Description: In the context of the Arctic amplification of climate change affecting the regional atmospheric hydrological cycle, it is crucial to characterize the present-day moisture sources of the Arctic. The isotopic composition is an important tool to enhance our understanding of the drivers of the hydrological cycle due to the different molecular characteristics of water stable isotopes during phase change. This study introduces 2 years of continuous in situ water vapour and precipitation isotopic observations conducted since July 2015 in the eastern Siberian Lena delta at the research station on Samoylov Island. The vapour isotopic signals are dominated by variations at seasonal and synoptic timescales. Diurnal variations of the vapour isotopic signals are masked by synoptic variations, indicating low variations of the amplitude of local sources at the diurnal scale in winter, summer and autumn. Low-amplitude diurnal variations in spring may indicate exchange of moisture between the atmosphere and the snow-covered surface. Moisture source diagnostics based on semi-Lagrangian backward trajectories reveal that different air mass origins have contrasting contributions to the moisture budget of the Lena delta region. At the seasonal scale, the distance from the net moisture sources to the arrival site strongly varies. During the coldest months, no contribution from local secondary evaporation is observed. Variations of the vapour isotopic composition during the cold season on the synoptic timescale are strongly related to moisture source regions and variations in atmospheric transport: warm and isotopically enriched moist air is linked to fast transport from the Atlantic sector, while dry and cold air with isotopically depleted moisture is generally associated with air masses moving slowly over northern Eurasia.

Description: Ice cores represent one of the most important palaeoclimate archives, which record, among many other parameters, changes in stable oxygen and hydrogen isotopic composition and soluble ionic impurities. While impurities serve, for example, as proxies for sea ice, marine biological activity and volcanism, records of isotopic composition are the major proxy for the reconstruction of natural polar temperature variability. The latter is based on the temperature-dependent distillation and fractionation of the isotopic composition of water vapour along its atmospheric pathway and empirically determined relationships thereof. However, temperature is by far not the only driver of isotopic composition changes. A single isotopic ice-core record will comprise variations caused by a multitude of processes, from variable atmospheric circulation and moisture pathways to the intermittency of precipitation and finally to the mixing and re-location of surface snow by wind drift (stratigraphic noise). Taken together, these additional processes constitute a large amount of noise in the single isotope record, which masks the true temperature-related variability. Averaging a sufficient number of records to reduce overall noise is one means to allow for quantitative reconstructions, but its effectiveness depends on the spatial scales of the involved processes. Here, we discuss an alternative approach. Assuming that major impurity species exhibit a seasonal cycle and are mainly also, along with the isotopic composition, deposited by precipitation and redistributed by wind, a large portion of their interannual variability should be linked, which would offer the possibility of using the impurities to correct the variability of the isotopic records. In this contribution, we present the "ideal" dataset for testing this idea. We sampled and analysed isotopic composition and major impurity species on a four metre deep and 50 metre long trench at Kohnen Station, East Antarctica. This enables us to study the two-dimensional structure and relationship of both proxies to learn about their deposition mechanisms, their seasonality, and to test the ability of a combined isotope–impurity approach to reconstruct local temperatures by comparing so obtained temperature reconstructions with the local weather station data.