EGU21-4361
https://doi.org/10.5194/egusphere-egu21-4361
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Evaluating a method for reconstruction of global, zonal and regional mean temperatures from sparse proxy data

Maximilian May1, Nils Weitzel2, Lukas Jonkers3, and Kira Rehfeld4
Maximilian May et al.
  • 1Institute of Environmental Physics, Heidelberg University, Heidelberg, Germany (mmay@iup.uni-heidelberg.de)
  • 2Institute of Environmental Physics, Heidelberg University, Heidelberg, Germany (nweitzel@iup.uni-heidelberg.de)
  • 3MARUM, University of Bremen, Bremen, Germany (ljonkers@marum.de)
  • 4Institute of Environmental Physics, Heidelberg University, Heidelberg, Germany (krehfeld@iup.uni-heidelberg.de)

Global mean surface temperature is a fundamental measure for climate evolution in both past and present and a key quantity to evaluate climate simulations. However, for paleoclimate periods, its calculation hinges on proxy data distributed sparsely and inhomogeneously in both space and time. Thus, large sets of different proxy records need to be combined in order to obtain global mean temperature reconstructions, but there is no widely accepted method to perform this task. Building on the work of [1], we suggest and evaluate an algorithm to reconstruct spatially averaged surface temperatures on centennial to orbital timescales. As the most abundant archive for continuous temperature reconstructions, we focus on marine sediment records as input data. Our implementation is applicable to any compilation of sea-surface temperature reconstructions and capable of calculating global, hemispherical and regional temperature. Major steps of the reconstruction algorithm are interpolation to a common timescale, zonal normalization and calculation of spatially weighted sums, including uncertainty propagation via Monte Carlo methods. We assess the applicability of the algorithm by employing it to the PalMod130k marine palaeoclimate data synthesis [2] and to pseudo-proxy data generated from transient simulations of the last glacial cycle. Our results suggest that the algorithm is capable of calculating average temperatures mostly consistent with expectations, however capturing centennial-scale variability is limited due to the low spatio-temporal distribution of the input data. This underlines the importance of both increasing the amount, resolution and age control of proxy data as well as extending the algorithm such that it also incorporates other types of paleoclimate archives.

 

References:

[1]  C. W. Snyder, “Evolution of global temperature over the past two million years,” Nature, vol. 538, no. 7624, pp. 226–228, 2016

[2]  L. Jonkers, O. Cartapanis, M. Langner, N. McKay, S. Mulitza, A. Strack, and M. Kucera, “Integrating palaeoclimate time series with rich metadata for uncertainty modelling:  Strategy and documentation of the PALMOD 130k marine palaeoclimate data synthesis,” Earth System Science Data, vol. 12, no. 2, pp. 1053–1081, 2020

How to cite: May, M., Weitzel, N., Jonkers, L., and Rehfeld, K.: Evaluating a method for reconstruction of global, zonal and regional mean temperatures from sparse proxy data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4361, https://doi.org/10.5194/egusphere-egu21-4361, 2021.

Displays

Display file