Abstract. Past temperature reconstructions from Antarctic ice cores require a good quantification and understanding of the relationship between snow isotopic composition and 2 m air or inversion (condensation) temperature. Here, we focus on the French–Italian Concordia Station, central East Antarctic plateau, where the European Project for Ice Coring in Antarctica (EPICA) Dome C ice cores were drilled. We provide a multi-year record of daily precipitation types identified from crystal morphologies, daily precipitation amounts and isotopic composition. Our sampling period (2008–2010) encompasses a warmer year (2009, +1.2 °C with respect to 2 m air temperature long-term average 1996–2010), with larger total precipitation and snowfall amounts (14 and 76 % above sampling period average, respectively), and a colder and drier year (2010, −1.8 °C, 4 % below long-term and sampling period averages, respectively) with larger diamond dust amounts (49 % above sampling period average). Relationships between local meteorological data and precipitation isotopic composition are investigated at daily, monthly and inter-annual scale, and for the different types of precipitation. Water stable isotopes are more closely related to 2 m air temperature than to inversion temperature at all timescales (e.g. R2 = 0.63 and 0.44, respectively for daily values). The slope of the temporal relationship between daily δ18O and 2 m air temperature is approximately 2 times smaller (0.49 ‰ °C−1) than the average Antarctic spatial (0.8 ‰ °C−1) relationship initially used for the interpretation of EPICA Dome C records. In accordance with results from precipitation monitoring at Vostok and Dome F, deuterium excess is anti-correlated with δ18O at daily and monthly scales, reaching maximum values in winter. Hoar frost precipitation samples have a specific fingerprint with more depleted δ18O (about 5 ‰ below average) and higher deuterium excess (about 8 ‰ above average) values than other precipitation types. These datasets provide a basis for comparison with shallow ice core records, to investigate post-deposition effects. A preliminary comparison between observations and precipitation from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and the simulated water stable isotopes from the Laboratoire de Météorologie Dynamique Zoom atmospheric general circulation model (LMDZiso) shows that models do correctly capture the amount of precipitation as well as more than 50 % of the variance of the observed δ18O, driven by large-scale weather patterns. Despite a warm bias and an underestimation of the variance in water stable isotopes, LMDZiso correctly captures these relationships between δ18O, 2 m air temperature and deuterium excess. Our dataset is therefore available for further in-depth model evaluation at the synoptic scale.

Abstract. The European Alps stretch over a range of climate zones which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine-wide analysis of snow depth from six Alpine countries – Austria, France, Germany, Italy, Slovenia, and Switzerland – including altogether more than 2000 stations of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions which match the climatic forcing zones: north and high Alpine, north-east, north-west, south-east, and south and high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations from November to May. The average trend among all stations for seasonal (November to May) mean snow depth was −8.4 % per decade, for seasonal maximum snow depth −5.6 % per decade, and for seasonal snow cover duration −5.6 % per decade. Stronger and more significant trends were observed for periods and elevations where the transition from snow to snow-free occurs, which is consistent with an enhanced albedo feedback. Additionally, regional trends differed substantially at the same elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.

Abstract. Antarctic surface snow has been studied by means of continuous measurements and observations over a period of 3 yr at Dome C. Snow observations include solid deposits in form of precipitation, diamond dust, or hoar, snow temperatures at several depths, records of deposition and erosion on the surface, and snow profiles. Together with meteorological data from automatic weather stations, this forms a unique dataset of snow conditions on the Antarctic Plateau. Large differences in snow amounts and density exist between solid deposits measured 1 m above the surface and deposition at the surface. We used the snow-cover model SNOWPACK to simulate the snow-cover evolution for different deposition parameterizations. The main adaptation of the model described here is a new event-driven deposition scheme. The scheme assumes that snow is added to the snow cover permanently only during periods of strong winds. This assumption followed from the comparison between observations of solid deposits and daily records of changes in snow height: solid deposits could be observed on tables 1 m above the surface on 94 out of 235 days (40 %) while deposition at the surface occurred on 59 days (25 %) during the same period, but both happened concurrently on 33 days (14 %) only. This confirms that precipitation is not necessarily the driving force behind non-temporary snow height changes. A comparison of simulated snow height to stake farm measurements over 3 yr showed that we underestimate the total accumulation by at least 33 %, when the total snow deposition is constrained by the measurements of solid deposits on tables 1 m above the surface. During shorter time periods, however, we may miss over 50 % of the deposited mass. This suggests that the solid deposits measured above the surface and used to drive the model, even though comparable to ECMWF forecasts in its total magnitude, should be seen as a lower boundary. As a result of the new deposition mechanism, we found a good agreement between model results and measurements of snow temperatures and recorded snow profiles. In spite of the underestimated deposition, the results thus suggest that we can obtain quite realistic simulations of the Antarctic snow cover by the introduction of event-driven snow deposition.

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