The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
The FLUXCOM ensemble of global land-atmosphere energy fluxes
Open accessAbstract
Although a key driver of Earth’s climate system, global land-atmosphere energy fluxes are poorly constrained. Here we use machine learning to merge energy flux measurements from FLUXNET eddy covariance towers with remote sensing and meteorological data to estimate global gridded net radiation, latent and sensible heat and their uncertainties. The resulting FLUXCOM database comprises 147 products in two setups: (1) 0.0833° resolution using MODIS remote sensing data (RS) and (2) 0.5° resolution using remote sensing and meteorological data (RS + METEO). Within each setup we use a full factorial design across machine learning methods, forcing datasets and energy balance closure corrections. For RS and RS + METEO setups respectively, we estimate 2001–2013 global (±1 s.d.) net radiation as 75.49 ± 1.39 W m −2 and 77.52 ± 2.43 W m −2 , sensible heat as 32.39 ± 4.17 W m −2 and 35.58 ± 4.75 W m −2 , and latent heat flux as 39.14 ± 6.60 W m −2 and 39.49 ± 4.51 W m −2 (as evapotranspiration, 75.6 ± 9.8 × 10 3 km 3 yr −1 and 76 ± 6.8 × 10 3 km 3 yr −1 ). FLUXCOM products are suitable to quantify global land-atmosphere interactions and benchmark land surface model simulations.
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Self-citationMODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets
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Recent decline in the global land evapotranspiration trend due to limited moisture supply
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Cited by
The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Cheah, Y.-W., Poindexter, C., Chen, J., Elbashandy, A., Humphrey, M., et al. (2020) · Scientific Data · doi:10.1038/s41597-020-0534-3 · Cited by 1,728
Self-citationJung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., et al. (2020) · Biogeosciences · doi:10.5194/bg-17-1343-2020 · Cited by 866
Self-citationRepresentativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites
Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., et al. (2021) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2021.108350 · Cited by 497
Pan, S., Pan, N., Tian, H., Friedlingstein, P., Sitch, S., Shi, H., Arora, V. K., Haverd, V., Jain, A. K., Kato, E., et al. (2020) · Hydrology and Earth System Sciences · doi:10.5194/hess-24-1485-2020 · Cited by 365
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., et al. (2025) · Scientific Data · doi:10.1038/s41597-025-04610-y · Cited by 281
Metadata
- Authors
- Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G., Papale, D., Schwalm, C., Tramontana, G., & Reichstein, M.
- Venue
- Scientific Data
- Published
- 2019-05-27
- Volume
- 6
- Issue
- 1
- Pages
- 74-74
- ISSN
- 2052-4463 (ISSN-L)
- OpenAlex
- W2904321320
- Cited by
- 803
- References
- 45
- Type
- data paper
- Language
- en
- Open access
- gold
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- Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G., Papale, D., Schwalm, C., Tramontana, G., & Reichstein, M. (2019). The FLUXCOM ensemble of global land-atmosphere energy fluxes. Scientific Data. https://doi.org/10.1038/s41597-019-0076-8
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