Frontiers in Earth Science (Sep 2022)

How the climate shapes stalagmites—A comparative study of model and speleothem at the Sofular Cave, Northern Turkey

  • Niklas Merz,
  • Alexander Hubig,
  • Thomas Kleinen,
  • Steffen Therre,
  • Georg Kaufmann,
  • Norbert Frank

DOI
https://doi.org/10.3389/feart.2022.969211
Journal volume & issue
Vol. 10

Abstract

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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.

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