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 variables (LSVs) that are input to the DNN. The DNN...

Development of a Deep Learning Surrogate Model to Simulate MetOp ASCAT Observations with Land Surface Parameters

In this study, deep neural networks are employed to act as a surrogate model between the Meteo France land surface model and Advanced SCATterometer (ASCAT) satellite observations. This provides a measurement operator for the assimilation of ASCAT satellite derivations into this model. Currently, TU Wien uses ASCAT measurements to retrieve soil...