Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data
The research area of climate field reconstructions has developed strongly during the past 20 years, motivated by the need to understand the complex dynamics of the earth system in a changing climate. Climate field reconstructions aim to build a consistent gridded climate reconstruction of different...
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fttriple:oai:gotriple.eu:1qX-6iBG9_E4864AiGXKe 2023-05-15T16:29:00+02:00 Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data Sjolte, Jesper Adolphi, Florian Vinther, Bo M. Muscheler, Raimund Sturm, Christophe Werner, Martin Lohmann, Gerrit 2020-09-11 https://doi.org/10.5194/cp-16-1737-2020 https://cp.copernicus.org/articles/16/1737/2020/ en eng Copernicus Publications doi:10.5194/cp-16-1737-2020 10670/1.lhrk6e 1814-9324 1814-9332 https://cp.copernicus.org/articles/16/1737/2020/ undefined Geographica Helvetica - geography eISSN: 1814-9332 geo anthro-bio Text https://vocabularies.coar-repositories.org/resource_types/c_18cf/ Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2020 fttriple https://doi.org/10.5194/cp-16-1737-2020 2023-01-22T17:39:16Z The research area of climate field reconstructions has developed strongly during the past 20 years, motivated by the need to understand the complex dynamics of the earth system in a changing climate. Climate field reconstructions aim to build a consistent gridded climate reconstruction of different variables, often from a range of climate proxies, using either statistical tools or a climate model to fill the gaps between the locations of the proxy data. Commonly, large-scale climate field reconstructions covering more than 500 years are of annual resolution. In this method study, we investigate the potential of seasonally resolved climate field reconstructions based on oxygen isotope records from Greenland ice cores and an isotope-enabled climate model. Our analogue-type method matches modeled isotope patterns in Greenland precipitation to the patterns of ice core data from up to 14 ice core sites. In a second step, the climate variables of the best-matching model years are extracted, with the mean of the best-matching years comprising the reconstruction. We test a range of climate reconstructions, varying the definition of the seasons and the number of ice cores used. Our findings show that the optimal definition of the seasons depends on the variability in the target season. For winter, the vigorous variability is best captured when defining the season as December–February due to the dominance of large-scale patterns. For summer, which has weaker variability, albeit more persistent in time, the variability is better captured using a longer season of May–October. Motivated by the scarcity of seasonal data, we also test the use of annual data where the year is divided during summer, that is, not following the calendar year. This means that the winter variability is not split and that the annual data then can be used to reconstruct the winter variability. In particularly when reconstructing the sea level pressure and the corresponding main modes of variability, it is important to take seasonality into account, ... Article in Journal/Newspaper Greenland Greenland ice cores ice core Unknown Greenland Climate of the Past 16 5 1737 1758 |
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geo anthro-bio Sjolte, Jesper Adolphi, Florian Vinther, Bo M. Muscheler, Raimund Sturm, Christophe Werner, Martin Lohmann, Gerrit Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data |
topic_facet |
geo anthro-bio |
description |
The research area of climate field reconstructions has developed strongly during the past 20 years, motivated by the need to understand the complex dynamics of the earth system in a changing climate. Climate field reconstructions aim to build a consistent gridded climate reconstruction of different variables, often from a range of climate proxies, using either statistical tools or a climate model to fill the gaps between the locations of the proxy data. Commonly, large-scale climate field reconstructions covering more than 500 years are of annual resolution. In this method study, we investigate the potential of seasonally resolved climate field reconstructions based on oxygen isotope records from Greenland ice cores and an isotope-enabled climate model. Our analogue-type method matches modeled isotope patterns in Greenland precipitation to the patterns of ice core data from up to 14 ice core sites. In a second step, the climate variables of the best-matching model years are extracted, with the mean of the best-matching years comprising the reconstruction. We test a range of climate reconstructions, varying the definition of the seasons and the number of ice cores used. Our findings show that the optimal definition of the seasons depends on the variability in the target season. For winter, the vigorous variability is best captured when defining the season as December–February due to the dominance of large-scale patterns. For summer, which has weaker variability, albeit more persistent in time, the variability is better captured using a longer season of May–October. Motivated by the scarcity of seasonal data, we also test the use of annual data where the year is divided during summer, that is, not following the calendar year. This means that the winter variability is not split and that the annual data then can be used to reconstruct the winter variability. In particularly when reconstructing the sea level pressure and the corresponding main modes of variability, it is important to take seasonality into account, ... |
format |
Article in Journal/Newspaper |
author |
Sjolte, Jesper Adolphi, Florian Vinther, Bo M. Muscheler, Raimund Sturm, Christophe Werner, Martin Lohmann, Gerrit |
author_facet |
Sjolte, Jesper Adolphi, Florian Vinther, Bo M. Muscheler, Raimund Sturm, Christophe Werner, Martin Lohmann, Gerrit |
author_sort |
Sjolte, Jesper |
title |
Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data |
title_short |
Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data |
title_full |
Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data |
title_fullStr |
Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data |
title_full_unstemmed |
Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data |
title_sort |
seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://doi.org/10.5194/cp-16-1737-2020 https://cp.copernicus.org/articles/16/1737/2020/ |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Greenland ice cores ice core |
genre_facet |
Greenland Greenland ice cores ice core |
op_source |
Geographica Helvetica - geography eISSN: 1814-9332 |
op_relation |
doi:10.5194/cp-16-1737-2020 10670/1.lhrk6e 1814-9324 1814-9332 https://cp.copernicus.org/articles/16/1737/2020/ |
op_rights |
undefined |
op_doi |
https://doi.org/10.5194/cp-16-1737-2020 |
container_title |
Climate of the Past |
container_volume |
16 |
container_issue |
5 |
container_start_page |
1737 |
op_container_end_page |
1758 |
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1766018683437580288 |