EGU23-2359
https://doi.org/10.5194/egusphere-egu23-2359
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Uncertainties in critical slowing down indicators of observation-based fingerprints of the AMOC

Maya Ben Yami1,2, Niklas Boers1,2, Vanessa Skiba2, and Sebastian Bathiany1
Maya Ben Yami et al.
  • 1Technical University of Munich, TUM School of Engineering and Design, Professorship of Earth System Modelling
  • 2Potsdam Institute of Climate Impact Research

In recent years, sea-surface temperature (SST) and salinity-based indices have been used to detect critical slowing down (CSD) indicators for a possible collapse of the Atlantic Meridional Overturning Circulation (AMOC). However, these observational SST and salinity datasets have inherent uncertainties and biases which could influence the CSD analysis. Here we present an in-depth uncertainty analysis of AMOC CSD indicators. We first use uncertainties provided with the HadSST4 and HadCRUT5 datasets to generate uncertainty ensembles and estimate the uncertainty of SST-based AMOC fingerprints, and we then calculate stringent significance measures on the CSD indicators in the EN4.2.2, HadISST1 and HadCRUT5 datasets.

How to cite: Ben Yami, M., Boers, N., Skiba, V., and Bathiany, S.: Uncertainties in critical slowing down indicators of observation-based fingerprints of the AMOC, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2359, https://doi.org/10.5194/egusphere-egu23-2359, 2023.

Supplementary materials

Supplementary material file