Abstract
Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.
Highlights
Background & SummaryChanges in vegetation cover influence the climate through both biogeochemical and biophysical mechanisms[1,2,3]
The biophysical effects are more local in nature and often result from more complex and bidirectional landclimate interactions[4]
These processes clearly show how the biophysical effects of land cover change can vary in sign and magnitude depending on the background climate[9] and must be quantified at local levels
Summary
Changes in vegetation cover influence the climate through both biogeochemical and biophysical mechanisms[1,2,3]. In cold climates the albedo effect is amplified by snow cover as trees are more effective than grasses in masking out the radiative cooling effect from snow on the ground, while in water limited regions variations in evapotranspiration become more relevant These processes clearly show how the biophysical effects of land cover change can vary in sign and magnitude depending on the background climate[9] and must be quantified at local levels. A third way that has gained increased traction lies in exploiting the capacity of satellite remote sensing observations to derive different diagnostics at different scales[5,7,8,19,20] These studies vary in complexity and scope, none have resulted in an explicit spatial dataset describing potential changes in i) the full energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would be required for the comprehensive evaluation of land based mitigation plans. We expect that our observation-driven dataset could serve as a baseline in the development of monitoring, reporting and verification guidelines for the implementation of landbased biophysical climate mitigation and adaptation options, mirroring what is currently done for biogeochemical land-processes
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