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Adapting observationally based metrics of biogeophysical feedbacks from land cover land use change to climate modeling
Adapting observationally based metrics of biogeophysical feedbacks from land cover land use change to climate modeling
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Adapting observationally based metrics of biogeophysical feedbacks from land cover land use change to climate modeling
Adapting observationally based metrics of biogeophysical feedbacks from land cover land use change to climate modeling

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Adapting observationally based metrics of biogeophysical feedbacks from land cover land use change to climate modeling
Adapting observationally based metrics of biogeophysical feedbacks from land cover land use change to climate modeling
Journal Article

Adapting observationally based metrics of biogeophysical feedbacks from land cover land use change to climate modeling

2016
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Overview
To assess the biogeophysical impacts of land cover land use change (LCLUC) on surface temperature, two observation-based metrics and their applicability in climate modeling were explored in this study. Both metrics were developed based on the surface energy balance, and provided insight into the contribution of different aspects of land surface change (such as albedo, surface roughness, net radiation and surface heat fluxes) to changing climate. A revision of the first metric, the intrinsic biophysical mechanism, can be used to distinguish the direct and indirect effects of LCLUC on surface temperature. The other, a decomposed temperature metric, gives a straightforward depiction of separate contributions of all components of the surface energy balance. These two metrics well capture observed and model simulated surface temperature changes in response to LCLUC. Results from paired FLUXNET sites and land surface model sensitivity experiments indicate that surface roughness effects usually dominate the direct biogeophysical feedback of LCLUC, while other effects play a secondary role. However, coupled climate model experiments show that these direct effects can be attenuated by large scale atmospheric changes (indirect feedbacks). When applied to real-time transient LCLUC experiments, the metrics also demonstrate usefulness for assessing the performance of climate models and quantifying land-atmosphere interactions in response to LCLUC.