Abstract. We study a firn and ice core drilled at the new “Lock-In” site in East Antarctica, located 136 km away from Concordia station towards Dumont d'Urville. High-resolution chemical and physical measurements were performed on the core, with a particular focus on the trapping zone of the firn where air bubbles are formed. We measured the air content in the ice, closed and open porous volumes in the firn, firn density, firn liquid conductivity, major ion concentrations, and methane concentrations in the ice. The closed and open porosity volumes of firn samples were obtained using the two independent methods of pycnometry and tomography, which yield similar results. The measured increase in the closed porosity with density is used to estimate the air content trapped in the ice with the aid of a simple gas-trapping model. Results show a discrepancy, with the model trapping too much air. Experimental errors have been considered but do not explain the discrepancy between the model and the observations. The model and data can be reconciled with the introduction of a reduced compression of the closed porosity compared to the open porosity. Yet, it is not clear if this limited compression of closed pores is the actual mechanism responsible for the low amount of air in the ice. High-resolution density measurements reveal the presence of strong layering, manifesting itself as centimeter-scale variations. Despite this heterogeneous stratification, all layers, including the ones that are especially dense or less dense compared to their surroundings, display similar pore morphology and closed porosity as a function of density. This implies that all layers close in a similar way, even though some close in advance or later compared to the bulk firn. Investigation of the chemistry data suggests that in the trapping zone, the observed stratification is partly related to the presence of chemical impurities.

Abstract. We present a global distribution of surface methane (CH₄) emission estimates for 2000–2012 derived using the CarbonTracker Europe-CH₄ (CTE-CH₄) data assimilation system. In CTE-CH₄, anthropogenic and biospheric CH₄ emissions are simultaneously estimated based on constraints of global atmospheric in situ CH₄ observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH₄ to surface in situ observations, vertical profiles of CH₄ made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH₄) from the Total Carbon Column Observing Network (TCCON), and XCH₄ from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH₄ is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000–2012 are 516±51Tg CH₄yr⁻¹, with an increase of 18Tg CH₄yr⁻¹ from 2000–2006 to 2007–2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations ( < 2Tg CH₄yr⁻¹ difference), and much smaller than suggested by EDGAR v4.2 FT2010 inventory (33Tg CH₄yr⁻¹), which was used for prior anthropogenic emission estimates. The result is in good agreement with other published estimates from inverse modelling studies (16–20Tg CH₄yr⁻¹). However, this study could not conclusively separate a small trend in biospheric emissions (−5 to +6.9Tg CH₄yr⁻¹) from the much larger trend in anthropogenic emissions (15–27Tg CH₄yr⁻¹). Finally, we find that the global and North American CH₄ balance could be closed over this time period without the previously suggested need to strongly increase anthropogenic CH₄ emissions in the United States. With further developments, especially on the treatment of the atmospheric CH₄ sink, we expect the data assimilation system presented here will be able to contribute to the ongoing interpretation of changes in this important greenhouse gas budget.

Abstract. Climate change projections still suffer from a limited representation of the permafrost–carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change.