Water, energy, and carbon with artificial neural networks (wecann): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence

HIGHLIGHTS

• who: Biogeosciences and collaborators from the of Earth and Environmental Engineering, University, New York, USA have published the research: Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence, in the Journal: (JOURNAL)
• what: The authors develop an ANN approach to retrieve monthly estimates of LE, H, and GPP on a global scale. In this study, FLUXNET measurements from the FLUXNET 2015, the La Thuile Synthesis dataset, and the Large-scale Biosphere-Atmosphere (LBA) experiment in Brazil are used . . .
  

   

  

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