Antarctica is a fundamental element of the global climate system. On the one hand, the ice masses of Antarctica are a unique climate archive that has steadily piled up over millennia. Analyses of stable water isotopes (δ18O and δ2H) and aerosols (including ions from sea salt and biogenic emissions), which serve as indirect indicators of climate in ice cores ("climate proxies"), make reconstructions of climate history possible. Gas inclusions in the ice even allow a direct study of the paleoatmosphere. On the other hand, Antarctica is strongly affected by global climate change. Rising temperatures cause a widespread mass loss in West Antarctica and a regional mass loss in East Antarctica. The whole Antarctic ice sheet may contribute to a global sea level rise of about 60 m if it melts entirely. This work provides important insights into both research aspects of glaciology – the look into the past and into the future. Particularly in areas that are logistically difficult to access, such as the East Antarctic Plateau, field data are scarce. However, these are essential both for studying the signal formation of climate proxies and for validating results from (satellite-based) remote sensing. The East Antarctic Plateau extends from 20°W to 45°E above an elevation of 2000 m asl. During the Antarctic summer of 2016/17, snow cores were sampled in that area on a traverse between Kohnen Station (0° 4’E, 75° 0’S) and the abandoned Plateau Station (40° 33’E, 79° 15’S). X-ray computed tomography was used to determine the density and stratigraphic properties of the snow. The cores were then cut into individual samples at 1 cm or 2 cm resolution under clean room conditions at -18°C, for which a special instrument was developed as part of this study. The distinct samples were analyzed for stable water isotopes as well as major ions. This approach of a multiparameter analysis allows a combined look at different individual parameters and thus better understand the snowpack history. Multiple snow cores per sampling location allow a more representative determination of the investigated parameters. The small-scale variability caused by stratigraphic noise or postdepositional processes can thus be filtered. The surface snow density is needed as a parameter to convert the elevation change of the ice sheet measured by satellites into a mass balance. Due to lack of large-scale data, this density is often modeled. The sampling approach allows us to obtain a representative surface snow density with a relative error of less than 1.5% at each sampling location. Along the traverse route, the mean surface snow density is 355 kg m-3 and shows a lower dependence on temperature and accumulation rate than assumed. The modeled values show a significant discrepancy of about -10% from the measured density. A simplified calculation shows that the modeled snow density underestimates the mass budget of the firn column on the East Antarctic Plateau by 3%. Parameterizations of surface snow density can be tuned with the presented data to reduce the uncertainty of the mass balance of East Antarctica. Crusts in polar snowpacks are a stratigraphic detail that has been used, for example, to characterize environmental conditions in remote regions of the ice sheets. In this work, the first dataset on the spatial distribution of crusts in polar snow is presented – not only with data from the East Antarctic Plateau, but also from Greenland. Contrary to the assumption of finding more crusts in locations with lower accumulation rates, the total number of crusts per meter decreases with decreasing accumulation rates. The results suggest a linear relationship between the number of crusts and the logarithmic accumulation rate. Also the use of crusts for seasonal dating is possible. They can be used as a stratigraphic element supporting the dating with chemical proxies. An effect of crusts on backscatter properties in remote sensing and on firn column ventilation could be future research topics. An exemplary combined study of stratigraphic and chemical properties of the snowpack allows a reconstruction of the continuous buildup of a dune by drifting snow. Whether the chemical signature is characteristic for this type of deposition, however, remains to be proven with further data. Measurements of δ18O and δ2H can be used to reconstruct paleoclimate from seasonal to millennial time scales because of their direct relationship to precipitation temperature. But on short time scales, mechanical (including redistribution by winds) and physical processes (including sublimation and diffusion) at the surface, especially in areas with low accumulation rates, complicate the temporal assignment of the measured signals. An increase in deuterium excess over the uppermost cm in the majority of the investigated snow cores suggest a strong sublimation effect. Samples over larger depth intervals show stronger correlation with temperature and elevation, as the uppermost snow layers can have a seasonal bias. Cycles in δ18O around Kohnen Station can still be interpreted as seasonal signals, but below an accumulation rate of 50 kg m-2a-1, however, they are overprinted by postdepositional diffusion and consequently no longer suitable for dating the snowpack on short time scales. A comparison with the atmospheric general circulation model ECHAM6-wiso validates the model trend along the traverse, but shows a constant offset in δ18O. Modeled snow profiles with precipitation values from ECHAM6-wiso and a diffusion model represent the measured profiles well at 1-2 m depth. However, from the surface to 1 m depth, redeposition and sublimation appear to contribute significantly to (postdepositionally) shaping of the δ18O signal. These processes need to be further quantified in the future to improve the interpretation of stable water isotopes as a proxy for temperature. On the one hand, the change in surface snow density between samples from 2005/06 and samples from this study can be attributed to different volume errors in sampling rather than to a change in climatic conditions. On the other hand, mean δ18O values over the recent decades show a trend of increasing δ18O (and thus increasing temperature) on the East Antarctic Plateau. While these values are within the range of natural variability, they may be early indications that climate proxies in the snow of the East Antarctic Plateau have already recorded the increase of the global temperature.