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 framework that combines the and data assimilation (DA) capabilities of Land Information System (LIS) with multi‐scale surface hydrological WRF‐Hydro model, both which are widely used in operations research. This builds on linkage between land models (LSMs), simulate boundary conditions atmospheric models, distributed hydrologic horizontal sub‐surface flow, adding new DA capabilities. In present study, we employ this Tuolumne River basin central California. We demonstrate added value Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates basin. analysis performed LIS as an LSM column model LIS/WRF‐Hydro, routing. Results ASO reduced bias by much 30% from open‐loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases 40%, improves skill scores wet dry years. Analysis soil moisture evapotranspiration (ET) reveals impacts routing simulations, would otherwise not be resolved model. By demonstrating beneficial impact SWE improving forecasts, article outlines importance such observational inputs for reservoir related management applications.