Assimilation of NASA’s Airborne Snow Observatory snow measurements for improved hydrological modeling: A case study enabled by the coupled LIS/WRF-Hydro system

Abstract:

The NASA LIS/WRF-Hydro system is a coupled modeling approach that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the surface hydrological modeling capabilities of the WRF-Hydro hydrologic model, both of which are widely used in both operations and research. This coupled modeling framework addresses the disconnect between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) observations in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias from the open-loop (OL) simulation compared to an independent dataset. It also reduces downstream streamflow runoff biases and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and ET also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. These physical added processes that affect soil moisture and ET may be important for land-atmosphere interactions.