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Abstract. We collected a debris-rich ice core from a buried icemass in Ong Valley, located in the Transantarctic Mountains in Antarctica. Wemeasured cosmogenic nuclide concentrations in quartz obtained from the icecore to determine the age of the buried ice mass and infer the processesresponsible for the emplacement of the debris currently overlaying the ice.Such ice masses are valuable archives of paleoclimate proxies; however, thepreservation of ice beyond 800 kyr is rare, and therefore much effort hasbeen recently focused on finding ice that is older than 1 Myr. In Ong Valley,the large, buried ice mass has been previously dated at > 1.1 Ma.Here we provide a forward model that predicts the accumulation of thecosmic-ray-produced nuclides 10Be, 21Ne, and 26Al in quartzin the englacial and supraglacial debris and compare the model predictionsto measured nuclide concentrations in order to further constrain the age.Large downcore variation in measured cosmogenic nuclide concentrationssuggests that the englacial debris is sourced both from subglacially derivedmaterial and recycled paleo-surface debris that has experienced surfaceexposure prior to entrainment. We find that the upper section of the icecore is 2.95 + 0.18 / −0.22 Myr old. The average ice sublimation rate duringthis time period is 22.86 + 0.10 / −0.09 m Myr−1, and the surfaceerosion rate of the debris is 0.206 + 0.013 / −0.017 m Myr−1. Burialdating of the recycled paleo-surface debris suggests that the lower sectionof the ice core belongs to a separate, older ice mass which we estimate tobe 4.3–5.1 Myr old. The ages of these two stacked, separate ice masses canbe directly related to glacial advances of the Antarctic ice sheet andpotentially coincide with two major global glaciations during the early andlate Pliocene epoch when global temperatures and CO2 were higher thanpresent. These ancient ice masses represent new opportunities for gatheringancient climate information. 

Abstract Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm −2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.