EVENTS

The global mean surface temperature record combining sea surface and near-surface air data is central to understanding climate variability and change. Understanding the past record also helps constrain uncertainty in future climate projections. In my talk, I will present a recent study (Sippel et al., 2024, Nature, doi:10.1038/s41586-024-08230-1) that refines our view of the historical record and explore its implications for near-future climate risk.

Past temperature record: The early temperature record (before ~1950) remains uncertain due to evolving methods, limited documentation, and sparse coverage. Independent reconstructions show that historical ocean temperatures were likely measured too cold by about 0.26 °C compared to land estimates despite strong agreement in other periods. This cold bias cannot be explained by natural variability; multiple lines of evidence (climate attribution, timescale analysis, coastal data, palaeoclimate records) support a substantial cold bias in early ocean records. While overall warming since the mid-19th century is unchanged, correcting the bias reduces early-20th-century warming trends, lowers global decadal variability, and brings models and observations into closer alignment.

Constraining climate risk: I will close my talk by discussing how these findings sharpen near-future temperature projections and our understanding of climate risk; and furthermore how new AI methods may provide an even clearer picture of past climate and near-future climate risk.

Institutions

• AI for Good