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A Sensitivity Analysis of Surface Biophysical, Carbon, and Climate Impacts of Tropical Deforestation Rates in CCSM4-CNDV

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  • 1 Department of Earth and Atmospheric Sciences, and Purdue Climate Change Research Center, Purdue University, West Lafayette, Indiana
  • 2 Department of Earth and Atmospheric Sciences, and Purdue Climate Change Research Center, Purdue University, West Lafayette, Indiana, and School of Life Sciences, Arizona State University, Tempe, Arizona
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Abstract

The biophysical–climate and combined biophysical and carbon–climate feedbacks of tropical deforestation rates are explored through sensitivity analyses using the Community Climate System Model 4 with prognostic carbon–nitrogen and dynamic vegetation. Simulations test 5%, 2%, 1%, and 0.5% annual deforestation rates, each paired with preservation targets of 10% per tropical tree type. Perturbations are applied over pan-tropical land but analyses also investigate responses over the subcontinental areas of the Amazon basin, central Africa, and Southeast Asia. Sensitivities [expressed as the change in a variable per million square kilometers (Mkm2) of change in tree cover] and means of selected biophysical, carbon, and climate variables during and after deforestation are compared across rates. The most apparent effect of the rates is in hastening/postponing climate change, but otherwise results show no consistent differences across rates and vary more across subcontinents (with the Amazon basin reflecting highest sensitivities in albedo and ground temperatures, and Southeast Asia for total ecosystem carbon). Additionally, biophysical feedbacks alone were found to have significant impact on climate over subcontinental scales. In the Amazon, ground temperature increase due to biophysical feedbacks is as much as 55%, and precipitation decrease up to 61%, of combined biophysical and carbon impacts. Replication with other models is required. Although it is still unclear whether a slow but prolonged deforestation differs in impacts from one that is rapid but short, the rate can still be relevant to planning with regards to the timing of impacts.

Supplemental information related to this paper is available at the Journals Online website at http://dx.doi.org/10.1175/JCLI-D-11-00382.s1.

Corresponding author address: C. Kendra Gotangco Castillo, Department of Environmental Science, Ateneo de Manila University, Loyola Heights, Quezon City 1120, Philippines. E-mail: kgotangco@ateneo.edu

Abstract

The biophysical–climate and combined biophysical and carbon–climate feedbacks of tropical deforestation rates are explored through sensitivity analyses using the Community Climate System Model 4 with prognostic carbon–nitrogen and dynamic vegetation. Simulations test 5%, 2%, 1%, and 0.5% annual deforestation rates, each paired with preservation targets of 10% per tropical tree type. Perturbations are applied over pan-tropical land but analyses also investigate responses over the subcontinental areas of the Amazon basin, central Africa, and Southeast Asia. Sensitivities [expressed as the change in a variable per million square kilometers (Mkm2) of change in tree cover] and means of selected biophysical, carbon, and climate variables during and after deforestation are compared across rates. The most apparent effect of the rates is in hastening/postponing climate change, but otherwise results show no consistent differences across rates and vary more across subcontinents (with the Amazon basin reflecting highest sensitivities in albedo and ground temperatures, and Southeast Asia for total ecosystem carbon). Additionally, biophysical feedbacks alone were found to have significant impact on climate over subcontinental scales. In the Amazon, ground temperature increase due to biophysical feedbacks is as much as 55%, and precipitation decrease up to 61%, of combined biophysical and carbon impacts. Replication with other models is required. Although it is still unclear whether a slow but prolonged deforestation differs in impacts from one that is rapid but short, the rate can still be relevant to planning with regards to the timing of impacts.

Supplemental information related to this paper is available at the Journals Online website at http://dx.doi.org/10.1175/JCLI-D-11-00382.s1.

Corresponding author address: C. Kendra Gotangco Castillo, Department of Environmental Science, Ateneo de Manila University, Loyola Heights, Quezon City 1120, Philippines. E-mail: kgotangco@ateneo.edu

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