More Accurately Representing Topography Impacts in Modeled Land Surface Processes
Topography significantly influences many land surface processes, including surface energy balance and how energy is absorbed and emitted/reflected from land. However, nearly all Earth system models (ESMs) assume that the terrain is flat and simply neglect the topographic effects on solar radiation. This study implemented a well-validated sub-grid topographic parameterization (TOP) in the Energy Exascale Earth System Model Land Model (ELM). It demonstrates that topography affects the surface energy budget and snow processes over the Tibetan Plateau. The magnitude of these topographic effects depends on the season, elevation, and spatial scale employed. The new TOP scheme reduces ELM’s biases for simulating surface energy balance and snow hydrology, particularly for high-elevation and snow-covered regions.
This study reveals that neglecting these topographic effects can lead to large uncertainties in the simulated surface energy budget, water cycle, and snow processes. It also demonstrates that while these topographic effects are larger at finer spatial scales, they still cannot be ignored at coarse spatial scales. The study highlights the necessity of accounting for sub-grid topographic effects in land surface models. It stresses that implementing a TOP scheme in ELM can help advance our understanding of and ability to model how surface topography affects terrestrial processes over complex terrain.
Topography significantly influences incoming solar radiation at the land surface. However, nearly all the ESMs that participated in the Coupled Model Intercomparison Project (CMIP6) use a plane-parallel radiative transfer scheme and assume that the terrain is flat. This study incorporated a well-validated sub-grid TOP scheme in the ELM to quantify the effects of sub-grid topography on solar radiation flux. The results show that topography has non-negligible effects on the modeled surface energy budget, snow cover, snow depth, and surface temperature over the Tibetan Plateau. The magnitude of the sub-grid topographic effects depends on the season, elevation, and spatial scale. When compared to remote sensing data, incorporating the TOP reduces ELM’s biases for simulating surface energy balance, snow cover, and surface temperature, especially for high-elevation and snow-covered regions. This study underscores the importance of representing sub-grid topographic effects in ESMs and motivates future research to understand sub-grid topographic effects on terrestrial processes over mountainous areas.