Nitrogen and argon stable isotope data obtained from ancient air in ice cores provide the opportunity to reconstruct past temperatures in Greenland. In this study, we use a recently developed fitting-algorithm based on a Monte Carlo inversion technique coupled with two firn densification and heat diffusion models to fit several Holocene gas-isotope data measured at the GISP2 ice core and infer temperature variations.

We present for the first time the resulting temperature estimates when fitting delta N-15, delta Ar-40, and delta N-15(excess) as individual targets. While the comparison between the reconstructions using delta N-15 and delta Ar-40 shows high agreement, the use of delta N-15(excess) for temperature reconstruction is problematic because the statistical and systematic data uncertainty is higher and has a particular impact on multi-decadal to multi-centennial signals.

Our analyses demonstrate that T(delta N-15) provides the most robust estimate. The T(delta N-15) estimate is in better agreement with Buizert et al. (2018) than with the temperature reconstruction of Kobashi et al. (2017). However, all three reconstruction strategies lead to different temperature realizations. (C) 2022 The Authors. Published by Elsevier Ltd.