Evaluating the Utility of High-Resolution Radar Precipitation Forcing for Land Surface Modeling in the Western United States

The hydrologic cycle in the western United States poses many challenges for meteorologists, hydrologists, and water resource managers due to the control that complex terrain exerts on precipitation patterns (location and phase) and the streamflow response in small catchments. Much of the arid and semi-arid western US depends on snowpack and/or groundwater for their annual water supply, which is essential for millions of people and key agricultural regions in the United States. The goal of this project is to provide estimates of variables such as groundwater recharge, soil moisture, snow water equivalent (SWE), and evapotranspiration (ET) in support of groundwater sustainability and agricultural decision making in the western United States using a combination of land surface models and remote sensing data.

The Land Information System (LIS) modeling framework developed at NASA Goddard Space Flight Center has recently been adapted and implemented for water resources applications in the western United States. The Western Land Data Assimilation System (WLDAS) leverages current advances in land surface modeling to produce spatially and temporally continuous, physically consistent estimates of the water and energy balances at a daily, 0.01 degree grid spacing using the Noah-Multiparameterization Land Surface Model. Given the fine spatial scale of the land surface simulations, precipitation forcing commensurate with the spatial scale of the model output is desirable. Multi-Radar, Multi-Sensor (MRMS) precipitation estimates (0.01 x 0.01 degrees) are the most recently developed quantitative precipitation products available from the operational radar network and are available with bias correction from gauges at an hourly timestep. In much of the western United States, however, complex topography hinders ground-based precipitation estimation.

In this presentation, various configuration and forcing schemes for the WLDAS will be introduced, and an evaluation of model performance at multiple spatial and temporal scales will be presented with specific focus on the implications and challenges of including MRMS for land surface modeling in this region. Comparisons have been conducted with numerous in situ and remotely sensed products to evaluate model performance in various components of the hydrological cycle: soil moisture, SWE, ET, and runoff at point and basin scales.