A subbasin-based framework to represent land surface processes in an Earth system model

• Main Authors: T. K. Tesfa, H.-Y. Li, L. R. Leung, M. Huang, Y. Ke, Y. Sun, Y. Liu
• Format: Article
• Language: English
• Published: Copernicus Publications 2014-05-01
• Series: Geoscientific Model Development
• Online Access: http://www.geosci-model-dev.net/7/947/2014/gmd-7-947-2014.pdf

Realistically representing spatial heterogeneity and lateral land surface processes within and between modeling units in Earth system models is important because of their implications to surface energy and water exchanges. The traditional approach of using regular grids as computational units in land surface models may lead to inadequate representation of subgrid heterogeneity and lateral movements of water, energy and carbon fluxes. Here a subbasin-based framework is introduced in the Community Land Model (CLM), which is the land component of the Community Earth System Model (CESM). Local processes are represented in each subbasin on a pseudo-grid matrix with no significant modifications to the existing CLM modeling structure. Lateral routing of water within and between subbasins is simulated with the subbasin version of a recently developed physically based routing model, Model for Scale Adaptive River Transport (MOSART). The framework is implemented in two topographically and climatically contrasting regions of the US: the Pacific Northwest and the Midwest. The relative merits of this modeling framework, with greater emphasis on scalability (i.e., ability to perform consistently across spatial resolutions) in streamflow simulation compared to the grid-based modeling framework are investigated by performing simulations at 0.125°, 0.25°, 0.5°, and 1° spatial resolutions. Comparison of the two frameworks at the finest spatial resolution showed that a small difference between the averaged forcing could lead to a larger difference in the simulated runoff and streamflow because of nonlinear processes. More systematic comparisons conducted using statistical metrics calculated between each coarse resolution and the corresponding 0.125°-resolution simulations showed superior scalability in simulating both peak and mean streamflow for the subbasin based over the grid-based modeling framework. Scalability advantages are driven by a combination of improved consistency in runoff generation and the routing processes across spatial resolutions.