The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
GLEAM4: global land evaporation and soil moisture dataset at 0.1° resolution from 1980 to near present
Open accessAbstract
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 −1 , and Kling–Gupta efficiency of 0.49. Global land evaporation is estimated at 68.5 × 10 3 km 3 yr −1 , with 62% attributed to transpiration. Beyond actual evaporation and its components (transpiration, interception loss, soil evaporation, etc.), the dataset also provides soil moisture, potential evaporation, sensible heat flux, and evaporative stress, facilitating a wide range of hydrological, climatic, and ecological studies.
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On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters
PRIESTLEY, C. H. B., & TAYLOR, R. J. (1972) · Monthly Weather Review · doi:10.1175/1520-0493(1972)100<0081:otaosh>2.3.co;2 · Cited by 6,574
Deep learning and process understanding for data-driven Earth system science
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., & Prabhat (2019) · Nature · doi:10.1038/s41586-019-0912-1 · Cited by 5,673
ERA5-Land: a state-of-the-art global reanalysis dataset for land applications
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., et al. (2021) · Earth System Science Data · doi:10.5194/essd-13-4349-2021 · Cited by 5,540
Self-citationMONTEITH, J. (1965) · PubMed · Cited by 5,169
Europe-wide reduction in primary productivity caused by the heat and drought in 2003
Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogée, J., Allard, V., Aubinet, M., Buchmann, N., Bernhofer, C., Carrara, A., et al. (2005) · Nature · doi:10.1038/nature03972 · Cited by 4,146
Improvements to a MODIS global terrestrial evapotranspiration algorithm
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The Global Precipitation Measurement Mission
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GLEAM v3: satellite-based land evaporation and root-zone soil moisture
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., & Verhoest, N. E. C. (2017) · Geoscientific Model Development · doi:10.5194/gmd-10-1903-2017 · Cited by 2,611
Self-citationERA5 hourly data on single levels from 1940 to present
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Metadata
- Authors
- Miralles, D. G., Bonte, O., Koppa, A., Baez-Villanueva, O. M., Tronquo, E., Zhong, F., Beck, H. E., Hulsman, P., Dorigo, W., Verhoest, N. E. C., & Haghdoost, S.
- Venue
- Scientific Data
- Published
- 2025-03-10
- Volume
- 12
- Issue
- 1
- Pages
- 416-416
- ISSN
- 2052-4463 (ISSN-L)
- OpenAlex
- W4408294926
- Cited by
- 281
- References
- 61
- Type
- data paper
- Language
- en
- Open access
- gold
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- The paper
- Miralles, D. G., Bonte, O., Koppa, A., Baez-Villanueva, O. M., Tronquo, E., Zhong, F., Beck, H. E., Hulsman, P., Dorigo, W., Verhoest, N. E. C., & Haghdoost, S. (2025). GLEAM4: global land evaporation and soil moisture dataset at 0.1° resolution from 1980 to near present. Scientific Data. https://doi.org/10.1038/s41597-025-04610-y
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