Terrestrial Remote Sensing of Snowmelt in a Diverse High-Arctic Tundra Environment Using Time-Lapse Imagery

Linking drought indices to atmospheric circulation in Svalbard, in the Atlantic sector of the High Arctic

Based on long-term climatological data from Ny-Ålesund, Svalbard Airport-Longyearbyen and the Polish Polar Station at Hornsund, we undertook an analysis of drought indices on Spitsbergen Island, Svalbard, for the period 1979-2019. The features and causes of spatiotemporal variability of atmospheric drought in Svalbard were identified, as expressed by the standardized precipitation evapotranspiration index (SPEI). There were several-year periods with SPEI indicating the dominance of drought or wet conditions. The long-term variability in the annual and half-year (May-October) SPEI values showed a prevalence of droughts in the 1980s and the first decade of the twenty-first century, while wet seasons were frequent in the 1990s and in the second decade of the twenty-first century. The seasonal SPEIs were characteristic of interannual variability. In MAM and JJA, droughts were more frequent after 2000; during SON and DJF of the same period, the frequency of wet seasons increased. The most remarkable changes in the scale of the entire research period occurred in autumn when negative values of SPEI occurred more often in the first part of the period, and positive values dominated in the last 20 years. The long-term pattern of the variables in consecutive seasons between 1979 and 2019 indicates relationships between the SPEI and anomalies of precipitable water and somewhat weaker relationships with anomalies of sea level pressure. The three stations are located at distances of more than 200 km from each other in the northern (Ny-Ålesund), central (Longyearbyen) and southern parts of Svalbard (Hornsund), and the most extreme values of drought conditions depended on the atmospheric circulation which could have been modified by local conditions thus droughts developed under various circulation types depending on the station. However, some similarities were identified in the atmospheric circulation patterns favouring drought conditions at Ny-Ålesund and Hornsund, both having more maritime climates than Longyearbyen. Extremely dry seasons were favoured by anticyclonic conditions, particularly a high-pressure ridge (type Ka) centred over Svalbard, air advection from the eastern sector under an influence of cyclone and negative precipitable water anomalies. During wet seasons anomalies of precipitable water were positive and cyclonic conditions dominated. These results were corroborated by the frequency of regional circulation types during JJA and DJF with the lowest and highest values of SPEI.

Hansbreen Snowpit Dataset - over 30-year of detailed snow research on an Arctic glacier

Snow cover is a key element in the water cycle, global heat balance and in the condition of glaciers. Characterised by high temporal and spatial variability, it is subject to short- and long-term changes in climatic conditions. This paper presents a unique dataset of snow measurements on Hansbreen, an Arctic glacier in Svalbard. The dataset includes 79 archived snow profiles performed from 1989 to 2021. It presents all available observations of physical properties for snow cover, such as grain shape and size, hardness, wetness, temperature and density, supplemented with organised metadata. All data has been revised and unified with current protocols and the present International Classification for Seasonal Snow on the Ground, allowing comparison of data from different periods and locations. The information included is essential for estimations of glacier mass balance or snow depth using indirect methods, such as ground-penetrating radar. A wide range of input data makes this dataset valuable to the greater community involved in the study of snow cover evolution and modelling related to glaciology, ecology and hydrology of glacierised areas.

Measurement(s)	snow cover, snow stratigraphy
Technology Type(s)	snow pit analyses, automatic weather stations
Factor Type(s)	Hansbreen
Sample Characteristic - Environment	seasonal snow cover, cryosphere, polar environment
Sample Characteristic - Location	glacier, Hansbreen, Hornsund, Spitsbergen, Svalbard, Arctic

Combined Use of Aerial Photogrammetry and Terrestrial Laser Scanning for Detecting Geomorphological Changes in Hornsund, Svalbard

The Arctic is a region undergoing continuous and significant changes in land relief due to different glaciological, geomorphological and hydrogeological processes. To study those phenomena, digital elevation models (DEMs) and highly accurate maps with high spatial resolution are of prime importance. In this work, we assess the accuracy of high-resolution photogrammetric DEMs and orthomosaics derived from aerial images captured in 2020 over Hornsund, Svalbard. Further, we demonstrate the accuracy of DEMs generated using point clouds acquired in 2021 with a Riegl VZ®-6000 terrestrial laser scanner (TLS). Aerial and terrestrial data were georeferenced and registered based on very reliable ground control points measured in the field. Both DEMs, however, had some data gaps due to insufficient overlaps in aerial images and limited sensing range of the TLS. Therefore, we compared and integrated the two techniques to create a continuous and gapless DEM for the scientific community in Svalbard. This approach also made it possible to identify geomorphological activity over a one-year period, such as the melting of ice cores at the periglacial zone, changes along the shoreline or snow thickness in gullies. The study highlights the potential for combining other techniques to represent the active processes in this region.

High Latitude Dust Transport Altitude Pattern Revealed from Deposition on Snow, Svalbard

High Latitude Dust (HLD) deposition in the surface snow layer in two distant locations in Svalbard (Hornsund and Pyramiden) were collected during the June/July 2019 field campaign and examined in the laboratory. Despite the differences in their climate and topography, both locations are characterised by very similar spatial patterns of the deposition. On the one hand, strong linear negative relationship between the altitude of the sample taken and its concentration was found in low altitude (below 300 m a.s.l.), suggesting a strong influence of local HLD sources. On the other hand, almost constant concentrations were found at higher elevated sampling sites (above 300 m a.s.l.). This suggests a predominantly long-range transport in high altitude areas. The importance of local sources in the lower altitude corresponds well with the generally higher concentrations of HLD in the Pyramiden area. This region has a drier, continental climate and more deglaciated bare land surfaces, which favour more sediment to be uplifted in comparison with the more maritime climate of Hornsund area in the southern part of Svalbard. The spatial division between the local and long-range transport is supported by the proportion of certain lithophile elements in the altitude gradient.

Monitoring the Snowpack Volume in a Sinkhole on Mount Lebanon using Time Lapse Photogrammetry

Lebanon has experienced serious water scarcity issues recently, despite being one of the wealthiest countries in the Middle East for water resources. A large fraction of the water resources originates from the melting of the seasonal snow on Mount Lebanon. Therefore, continuous and systematic monitoring of the Lebanese snowpack is becoming crucial. The top of Mount Lebanon is punctuated by karstic hollows named sinkholes, which play a key role in the hydrological regime as natural snow reservoirs. However, monitoring these natural snow reservoirs remains challenging using traditional in situ and remote sensing techniques. Here, we present a new system in monitoring the evolution of the snowpack volume in a pilot sinkhole located in Mount Lebanon. The system uses three compact time-lapse cameras and photogrammetric software to reconstruct the elevation of the snow surface within the sinkhole. The approach is validated by standard topographic surveys. The results indicate that the snow height can be retrieved with an accuracy between 20 and 60 cm (residuals standard deviation) and a low bias of 50 cm after co-registration of the digital elevation models. This system can be used to derive the snowpack volume in the sinkhole on a daily basis at low cost.

Automated Classification of Terrestrial Images: The Contribution to the Remote Sensing of Snow Cover

The relation between the fraction of snow cover and the spectral behavior of the surface is a critical issue that must be approached in order to retrieve the snow cover extent from remotely sensed data. Ground-based cameras are an important source of datasets for the preparation of long time series concerning the snow cover. This study investigates the support provided by terrestrial photography for the estimation of a site-specific threshold to discriminate the snow cover. The case study is located in the Italian Alps (Falcade, Italy). The images taken over a ten-year period were analyzed using an automated snow-not-snow detection algorithm based on Spectral Similarity. The performance of the Spectral Similarity approach was initially investigated comparing the results with different supervised methods on a training dataset, and subsequently through automated procedures on the entire dataset. Finally, the integration with satellite snow products explored the opportunity offered by terrestrial photography for calibrating and validating satellite-based data over a decade.

Using stable isotopes to estimate travel times in a data-sparse Arctic catchment: Challenges and possible solutions

Use of isotopes to quantify the temporal dynamics of the transformation of precipitation into run-off has revealed fundamental new insights into catchment flow paths and mixing processes that influence biogeochemical transport. However, catchments underlain by permafrost have received little attention in isotope-based studies, despite their global importance in terms of rapid environmental change. These high-latitude regions offer limited access for data collection during critical periods (e.g., early phases of snowmelt). Additionally, spatio-temporal variable freeze-thaw cycles, together with the development of an active layer, have a time variant influence on catchment hydrology. All of these characteristics make the application of traditional transit time estimation approaches challenging. We describe an isotope-based study undertaken to provide a preliminary assessment of travel times at Siksik Creek in the western Canadian Arctic. We adopted a model-data fusion approach to estimate the volumes and isotopic characteristics of snowpack and meltwater. Using samples collected in the spring/summer, we characterize the isotopic composition of summer rainfall, melt from snow, soil water, and stream water. In addition, soil moisture dynamics and the temporal evolution of the active layer profile were monitored. First approximations of transit times were estimated for soil and streamwater compositions using lumped convolution integral models and temporally variable inputs including snowmelt, ice thaw, and summer rainfall. Comparing transit time estimates using a variety of inputs revealed that transit time was best estimated using all available inflows (i.e., snowmelt, soil ice thaw, and rainfall). Early spring transit times were short, dominated by snowmelt and soil ice thaw and limited catchment storage when soils are predominantly frozen. However, significant and increasing mixing with water in the active layer during the summer resulted in more damped steam water variation and longer mean travel times (~1.5 years). The study has also highlighted key data needs to better constrain travel time estimates in permafrost catchments.