Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

Earth & Environmental Sciences

• machine learning 78%
• land surface 68%
• parameter 27%
• surface flux 10%
• eddy covariance 9%
• bare soil 9%
• surface energy 9%
• energy balance 8%
• parameterization 7%
• climate modeling 7%
• evaporation 6%
• spatial resolution 6%
• weather 6%
• calibration 5%
• prediction 4%
• method 1%

Physics & Astronomy

• machine learning 100%
• estimates 46%
• globes 24%
• climate 11%
• weather 10%
• parameterization 9%
• soils 9%
• surface energy 8%
• partitions 8%
• spatial resolution 6%
• evaporation 6%
• exponents 6%
• vortices 6%
• predictions 4%
• performance 3%