Abstract
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.
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