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Glacial groundwater can mobilize deep-seated methane from beneath glaciers and permafrost in the Arctic, leading to atmospheric emissions of this greenhouse gas. We present a temporal, hydro-chemical dataset of methane- rich groundwater collected during two melt seasons from a high Arctic glacial forefield to explore the seasonal dynamics of methane emissions. We use methane and ion concentrations and the isotopic composition of water and methane to investigate the sources of groundwater and the origin of the methane that the groundwater transports to the surface. Our results suggest two sources of groundwater, one shallow and one deep, which mix, and moderate methane dynamics. During summer, deep methane-rich groundwater is diluted by shallow oxygenated groundwater, leading to some microbial methane oxidation prior to its emergence at the surface. Characterization of the microbial compositions in the groundwater shows that microbial activity is an important seasonal methane sink along this flow-path. In the groundwater pool studied, we found that potential methane emissions were reduced by an average of 29% (±14%) throughout the summer due to microbial oxidation. During winter, deep groundwater remains active while many shallow systems shut down due to freezing, reducing subsurface methane oxidation, and potentially permitting larger methane emissions. Our results suggest that ratios of the different groundwater sources will change in the future as aquifer capacities and recharge volumes increase in a warming climate. [ABSTRACT FROM AUTHOR]

Rain-on-snow (ROS) events are becoming an increasingly common feature of the wintertime climate Svalbard in the High Arctic due to a warming climate. Changes in the frequency, intensity, and spatial distribution of wintertime ROS events in Svalbard are important to understand and quantify due their wideranging impacts on the physical environment as well as on human activity. Due to the sparse nature of ground observations across Svalbard, tools for mapping and long-term monitoring of ROS events over large spatial areas are reliant on remote sensing, snow models and atmospheric reanalyses. However, different methods of identifying and measuring ROS events can often present different interpretations of ROS climatology. This study compares a recently published Synthetic Aperture Radar (SAR) based ROS dataset for Svalbard to ROS derived from two snow models and a reanalysis dataset for 2004-2020. Although the number of ROS events differs across the datasets, all datasets exhibit both similarities and differences in the geographical distribution of ROS across the largest island, Spitsbergen. Southern and western coastal areas experience ROS most frequently during the wintertime, with the early winter (November-December) experiencing overall most events compared to the spring (March-April). Moreover, we find that different temperature thresholds are required to obtain the best spatial agreement of ROS events in the model and reanalysis datasets with ground observations. The reanalysis dataset evaluated against ground observations was superior to the other datasets in terms of accuracy due to the assimilation of ground observations into the dataset. The SAR dataset consistently scored lowest in terms of its overall accuracy due to many more false detections, an issue which is most likely explained by the persistence of moisture in the snowpack following the end of a ROS event. Our study not only highlights some spatial differences in ROS frequency and trends but also how comparisons between different datasets can confirm knowledge about the climatic variations across Svalbard where in-situ observations are sparse. [ABSTRACT FROM AUTHOR]