Greenland Ice Sheet influence on Last Interglacial climate: global sensitivity studies performed with an atmosphere–ocean general circulation model

• Published in: Climate of the Past
• Main Authors: Pfeiffer, Madlene, Lohmann, Gerrit
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: COPERNICUS GESELLSCHAFT MBH 2016
• Subjects: Greenland; Ice Sheet
• Online Access: https://epic.awi.de/id/eprint/41111/; https://epic.awi.de/id/eprint/41111/1/cp-12-1313-2016.pdf; https://hdl.handle.net/10013/epic.48069; https://hdl.handle.net/10013/epic.48069.d001

During the Last Interglacial (LIG, ~130–115 kiloyears (kyr) before present (BP)), the northern high latitudes were characterized by higher temperatures than those of the late Holocene and a lower Greenland Ice Sheet (GIS). However, the impact of a reduced GIS on the global climate has not yet been well constrained. In this study, we quantify the contribution of the GIS to LIG warmth by performing various sensitivity studies based on equilibrium simulations, employing the Community Earth System Models (COSMOS), with a focus on height and extent of the GIS. We present the first study on the effects of a reduction in the GIS on the surface temperature (TS) on a global scale and separate the contribution of astronomical forcing and changes in GIS to LIG warmth. The strong Northern Hemisphere summer warming of approximately 2°C (with respect to preindustrial) is mainly caused by increased summer insolation. Reducing the height by ~1300m and the extent of the GIS does not have a strong influence during summer, leading to an additional global warming of only +0.24°C compared to the purely insolation-driven LIG. The effect of a reduction in the GIS is, however, strongest during local winter, with up to +5°C regional warming and with an increase in global average temperature of +0.48°C. In order to evaluate the performance of our LIG simulations, we additionally compare the simulated TS anomalies with marine and terrestrial proxy-based LIG temperature anomalies derived from three different proxy data compilations. Our model results are in good agreement with proxy records with respect to the warming pattern but underestimate the magnitude of temperature change when compared to reconstructions, suggesting a potential misinterpretation of the proxy records or deficits in our model. However, we are able to partly reduce the mismatch between model and data by additionally taking into account the potential seasonal bias of the proxy record and/or the uncertainties in the dating of the proxy records for the LIG thermal ...