184.108.40.206 Coupled Climate-Carbon Cycle Projections
The TAR reported two initial climate projections using AOGCMs with interactive carbon cycles. Both indicated positive feedback due largely to the impacts of climate warming on land carbon storage (Cox et al., 2000; Friedlingstein et al., 2001), but the magnitude of the feedback varied markedly between the models (Friedlingstein et al., 2003). Since the TAR a number of other climate modelling groups have completed climate-carbon cycle projections (Brovkin et al., 2004; Thompson et al., 2004; N. Zeng et al., 2004, Fung et al., 2005; Kawamiya et al., 2005; Matthews et al., 2005; Sitch et al., 2005) as part of C4MIP. The 11 models involved in C4MIP differ in the complexity of their components (Friedlingstein et al., 2006), including both Earth System Models of Intermediate Complexity and AOGCMs.
The models were forced by historical and Special Report on Emission Scenarios (SRES; IPCC, 2000) A2 anthropogenic CO2 emissions for the 1850 to 2100 time period. Each modelling group carried out at least two simulations: one ‘coupled’ in which climate change affects the carbon cycle, and one ‘uncoupled’ in which atmospheric CO2 increases do not influence climate (so that the carbon cycle experiences no CO2-induced climate change). A comparison of the runs defines the climate-carbon cycle feedback, quantified by the feedback factor: F = ∆CAc / ∆CAu ,where ∆CAc is the change in CO2 in the coupled run, and ∆CAu is the change in CO2 in the uncoupled run. All of the eleven C4MIP models produce a positive climate-carbon cycle feedback, but with feedback factors varying from 1.04 (Model E) to 1.44 (Model A). This translates into an additional CO2 concentration of between 20 and 224 ppm by 2100, with a mean of 87 ppm (Table 7.4).
Table 7.4. Impact of carbon cycle feedbacks in the C4MIP models. Column 2 shows the impact of climate change on the CO2 concentration by 2100, and column 3 shows the related amplification of the atmospheric CO2 increase (i.e., the climate-carbon cycle feedback factor). Columns 4 to 8 list effective sensitivity parameters of the models: transient sensitivity of mean global temperature to CO2, and the sensitivities of land and ocean carbon storage to CO2 and climate (Friedlingstein et al., 2006). These parameters were calculated by comparison of the coupled and uncoupled runs over the entire period of the simulations (typically 1860 to 2100). Model details are given in Friedlingstein et al. (2006).
|Modela ||Impact of Climate Change on the CO2 Concentration by 2100 (ppm) ||Climate-Carbon Feedback Factor ||Transient Climate Sensitivity to Doubling CO2 (°C) ||Land Carbon Storage Sensitivity to CO2 (GtC ppm–1) ||Ocean Carbon Storage Sensitivity to CO2 (GtC ppm–1) ||Land Carbon Storage Sensitivity to Climate (GtC °C–1) ||Ocean Carbon Storage Sensitivity to Climate (GtC °C–1) |
|A. HadCM3LC ||224 ||1.44 ||2.3 ||1.3 ||0.9 ||–175 ||–24 |
|B. IPSL-CM2C ||74 ||1.18 ||2.3 ||1.6 ||1.6 ||–97 ||–30 |
|C. MPI-M ||83 ||1.18 ||2.6 ||1.4 ||1.1 ||–64 ||–22 |
|D. LLNL ||51 ||1.13 ||2.5 ||2.5 ||0.9 ||–81 ||–14 |
|E. NCAR CSM-1 ||20 ||1.04 ||1.2 ||1.1 ||0.9 ||–24 ||–17 |
|F. FRCGC ||128 ||1.26 ||2.3 ||1.4 ||1.2 ||–111 ||–47 |
|G. Uvic-2.7 ||129 ||1.25 ||2.3 ||1.2 ||1.1 ||–97 ||–43 |
|H. UMD ||98 ||1.17 ||2.0 ||0.2 ||1.5 ||–36 ||–60 |
|I. BERN-CC ||65 ||1.15 ||1.5 ||1.6 ||1.3 ||–104 ||–38 |
|J. CLIMBER2-LPJ ||59 ||1.11 ||1.9 ||1.2 ||0.9 ||–64 ||–22 |
|K. IPSL-CM4-LOOP ||32 ||1.07 ||2.7 ||1.2 ||1.1 ||–19 ||–17 |
|Mean ||87 ||1.18 ||2.1 ||1.4 ||1.1 ||–79 ||–30 |
|Standard Deviation ||±57 ||±0.11 ||±0.4 ||±0.5 ||±0.3 ||±45 ||±15 |
All C4MIP models predict that an increasing fraction of total anthropogenic CO2 emissions will remain airborne through the 21st century. Figure 7.13 shows the simulated partitioning of anthropogenic CO2 for the entire simulation period to 2100 from each of the coupled models, and compares this with the partitioning simulated by the same models over the historical period to 1999. The dashed box shows observational constraints on the historical CO2 partitioning, based on estimates of changes in ocean carbon storage (Sabine et al., 2004a) and total anthropogenic CO2 emissions. The area of this box is largely due to uncertainties in the net land use emissions. The majority of the models sit within or very close to the historical constraints, but they differ in the magnitude of the changes projected for the 21st century. However, all models produce an increase in the fraction of total emissions that remain in the atmosphere, and most also indicate a decline in the fraction of emissions absorbed by the ocean (9 out of 11 models) and the land (10 out of 11 models). In the case of the oceanic uptake, this is largely a consequence of the reduced buffering capacity as CO2 increases, and therefore also occurs in the uncoupled C4MIP models.
Figure 7.13. Predicted increase in the fraction of total emissions that add to atmospheric CO2. Changes in the mean partitioning of emissions as simulated by the C4MIP models up to 2000 (black symbols) and for the entire simulation period to 2100 (red symbols). The letters represent the models as given in Table 7.4. The box shown by the dotted line is a constraint on the historical carbon balance based on records of atmospheric CO2 increase, and estimates of total emissions (fossil fuel plus land use emissions) and the oceanic uptake of anthropogenic CO2 (Sabine et al., 2004a). The black and red diamonds show the model-mean carbon partitioning for the historical period and the entire simulation period, respectively. The red line shows the mean tendency towards an increasing airborne fraction through the 21st century, which is common to all models.