Abstract
Abstract. Paleoclimate archives, such as high-resolution ice core records, provide a means to investigate past climate variability. Until recently, the Law Dome (Dome Summit South site) ice core record remained one of few millennial-length high-resolution coastal records in East Antarctica. A new ice core drilled in 2017/2018 at Mount Brown South, approximately 1000 km west of Law Dome, provides an additional high-resolution record that will likely span the last millennium in the Indian Ocean sector of East Antarctica. Here, we compare snow accumulation rates and sea salt concentrations in the upper portion (∼ 20 m) of three Mount Brown South ice cores and an updated Law Dome record over the period 1975–2016. Annual sea salt concentrations from the Mount Brown South site record preserve a stronger signal for the El Niño–Southern Oscillation (ENSO; austral winter and spring, r = 0.533, p < 0.001, Multivariate El Niño Index) compared to a previously defined Law Dome record of summer sea salt concentrations (November–February, r = 0.398, p = 0.010, Southern Oscillation Index). The Mount Brown South site record and Law Dome record preserve inverse signals for the ENSO, possibly due to longitudinal variability in meridional transport in the southern Indian Ocean, although further analysis is needed to confirm this. We suggest that ENSO-related sea surface temperature anomalies in the equatorial Pacific drive atmospheric teleconnections in the southern mid-latitudes. These anomalies are associated with a weakening (strengthening) of regional westerly winds to the north of Mount Brown South that correspond to years of low (high) sea salt deposition at Mount Brown South during La Niña (El Niño) events. The extended Mount Brown South annual sea salt record (when complete) may offer a new proxy record for reconstructions of the ENSO over the recent millennium, along with improved understanding of regional atmospheric variability in the southern Indian Ocean, in addition to that derived from Law Dome.
Highlights
Ice cores collected from the Antarctic ice sheet contain chemical signals that are used to reconstruct past climate conditions
The lower sample resolution in the MBS site record and the potential for seasonal variability in snow accumulation identified in this work mean that the climatology of sea salts should be interpreted with caution until the periodicity of snowfall events at MBS is determined in greater detail and a longer record is developed
Investigation into the environmental conditions leading to the preservation of the El Niño–Southern Oscillation (ENSO) signal in the MBS site record indicates ENSO-like patterns in sea surface temperature (SST) anomalies in the equatorial Pacific and changes in the strength of the Amundsen Sea Low
Summary
Ice cores collected from the Antarctic ice sheet contain chemical signals that are used to reconstruct past climate conditions. Multiple studies have highlighted the need for additional millennial-length high-resolution ice cores in the Indian Ocean sector of East Antarctica (Stenni et al, 2017; IPCC, 2013; Thomas et al, 2017; Vance et al, 2016) Such records are required to fill spatial gaps in reconstructions of Antarctic temperature variability, aid in calibrating radar estimates of net surface mass balance, and provide additional climate proxy records that enhance the confidence and reliability of global climate reconstructions. Additional ice cores may contain signals for major sources of climate variability over the past millennia, including the dominant climate modes in the Southern Hemisphere: the Southern Annular Mode (SAM), the El Niño–Southern Oscillation (ENSO), and potentially the Indian Ocean Dipole (IOD) Understanding how these climate modes have varied in the past is important for a global initiative, the Past Global Changes 2k Network, that aims to integrate regional climate proxies to create global climate reconstructions over the past 2 millennia (PAGES 2k Consortium, 2013). Expanding the Past Global Changes 2k Network enables climate modellers to better understand natural climate variability, which in turn assists the reliability of future climate projections
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