Journal Article
Geoscientific Model Development, vol. 15, iss. 14, pp. 5489-5510, 2022
Authors
Lingcheng Li, Gautam Bisht, L. Ruby Leung
Abstract
Abstract. Understanding the influence of land surface heterogeneity on surface water and energy fluxes is crucial for modeling earth system variability and
change. This study investigates the effects of four dominant heterogeneity sources on land surface modeling, including atmospheric forcing (ATM),
soil properties (SOIL), land use and land cover (LULC), and topography (TOPO). Our analysis focused on their impacts on the partitioning of
precipitation (P) into evapotranspiration (ET) and runoff (R), partitioning of net radiation into sensible heat and latent heat, and
corresponding water and energy fluxes. An initial set of 16 experiments were performed over the continental US (CONUS) using the E3SM land model
(ELMv1) with different combinations of heterogeneous and homogeneous datasets. The Sobol' total and first-order sensitivity indices were utilized to
quantify the relative importance of the four heterogeneity sources. Sobol' total sensitivity index measures the total heterogeneity effects induced
by a given heterogeneity source, consisting of the contribution from its own heterogeneity (i.e., the first-order index) and its interactions with
other heterogeneity sources. ATM and LULC are the most dominant heterogeneity sources in determining spatial variability of water and energy
partitioning, mainly contributed by their own heterogeneity and slightly contributed by their interactions with other heterogeneity sources. Their
heterogeneity effects are complementary, both spatially and temporally. The overall impacts of SOIL and TOPO are negligible, except TOPO dominates
the spatial variability of R/P across the transitional climate zone between the arid western and humid eastern CONUS. Accounting for more
heterogeneity sources improves the simulated spatial variability of water and energy fluxes when compared with ERA5-Land reanalysis dataset. An
additional set of 13 experiments identified the most critical components within each heterogeneity source, which are precipitation, temperature, and
longwave radiation for ATM, soil texture, and soil color for SOIL and maximum fractional saturated area parameter for TOPO.
