Seasonal‐Scale Dating of a Shallow Ice Core From Greenland Using Oxygen Isotope Matching Between Data and Simulation

Abstract

A precise age scale based on annual layer counting is essential for investigating past environmental changes from ice core records. However, subannual scale dating is hampered by the irregular intraannual variabilities of oxygen isotope (δ18O) records. Here we propose a dating method based on matching the δ18O variations between ice core records and records simulated by isotope‐enabled climate models. We applied this method to a new δ18O record from an ice core obtained from a dome site in southeast Greenland. The close similarity between the δ18O records from the ice core and models enables correlation and the production of a precise age scale, with an accuracy of a few months. A missing δ18O minimum in the 1995/1996 winter is an example of an indistinct δ18O seasonal cycle. Our analysis suggests that the missing δ18O minimum is likely caused by a combination of warm air temperature, weak moisture transport, and cool ocean temperature. Based on the age scale, the average accumulation rate from 1960 to 2014 is reconstructed as 1.02 m yr−1 in water equivalent. The annual accumulation rate shows an increasing trend with a slope of 3.6 mm yr−1, which is mainly caused by the increase in the autumn accumulation rate of 2.6 mm yr−1. This increase is likely linked to the enhanced hydrological cycle caused by the decrease in Arctic sea ice area. Unlike the strong seasonality of precipitation amount in the ERA reanalysis data in the southeast dome region, our reconstructed accumulation rate suggests a weak seasonality.

A 60 Year Record of Atmospheric Aerosol Depositions Preserved in a High‐Accumulation Dome Ice Core, Southeast Greenland

“…The annual mean temperature at the SE‐Dome is −20.9°C, based on 20 m deep firn‐temperature measurements (Iizuka et al, ). For a time scale, we use the SEIS2016 age scale for 1960–2014, which is determined by the oxygen‐isotope matching method (Furukawa et al, ). The SEIS2016 scale has been carefully evaluated with independent age markers, and its precision is within a few months.…”

“…The annual ion fluxes are based on the sum of four seasons with the boundary of 1 March. These annual and seasonal accumulation rates are precisely estimated based on the SEIS2016 age scale (Furukawa et al, ). This method is similar to that used previously for the NO 3 − concentration of the SIGMA‐D ice core in northwestern Greenland.…”

“…The SE‐Dome region has the distinct characteristic of having the highest accumulation rate of any known dome of the Antarctic and Greenland ice sheets, a value in water equivalent (we) of 1.01 ± 0.22 m yr −1 (1960–2014), which is about 4 times that of a typical inland Greenland ice core and about 30 times that of a typical inland Antarctic ice core (Iizuka et al, ). Moreover, the precise age scale for the SE‐Dome ice core allows us to investigate seasonal variations of the climatic records from 1960 to 2014 (Furukawa et al, ). In this paper, we argue that the SE‐Dome ice core preserves the NO 3 − flux better than previous polar ice records, and we evaluate the SO 4 2− and NO 3 − record against known emissions of SO x and NO x over the past 60 years.…”

Microstructure of Snow and Its Link to Trace Elements and Isotopic Composition at Kohnen Station, Dronning Maud Land, Antarctica

“…More specifically, stable water isotopes are a well-established proxy for past air temperature variations in Greenland (e.g. White et al, 1997;Vinther et al, 2010;Furukawa et al, 2017;Zheng et al, 2018) and Antarctica (e.g. Masson-Delmotte et al, 2008;Stenni et al, 2017).…”

Chronological characteristics for snow accumulation on Styx Glacier in northern Victoria Land, Antarctica

“…Ice core chronology is an initial and essential step for the interpretation of the past records of climate, environment and atmospheric circulation from polar ice cores (Legrand and Mayewski, 1997; Traversi and others, 2004; Sinclair and others, 2010; Furukawa and others, 2017). A precise chronology provides an accurate quantification of snow accumulation rate in sub-annual and annual scales which is an important measure to surface mass-balance studies (Frezzotti and others, 2007; Rignot and others, 2011).…”