Assessment of the impacts on data assimilation performance caused by spatio-temporal gaps in satellite soil moisture data

Previous studies have shown that assimilating satellite soil moisture data in land surface models can improve the estimations of soil moisture. One of the limitations of these satellite soil moisture products is that there are often spatial gaps (in the horizontal direction) in data availability over certain areas due to issues such as dense vegetation or hilly terrain. These products are also limited in the vertical direction because, for the microwave-based products for example, the microwave radiation captured by the satellite sensors to estimate soil moisture is usually representative of a very thin top layer of soil (up to about 5 cm). Lastly, data over a specific watershed may not be available every day (i.e. temporal gaps) because of the orbital configuration of the satellite in question. From the existing literature, it is not clear what the benefits will be for soil moisture modeling, if these spatio-temporal gaps in satellite soil moisture datasets could somehow be minimized or eliminated. To answer this question, a synthetic assimilation study was carried out on the Noah-MP land surface model within the WRF-Hydro modeling system. The study was conducted with ERA5 forcing data on the Susquehanna River Basin and the Ensemble Kalman Filter was the chosen assimilation algorithm. Multiple scenarios were explored in which spatio-temporal gaps were introduced in the synthetic observations by mimicking the actual spatio-temporal gaps that are present in the SMAP soil moisture product. Results indicate that the model’s ability to accurately simulate soil moisture is much lower when assimilated observations have spatio-temporal gaps, compared to model simulations where there are no gaps in the assimilated observations. However, it was found that this lower model accuracy can be improved if the model grids with missing observations are updated based on the covariance between the soil moisture of those grids and their surrounding grids.