Accurate description of snow and firn processes is necessary for estimating the fraction of glacier surface melt that contributes to runoff. Most processes in snow and firn are to a great extent controlled by the temperature therein and in the absence of liquid water, the temperature evolution is dominated by the conductive heat exchange. The latter is controlled by the effective thermal conductivity k. Here we reconstruct the effective thermal conductivity of firn at Lomonosovfonna, Svalbard, using an optimization routine minimizing the misfit between simulated and measured subsurface temperatures and densities. The optimized k_* values in the range from 0.2 to 1.6 W (m K)⁻¹ increase downwards and over time. The results are supported by uncertainty quantification experiments, according to which k_* is most sensitive to systematic errors in empirical temperature values and their estimated depths, particularly in the lower part of the vertical profile. Compared to commonly used density-based parameterizations, our k values are consistently larger, suggesting a faster conductive heat exchange in firn.

The dynamic response of High Arctic glaciers to increased runoff in a warming climateremains poorly understood. We analyze a 10-year record of continuous velocity data collected atmultiple sites on Nordenskiöldbreen, Svalbard, and study the connec tion between ice flow andrunoff within and between seasons. During the melt season, the sensitivit y of ice motion to runoffat sites in the ablation and lower accumulation zone drops by a fac tor of 3 when cumulative runoff exceedsa local threshold, which is likely associated with a transition from inefficient (distributed) to efficient(channelized) drainage. Average summer (June–August) velocities are found to increase with summerablation, while subsequent fall (September–November) velocities decrease. Spring (March–May)velocities are largely insensitive to summer ablation, which suggests a short-lived impact of summermelt on ice flow during the cold season. The net impact of summer ablation on annual velocities is foundto be insignificant.

Spatial heterogeneity of snow and firn properties on glaciers introduces uncertainty in interpretation of point and profile observations and complicates modelling of meltwater percolation and runoff. Here we present a study of the temporal and spatial dynamics of firn density and stratigraphy at the plot-scale (approximate to 10 m x 10 m x 10 m) repeated annually during 2012-14 at the Lomonosovfonna ice-field, Svalbard. Results from cores, video inspections in boreholes and radar grid surveys are compared. Ice layers 0.1-50 cm thick comprised approximate to 8% of the borehole length. Most of them are 1-3 cm thick and could not be traced between boreholes separated by 3 m. Large lateral variability of firn structure affects representativeness of observations in single holes and calls for repeated studies in multiple points to derive a representative stratigraphy signal. Radar reflections are poorly correlated with ice layers in individual boreholes. However, the match between the high amplitude peaks in the grid-averaged radar signal and horizons of preferential ice layer formation revealed by averaging the video surveys over multiple boreholes is higher. These horizons are interpreted as buried firn layers previously exposed to melt-freeze or wind-driven densification and several of them are consistently recovered throughout three field campaigns.

Deep preferential percolation of melt water in snow and firn brings water lower along the vertical profile than a laterally homogeneous wetting front. This widely recognized process is an important source of uncertainty in simulations of subsurface temperature, density, and water content in seasonal snow and in firn packs on glaciers and ice sheets. However, observation and quantification of preferential flow is challenging and therefore it is not accounted for by most of the contemporary snow/firn models. Here we use temperature measurements in the accumulation zone of Lomonosovfonna, Svalbard, done in April 2012-2015 using multiple thermistor strings to describe the process of water percolation in snow and firn. Effects of water flow through the snow and firn profile are further explored using a coupled surface energy balance - firn model forced by the output of the regional climate model WRF. In situ air temperature, radiation, and surface height change measurements are used to constrain the surface energy and mass fluxes. To account for the effects of preferential water flow in snow and firn we test a set of depth-dependent functions allocating a certain fraction of the melt water available at the surface to each snow/firn layer. Experiments are performed for a range of characteristic percolation depths and results indicate a reduction in root mean square difference between the modeled and measured temperature by up to a factor of two compared to the results from the default water infiltration scheme. This illustrates the significance of accounting for preferential water percolation to simulate subsurface conditions. The suggested approach to parameterization of the preferential water flow requires low additional computational cost and can be implemented in layered snow/ firn models applied both at local and regional scales, for distributed domains with multiple mesh points.

Physical and chemical properties of four different ice cores (LF-97, LF-08, LF-09 and LF-11) drilled at Lomonosovfonna, Svalbard, were compared to investigate the effects of meltwater percolation on the chemical and physical stratigraphy of these records. A synthetic ice core approach was employed as reference record to estimate the ionic relocation and meltwater percolation length at this site during the period 2007-2010. Using this method, a partial ion elution sequence obtained for Lomonosovfonna was NO(3)(-)aEuro-> aEuro-SO42-, Mg2+, Cl-, K+, Na+ with nitrate being the most mobile within the snowpack. The relocation length of most of the ions was on the order of 1aEuro-m during this period. In addition, by using both a positive degree day (PDD) and a snow-energy model approaches to estimate the percentage of melt at Lomonosovfonna, we have calculated a melt percentage (MP) of the total annual accumulation within the range between 48 and 70aEuro-%, for the period between 2007 and 2010, which is above the MP range suggested by the ion relocation evidenced in the LF-syn core (i.e., MPaEuro-aEuro parts per thousand= aEuro-30aEuro-%). Using a firn-densification model to constrain the melt range, a MP of 30aEuro-% was found over the same period, which is consistent with the results of the synthetic ice core approach, and a 45aEuro-% of melt for the last 60 years. Considering the ionic relocation lengths and annual melt percentages, we estimate that the atmospheric ionic signal remains preserved in recently drilled Lomonosovfonna ice cores at an annual or bi-annual resolution when weather conditions were similar to those during the 2007-2010 period.

Svalbard climate is undergoing amplified change with respect to the global mean. Changing climate conditions directly affect the evolution of the seasonal snowpack, through its impact on accumulation, melt, and moisture exchange. We analyze long-term trends and spatial patterns of seasonal snow conditions in Svalbard between 1961 and 2012. Downscaled regional climate model output is used to drive a snow modeling system (SnowModel), with coupled modules simulating the surface energy balance and snowpack evolution. The precipitation forcing is calibrated and validated against snow depth data on a set of glaciers around Svalbard. Climate trends reveal seasonally inhomogeneous warming and a weakly positive precipitation trend, with strongest changes in the north. In response to autumn warming the date of snow onset increased (2days decade(-1)), whereas in spring/summer opposing effects cause a nonsignificant trend in the snow disappearance date. Maximum snow water equivalent (SWE) in winter/spring shows a modest increase (+0.01 meters water equivalent (mwe)decade(-1)), while the end-of-summer minimum snow area fraction declined strongly (from 48% to 36%). The equilibrium line altitude is highest in relatively dry inland regions, and time series show a clear positive trend (25mdecade(-1)) as a result of summer warming. Finally, rain-on-snow in the core winter season, affecting ground ice formation and limiting access of grazing animals to food supplies, peaks during specific years (1994, 1996, 2000, and 2012) and is found to be concentrated in the lower lying coastal regions in southwestern Svalbard.

Samples from two ice cores drilled at Lomonosovfonna, Svalbard, covering the period 1957-2009, and 1650-1995, respectively, were analyzed for NO(3)(-)concentrations, and NO3- stable isotopes (N-15 and O-18). Post-1950 N-15 has an average of (-6.91.9), which is lower than the isotopic signal known for Summit, Greenland but agrees with values observed in recent Svalbard snow and aerosol. Pre-1900 N-15 has an average of (4.21.6)parts per thousand suggesting that natural sources, enriched in the N-15 isotope, dominated before industrialization. The post-1950 O-18 average of (75.1 +/- 4.1)parts per thousand agrees with data from low and polar latitudes, suggesting similar atmospheric NOy (NOy=NO+NO2+HNO3) processing pathways. The combination of anthropogenic source N-15 and transport isotope effect was estimated as -29.1 parts per thousand for the last 60years. This value is below the usual range of NOx (NOx=NO+NO2) anthropogenic sources which is likely the result of a transport isotope effect of -32 parts per thousand. We suggest that the N-15 recorded at Lomonosovfonna is influenced mainly by fossil fuel combustion, soil emissions, and forest fires; the first and second being responsible for the marked decrease in N-15 observed in the post-1950s record with soil emissions being associated to the decreasing trend in N-15 observed up to present time, and the third being responsible for the sharp increase of N-15 around 2000.

Increasing reactive nitrogen (N-r) deposition in the Arctic may adversely impact N-limited ecosystems. To investigate atmospheric transport of N-r to Svalbard, Norwegian Arctic, snow and firn samples were collected from glaciers and analysed to define spatial and temporal variations (1 10 years) in major ion concentrations and the stable isotope composition (delta N-15 and delta O-18) of nitrate (NO3-) across the archipelago. The delta N-15(NO3-) and delta O-18(NO3-) averaged -4 parts per thousand and 67 parts per thousand in seasonal snow (2010-11) and -9 parts per thousand and 74 parts per thousand in firn accumulated over the decade 2001-2011. East-west zonal gradients were observed across the archipelago for some major ions (non-sea salt sulphate and magnesium) and also for delta N-15(NO3-) and delta O-18(NO3-) in snow, which suggests a different origin for air masses arriving in different sectors of Svalbard. We propose that snowfall associated with long-distance air mass transport over the Arctic Ocean inherits relatively low delta N-15(NO3-) due to in-transport N isotope fractionation. In contrast, faster air mass transport from the north-west Atlantic or northern Europe results in snowfall with higher delta N-15(NO3-) because in-transport fractionation of N is then time-limited.

This study used remotely sensed maps of nightlights to investigate the etiology of increasing disaster losses from hydrometeorological hazards in a data-scarce area. We explored trends in the probability of occurrence of hazardous events (extreme rainfall) and exposure of the local population as components of risk. The temporal variation of the spatial distribution of exposure to hydrometeorological hazards was studied using nightlight satellite imagery as a proxy. Temporal (yearly) and spatial (1 km) resolution make them more useful than official census data. Additionally, satellite nightlights can track informal (unofficial) human settlements. The study focused on the Samala River catchment in Guatemala. The analyses of disasters, using DesInventar Disaster Information Management System data, showed that fatalities caused by hydrometeorological events have increased. Such an increase in disaster losses can be explained by trends in both: (i) catchment conditions that tend to lead to more frequent hydrometeorological extremes (more frequent occurrence of days with wet conditions); and (ii) increasing human exposure to hazardous events (as observed by amount and intensity of nightlights in areas close to rivers). Our study shows the value of remote sensing data and provides a framework to explore the dynamics of disaster risk when ground data are spatially and temporally limited.