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    Author(s): Guang-Shan Chen; Michael Notaro; Zhengyu Liu; Yongqiang Liu
    Date: 2012
    Source: Jouranl of Climate
    Publication Series: Scientific Journal (JRNL)
    Station: Southern Research Station
    PDF: Download Publication  (1.74 MB)


    Afforestation has been proposed as a climate change mitigation strategy by sequestrating atmospheric carbon dioxide. With the goal of increasing carbon sequestration, a Congressional project has been planned to afforest about 18 million acres by 2020 in the Southeast United States (SEUS), the Great Lake states, and the Corn Belt states. However, biophysical feedbacks of afforestation have the potential to counter the beneficial climatic consequences of carbon sequestration. To assess the potential biophysical effects of afforestation over the SEUS, the authors designed a set of initial value ensemble experiments and long-term quasi-equilibrium experiments in a fully coupled Community Climate System Model, version 3.5 (CCSM3.5). Model results show that afforestation over the SEUS not only has a local cooling effect in boreal summer [June–August (JJA)] at short and long time scales but also induces remote warming over adjacent regions of the SEUS at long time scales. Precipitation, in response to afforestation, increases over the SEUS (local effect) and decreases over adjacent regions (remote effect) in JJA. The local surface cooling and increase in precipitation over SEUS in JJA are hydrologically driven by the changes in evapotranspiration and latent heat flux. The remote surface warming and decrease in precipitation over adjacent regions are adiabatically induced by anomalous subsidence. Our results suggest that the planned afforestation efforts should be developed carefully by taking account of short-term (local) and long-term (remote) biophysical effects of afforestation.

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    Chen, Guang-Shan, Michael Notaro, Zhengyu Liu, Yongqiang Liu, 2012: Simulated Local and Remote Biophysical Effects of Afforestation over the Southeast United States in Boreal Summer. J. Climate, 25, 4511–4522. doi:


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    Climate models, Hydrologic models, Land surface model, Numerical analysis/modeling

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