Abstract Motivated by the need to improve the representation of small‐scale surface heterogeneity in Earth System Models (ESMs), new algorithms have been introduced to discretize ESM computational units (CUs) into a variable number of subgrid topographic units for improving model simulations with minimal increase in computational demand. The algorithms can be applied to structured (regular grid) and unstructured (e.g., watersheds) CUs to derive topography‐based subgrid units (TGUs). This study evaluates the capability of the TGUs to capture surface heterogeneity within grid‐ versus watershed‐based CUs. For this purpose, TGUs are derived for the grid‐ and watershed‐based CUs at four equivalent spatial scales (1°, 0.5°, 0.25°, and 0.125° for grid‐based and Hydrologic Unit Code levels HUC07, HUC08, HUC09, and HUC10 for watershed‐based) over the CONUS domain. Statistical metrics are computed at the CU and TGU levels at each spatial scale for comparison. Results show that compared to the grid‐based TGUs, the watershed‐based TGUs are superior in capturing spatial heterogeneity associated with topographic slope, land cover, and surface hydrometeorology, despite their similar capability in capturing topographic elevation. This improved capability of the watershed‐based TGUs resulting from the combined effects of the CU and TGU level discretization is consistently found across all spatial scales examined. At the finest spatial scales (0.125° and HUC10), the watershed‐based TGUs better capture the observed precipitation, temperature, and snow water equivalent than the grid‐based TGUs at 94%, 84%, and 72% of the SNOwpack TELemetry sites, respectively, highlighting the potential advantage of the watershed‐based TGUs for improving accuracy and realism in ESM simulations.
Tesfa et al. (Thu,) studied this question.