The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400–1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long-term snow property records essential for climate monitoring and data assimilation studies—especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.

Abstract. Ice cores from polar ice sheets and glaciers are an important climate archive. Snow layers, consecutively deposited and buried, contain climatic information from the time of their formation. However, particularly low-accumulation areas are characterised by temporally intermittent precipitation, which can be further redistributed after initial deposition, depending on the local surface features at different spatial scales. Therefore, the accumulation conditions at an ice core site influence the quantity and quality of the recorded climate signal in proxy records. This study aims to characterise the local accumulation patterns and the evolution of the snow height to describe the contribution of the snow (re-)deposition to the overall noise level in climate records from ice cores. To this end, we applied a structure-from-motion photogrammetry approach to generate near-daily elevation models of the surface snow for a 195 m2 area in the vicinity of the deep drilling site of the East Greenland Ice-core Project in northeast Greenland. Based on the snow height information we derive snow height changes on a day-to-day basis throughout our observation period from May to August 2018 and find an average snow height increase of ∼ 11 cm. The spatial and temporal data set also allows an investigation of snow deposition versus depositional modifications. We observe irregular snow deposition and erosion causing uneven snow accumulation patterns, a removal of more than 60 % of the deposited snow, and a negative relationship between the initial snow height and the amount of accumulated snow. Furthermore, the surface roughness decreased by approximately a factor of 2 throughout the spring and summer season at our study site. Finally, our study shows that structure from motion is a relatively simple method to demonstrate the potential influences of depositional processes on proxy signals in snow and ice.

Abstract. Ice core water isotope records from Greenland and Antarctica are a valuable proxy for paleoclimate reconstruction, yet the processes influencing the climate signal stored in the isotopic composition of the snow are being challenged and revisited. Apart from precipitation input, post-depositional processes such as wind-driven redistribution and vapor–snow exchange processes at and below the surface are hypothesized to contribute to the isotope climate signal subsequently stored in the ice. Recent field studies have shown that surface snow isotopes vary between precipitation events and co-vary with vapor isotopes, which demonstrates that vapor–snow exchange is an important driving mechanism. Here we investigate how vapor–snow exchange processes influence the isotopic composition of the snowpack. Controlled laboratory experiments under forced sublimation show an increase in snow isotopic composition of up to 8 ‰ δ18O in the uppermost layer due to sublimation, with an attenuated signal down to 3 cm snow depth over the course of 4–6 d. This enrichment is accompanied by a decrease in the second-order parameter d-excess, indicating kinetic fractionation processes. Our observations confirm that sublimation alone can lead to a strong enrichment of stable water isotopes in surface snow and subsequent enrichment in the layers below. To compare laboratory experiments with realistic polar conditions, we completed four 2–3 d field experiments at the East Greenland Ice Core Project site (northeast Greenland) in summer 2019. High-resolution temporal sampling of both natural and isolated snow was conducted under clear-sky conditions and demonstrated that the snow isotopic composition changes on hourly timescales. A change of snow isotope content associated with sublimation is currently not implemented in isotope-enabled climate models and is not taken into account when interpreting ice core isotopic records. However, our results demonstrate that post-depositional processes such as sublimation contribute to the climate signal recorded in the water isotopes in surface snow, in both laboratory and field settings. This suggests that the ice core water isotope signal may effectively integrate across multiple parameters, and the ice core climate record should be interpreted as such, particularly in regions of low accumulation.