Toward hyper-resolution land-surface modeling: The effects of fine-scale topography and soil texture on CLM4.0 simulations over the Southwestern US

Increasing computational efficiency and the need for improved accuracy are currently driving the development of hyper-resolution land-surface models that can be implemented at continental scales with resolutions of 1 km or finer. Here we report research incorporating fine-scale grid resolutions into the NCAR Community Land Model (CLM v4.0) for simulations at 1, 25, and 100 km resolution using 1 km soil and topographic information. Multiyear model runs were performed over the Southwestern U.S., including the entire state of California and the Colorado River basin. The results show changes in the total amount of CLM-modeled water storage, and changes in the spatial and temporal distributions of water in snow and soil reservoirs, as well as changes in surface fluxes and the energy balance. To inform future model progress and continued development needs and weaknesses, we compare simulation outputs to station and gridded observations of model fields. Although the higher grid-resolution model is not driven by high-resolution forcing, grid resolution changes alone yield significant improvement (reduction in error) between model outputs and observations, where the RMSE decreases by more than 35%, 36%, 34%, and 12% for soil moisture, terrestrial water storage anomaly, sensible heat, and snow water equivalent, respectively. As an additional exercise, we performed a 100 m resolution simulation over a spatial subdomain. Those results indicate that parameters such as drainage, runoff, and infiltration are significantly impacted when hillslope scales of approximate to 100 m or finer are considered, and we show the ways in which limitations of the current model physics, including no lateral flow between grid cells, may affect model simulation accuracy.