Dampened predictable decadal North Atlantic climate fluctuations due to ice melting

The melting of the northern hemisphere ice sheet after the last glacial period disrupted decadal climate variability in the North Atlantic and European sector, and may do so in the near future if ice melting on Greenland persists. The findings are published in the journal of Nature Geoscience and are based on the study of past climate variability recorded in annually-laminated lake sediments and climate model simulations.

The authors used climate information recorded in the annual deposits of sediments accumulated at the bottom of Diss Mere, a lake in Norfolk, and compared their observations with climate model simulations during the last ten millennia. Laura Boyall, a co-author said: “our findings show that the recurrence of decadal oscillatory signals was dampened when a great amount of fresh water was released into the North Atlantic Ocean from direct continental ice melting, happening around eight thousand years ago. When the melting ceased a millennium later, the decadal signals appeared again suggesting that the climate system started behaving in a more predictable way and highlighting the links between continental ice sheet and decadal climate variability.”

The impact of sea ice on muted decadal climate variability has been studied in past climate periods and is well represented in the decadal prediction models, however, the potential role of continental ice may be underestimated. This is likely due to the complexity of the Greenland ice melting processes, the lack of adequate long-term observations, and the technical difficulties in simulating their effect. As a result of the findings from this new paper, the authors suggest that, although challenging, some effort should be put into a better consideration of the changing Greenland ice sheet for coming climate predictions.

Martin-Puertas, C., Hernandez, A., Pardo-Igúzquiza, E. et al. Dampened predictable decadal North Atlantic climate fluctuations due to ice melting. Nat. Geosci. 16, 357–362 (2023). https://doi.org/10.1038/s41561-023-01145-y