Terrestrial Carbon Cycle Dynamics under Recent and Future Climate Change

2005 ◽  
Vol 18 (10) ◽  
pp. 1609-1628 ◽  
Author(s):  
H. Damon Matthews ◽  
Andrew J. Weaver ◽  
Katrin J. Meissner

Abstract The behavior of the terrestrial carbon cycle under historical and future climate change is examined using the University of Victoria Earth System Climate Model, now coupled to a dynamic terrestrial vegetation and global carbon cycle model. When forced by historical emissions of CO2 from fossil fuels and land-use change, the coupled climate–carbon cycle model accurately reproduces historical atmospheric CO2 trends, as well as terrestrial and oceanic uptake for the past two decades. Under six twenty-first-century CO2 emissions scenarios, both terrestrial and oceanic carbon sinks continue to increase, though terrestrial uptake slows in the latter half of the century. Climate–carbon cycle feedbacks are isolated by comparing a coupled model run with a run where climate and the carbon cycle are uncoupled. The modeled positive feedback between the carbon cycle and climate is found to be relatively small, resulting in an increase in simulated CO2 of 60 ppmv at the year 2100. Including non-CO2 greenhouse gas forcing and increasing the model’s climate sensitivity increase the effect of this feedback to 140 ppmv. The UVic model does not, however, simulate a switch from a terrestrial carbon sink to a source during the twenty-first century, as earlier studies have suggested. This can be explained by a lack of substantial reductions in simulated vegetation productivity due to climate changes.

2008 ◽  
Vol 5 (6) ◽  
pp. 4847-4866 ◽  
Author(s):  
P. Friedlingstein ◽  
P. Cadule ◽  
S. L. Piao ◽  
P. Ciais ◽  
S. Sitch

Abstract. Future climate change will have impact on global and regional terrestrial carbon balances. The fate of African tropical forests over the 21st century has been investigated through global coupled climate carbon cycle model simulations. Under the SRES-A2 socio-economic CO2 emission scenario of the IPCC, and using the Institut Pierre Simon Laplace coupled ocean-terrestrial carbon cycle and climate model, IPSL-CM4-LOOP, we found that the warming over African ecosystems induces a reduction of net ecosystem productivity, making a 20% contribution to the global climate-carbon cycle positive feedback. However, the African rainforest ecosystem alone makes only a negligible contribution to the overall feedback, much smaller than the one arising from the Amazon forest. This is first because of the two times smaller area of forest in Africa, but also because of the relatively lower local land carbon cycle sensitivity to climate change. This beneficial role of African forests in mitigating future climate change should be taken into account when designing forest conservation policy.


2017 ◽  
Vol 30 (17) ◽  
pp. 6701-6722 ◽  
Author(s):  
Daniel Bannister ◽  
Michael Herzog ◽  
Hans-F. Graf ◽  
J. Scott Hosking ◽  
C. Alan Short

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.


2014 ◽  
Vol 112 (2) ◽  
pp. 436-441 ◽  
Author(s):  
David Schimel ◽  
Britton B. Stephens ◽  
Joshua B. Fisher

Feedbacks from the terrestrial carbon cycle significantly affect future climate change. The CO2 concentration dependence of global terrestrial carbon storage is one of the largest and most uncertain feedbacks. Theory predicts the CO2 effect should have a tropical maximum, but a large terrestrial sink has been contradicted by analyses of atmospheric CO2 that do not show large tropical uptake. Our results, however, show significant tropical uptake and, combining tropical and extratropical fluxes, suggest that up to 60% of the present-day terrestrial sink is caused by increasing atmospheric CO2. This conclusion is consistent with a validated subset of atmospheric analyses, but uncertainty remains. Improved model diagnostics and new space-based observations can reduce the uncertainty of tropical and temperate zone carbon flux estimates. This analysis supports a significant feedback to future atmospheric CO2 concentrations from carbon uptake in terrestrial ecosystems caused by rising atmospheric CO2 concentrations. This feedback will have substantial tropical contributions, but the magnitude of future carbon uptake by tropical forests also depends on how they respond to climate change and requires their protection from deforestation.


Author(s):  
Kevin Schaefer ◽  
G. James Collatz ◽  
Pieter Tans ◽  
A. Scott Denning ◽  
Ian Baker ◽  
...  

Author(s):  
Xin Li ◽  
Hanqing Ma ◽  
Youhua Ran ◽  
Xufeng Wang ◽  
Gaofeng Zhu ◽  
...  

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