. Estimates are inter-compared with existing global evaporation products and validated against in situ measurements, including data from 473 eddy-covariance sites, showing a median correlation of 0.73, root-mean-square error of 0.95 mm d

Identifiers

PMID40064907
PMCPMC11894173

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.