Global impacts of vegetation clumping on regulating land surface heat fluxes

AGRICULTURAL AND FOREST METEOROLOGY(2024)

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Abstract
The clumping index (CI) quantifies the non-random distribution of vegetation across space, which regulates the canopy radiative transfer processes and land surface carbon, water, and energy cycles. However, its impact on global surface energy budget, particularly sensible heat fluxes and surface temperature, is not well understood. Additionally, while there have been studies showing significant seasonal variations in CI, the impacts of these variations on surface energy fluxes remain unclear. In this study, we incorporated satellite-derived spatially and temporally explicit CI data into the Community Land Model version 5 (CLM5) to evaluate the effects of CI on global land energy fluxes. Our results showed that including CI increased the global mean sensible heat flux dissipated from ground by 3.9 W m(- 2) (similar to 18%), while decreasing the global mean vegetation sensible heat flux by 4.9 W m(- 2) (similar to 65%), resulting in a total sensible heat decrease of 1.0 W m(- 2) (similar to 3%). In contrast, CI increased the global mean latent heat flux by 0.8 W m(- 2) (similar to 2%), primarily due to increased evapotranspiration (up to 11 W m(-2)) in tropical regions. We also found considerable impacts of seasonal variations in CI, particularly on sensible heat fluxes from ground and vegetation in evergreen needleleaf forests and deciduous needleleaf forests. Using constant CI rather than considering seasonal variations resulted in significant overestimation and underestimation of the sensible heat fluxes from vegetation and ground, respectively, in boreal summer. These changes in surface energy fluxes caused by CI and its seasonal variations led to up to 1.7 and 0.5 K differences in simulated mean ground temperature. These findings highlight the importance of including CI and considering its seasonal variations in modeling land surface energy fluxes.
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Key words
Clumping index,Canopy structure,Surface energy fluxes,Surface temperature,Land surface modeling
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