Towards constraining soil and vegetation dynamics in land surface models: Modeling ASCAT backscatter incidence-angle dependence with a Deep Neural Network

Towards constraining soil and vegetation dynamics in land surface models: Modeling ASCAT backscatter incidence-angle dependence with a Deep Neural Network

A Deep Neural Network (DNN) is used to estimate the Advanced Scatterometer (ASCAT) C-band microwave normalized backscatter (σ40o), slope (σ′) and curvature (σ″) over France. The Interactions between Soil, Biosphere and Atmosphere (ISBA) land surface model (LSM) is used to produce land surface variab...

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Bibliographic Details
Main Authors: Albergel, C. (Author), Bonan, B. (Author), Calvet, J.-C (Author), Georgievska, S. (Author), Hahn, S. (Author), Huber, M. (Author), Ku, O. (Author), Shan, X. (Author), Steele-Dunne, S. (Author), Wagner, W. (Author)
Format: Article
Language:English
Published: Elsevier Inc. 2022
Subjects:
Advanced scatterometers
ASCAT
Backscattering
Deep Neural Network
Deep neural networks
Dynamics
Land surface
Land surface model
Land surface models
Machine learning
Machine-learning
Meteorological instruments
Normalised sensitivity coefficients
Plant water
Plant water dynamic
Plant water dynamics
Radar
Scatterometry
Soil moisture
Surface measurement
Surface variables
Vegetation
Water content
Water dynamics
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