Contribution of natural variability to future terrestrial ecosystem carbon balance uncertainties
Abstract
A considerable part of the uncertainty surrounding the magnitude of a future climate change is the response of the terrestrial carbon cycle. One of the largest sources of this uncertainty is the heterogeneity of the predictions of future climate made by different climate models (general circulation models, GCMs). Not only do GCMs differ in their climate sensitivities and in regional distributions of changes in temperature, precipitation and radiation, they also differ markedly in simulated natural variability. To investigate the role of natural variability in the uncertainties induced by differences between climate models we forced the detailed individual based ecosystem model LPJ-GUESS with outputs from four CMIP3 climate models under three SRES CO2 concentration ([CO2]) pathways. Based on results from the ecosystem model, we parameterized a simple global carbon cycle model including only global temperature and [CO2] as the independent variables, scaled by parameters representing natural variability and regionality (α) and the land-to-global warming ratio (γ). Using singular value decomposition of simulated sea surface temperatures, a main driver of inter-annual variability in the climate system, we investigated the dominant patterns of variability and the resulting spatial carbon cycle patterns resulting from applying the four GCMs. We find that the uptake of carbon differs more between climate models than between different [CO2] pathways. Sampling the parameters of the simple carbon cycle model we create 60 "artificial" climate models. Applying the simplified model with these 60 parameterizations plus the original four GCMs under three [CO2] pathways (based on A2, A1B and B1 emission scenarios) resulted in a total of 192 simulations. We applied ANOVA to estimate how much of the variability in the simulated total carbon pool at year 2099 that can be explained by each factor, emission scenario, α and γ. The discrepancies in climate model natural variability, dominated by differences in El Niño-Southern Oscillation (ENSO) strength (α), explain 83% of the carbon balance uncertainties in our results (Figure 1). Recent studies applying remote sensing and modeling to estimate past decades' NPP variability suggest that large-scale droughts are likely to have had an important and possibly dominant causal role in the NPP variations. Similarly, our results suggest that improved simulation of ENSO and low latitude precipitation patterns are important targets for narrowing the uncertainties in future climate change projections using ESMs or GCM-driven ecosystem impact models. Figure 1. Results of the simplified carbon cycle model. The spread under the 3 scenarios is illustrated on the left hand side. Middle show the distribution, and to the right the degree of explanation.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2012
- Bibcode:
- 2012AGUFM.B13B0505A
- Keywords:
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- 0416 BIOGEOSCIENCES / Biogeophysics;
- 0428 BIOGEOSCIENCES / Carbon cycling;
- 1615 GLOBAL CHANGE / Biogeochemical cycles;
- processes;
- and modeling;
- 1626 GLOBAL CHANGE / Global climate models