The monitoring of the mass balance of the Werenskioldbreen (Wedel Jarlsberg Land, Spitsbergen, Svalbard) in the years 1999-2002 and 2009-2018. It is calculated on the base of 4 to 9 ablation stakes (depend on year). The mass balance is determined by conducting field surveys on floating calendar dates (floating-date system). Data have also been submitted to the World Glacier Monitoring Sevice (WGMS, https://wgms.ch)

Results of supervised classification of six Landsat 8 images acquired on: 25 May, 3 June, 22 June, 15 July, 4 August and 20 August 2014, covering glaciers in Hornsund fiord. Method of classification: Maximum Likelihood. The results show variability of snow cover areas in melting period of 2014 for glaciers located in Hornsund fiord and larger than 9 km2 (Körberbreen, Samarinbreen, Chomjakovbreen, Mendelejevbreen, Svalisbreen, Hornbreen, Storbreen, Kvalfangarbreen, Mühlbacherbreen, Paierlbreen and Hansbreen). For more information, please check: https://doi.org/10.3390/w9100804 Overview: Results of Maximum Likelihood classification of Landsat 8 images for analysed glaciers. Red - snow cover, yellow - glacier ice, black - debirs, grey - cloud cover.

The positions of the glacier termini in Hornsund are derived with very high frequency in the period 1991–2018. Over 230 multispectral and Synthetic Aperture Radar (SAR) data were used: LANDSAT 5, LANDSAT 7, LANDSAT 8, Terra ASTER, Alos AVNIR, SPOT 5, ERS-1, ERS-2, ENVISAT, Alos PALSAR, TerraSAR-X, TanDEM-X, and Sentinel-1. SAR data were used to detect any variability in the glacier front during the polar night. The satellite data were digitized manually to obtain the ice cliff position. Multispectral images were orthorectified and geocoded in PCI Geomatica and ArcGIS software. SAR data were usually provided at the SLC level, so that both radiometric and geometric corrections could be applied using the same methods, and with the same digital elevation model (2008 DEM SPOT developed by the IPY-SPIRIT Project; Korona et al., 2009). The SAR data were processed in BEAM (http://www.brockmann-consult.de/cms/web/beam). Sentinel data downloaded from the Sentinel’s Data Hub were already processed. Data not published.

Since 2010, continuous monitoring of the front zone of the Hansa Glacier with the use of Canon Eos 1000D photo cameras has been carried out (timelapse). Pictures in different periods of time were taken by 3 different cameras. Two cameras (106 and 107) were located on the Fugleberget slope and one (601) on the Baranowskiodden. The periods for which data are available and the interval of taking pictures are shown in Appendix 1.

DEMs from WorldView-2 and Pléaides were extracted using the Rational Function Model (RFM). To improve images orientation, one ground control points (GCPs) was used for each stereo pair. Data format: grid (2m), UTM 33X / EGM 2008. DEMs were developed in OrthoEngine module of PCI Geomatica 2016 with the low level of detail and mountainous type of relief.

Subglacial topography was derived from radio-echo sounding (RES) survey conducted in spring 2008 by the University of Silesia research team (M. Grabiec and J. Jania) in cooperation with the Institute of Geophysics Polish Academy of Sciences (D. Puczko) and the Maria Curie-Sklodowska University (G.Gajek). The profiles were acquired by the radar system equipped with 25 MHz unshielded antenna pulled behind snowmobile. Traces were recorded every 0.5 s, that translates into 1.5-2.0 trace-to-trace distance depending on the vehicle’s velocity. Traces were positioned by GNSS receiver working in differential mode with 3D accuracy ± 1m. In total over 100 km of RES profiles were acquired on Hansbreen, 66 km on Werenskioldbreen and 43 km on Renardbreen. RES data were processed using standard procedure including: DC-offset, time-zero adjustment, 2-D filter, amplitude correction, bandpass filtering and migration. Time-to-depth conversion applied average radio-wave velocity in glacier ice 16.4 cm ns-1 calculated based on CMP analysis performed on Hansbreen in the same season as the GPR profiling. The ice/bed interface was picked up semi-automatically with RMSE 5.3 ns (0.43 m) (Grabiec, 2017). Then the bedrock elevation data were interpolated over studied glaciers taking into account elevation of nonglaciated surroundings (Grabiec 2017) and bathymetry at the front of tidewater Hansbreen (Grabiec et al. 2012). Finally produced 100 m resolution DEMs are in UTM 33X WGS84 reference system. DEM of 300 m resolution is freely available. For 100 m resolution DEM please contact: mariusz.grabiec@us.edu.pl. The data were collected and processed under following projects: • IPY/269/2006 GLACIODYN The dynamic response of Arctic glaciers to global warming • UE FP7-ENV-2008-1 ice2sea Estimating the future contribution of continental ice to sea-level rise • PNRF-22-AI-1/07 AWAKE Arctic Climate and Environment of the Nordic Seas and the Svalbard – Greenland Area • 03/KNOW2/2014 KNOW Leading National Research Centre Reference: Grabiec M., Jania J., Puczko D., Kolondra L., and Budzik T., 2012: Surface and bed morphology of Hansbreen, a tidewater glacier in Spitsbergen. Polish Polar Research 38(2): 111-138. Grabiec M. 2017: Stan i współczesne zmiany systemów lodowcowych południowego Spitsbergenu w świetle badań metodami radarowymi. Wydawnictwo Uniwersytetu Śląskiego, 328 s. Decaux, L., Grabiec, M., Ignatiuk, D., and Jania, J. 2018: Role of discrete recharge from the supraglacial drainage system for modelling of subglacial conduits pattern of Svalbard polythermal glaciers, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-219, in review.

The orthophotomap was prepared on the basis of infrared aerial photographs taken by EUROSENSE in September 1998. The study covers the Dolina Kiezmarskej Bieley vody valley located in the High Tatra Mountains (Slovakia). Cartographic projection: Universal Transverse Mercator, Ellipsoid: WGS 84, Coordinates system: UTM zone 34. The project was financed by No.3P04E 045 23. Editors: Bogdan Gądek, Milan Koren (sen.), Milan Koren (jun.) The project was financed by the Polish Commitee on Scientific Research under term of research grant No. 3P04E 045 23.

Dataset contains detailed measurements of physical features of seasonal snow cover, according to International Classification of Seasonal Snow on the Ground (Fierz et al. 2009). Fieldwork has been done during peak of accumulation on several glaciers in the region of Hornsund, Svalbard: Amundsenisen (2013) Hansbreen (three sites; 2010, 2012, 2013, 2014, 2015, 2017, 2018) Werenskioldbreen (two sites; 2013, 2015) Nannbreen (2013) Ariebreen (2014) Acknowledgements: Research Council of Norway, Arctic Field Grant 2013: Spatial distribution of snow cover and drainage systems on the glaciers on Wedel Jarlsberg Land (RiS ID: 6158); the National Science Centre PRELUDIUM 4: Role of meltwater from snow cover for supplying drainage systems of the Spitsbergen glaciers (2012/07/N/ST10/03784) References: Laska M., Luks B., Budzik T., 2016. Influence of snowpack internal structure on snow metamorphism and melting intensity on Hansbreen, Svalbard. Polish Polar Research, 37(2): 193–218. doi:10.1515/popore-2016-0012 Laska M., Grabiec M., Ignatiuk D., Budzik T., 2017. Snow deposition patterns on southern Spitsbergen glaciers, Svalbard, in relation to recent meteorological conditions and local topography. Geografiska Annaler, Series A: Physical Geography, 99(3): 262–287 doi:10.1080/04353676.2017.1327321 Laska M., Barzycka B., Luks B., 2017. Melting Characteristics of Snow Cover on Tidewater Glaciers in Hornsund Fjord, Svalbard. Water, 9(10), 804. doi:10.3390/w9100804

Thermal structure of selected S Spitsbergen glaciers was derived from ground based radio-echo sounding (RES). The division between cold and temperate ice layers is based on indirect interpretation of GPR (ground penetrating radar) image. Cold ice layer is virtually “transparent” for radio waves, while temperate ice layer is characterised by numerous diffractions on water inclusions. The database contains results from 479.7 km of RES profiles acquired in 2007-2014 on 12 glaciers in Wedel Jarlsberg Land and Torell Land (S Spitsbergen) including: Amundsenisen, Austre Torellbreen, Vestre Torellbreen, Hansbreen, Storbreen, Hornbreen, Hambergbreen, Recherchebreen, Scottbreen, Renardbreen, Werenskioldbreen and Ariebreen. Basic characteristics of investigated glaciers and its thermal structure is provided in table 1 (supplementary information). The surveys used GPR antennas in range 25-200 MHz, selected according to expected ice depth. Thanks to that on 87% of the profiles ice/bed interface has been identified. The radar system was pulled behind the snowmobile moving with velocity c. 20 km h-1. Applying trace interval 0.2-1.0 s, trace-to-trace distance was in range 1-5m. Trace positions were acquired by GNSS receivers working in navigation or differential mode with respective accuracy 3.0 m and 0.1m. RES data were processed applying standard filtering procedure (DC-offset, time-zero adjustment, 2-D filter, amplitude correction and bandpass filtering). Time-to-depth conversion used average radio wave velocity (RWV) for glacier ice 16.4 cm ns-1, 16.7 and 16.1 for cold and temperate ice respectively, based on CMP survey. More precise description of data collection, processing and quality is provided by Grabiec (2017). In S Spitsbergen polythermal glaciers are predominant. 57.8% of surveyed profiles consist of both: temperate and cold ice layers; 22.7% profiles is entirely temperate while 6.6% contains cold ice only (remaining profiles have undefined thermal structure). Studied glaciers represent broad spectrum of polythermal structure with cold-to-temperate ice ratio from 99:1% (Ariebreen) to 2:98% (accumulation zone of Vestre Torellbreen). The data were collected and processed under following projects: • IPY/269/2006 GLACIODYN The dynamic response of Arctic glaciers to global warming • UE FP7-ENV-2008-1 ice2sea Estimating the future contribution of continental ice to sea-level rise • PNRF-22-AI-1/07 AWAKE Arctic Climate and Environment of the Nordic Seas and the Svalbard – Greenland Area • NCBiR/PolarCLIMATE-2009/2-1/2010 SvalGlac Sensitivity of Svalbard glaciers to climate change • Pol-Nor/198675/17/2013 AWAKE-2 Arctic climate system study of ocean, sea ice and glaciers interactions in Svalbard area • 03/KNOW2/2014 KNOW Leading National Research Centre Reference: Grabiec M. 2017: Stan i współczesne zmiany systemów lodowcowych południowego Spitsbergenu w świetle badań metodami radarowymi. Wydawnictwo Uniwersytetu Śląskiego, 328 s.

High resolution orthophoto images from Geoeye, WorldView-2 and Pléaides processed in OrthoEngine module of PCI Geomatica. Data format: grid, UTM 33X / EGM 2008. Spatial resolution: 0.5 m (panchromatic and pansharpened) and 2 m (multispectral).