Assimilation and downscaling of satellite observed soil moisture over the Little River Experimental Watershed in Georgia, USA

Downscaling of seasonal soil moisture forecasts using satellite data

A new approach to downscaling soil moisture forecasts from the seasonal ensemble prediction forecasting system of the ECMWF (European Centre for Medium-Range Weather Forecasts) is presented in this study. Soil moisture forecasts from this system are rarely used nowadays, although they could provide valuable information. Weaknesses of the model soil scheme in forecasting soil water content and t...

Comparison of Different Machine Learning Approaches for Monthly Satellite-Based Soil Moisture Downscaling over Northeast China

Although numerous satellite-based soil moisture (SM) products can provide spatiotemporally continuous worldwide datasets, they can hardly be employed in characterizing fine-grained regional land surface processes, owing to their coarse spatial resolution. In this study, we proposed a machine-learning-based method to enhance SM spatial accuracy and improve the availability of SM data. Four machi...

Hydrological downscaling of soil moisture

Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau

The inter-comparison of different soil moisture (SM) products over the Tibetan Plateau (TP) reveals the inconsistency among different SM products, when compared to in situ measurement. It highlights the need to constrain the model simulated SM with the in situ measured data climatology. In this study, the in situ soil moisture networks, combined with the classification of climate zones over the...

Downscaling of radio brightness measurements for soil moisture estimation: A four-dimensional variational data assimilation approach

This paper investigates the feasibility of estimating large-scale soil moisture profiles and related land surface variables from 1.4 GHz (L-band) passive microwave measurements, using variational data assimilation. Our four-dimensional assimilation algorithm takes into account both model and measurement uncertainties and provides dynamically consistent interpolation and extrapolation of remote ...