Abstract
Land-use and land-cover change significantly modify local land-surface characteristics and water/energy exchanges, which can lead to atmospheric circulation and regional climate changes. In particular, deforestation accounts for a large portion of global land-use changes, which transforms forests into other land cover types, such as croplands and grazing lands. Many previous efforts have focused on observing and modeling land–atmosphere–water/energy fluxes to investigate land–atmosphere coupling induced by deforestation. However, interpreting land–atmosphere–water/energy-flux responses to deforestation is often complicated by the concurrent impacts from shifts in land-surface properties versus background atmospheric forcings. In this study, we used 29 paired FLUXNET sites, to improve understanding of how deforested land surfaces drive changes in surface-energy-flux partitioning. Each paired sites included an intact forested and non-forested site that had similar background climate. We employed transfer entropy, a method based on information theory, to diagnose directional controls between coupling variables, and identify nonlinear cause–effect relationships. Transfer entropy is a powerful tool to detective causal relationships in nonlinear and asynchronous systems. The paired eddy covariance flux measurements showed consistent and strong information flows from vegetation activity (gross primary productivity (GPP)) and physical climate (e.g. shortwave radiation, air temperature) to evaporative fraction (EF) over both non-forested and forested land surfaces. More importantly, the information transfers from radiation, precipitation, and GPP to EF were significantly reduced at non-forested sites, compared to forested sites. We then applied these observationally constrained metrics as benchmarks to evaluate the Energy Exascale Earth System Model (E3SM) land model (ELM). ELM predicted vegetation controls on EF relatively well, but underpredicted climate factors on EF, indicating model deficiencies in describing the relationships between atmospheric state and surface fluxes. Moreover, changes in controls on surface energy flux partitioning due to deforestation were not detected in the model. We highlight the need for benchmarking model simulated surface-energy fluxes and the corresponding causal relationships against those of observations, to improve our understanding of model predictability on how deforestation reshapes land surface energy fluxes.
Highlights
The land surface and atmosphere are closely coupled through energy, water, and carbon cycles (Santanello et al 2013, Gentine et al 2019)
The E3SM land model (ELM) simulated causal controls from environmental factors to evaporative fraction (EF) can be directly compared with those derived from observations
How deforestation changes the land-surface energy partitioning First, we investigate the deforestation effects on landsurface energy partitioning between H and LE using the EF
Summary
The land surface and atmosphere are closely coupled through energy, water, and carbon cycles (Santanello et al 2013, Gentine et al 2019). The dissipated latent heat and evapotranspiration fluxes modulate atmospheric temperature and water vapor pressure, which in return can affect vegetation and soil processes (Allison and Treseder 2011, Lombardozzi et al 2015). The strengths of such two-way interactions between land and atmosphere are strongly dependent on landsurface characteristics (e.g. soil temperature, wetness) (Dirmeyer 2011, Ford et al 2014, Feldman et al 2019), and atmospheric conditions (e.g. vapor pressure deficit (VPD), radiation, and air temperature) (Zhang et al 2014, Zhou et al 2014, Kukal and Irmak 2016). Land–atmosphere interactions are largely mediated by local vegetation (e.g. grass or tree) and exhibit complex energy, water, and carbon coupling among the soil, the vegetation, and the atmosphere (Puma et al 2013, Williams and Torn 2015)
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