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  The FLUXCOM ensemble of global land-atmosphere energy fluxes

Jung, M., Koirala, S., Weber, U., Ichii, K., Gans, F., Camps-Valls, G., et al. (2019). The FLUXCOM ensemble of global land-atmosphere energy fluxes. Scientific Data, 6: 74. doi:10.1038/s41597-019-0076-8.

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http://dx.doi.org/10.1038/s41597-019-0076-8 (Publisher version)
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 Creators:
Jung, Martin1, Author           
Koirala, Sujan2, Author           
Weber, Ulrich3, Author           
Ichii, Kazuhito, Author
Gans, Fabian1, 4, Author           
Camps-Valls, Gustau, Author
Papale, Dario, Author
Schwalm, Christopher, Author
Tramontana, Gianluca, Author
Reichstein, Markus3, Author           
Affiliations:
1Global Diagnostic Modelling, Dr. Martin Jung, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938311              
2Model-Data Integration, Dr. Nuno Carvalhais, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938310              
3Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1688139              
4Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938312              

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 Abstract: 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 × 103 km3 yr−1 and 76 ± 6.8 × 103 km3 yr−1). FLUXCOM products are suitable to quantify global land-atmosphere interactions and benchmark land surface model simulations.

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 Dates: 2019-04-172019-05-27
 Publication Status: Published online
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 Identifiers: Other: BGC3083
DOI: 10.1038/s41597-019-0076-8
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Title: Scientific Data
  Abbreviation : Sci. Data
Source Genre: Journal
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Publ. Info: London, United Kingdom : Nature Publishing Group
Pages: - Volume / Issue: 6 Sequence Number: 74 Start / End Page: - Identifier: ISSN: 2052-4463
CoNE: https://pure.mpg.de/cone/journals/resource/2052-4463