Reconciling different approaches to quantifying land surface temperature impacts of afforestation using satellite observations

Abstract

Satellite observations have been widely used to examine afforestation effects on local surface temperature at large spatial scales. Different approaches, which potentially lead to differing definitions of the afforestation effect, have been used in previous studies. Despite their large differences, the results of these studies have been used in climate model validation and cited in climate synthesis reports. Such differences have been simply treated as observational uncertainty, which can be an order of magnitude bigger than the signal itself. Although the fraction of the satellite pixel actually afforested has been noted to influence the magnitude of the afforestation effect, it remains unknown whether it is a key factor which can reconcile the different approaches. Here, we provide a synthesis of three influential approaches (one estimates the actual effect and the other two the potential effect) and use large-scale afforestation over China as a test case to examine whether the different approaches can be reconciled. We found that the actual effect (ΔTa) often relates to incomplete afforestation over a medium-resolution satellite pixel (1 km). Ta increased with the afforestation fraction, which explained 89 % of its variation. One potential effect approach quantifies the impact of quasi-full afforestation (ΔTp1), whereas the other quantifies the potential impact of full afforestation (ΔTp2) by assuming a shift from 100% openland to 100% forest coverage. An initial paired-sample t test shows that ΔTa