Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores

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) datasets. We present...

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Published in:Climate of the Past
Main Authors: M. Döring, M. C. Leuenberger
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2018
Subjects:
geo
Online Access:https://doi.org/10.5194/cp-14-763-2018
https://www.clim-past.net/14/763/2018/cp-14-763-2018.pdf
https://doaj.org/article/3f8e6e4eaff84bb6948cf5318bd0a2a1
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record_format openpolar
spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:3f8e6e4eaff84bb6948cf5318bd0a2a1 2023-05-15T16:28:40+02:00 Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores M. Döring M. C. Leuenberger 2018-06-01 https://doi.org/10.5194/cp-14-763-2018 https://www.clim-past.net/14/763/2018/cp-14-763-2018.pdf https://doaj.org/article/3f8e6e4eaff84bb6948cf5318bd0a2a1 en eng Copernicus Publications doi:10.5194/cp-14-763-2018 1814-9324 1814-9332 https://www.clim-past.net/14/763/2018/cp-14-763-2018.pdf https://doaj.org/article/3f8e6e4eaff84bb6948cf5318bd0a2a1 undefined Climate of the Past, Vol 14, Pp 763-788 (2018) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2018 fttriple https://doi.org/10.5194/cp-14-763-2018 2023-01-22T18:52:17Z 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) datasets. 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 completely independent from ice-core stable-water isotopes, providing the opportunity to validate water-isotope-based reconstructions or reconstructions where water isotopes are used together with δ15N or δ40Ar. We solve the inverse problem T(δ15N, Acc) by using a combination of a Monte Carlo based iterative approach and the analysis of remaining mismatches between modelled and target data, based on cubic-spline filtering of random numbers and the laboratory-determined temperature sensitivity for nitrogen isotopes. Additionally, the presented reconstruction approach was tested by fitting measured δ40Ar and δ15Nexcess data, which led as well to a robust agreement between modelled and measured data. The obtained final mismatches follow a symmetric standard-distribution function. For the study on synthetic data, 95 % of the mismatches compared to the synthetic target data are in an envelope between 3.0 to 6.3 permeg for δ15N and 0.23 to 0.51 K for temperature (2σ, respectively). In addition to Holocene temperature ... Article in Journal/Newspaper Greenland Greenland ice cores ice core Unknown Greenland Climate of the Past 14 6 763 788
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic geo
envir
spellingShingle geo
envir
M. Döring
M. C. Leuenberger
Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores
topic_facet geo
envir
description 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) datasets. 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 completely independent from ice-core stable-water isotopes, providing the opportunity to validate water-isotope-based reconstructions or reconstructions where water isotopes are used together with δ15N or δ40Ar. We solve the inverse problem T(δ15N, Acc) by using a combination of a Monte Carlo based iterative approach and the analysis of remaining mismatches between modelled and target data, based on cubic-spline filtering of random numbers and the laboratory-determined temperature sensitivity for nitrogen isotopes. Additionally, the presented reconstruction approach was tested by fitting measured δ40Ar and δ15Nexcess data, which led as well to a robust agreement between modelled and measured data. The obtained final mismatches follow a symmetric standard-distribution function. For the study on synthetic data, 95 % of the mismatches compared to the synthetic target data are in an envelope between 3.0 to 6.3 permeg for δ15N and 0.23 to 0.51 K for temperature (2σ, respectively). In addition to Holocene temperature ...
format Article in Journal/Newspaper
author M. Döring
M. C. Leuenberger
author_facet M. Döring
M. C. Leuenberger
author_sort M. Döring
title Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores
title_short Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores
title_full Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores
title_fullStr Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores
title_full_unstemmed Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores
title_sort novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores
publisher Copernicus Publications
publishDate 2018
url https://doi.org/10.5194/cp-14-763-2018
https://www.clim-past.net/14/763/2018/cp-14-763-2018.pdf
https://doaj.org/article/3f8e6e4eaff84bb6948cf5318bd0a2a1
geographic Greenland
geographic_facet Greenland
genre Greenland
Greenland ice cores
ice core
genre_facet Greenland
Greenland ice cores
ice core
op_source Climate of the Past, Vol 14, Pp 763-788 (2018)
op_relation doi:10.5194/cp-14-763-2018
1814-9324
1814-9332
https://www.clim-past.net/14/763/2018/cp-14-763-2018.pdf
https://doaj.org/article/3f8e6e4eaff84bb6948cf5318bd0a2a1
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op_doi https://doi.org/10.5194/cp-14-763-2018
container_title Climate of the Past
container_volume 14
container_issue 6
container_start_page 763
op_container_end_page 788
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