ALBERT

Description: The present study investigates the response of the high-latitude carbon cycle to changes in atmospheric greenhouse gas (GHG) concentrations in idealized climate change scenarios. To this end we use an adapted version of JSBACH – the land surface component of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) – that accounts for the organic matter stored in the permafrost-affected soils of the high northern latitudes. The model is run under different climate scenarios that assume an increase in GHG concentrations, based on the Shared Socioeconomic Pathway 5 and the Representative Concentration Pathway 8.5, which peaks in the years 2025, 2050, 2075 or 2100, respectively. The peaks are followed by a decrease in atmospheric GHGs that returns the concentrations to the levels at the beginning of the 21st century, reversing the imposed climate change. We show that the soil CO2 emissions exhibit an almost linear dependence on the global mean surface temperatures that are simulated for the different climate scenarios. Here, each degree of warming increases the fluxes by, very roughly, 50 % of their initial value, while each degree of cooling decreases them correspondingly. However, the linear dependence does not mean that the processes governing the soil CO2 emissions are fully reversible on short timescales but rather that two strongly hysteretic factors offset each other – namely the net primary productivity and the availability of formerly frozen soil organic matter. In contrast, the soil methane emissions show a less pronounced increase with rising temperatures, and they are consistently lower after the peak in the GHG concentrations than prior to it. Here, the net fluxes could even become negative, and we find that methane emissions will play only a minor role in the northern high-latitude contribution to global warming, even when considering the high global warming potential of the gas. Finally, we find that at a global mean temperature of roughly 1.75 K (±0.5 K) above pre-industrial levels the high-latitude ecosystem turns from a CO2 sink into a source of atmospheric carbon, with the net fluxes into the atmosphere increasing substantially with rising atmospheric GHG concentrations. This is very different from scenario simulations with the standard version of the MPI-ESM, in which the region continues to take up atmospheric CO2 throughout the entire 21st century, confirming that the omission of permafrost-related processes and the organic matter stored in the frozen soils leads to a fundamental misrepresentation of the carbon dynamics in the Arctic.

Description: Understanding how stalagmites grow under changing climate conditions is of great significance for their application as a paleoclimate archive. In this study, we present a shape modeling approach to stalagmite growth by combining three existing models accounting for climate variables, karst water chemistry, and speleothem deposition. The combined model requires only four input parameters: calcium concentration of the water drop, drip interval, cave temperature, and cave carbon dioxide (CO2) concentration. Using the output of the coupled atmosphere–ocean–land surface model MPI-ESM1.2 and the CaveCalc model for speleothem chemistry, we simulated stalagmite growth at Sofular Cave, Northern Turkey, (in the last 25 kyr) and compared the results to those of the existing So-1 stalagmite from the same cave. This approach allows simulating, completely independent of measured boundary conditions, a stalagmite geometry that follows the trend of the experimental data for the growth rate, with input parameters within the respective error ranges. When testing the sensitivity of the individual model parameters, the model suggests that the stalagmite radius mainly depends on the drip interval, whereas the growth rate is driven by the calcium concentration of the water drop. The model is also capable of showing some basic phenomena, like a decrease in growth rate (as observed in the real stalagmite), as CO2 concentration in the cave increases. The coupling of input parameters for the model to climate models represents the first attempt to understand an important climate archive in its shape and isotope content and opens the possibility for a new inverse approach to paleoclimate variables and model constraints.