B21D-0502
Carbon Residence Time Explains Changes in Predicted 21st Century Vegetation Carbon across CMIP5 Earth System Models

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Lifen Jiang, University of Oklahoma Norman Campus, Norman, OK, United States
Abstract:
Global averaged surface temperature has increased by 0.6 °C over the period 1986 to 2005; and will continue rising 1.0-3.7 °C during the last 30 years of this century. Land ecosystems can sequester approximately one third of annual anthropogenic carbon dioxide emission. Therefore, dynamics of land sink is one of the key components to determine the future atmospheric CO2 concentration and accordingly surface temperature. The accuracy of predicted surface temperature will largely depend on the uncertainty of predicted land carbon uptake. Unfortunately, the uncertainties of future land sink predicted by Earth System Models (ESMs) involved in CMIP5 turned out to be very large. The spread of the land carbon uptake within a specific Representative Concentration Pathway (RCP) scenario was larger than those variation between the four scenarios. Moreover, predicted soil carbon stocks by the end of this century extended to a wide range. Quantifying the uncertainties in predicted vegetation carbon and identifying the causes for the uncertainties will help improve ESMs’ performance and give the priorities for model development. In this study, we investigated uncertainties in projections of vegetation carbon by twelve CMIP5 ESMs during the twenty-first century and explored the sources of uncertainties across the models. We found that the predicted changes of vegetation carbon by the end of this century varied quite much across the ESMs under the RCP8.5 scenario, from declining of 190 Pg C to increasing of 320 Pg C. These changes of vegetation carbon can be attributed mostly to the changes in carbon residence time, rather than net primary productivity. We further investigated model’s differences in their responses of vegetation carbon to temperature, precipitation and CO2 among the ESMs. Our results have the potential to help improve CMIP5 ESMs for more reliable predictions.