Assessing the robustness of Antarctic temperature reconstructions over the past 2 millennia using pseudoproxy and data assimilation experiments
Authors: Klein François , Abram Nerilie J. , Curran Mark A. J. , Goosse Hugues , Goursaud Sentia , Masson-Delmotte Valérie , Moy Andrew , Neukom Raphael , Orsi Anaïs , Sjolte Jesper , Steiger Nathan , Stenni Barbara , Werner Martin 
Published: April 2019

Abstract. The Antarctic temperature changes over the past millennia remain more
uncertain than in many other continental regions. This has several origins:
(1) the number of high-resolution ice cores is small, in particular on the
East Antarctic plateau and in some coastal areas in East Antarctica; (2) the
short and spatially sparse instrumental records limit the calibration period
for reconstructions and the assessment of the methodologies; (3) the link
between isotope records from ice cores and local climate is usually complex
and dependent on the spatial scales and timescales investigated. Here, we use
climate model results, pseudoproxy experiments and data assimilation
experiments to assess the potential for
reconstructing the Antarctic temperature over the last 2 millennia based on a
new database of stable oxygen isotopes in ice cores compiled in the framework
of Antarctica2k (Stenni et al., 2017). The well-known covariance between
δ18O and temperature is reproduced in the two isotope-enabled
models used (ECHAM5/MPI-OM and ECHAM5-wiso), but is generally weak over the
different Antarctic regions, limiting the skill of the reconstructions.
Furthermore, the strength of the link displays large variations over the past
millennium, further affecting the potential skill of temperature
reconstructions based on statistical methods which rely on the assumption
that the last decades are a good estimate for longer temperature
reconstructions. Using a data assimilation technique allows, in theory, for
changes in the δ18O–temperature link through time and space
to be taken into account. Pseudoproxy experiments confirm the benefits of
using data assimilation methods instead of statistical methods that provide
reconstructions with unrealistic variances in some Antarctic subregions. They
also confirm that the relatively weak link between both variables leads to a
limited potential for reconstructing temperature based on
δ18O. However, the reconstruction skill is higher and more
uniform among reconstruction methods when the reconstruction target is the
Antarctic as a whole rather than smaller Antarctic subregions. This
consistency between the methods at the large scale is also observed when
reconstructing temperature based on the real δ18O regional
composites of Stenni et al. (2017). In this case, temperature reconstructions
based on data assimilation confirm the long-term cooling over Antarctica
during the last millennium, and the later onset of anthropogenic warming
compared with the simulations without data assimilation, which is especially
visible in West Antarctica. Data assimilation also allows for models and
direct observations to be reconciled by reproducing the east–west contrast
in the recent temperature trends. This recent warming pattern is likely
mostly driven by internal variability given the large spread of individual
Paleoclimate Modelling Intercomparison Project (PMIP)/Coupled Model
Intercomparison Project (CMIP) model realizations in simulating it. As in the
pseudoproxy framework, the reconstruction methods perform differently at the
subregional scale, especially in terms of the variance of the time series
produced. While the potential benefits of using a data assimilation method
instead of a statistical method have been highlighted in a pseudoproxy
framework, the instrumental series are too short to confirm this in a
realistic setup.