| 1. |
- Faber, Anne Katrine, et al.
(författare)
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How does sea ice influence δ18O of Arctic precipitation?
- 2017
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Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 17:9, s. 5865-5876
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Tidskriftsartikel (refereegranskat)abstract
- This study investigates how variations in Arctic sea ice and sea surface conditions influence δ18O of present-day Arctic precipitation. This is done using the model isoCAM3, an isotope-equipped version of the National Center for Atmospheric Research Community Atmosphere Model version 3. Four sensitivity experiments and one control simulation are performed with prescribed sea surface temperature (SST) and sea ice. Each of the four experiments simulates the atmospheric and isotopic response to Arctic oceanic conditions for selected years after the beginning of the satellite era in 1979. Changes in sea ice extent and SSTs have different impacts in Greenland and the rest of the Arctic. The simulated changes in central Arctic sea ice do not influence δ18O of Greenland precipitation, only anomalies of Baffin Bay sea ice. However, this does not exclude the fact that simulations based on other sea ice and sea surface temperature distributions might yield changes in the δ18O of precipitation in Greenland. For the Arctic, δ18O of precipitation and water vapour is sensitive to local changes in sea ice and sea surface temperature and the changes in water vapour are surface based. Reduced sea ice extent yields more enriched isotope values, whereas increased sea ice extent yields more depleted isotope values. The distribution of the sea ice and sea surface conditions is found to be essential for the spatial distribution of the simulated changes in δ18O.
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| 2. |
- Sinnl, Giulia, et al.
(författare)
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A multi-ice-core, annual-layer-counted Greenland ice-core chronology for the last 3800 years : GICC21
- 2022
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Ingår i: Climate of the Past. - : Copernicus GmbH. - 1814-9324 .- 1814-9332. ; 18:5, s. 1125-1150
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Tidskriftsartikel (refereegranskat)abstract
- Ice-core timescales are vital for the understanding of past climate; hence they should be updated whenever significant amounts of new data become available. Here, the Greenland ice-core chronology GICC05 was revised for the last 3835 years by synchronizing six deep ice cores and three shallow ice cores from the central Greenland ice sheet. A new method was applied by combining automated counting of annual layers on multiple parallel proxies and manual fine-tuning. A layer counting bias was found in all ice cores because of site-specific signal disturbances; therefore the manual comparison of all ice cores was deemed necessary to increase timescale accuracy. After examining sources of error and their correlation lengths, the uncertainty rate was quantified to be 1 year per century. The new timescale is younger than GICC05 by about 13 years at 3835 years ago. The most recent 800 years are largely unaffected by the revision. Between 800 and 2000 years ago, the offset between timescales increases steadily, with the steepest offset occurring between 800 and 1100 years ago. Moreover, offset oscillations of about 5 years around the average are observed between 2500 and 3800 years ago. The non-linear offset behavior is attributed to previous mismatches of volcanic eruptions, to the much more extensive dataset available to this study, and to the finer resolution of the new ice-core ammonium matching. By analysis of the common variations in cosmogenic radionuclides, the new ice-core timescale is found to be in alignment with the IntCal20 curve (Reimer et al., 2020).
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| 3. |
- Zheng, Minjie, et al.
(författare)
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Climate information preserved in seasonal water isotope at NEEM : Relationships with temperature, circulation and sea ice
- 2018
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Ingår i: Climate of the Past. - : Copernicus GmbH. - 1814-9324 .- 1814-9332. ; 14:7, s. 1067-1078
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Tidskriftsartikel (refereegranskat)abstract
- Analyzing seasonally resolved δ18O ice core data can aid the interpretation of the climate information in ice cores, also providing insights into factors governing the δ18O signal that cannot be deciphered by investigating the annual δ18O data only. However, the seasonal isotope signal has not yet been investigated in northern Greenland, e.g., at the NEEM (North Greenland Eemian Ice Drilling) ice core drill site. Here, we analyze seasonally resolved δ18O data from four shallow NEEM ice cores covering the last 150 years. Based on correlation analysis with observed temperature, we attribute about 70 and 30%of annual accumulation to summer and winter, respectively. The NEEM summer δ18O signal correlates strongly with summer western Greenland coastal temperature and with the first principal component (PC1) of summer δ18O from multiple seasonally resolved ice cores from central/southern Greenland. However, there are no significant correlations between NEEM winter δ18O data and western Greenland coastal winter temperature or southern/central Greenland winter δ18O PC1. The stronger correlation with temperature during summer and the dominance of summer precipitation skew the annual δ18O signal in NEEM. The strong footprint of temperature in NEEM summer δ18O record also suggests that the summer δ18O record rather than the winter δ18O record is a better temperature proxy at the NEEM site. Despite the dominant signal of the North Atlantic Oscillation (NAO) and the Atlantic Multidecadal Oscillation (AMO) in the central?southern ice core data, both NAO and AMO exert weak influences on NEEM seasonal δ18O variations. The NEEM seasonal δ18O is found to be highly correlated with Baffin Bay sea ice concentration (SIC) in the satellite observation period (1979?2004), suggesting a connection of the sea ice extent with δ18O at NEEM. NEEM winter δ18O significantly correlates with SIC even for the period prior to satellite observation (1901? 1978). The NEEM winter δ18O may reflect sea ice variationsof Baffin Bay rather than temperature itself. This study shows that seasonally resolved δ18O records, especially for sites with a seasonal precipitation bias such as NEEM, provide a better understanding of how changing air temperature and circulation patterns are associated with the variability in the δ18O records.
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