Project Details
Projekt
ICEBAY - Temperature reconstruction combining boreholes thermometry and ice-cores with Bayesian hierarchical modeling; Global warming vs. natural variability in Dronning Maud Land, Antarctica
Subject Area
Atmospheric Science
Term
since 2025
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 562109601
The Antarctic Ice Sheet represents the greatest potential source of global sea-level rise, and its response to climate change is a key source of uncertainty for future projections. Understanding the causes of recent climatic trends in East Antarctica is hampered by a short instrumental record. Paleoclimatic information from ice cores could in principle provide this information. But despite dozens of ice-cores drilled in Antarctica, the climate evolution of the last centuries, especially on the East Antarctic Plateau, is still largely unknown. This is due to noise terms distorting the climate records of ice cores, uncertainties in the transfer function between climate and ice-core records and a lack of methodologies for optimal integration of diverse datasets and physical constraints into climate reconstructions. Borehole thermometry can reconstruct past surface temperature (ST) history but only very few borehole temperature profiles exist on the East Antarctic Plateau and current field reconstruction methodologies cannot integrate time-integrated bore-hole data with time-instantaneous isotopic or instrumental data. In this project, we combine the expertise from a detailed signal understanding of ice-cores and ice-core based climate reconstructions with the expertise of Bayesian inference and uncertainty modeling and machine learning to develop a systematic approach to the Antarctic climate reconstruction problem. New borehole temperature and isotope datasets generated in this project, will allow us to apply our methodology to the Dronning Maud Land (DML) Sector of the East Antarctic Plateau. The novel Bayesian hierarchical reconstruction approach combines borehole thermometry with isotope, instrumental and reanalysis data, leading to a temperature field reconstruction of the last two centuries, being an important contribution to the SPP sub-foci ‘Climate History and What to Learn for Predictions of Future Developments’ and ‘Antarctic Climate Change in the Global Context’. Within the priority program, we offer to share our expertise in the quantitative interpretation of ice-core records as well as in uncertainty modeling and Bayesian inference, including efficient machine learning solutions of inference problems. We not only deliver a robust temperature reconstruction and thus quantify DML's response to global change, but also to provide a methodological framework that holds promise for resolving the broader Antarctic temperature reconstruction challenge.
DFG Programme
Infrastructure Priority Programmes
