The expansion of the glacial ice shield on Iceland and its lateral expansion is a big unknown in paleoclimate and paleoceanography. Its expansion into the Denmark Strait region has major implication on the water mass exchange across the Strait, in particular for the outlfow of Denmark Strait Overflow Water. This modeling study is bringing exciting new insights and constrains on the behavior of the Iceland ice cap throughout the last glacial cycle.

This study provides valuable insight into the timing of meltwater events and associated response of AMOC during the last deglaciation. The strength of the work lies in its precisely dated chronology from a northwest Iberian stalagmite, which overcomes the chronological limitations of North Atlantic sediment records. As highlighted by Reviewer 2 “this represents a substantial advance given the impasse in what is possible based on the less precise dates of sediment cores in this interval.” The analysis of multiple proxies within the same stalagmite allows the authors to directly compare the timing of surface ocean freshening relative to regional temperature changes. Their findings reinforce the hypothesis that the AMOC response to freshwater forcing is nonlinear and may involve threshold-like transitions that are dependent on background climate states. This has broader relevance to the ongoing debate surrounding future AMOC stability.

The paper shows that historical records of wine yield and quality from Central Europe (1416–1988) can be combined into a Yield Quality Index (YQI). This index serves as a reliable indicator of climate conditions from May to July. Using long-term tax, tithe, and estate records from the Moselle region in Germany and the Swiss Plateau, the study shows that high YQI values correspond to warm summers, early harvests, and supportive tree-ring evidence. Conversely, low values often reflect cold summers or frost damage. These results confirm that wine production data can significantly improve climate reconstructions and help explain the social and economic impacts of past climate extremes.

This study uses historical weather observations rescued from across Europe, as well as machine learning techniques to improve our understanding of a series of heatwaves in 1806. The results indicate that while machine learning models can do a good job of reproducing historical weather observations, they can't capture the physics behind why a heatwave would occur.