Due to recent climate change conditions, i.e. increasing temperatures and changing precipitation patterns, arctic snow cover dynamics exhibit strong changes in terms of extent and duration. Arctic amplification processes and impacts are well documented expected to strengthen in coming decades. In this context, innovative observation methods are helpful for a better comprehension of the spatial variability of snow properties relevant for climate research and hydrological applications.

Microwave remote sensing provides exceptional spatial and temporal performance in terms of all-weather application and target penetration. Time-series of Synthetic Active Radar images (SAR) are becoming more accessible at different frequencies and polarimetry has demonstrated a significant advantage for detecting changes in different media. Concerning arctic snow monitoring, SAR sensors can offer continuous time-series during the polar night and with cloud cover, providing a consequent advantage in regard of optical sensors.

The aim of this study is dedicated to the spatial/temporal variability of snow in the Ny-Ålesund area on the Br∅gger peninsula, Svalbard (N 78°55’ / E 11° 55’). The TerraSAR-X satellite (DLR, Germany) operated at X-band (3.1 cm, 9.6 GHz) with dual co-pol mode (HH/VV) at 5-m spatial resolution, and with high incidence angles (36° to 39°) poviding a better snow penetration and reducing topographic constraints. A dataset of 92 images (ascending and descending) is available since 2017, together with a high resolution DEM (NPI 5-m) and consistent in-situ measurements of meteorological data and snow profiles including glaciers sites.

Polarimetric processing is based on the Kennaugh matrix decomposition, copolar phase coherence (CCOH) and copolar phase difference (CPD). The Kennaugh matrix elements K₀, K₃, K_4, and K₇ are, respectively, the total intensity, phase ratio, intensity ratio, and shift between HH and VV phase center. Their interpretation allows analysing the structure of the snowpack linked to the near real time of in-situ measurements (snow profiles).

The X-band signal is strongly influenced by the snow stratigraphy: internal ice layers reduce or block the penetration of the signal into the snow pack. The best R² correlation performances between estimated and measured snow heights are ranging from 0.50 to 0.70 for dry snow conditions. Therefore, the use of the X-band for regular snow height estimations remains limited under these conditions.

Conversely, this study shows the benefit of TerraSAR-X thanks to the Kennaugh matrix elements analysis. A focus is set on the Copolar Phase Difference (CPD, Leinss 2016) between VV and HH polarization: Φ CPD = Φ _VV – Φ _HH. Our results indicate that the CPD values are related to the snow metamorphism: positive values correspond to dry snow (horizontal structures), negative values indicate recrystallization processes (vertical structures).

Backscattering evolution in time offer a good proxy for meteorological events detection, impacting on snow metamorphism. Fresh snowfalls or melting processes can then be retrieved at the regional scale and linked to air temperature or precipitation measurements at local scale. Polarimetric SAR time series is therefore of interest to complement satellite-based precipitation measurements in the Arctic.

Abstract. The EPICA Dome C (EDC) ice core provides the longest continuous climatic record covering the last 800 000 years (800 kyrs). Obtaining homogeneous high resolution measurements and accounting for diffusion provide a unique opportunity to study the evolution of decadal to millennial variability within the past glacial and interglacial periods. We present here a compilation of high resolution (11 cm) water isotopic records with 27 000 ?¹⁸O measurements and 7 920 ?D measurements (covering respectively 94 % and 27 % of the whole EDC record), including published and new measurements (2 900 for both ?¹⁸O and ?D) over the last 800 kyrs on the EDC ice core. We show that overlapping measurement series performed over multiple depth ranges over the past 20 years, using different analytical methods and in different laboratories, are consistent within analytical uncertainty, and therefore can be combined to provide a homogeneous data set. A frequency decomposition of the most complete ?¹⁸O record and a simple assessment of the possible influence of diffusion on the measured profile shows that the variability during glacial periods at multi-decadal to multi-centennial timescale is higher than variability of the interglacial periods. This analysis shows as well that during interglacial periods characterized by a temperature optimum at its beginning, the multi-centennial variability is the strongest over this temperature optimum.