Earth system model simulations show different feedback strengths of the terrestrial carbon cycle under glacial and interglacial conditions

Abstract

Abstract. In simulations with the MPI Earth System Model, we study the feedback between the terrestrial carbon cycle and atmospheric CO 2 concentrations under ice age and interglacial conditions. We find different sensitivities of terrestrial carbon storage to rising CO 2 concentrations in the two settings. This result is obtained by comparing the transient response of the terrestrial carbon cycle to a fast and strong atmospheric CO 2 concentration increase (roughly 900 ppm) in Coupled Climate Carbon Cycle Model Intercomparison Project (C 4 MIP)-type simulations starting from climates representing the Last Glacial Maximum (LGM) and pre-industrial times (PI). In this set-up we disentangle terrestrial contributions to the feedback from the carbon-concentration effect, acting biogeochemically via enhanced photosynthetic productivity when CO 2 concentrations increase, and the carbonclimate effect, which affects the carbon cycle via greenhouse warming. We find that the carbon-concentration effect is larger under LGM than PI conditions because photosynthetic productivity is more sensitive when starting from the lower, glacial CO 2 concentration and CO 2 fertilization saturates later. This leads to a larger productivity increase in the LGM experiment. Concerning the carbon-climate effect, it is the PI experiment in which land carbon responds more sensitively to the warming under rising CO 2 because at the already initially higher temperatures, tropical plant productivity deteriorates more strongly and extratropical carbon is respired more effectively. Consequently, land carbon losses increase faster in the PI than in the LGM case. Separating the carbon-climate and carbon-concentration effects, we find that they are almost additive for our model set-up; i.e. their synergy is small in the global sum of carbon changes. Together, the two effects result in an overall strength of the terrestrial carbon cycle feedback that is almost twice as large in the LGM experiment as in the PI experiment. For PI, ocean and land contributions to the total feedback are of similar size, while in the LGM case the terrestrial feedback is dominant.

The PMIP4-CMIP6 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3-CMIP5 simulations

“…LGM simulations are currently available, and there were a comparable number of models that ran LGM simulations in PMIP3-CMIP5 (Table 1). The PMIP3-CMIP5 ensemble includes one model that ran an additional sensitivity test to ice-sheet height (GISS-E2R: Ullman et al, 2014) and one model that ran simulations with and without dynamic vegetation (MPI-ESM-P: Adloff et al, 2018). The PMIP4-CMIP6 ensemble includes two simulations made with updated versions of the models that contributed to PMIP3-CMIP5, specifically MIROC and MPI-ESM (Table 1).…”

Vegetation Pattern and Terrestrial Carbon Variation in Past Warm and Cold Climates

“…Lu, Z., Miller, P. A., Zhang, Q., Wårlind, D., Nieradzik, L., Sjolte, J., et al (2019). (Wang et al, 2013;Wang et al, 2014), moisture (Humphrey et al, 2018;Jung et al, 2017), and atmospheric CO 2 concentration (pCO 2 ; Adloff et al, 2018;Claussen et al, 2013;Kaplan et al, 2002) change in driving ecosystem structural and functional shifts.…”

“…While past cold episodes have received some attention in the literature, warm periods that can be seen as analogues of the future climate, such as the Pliocene (3.2 Ma;Haywood et al, 2016), have not often been considered. An evaluation based on a past warm period would be particularly relevant, however, as an analogue for future climate change, specifically to understand the roles of temperature (Wang et al, 2013;Wang et al, 2014), moisture (Humphrey et al, 2018;Jung et al, 2017), and atmospheric CO 2 concentration (pCO 2 ; Adloff et al, 2018;Claussen et al, 2013;Kaplan et al, 2002) change in driving ecosystem structural and functional shifts.…”

What can Palaeoclimate Modelling do for you?

“…The integration of biogeochemical processes into palaeoclimate models also allows us to reconstruct the influence of changing climate and biogeochemistry on shorter timescales and gain a greater understanding of thresholds, sensitivity and tipping points. More temporally constrained work allows us to investigate the impact of glacial-interglacial climates on ocean chemistry and carbon cycling on timescales relevant to humans (Buchanan et al 2016;Adloff et al 2018).…”