Assessing the robustness of Antarctic temperature reconstructions over the past two 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: August 2018

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 Antarctic Plateau and in some coastal areas in East Antarctica; 2) the short 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 and time scales investigated. Here, we use climate model results, pseudoproxy and data assimilation experiments to assess the potential of reconstructing the Antarctic temperature over the last two 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 taking into account changes in the δ18O-temperature link through time and space. Pseudoproxy experiments confirm the benefits of using data assimilation methods instead of statistical ones 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. The reconstruction skill is however 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 to the simulations without data assimilation, especially visible in West Antarctica. Data assimilation also allows reconciling models and direct observations by reconstructing the East-West contrast regarding the recent temperature trends, indicating that internal variability likely plays a major role in driving this heterogeneous recent warming. This is further supported by the large spread of individual PMIP/CMIP model realizations regarding the recent warming pattern. As in the pseudoproxy framework, the reconstruction methods perform differently at the subregional scale, especially in terms of the variance of the produced time series. While the potential benefits of using a data assimilation method instead of a statistical one have been highlighted in a pseudoproxy framework, the instrumental series are too short to confirm it in a realistic setup.