New Reconstruction of Antarctic Near-Surface Temperatures: Multidecadal Trends and Reliability of Global Reanalyses*,+

Nicolas, Julien P.; Bromwich, David H.

doi:10.1175/jcli-d-13-00733.1

Cited by 202 publications

(268 citation statements)

References 111 publications

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“…The 2500 m a.s.l. elevation contour is marked by a grey line; colours indicate the annual mean surface air temperature (Nicolas and Bromwich, 2014).…”

Section: Methodsmentioning

confidence: 99%

On the similarity and apparent cycles of isotopic variations in East Antarctic snow pits

et al. 2018

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Abstract. Stable isotope ratios δ 18 O and δD in polar ice provide a wealth of information about past climate evolution. Snow-pit studies allow us to relate observed weather and climate conditions to the measured isotope variations in the snow. They therefore offer the possibility to test our understanding of how isotope signals are formed and stored in firn and ice. As δ 18 O and δD in the snowfall are strongly correlated to air temperature, isotopes in the near-surface snow are thought to record the seasonal cycle at a given site. Accordingly, the number of seasonal cycles observed over a given depth should depend on the accumulation rate of snow. However, snow-pit studies from different accumulation conditions in East Antarctica reported similar isotopic variability and comparable apparent cycles in the δ 18 O and δD profiles with typical wavelengths of ∼ 20 cm. These observations are unexpected as the accumulation rates strongly differ between the sites, ranging from 20 to 80 mm w.e. yr −1 (∼ 6-21 cm of snow per year). Various mechanisms have been proposed to explain the isotopic variations individually at each site; however, none of these are consistent with the similarity of the different profiles independent of the local accumulation conditions.Here, we systematically analyse the properties and origins of δ 18 O and δD variations in high-resolution firn profiles from eight East Antarctic sites. First, we confirm the suggested cycle length (mean distance between peaks) of ∼ 20 cm by counting the isotopic maxima. Spectral analysis further shows a strong similarity between the sites but indicates no dominant periodic features. Furthermore, the apparent cycle length increases with depth for most East Antarctic sites, which is inconsistent with burial and compression of a regular seasonal cycle. We show that these results can be explained by isotopic diffusion acting on a noise-dominated isotope signal. The firn diffusion length is rather stable across the Antarctic Plateau and thus leads to similar power spectral densities of the isotopic variations. This in turn implies a similar distance between isotopic maxima in the firn profiles.Our results explain a large set of observations discussed in the literature, providing a simple explanation for the interpretation of apparent cycles in shallow isotope records, without invoking complex mechanisms. Finally, the results underline previous suggestions that isotope signals in single ice cores from low-accumulation regions have a small signal-to-noise ratio and thus likely do not allow the reconstruction of interannual to decadal climate variations.

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“…The 2500 m a.s.l. elevation contour is marked by a grey line; colours indicate the annual mean surface air temperature (Nicolas and Bromwich, 2014).…”

Section: Methodsmentioning

confidence: 99%

On the similarity and apparent cycles of isotopic variations in East Antarctic snow pits

et al. 2018

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“…Furthermore, we test the correlation with the nearsurface Antarctic temperature reconstruction by Nicolas and Bromwich (2014; referred to as NB2014), which uses three reanalysis products and takes advantage of the revised Byrd Station temperature record (Bromwich et al, 2013) to provide an improved reanalysis product for Antarctica for the time period 1958-2012 CE. We find no correlation between the NB2014 record and the ERAi data at the RICE site, nor the RICE δD o data for the 1979-2012 time period, perhaps suggesting some regional challenges.…”

Section: Isotope Temperature Correlationmentioning

confidence: 99%

“…-NB2014 were accessed via http://polarmet.osu.edu/ datasets/Antarctic_recon/ (Nicolas and Bromwich, 2014).…”

Section: Data Availabilitymentioning

confidence: 99%

The Ross Sea Dipole – temperature, snow accumulation and sea ice variability in the Ross Sea region, Antarctica, over the past 2700 years

et al. 2018

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“…Dee et al, 2011) in order to find out to what extent simulated wind fields in the region can reproduce the statistical relationship and dependence between weather and sea ice anomalies. This work therefore has a wider relevance given that atmospheric circulation changes in the Ross Sea may explain a significant portion of the climate variation in the region and particularly increases in sea ice extent and the northward drift of sea ice (Holland and Kwok, 2012;Nicolas and Bromwich, 2014).…”

Section: Introductionmentioning

confidence: 99%

Atmospheric forcing of sea ice anomalies in the Ross Sea polynya region

et al. 2017

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Abstract. We investigate the impacts of strong wind events on the sea ice concentration within the Ross Sea polynya (RSP), which may have consequences on sea ice formation. Bootstrap sea ice concentration (SIC) measurements derived from satellite SSM/I brightness temperatures are correlated with surface winds and temperatures from Ross Ice Shelf automatic weather stations (AWSs) and weather models (ERAInterim). Daily data in the austral winter period were used to classify characteristic weather regimes based on the percentiles of wind speed. For each regime a composite of a SIC anomaly was formed for the entire Ross Sea region and we found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea polynya and vice versa. By analyzing sea ice motion vectors derived from the SSM/I brightness temperatures we find significant sea ice motion anomalies throughout the Ross Sea during strong wind events, which persist for several days after a strong wind event has ended. Strong, negative correlations are found between SIC and AWS wind speed within the RSP indicating that strong winds cause significant advection of sea ice in the region. We were able to partially recreate these correlations using colocated, modeled ERA-Interim wind speeds. However, large AWS and model differences are observed in the vicinity of Ross Island, where ERA-Interim underestimates wind speeds by a factor of 1.7 resulting in a significant misrepresentation of RSP processes in this area based on model data. Thus, the cross-correlation functions produced by compositing based on ERA-Interim wind speeds differed significantly from those produced with AWS wind speeds. In general the rapid decrease in SIC during a strong wind event is followed by a more gradual recovery in SIC. The SIC recovery continues over a time period greater than the average persistence of strong wind events and sea ice motion anomalies. This suggests that sea ice recovery occurs through thermodynamic rather than dynamic processes.

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New Reconstruction of Antarctic Near-Surface Temperatures: Multidecadal Trends and Reliability of Global Reanalyses*,+

Abstract: A reconstruction of Antarctic monthly mean near-surface temperatures spanning 1958-2012 is presented.

Cited by 202 publications

References 111 publications

On the similarity and apparent cycles of isotopic variations in East Antarctic snow pits

On the similarity and apparent cycles of isotopic variations in East Antarctic snow pits

The Ross Sea Dipole – temperature, snow accumulation and sea ice variability in the Ross Sea region, Antarctica, over the past 2700 years

Atmospheric forcing of sea ice anomalies in the Ross Sea polynya region

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