Hydrographic and current time series data from outside the southern side of the Isfjorden Mouth during 8 September 2011 to 3 September 2012 at 78°03.637’ N; 013°31.271’ E, and 205 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor inflow of Atlantic Water to Isfjorden, and was equipped with three Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper, the intermediate, and the bottom layer. Additionally, three SBE 37 MicroCAT CTDs and five VEMCO mini temperature loggers were evenly distributed over the water column. For further details of the mooring and data, see Skogseth et al. (2019).

Hydrographic and current time series data from outside the southern side of the Isfjorden Mouth during 31 August 2014 to 24 August 2015 at 78°03.764’ N; 013°31.701’ E, and 211 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor inflow of Atlantic Water to Isfjorden, and was equipped with three Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper, the intermediate, and the bottom layer. Additionally, three SBE 37 MicroCAT CTDs and four AUQAlogg temperature loggers were evenly distributed over the water column. For further details of the mooring and data, see Skogseth et al. (2019).

Hydrographic and current time series data from outside the southern side of the Isfjorden Mouth during 31 August 2015 to 12 August 2016 at 78.0611 deg. N and 13.5249 deg. E, and 205 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor inflow of Atlantic Water to Isfjorden, and was equipped with three Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper, the intermediate, and the bottom layer. Additionally, three SBE 37 MicroCAT CTDs and five VEMCO mini temperature loggers were evenly distributed over the water column. For further details of the mooring and data, see Skogseth et al. (2019).

Hydrographic and current time series data from outside the northern side of the Isfjorden Mouth during 31 August 2015 to 12 August 2016 at 78°10.829’ N; 013°22.737’ E, and 228 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor outflow from Isfjorden and the hydrographic differences between the northern and southern part of the mouth. It was equipped with three Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper, the intermediate, and the bottom layer. For further details of the mooring and data, see Skogseth et al. (2019).

Hydrographic and current time series data from outside the northern side of the Isfjorden Mouth during 5 October 2017 to 24 August 2018 at 78°10.911’ N; 013°23.350’ E, and 242 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor outflow from Isfjorden and the hydrographic differences between the northern and southern part of the mouth. It was equipped with two Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper and the bottom layer. Additionally, three SBE 37 MicroCAT CTDs and three VEMCO mini temperature loggers were evenly distributed over the water column. For further details of the mooring and data, see Skogseth et al. (2019).

### Introduction This dataset contains GPS and sensor data from buoys deployed on sea ice north of Svalbard from January to June 2015. The data is described and used in Itkin et al (2017) [Thin ice and storms: a case study of sea ice deformation from buoy arrays deployed during N-ICE2015](https://doi.org/10.1002/2016JC012403), Provost et al (2017) [Observations of flooding and snow-ice formation in a thinner Arctic sea ice regime during the N-ICE2015 campaign: Influence of basal ice melt and storms](https://doi.org/10.1002/2016JC012011), Rösel et al (2018) [Thin Sea Ice, Thick Snow, and Widespread Negative Freeboard Observed During N-ICE2015 North of Svalbard](https://doi.org/10.1002/2017JC012865), and Shestov et al (2018) [Decay phase thermodynamics of ice ridges in the Arctic Ocean](https://doi.org/10.1016/j.coldregions.2018.04.005). A sub-set of these buoy data was published at [PANGAEA](https://www.pangaea.de/). In addition, two complex atmosphere and ocean observing systems were deployed as part of N-ICE2915 expedition. Together with the data from those, published at [SEANOE](https://doi.org/10.17882/59624), this data base offers a complete collection of all buoy data obtained during N-ICE2015 expedition. ### Deployment During the [N-ICE2015 expedition](http://npolar.no/n-ice2015) 42 buoys were deployed in the sea ice covered area north of Svalbard. Buoys were deployed in two nested arrays, 5-100 km apart. [Winter deployments](https://api.npolar.no/dataset/6ed9a8ca-95b0-43be-bedf-8176bf56da80/_file/tracks_d1_updt.png) were done in January/February and [spring deployments](https://api.npolar.no/dataset/6ed9a8ca-95b0-43be-bedf-8176bf56da80/_file/tracks_d2_updt.png ) in April/May, on the first- and second-year ice that was characteristic for the region. The winter array was deployed during N-ICE2015 leg 1, during polar night with an assistance of an ice breaker, snow machines and man hauling on ski. The spring array was deployed on leg 3 from a helicopter and R/V Lance. Two buoys (SIMBA_2015d and SNOW_2015d) were deployed in March 2015 on leg 2 separately from all the rest. During most of the buoy deployments additional information on the sea ice situation including, snow depth and sea ice thickness was collected. Normally three holes were drilled and about 30 snow depth measurements (1 meter spacing) were taken along the sides of unilateral triangles with ~10 m long legs. In addition, a deployment photo was taken. All this information in available in the [deployment logs for winter](https://api.npolar.no/dataset/6ed9a8ca-95b0-43be-bedf-8176bf56da80/_file/deployment_conditions_winter.zip) and [deployment logs for spring](https://api.npolar.no/dataset/6ed9a8ca-95b0-43be-bedf-8176bf56da80/_file/deployment_conditions_spring.zip) . Most of the buoys were deployed on remote locations and never revisited. Those close to the ice camp were revisited. Some of the buoys were deployed in pairs or clusters. For both deployments the buoys were deployed over a large time span of approximately 1 month and individual buoys have a relatively short life time of up to 3 months. Some buoys stopped functioning before the deployment of the full array was completed. After ice floes disintegrated, the majority of the buoys sank into the ocean and stopped transmitting data. The drifters with a flotation support (SVPs) continued drifting with the ocean surface currents. The winter array drifted in a south and south-east direction with some of the buoys covering over 1000 km distance, while the spring array drifted south-westwards and covered a 700 km distance. Overview table of all buoy deployments as published by Itkin et al, 2017:   ### Buoy types The 42 buoys deployed at N-ICE2015 are: * 14 drifters (7 CALIB, 6 SVP and 1 ice beacon - IC) produced by MetOcean, Halifax, Canada * 5 snow buoys (SNOW) produced by MetOcean, Halifax, Canada * 7 sea ice mass balance buoys (SIMBA) produced by SRSL, Oban, Scotland, * 3 sea ice mass balance buoys (IMB-B) produced by Bruncin, Zagreb Croatia * 1 sea ice mass balance buoys (IMB) produced by MetOcean, Halifax, Canada * 3 radiation buoys (AFAR) produced by MetOcean, Halifax, Canada * 6 wave buoys (WAVE) produced by Bruncin, Zagreb, Croatia * 1 sea ice stress buoy (STRESS) produced by Cold Regions Research and Engineering Laboratory, Hanover, USA * 2 ridge IMB buoys (RIDGE) produced by Oceanic Measurement, Sydney, Canada * 1 seasonal sea ice mass balance buoy buoy (IMB-S) produced by Cold Regions Research and Engineering Laboratory, Hanover, USA. ###Ice-mass-balance (IMB) buoys IMB buoys were typically deployed on level ice portion of the ice floe. The SIMBA and IMB-B type buoys consist of a 5 m long thermistor chain hanging through the air-snow-ice-ocean. The chain was deployed hanging from a wooden tripod about one meter over the ice surface. The chain comprises solid state sensors that measure temperature with an accuracy of 0.1˚C at 2 cm vertical resolution. Temperature was recorded every six hours. In addition, the buoys had a heating mode that can be used as a proxy for thermal diffusivity. With the combination of the temperature and thermal diffusivity proxy one can identify the interfaces between ice-water, ice-snow, snow-air, and detect flooding of the snow. The temperature profiles used for the interface detection were quality controlled and erroneous data was removed and replaced by averages between neighbors. The interfaces were automatically determined using a method similar, but not identical, to Provost et al (2017) [Observations of flooding and snow ice formation in a thinner Arctic sea ice regime during the N-ICE2015 campaign: Influence of basal ice melt and storms](https://doi.org/10.1002/2016JC012011). The detection of air-snow and snow-ice interfaces was based on the thermal diffusivity proxy, while the ice-ocean interface is determined based on the temperature profile. All abrupt changes in the interface location were removed from the data and replaced by nearest neighbors. These were then smoothed with a 36-h running mean (Fig. 3 to 8). The IMB-B type buoys were deployed in the same way as the SIMBAs. In addition, they have a low resolution wide-angle camera, that takes pictures once a day (noon). The Python code used to derive the interfaces from the SIMBA data is available here: https://github.com/loniitkina/storm_syn Snow buoys measure the distance to the snow surface with four sonic sensors. At deployment, the initial snow depth was measured and afterwards used to calibrate the values measured by the buoy. IMB and IMB-S are instruments that combine the measuring principles of a sonic snow buoy and a thermistor IMB ([Polashenski et al., 2011](https://doi.org/10.3189/172756411795931516)). Additionally to the thermistor string (50 mm vertical resolution), it also has an underwater sonic sensor that provides the sea ice thickness measurements by measuring the distance from the sensor to the bottom ice surface. IMB-S has all sensors sheltered in a floating elongated tube that should potentially survive summer melt and fall freeze up processes. ### Figures  Figure 1:Drifts of the a) winter and b) spring deployments (Itkin et al, 2017). Many of the buoys were deployed in small clusters where several instruments (e.g. snow buoy, IMB buoy and sea ice stress buoy) were deployed together (check Tables 1 and 2 for more details). On this map only one buoy from each cluster is represented. The winter array drifted predominantly in the SE direction, while the spring array drifted in the SW direction. The tracks after the breaks are shaded in grey.  Figure 2: IMB data: both raw and processed data is available for download. Here a combined plot for snow depth (above) and sea ice thickness (bellow) from the IMB and snow buoys and snow stake fields and hot wires (Rösel et al, 2018). The purple shading in the background indicates storm events, The stars show major snow fall events. Note that before 2 February 2015 and between 18 March and 18 April 2015 no meteorological data are available.  Figure 3: SIMBA_2015a: temperature and thermal resistivity proxy through air-snow-ice-ocean. The derived interfaces are delineated by white lines. Initial interfaces are marked by dashed lines.  Figure 4: SIMBA_2015b: temperature and thermal resistivity proxy through air-snow-ice-ocean. The derived interfaces are delineated by white lines. Initial interfaces are marked by dashed lines.  Figure 5: SIMBA_2015d: temperature and thermal resistivity proxy through air-snow-ice-ocean. The derived interfaces are delineated by white lines.Initial interfaces are marked by dashed lines.  Figure 6: SIMBA_2015e: temperature and thermal resistivity proxy through air-snow-ice-ocean. The derived interfaces are delineated by white lines. Initial interfaces are marked by dashed lines.  Figure 7: SIMBA_2015f: temperature and thermal resistivity proxy through air-snow-ice-ocean. The derived interfaces are delineated by white lines. Initial interfaces are marked by dashed lines.  ###Literature Itkin et al (2017) [Thin ice and storms: a case study of sea ice deformation from buoy arrays deployed during N-ICE2015](https://doi.org/10.1002/2016JC012403) Provost et al (2017) [Observations of flooding and snow-ice formation in a thinner Arctic sea ice regime during the N-ICE2015 campaign: Influence of basal ice melt and storms](https://doi.org/10.1002/2016JC012011) Rösel et al (2018) [Thin Sea Ice, Thick Snow, and Widespread Negative Freeboard Observed During N-ICE2015 North of Svalbard](https://doi.org/10.1002/2017JC012865) Shestov et al (2018) [Decay phase thermodynamics of ice ridges in the Arctic Ocean](https://doi.org/10.1016/j.coldregions.2018.04.005). Polashenski et al., (2011) [Seasonal ice mass-balance buoys: adapting tools to the changing Arctic](https://doi.org/10.3189/172756411795931516)

# Sea Ice Frequency Dataset Sea Ice Frequency charts display the percentage of ice-covered days of a given month over the last 30 years. These charts, available as GeoTIFF raster data, are derived from daily sea ice concentration data provided by the National Snow and Ice Data Center (NSIDC), USA. Ice frequency is defined as the frequency of occurence of sea ice concentration values equal or higher than 0.15. A value of 100% indicates areas where every single day of a given month sea ice concentrations were equal or higher than 0.15, while a value of 0% indicates areas where such sea ice concentrations have never been observed. A value of 0.5% indicates that sea ice concentrations were equal or higher than 0.15 during approximately 5 days within 30 years period for that particular month. In addition to the raster files in GeoTIFF format vector polygon files, called isobands, are provided in ESRI Shapefile format. As polygons they represent the area, unlike the contour lines which represent the interval boundaries. To reduce the noise and improve the visual representation of the data we set the lower and upper threshold to 0.5% and 99.5% respectively. Please refer to the raster files for exact pixel values. ## Reserved values Several mask values are reserved in the raster dataset: * -1 - Missing data * -2 - Landmask * -3 - Coastal areas ## Coordinate reference system and extent The dataset comes in the same geographic projection as the source NSIDC dataset: EPSG 3411 or "NSIDC Polar Stereographic North". Please refer to https://nsidc.org/data/polar-stereo/ps_grids.html for the complete grid definition. ## References * Meier, W., F. Fetterer, M. Savoie, S. Mallory, R. Duerr, and J. Stroeve. 2017. NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 3. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/N59P2ZTG. [2017-07-04]. * Peng, G., W. Meier, D. Scott, and M. Savoie. 2013. A long-term and reproducible passive microwave sea ice concentration data record for climate studies and monitoring, Earth Syst. Sci. Data. 5. 311-318. https://doi.org/10.5194/essd-5-311-2013 # Changelog ## 2018-08-23 * Lower and upper boundaries in vector data set to 0.5% and 99.5% respectively * Minimum and maximum extent shapefiles are not included anymore since the information is already provided in the isoband files * Attribute name for ice frequency values in shapefile attribute table is changed from "value" to "ice_freq" ## 2018-07-02 This dataset update includes a major change where the new type of source data is used: (Sea Ice Concentration Climate Data Record, G02202-v3)[http://nsidc.org/data/G02202/versions/3]. Major changes: * Transition to NSIDC G02202-v3 Sea Ice Concentration Climate Data Record dataset. * Filling polar pole: we assume that the polar hole areas always contain sea ice concentrations above 15%. Therefore we set the values to 100% * In contrast with the previous processing scheme we do not fill the missing days with the values from the preceding day in 1987. However the weight of each observation is maintained and the final occurence frequency values are not affected.

Hydrographic and current time series data from outside the southern side of the Isfjorden Mouth during 19 August 2016 to 2 October 2017 at 78°03.667’ N; 013°31.492’ E, and 205 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor inflow of Atlantic Water to Isfjorden, and was equipped with one Aanderaa Instruments recording Doppler current profiler (RDCP) and two Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper, the intermediate, and the bottom layer. Additionally, three SBE 37 MicroCAT CTDs and five VEMCO mini temperature loggers were evenly distributed over the water column. For further details of the mooring and data, see Skogseth et al. (2019).

Hydrographic and current time series data from outside the northern side of the Isfjorden Mouth during 15 October 2016 to 2 October 2017 at 78°10.927’ N; 013°23.000’ E, and 224 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor outflow from Isfjorden and the hydrographic differences between the northern and southern part of the mouth. It was equipped with three Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper, the intermediate, and the bottom layer. Additionally, two SBE 37 MicroCAT CTDs were evenly distributed over the water column. For further details of the mooring and data, see Skogseth et al. (2019).