Deep learning optimizes data-driven representation of soil organic carbon in earth system model over the conterminous united states

HIGHLIGHTS

• who: Yiqi Luo from the United States of Exeter, United Kingdom United States have published the Article: Deep Learning Optimizes Data-Driven Representation of Soil Organic Carbon in Earth System Model Over the Conterminous United States, in the Journal: (JOURNAL)
• how: This study presents an innovative method via combined data assimilation and deep learning that can be used to optimally represent SOC in a complex land biogeochemical model (CLM5) with an extensive dataset of vertical soil profiles across the conterminous United_States. The authors used two sets of global SOC data WISE30sec (Batjes 2016) and SoilGrids250m . . .
  

   

  

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