Synthetic and fitted d15N and temperature data and GISP2 accumulation rates (13.5-52497.5 yr b2k) on GICC05 time scale ...
Greenland past temperature history can be reconstructed by forcing the output of a firn-densification and heat-diffusion model to fit multiple gas-isotope data (δ15N or δ40Ar or δ15Nexcess) extracted from ancient air in Greenland ice cores using published accumulation-rate (Acc) data-sets. We presen...
| Main Authors: | , |
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| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
PANGAEA
2018
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.1594/pangaea.888997 https://doi.pangaea.de/10.1594/PANGAEA.888997 |
| Summary: | Greenland past temperature history can be reconstructed by forcing the output of a firn-densification and heat-diffusion model to fit multiple gas-isotope data (δ15N or δ40Ar or δ15Nexcess) extracted from ancient air in Greenland ice cores using published accumulation-rate (Acc) data-sets. We present here a novel methodology to solve this inverse problem, by designing a fully-automated algorithm. To demonstrate the performance of this novel approach, we begin by intentionally constructing synthetic temperature-histories and associated δ15N datasets, mimicking real Holocene data that we use as “true values” (targets) to be compared to the output of the algorithm. This allows us to quantify uncertainties originating from the algorithm itself. The presented approach is completely automated and therefore minimizes the "subjective" impact of manual parameter-tuning, leading to reproducible temperature-estimates. In contrast to many other ice-core-based temperature-reconstruction methods, the presented approach is ... |
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