Nonlinearity of Land Carbon Sensitivities in Climate Change Simulations

In the climate-carbon cycle system, the terrestrial ecosystem feedback is significant. In studies on feedback analysis, the ecosystem feedback is divided into the sensitivity of carbon storage to atmospheric CO2 concentration (bL), and temperature change (gL). Although ecosystems include many nonlinear processes, the scenarioand time-dependency of bL and gL have not been explicitly discussed. To check the validity of this simplification and its robustness, we carried out two, 1% per year (p.a.) increase and RCP4.5 scenario, experiments, using a processbased terrestrial ecosystem model forced by an existing GCM output, combined with an energy moisture balance model for the latter experiment, with 300 ensemble members perturbing twelve important and a priori unconstrained parameters. In the 1% p.a. experiment, bL peaked around 500 ppm and then gradually decreased with increasing CO2 level, while gL decreased with some inter-annual variability as temperature increases. The time-dependency of bL was small (at least for CO2 level > 550 ppm), but that of gL was significant, and the e¤ect of this was larger than that of the nonlinear term (i.e., combined e¤ect of CO2 and temperature change). The scenario-dependency is also significant, but the e¤ect in the estimated carbon uptake was smaller than that by the time-dependency. By investigating the background of this e¤ect, we found that in the 1% p.a. CO2 increase scenario, the maximum photosynthesis rate and specific leaf area (SLA, leaf area per unit dry mass) had the most significant contribution to both of bL and gL, and the contributions are dependent on the climate state (i.e., temperature and atmospheric CO2 level). For carbon uptake in both experiments, SLA and coe‰cient of plant respiration were most significant. We also attempted to constrain the ensemble members, and found that for net primary production, soil carbon and soil respiration, the default parameter set was already well-tuned, while observations of leaf area index (LAI) strongly constrains bL, gL, airborne fraction and ecosystem carbon balance as the default model overestimated the LAI.