Three Trident Sensors Helix beacons (Unit 1,2,3) were deployed about on ice floes close to latitude 62.8 S and longitude 29.8 E on 4th July 2017 to measure sea ice drift. The region where the instruments were deployed (Antarctic Marginal Ice Zone) consisted of first-year ice on average ~50 cm thick. The instruments were deployed by hand by three people, lowered by crane from the ship to the ice on a basket cradle on floes ~5 m in diameter. The temporal resolution is 4 hours. The survival of the sensors depended on staying fixed to the floe and the battery life. Unit 1 provided GPS location from the 5th July 2017 to 1st December 2017, started at 62.84 S and 30.20 E and finished at 61.55 S and 55.99 E. Unit 2 provided GPS location from the 5th July 2017 to 3rd August 2017, started at 62.83 S and 30.20 E and finished at 62.36 S and 31.57 E. Unit 3 provided GPS location from the 5th July 2017 to 15st August December 2017, started at 62.59 S and 29.98 E and finished at 61.16 S and 35.60 E. In the .xlsx submission sheet 1 refers to Unit 1, sheet 2 to Unit 2, and sheet 3 to Unit 3. First column is the Unit Identifier (1,2,3) Second column is the date in the format day/month/year Third column is the UTC time in the format hh:mm:ss Fourth column is the latitude in degrees and decimals, the negative refers to South Fifth column is the longitude in degrees and decimals, the positive refers to East

Two Waves In Ice Observation Systems (Kohout, Alison L., Bill Penrose, Scott Penrose, and Michael J M Williams. 2015. “A Device for Measuring Wave-Induced Motion of Ice Floes in the Antarctic Marginal Ice Zone.” Annals of Glaciology 56 (69): 415–24. doi:10.3189/2015AoG69A600) were deployed about 1.5 km apart on ice floes close to latitude 62.8 S and longitude 29.8 E on 4th July 2017 (NYU1 and NYU2). The region where the instruments were deployed (Antarctic Marginal Ice Zone) consisted of first-year ice on average 40 – 60 cm thick. The instruments were deployed by hand by three people, lowered by crane from the ship to the ice on a basket cradle. NYU 1 was deployed on a rectangular ice floe of length 8 m and width 3 m, with a thickness of about 40 – 50 cm. NYU 2 was deployed on a triangular ice floe of length 4 m and thickness 40 cm. The temporal resolution is variability (every 15 minutes to 2 hourly). The survival of the sensors depended on staying fixed to the floe and the battery life. On 12th July, the sampling rate of NYU 2 was reduced from 15 minutes to 2 hourly to extend the battery life. On 13th July, NYU 1 overheated and the battery dropped below the operating voltage. NYU 2 continued to send back data for another six days, but then stopped sending data for an unknown reason on 19th July. Records can support 1. the assessment of metocean conditions in the Southern Oceans; and 2. calibration and validation of wave and global circulation models.

Sea-ice cores (0.09 m internal diameter) were sampled during Polarstern voyage PS117 to the Weddell Sea during December 2018 to January 2019. Ice core measurements include position, snow thickness, ice thickness, ice core temperature and bulk-salinity profiles, macro-nutrient concentrations as well as Chlorophyll-a pigment content. In addition on each ice station downwelling (surface) and under-ice irradiances were measured with a hyperspectral radiometer.

Although the floating sea ice surrounding the Antarctic damps ocean waves, they may still be detected hundreds of kilometres from the ice edge. Over this distance the waves leave an imprint of broken ice, which is susceptible to winds, currents, and lateral melting. The important omission of wave-ice interactions in ice/ocean models is now being addressed, which has prompted campaigns for experimental data. These exciting developments must be matched by innovative modelling techniques to create a true representation of the phenomenon that will enhance forecasting capabilities. This metadata record details laboratory wave basin experiments that were conducted to determine: (i) the wave induced motion of an isolated wooden floe; (ii) the proportion of wave energy transmitted by an array of 40 floes; and (iii) the proportion of wave energy transmitted by an array of 80 floes. Monochromatic incident waves were used, with different wave periods and wave amplitudes. The dataset provides: (i) response amplitude operators for the rigid-body motions of the isolated floe; and (ii) transmission coefficients for the multiple-floe arrays, extracted from raw experimental data using spectral methods. The dataset also contains codes required to produce theoretical predictions for comparison with the experimental data. The models are based on linear potential flow theory. These data models were developed to be applicable to Southern Ocean conditions.

These data were collected to provide a spatial context for activities on SIPEX-2. Please see the document 'SIPEX II ice floe surveying report' for more detail. Files generated and stored in this dataset will be familiar to users of Trimble and Leica GPS equipment, and the UNAVCO 'teqc' utility. Please refer to the relevant documentation from Leica, Trimble and UNAVCO. Total station data is extracted to comma separated point lists with either .csv of .asc extensions. The point code list is named 'totalstation.codelist.txt'. It also forms an appendix of the surveying report.

Raw GPS and ship motion data collected during the Antarctic Circumnavigation Expedition 2016/2017. Waves in the Southern Ocean are the biggest on the planet. They exert extreme stresses on the coastline of the Sub-Antarctic Islands, which affects coastal morphology and the delicate natural environment that the coastline offers. In Antarctic waters, the sea ice cover reflects a large proportion of the wave energy, creating a complicated sea state close to the ice edge. The remaining proportion of the wave energy penetrates deep into the ice-covered ocean and breaks the ice into relatively small floes. Then, the waves herd the floes and cause them to collide and raft. There is a lack of field data in the Sub-Antarctic and Antarctic Oceans. Thus, wave models are not well calibrated and perform poorly in these regions. Uncertainties relate to the difficulties to model the strong interactions between waves and currents (the Antarctic Circumpolar and tidal currents) and between waves and ice (reflected waves modify the incident field and ice floes affect transmission into the ice-covered ocean). Drawbacks in wave modelling undermine our understanding and ability to protect this delicate ocean and coastal environment. By installing a Wave and Surface Current Monitoring System (WaMoS II, a marine X-Band radar) on the research vessel Akademic Thresnikov and using the meteo-station and GPS on-board, this project has produced a large database of winds, waves and surface currents. Dara were collected during the Antarctic Circmumnavigaion Expedition, which took place from Dec. 2016 to Mar. 2017. The instrumentation operated in any weather and visibility conditions, and at night, monitoring the ocean continuously over the entire Circumnavigation. Records can support 1. the assessment of metocean conditions in the Southern Oceans; and 2. calibration and validation of wave and global circulation models. Data - AAS_4434_ACE_GPS contains basic metereological conditions acquired form the ship’s meteo-station, gepgraphical coordinates (latitude, longitude and altitude) from the ship’s GPS and ship motion data from the ship’s Inertial Measurement Unit (IMU). These data are stored as time series with a sampling frequency of 1Hz.

This dataset contains in situ measurements of ice thickness, snow thickness, and freeboard along transects on the ice-station floes from the SIPEX2012. Ice cores were collected and snow pits were measured at the 0m, 50m and 100m mark along each transect, where possible. Ice temperature measurements are taken in the field as soon as the ice core sections have been recovered from the core hole. Additionally, ice cores were taken for density analysis at a few of the ice-core sites for independent verification of ice density. In addition, electromagnetic [EM] induction measurements of total ice and snow thickness were conducted along the transect where possible. Ice core were transferred -20oC freezer for thin-section analysis for sea-ice stratigraphy and crystallography. The cores are then cut up into suitable short sections, generally about 5cm long, to be melted for analysis of salinity and stable oxygen isotopes. The latter will occur after the end of this cruise. There is a data file for each ice station, containing a spreadsheet with the data. The spreadsheet contains information about how to interpret the data. Also included are the scanned field notes containing the hand-written (raw) data collected in the field. Among many, many volunteers, whose help is gratefully acknowledged here, the following persons were involved in data collection along the transect: Mr Olivier Lecomte, Univ Catholique, Louvain-la-Neuve, Belgium, Member of observation team, olivier.lecomte@uclouvain.be Dr T. Toyota, Inst Low Temp Science, Japan, Member of observation team, toyota@lowtem.hokudai.ac.jp Dr A. Giles, ACE CRC, Member of observation team, barry.giles@utas.edu.au Dr T. Tamura, NIPR, Japan, Member of EM observation team; tamura.takeshi@nipr.ac.jp Mr K. Nakata, EES, Japan, Member of EM observation team; kazuki-nakata@ees.hokudai.ac.jp Data were collected on the following dates: Ice Station 2: 27 - 28 September 2012 Ice Station 3: 03 - 04 October 2012 Ice Station 4: 06 - 08 October 2012 Ice Station 6: 13 - 14 October 2012 Ice Station 7: 19 - 23 October 2012 Ice Station 8: 29 October - 04 November 2012

WAMOS (marine radar) data collected during the Antarctic Circumnavigation Expedition (ACE, https://spi-ace-expedition.ch/), from December 2016 to March 2017. Waves in the Southern Ocean are the biggest on the planet. They exert extreme stresses on the coastline of the Sub-Antarctic Islands, which affects coastal morphology and the delicate natural environment that the coastline offers. In Antarctic waters, the sea ice cover reflects a large proportion of the wave energy, creating a complicated sea state close to the ice edge. The remaining proportion of the wave energy penetrates deep into the ice-covered ocean and breaks the ice into relatively small floes. Then, the waves herd the floes and cause them to collide and raft. There is a lack of field data in the Sub-Antarctic and Antarctic Oceans. Thus, wave models are not well calibrated and perform poorly in these regions. Uncertainties relate to the difficulties to model the strong interactions between waves and currents (the Antarctic Circumpolar and tidal currents) and between waves and ice (reflected waves modify the incident field and ice floes affect transmission into the ice-covered ocean). Drawbacks in wave modelling undermine our understanding and ability to protect this delicate ocean and coastal environment. By installing a Wave and Surface Current Monitoring System (WaMoS II, a marine X-Band radar) on the research vessel Akademic Thresnikov and using the meteo-station and GPS on-board, this project has produced a large database of winds, waves and surface currents. Dara were collected during the Antarctic Circmumnavigaion Expedition, which took place from Dec. 2016 to Mar. 2017. The instrumentation operated in any weather and visibility conditions, and at night, monitoring the ocean continuously over the entire Circumnavigation. Records can support 1. the assessment of metocean conditions in the Southern Oceans; and 2. calibration and validation of wave and global circulation models. Data - AAS_4434_ACE_WAMOS contains sea state conditions monitored continuously with a Wave and Surface Current Monitoring System (WaMoS II), a wave devise based on the marine X-Band radar (see Hessner, K. G., Nieto-Borge, J. C., and Bell, P. S., 2007, Nautical Radar Measurements in Europe: Applications of WaMoS II as a Sensor for Sea State, Current and Bathymetry. In V. Barale, and M. Gade, Sensing of the European Seas, pp. 435-446, Springer). Sea state consists of the directional wave energy spectrum, angular frequency and direction of propagation. Basic parameters such as the significant wave height (a representative measure of the average wave height), the dominant period, wavelength, mean wave direction, etc… were inferred from the wave spectrum. Surface current speed and the concurrent direction were also detected. Post processed data are available anytime the X-Band radar was operated in a range of 1.5NM; a full spectrum was generally obtained evert 20 minutes. Data are subdivided in: - WaMoS II frequency spectrum (1-D spectra) - WaMoS II wave number spectrum (2-D spectra) - WaMoS II frequency direction spectrum (2-D spectra) Data are quality controlled. ************************************************************************************************************** File informations Path to the spectra: \RESULTS\YYYY\MM\DD\HH\ : Year, month, day, hour. space\ : spatial mean results. single\ : raw spectra. mean\ : time averaged files. Header of the spectra: Additional information that might be needed for data analysis is stored in the headers. The output results generated using different WaMoS II software modules are separated by comment lines starting with ‘CC’. All headers are subdivided into: 1) Polar Header: including data acquisition parameters. 2) Car Header: including Cartesian transformation parameters. 3) Wave-Current Analysis Header: including wave and current analysis related parameters. There is a keyword of maximum 5 characters in each line of the header followed by some values and a comment, after the comment marker ‘CC’, describing the keyword. Values of missing parameters are set to -9, -9.0, -99.0, etc. depending on the data type. The 'end of header' keyword 'EOH', indicated the last line of the header section. ******************************************************************* WaMoS II frequency spectrum (1-D spectra): File Name: YYYY : Year. MM : Month. DD : Day. HH : Hour. MM : Minute. SS : Second. rigID : WaMoS II platform’s ID code (3 letters) Suffix: ’*.D1S’ : spatial mean of the spectra (that pass the WaMoS II internal quality control) averaged over WaMoS II analysis areas (up to 9) placed within the radar field of view. ‘*.D1M’ : temporal average spectra calculated using all spectra collected during the past dt=30 minutes of the time specified in the file. Time reference: CPU clock. Data Content: Frequency (f - Hz). Spectral energy (S(f) - m*m/Hz). Mean Wave Direction (MDIR(f) - deg), ���coming from’. Directional Spreading (SPR(f) - deg/Hz). ******************************************************************* WaMoS II wave number spectrum (2-D spectra): File Name: YYYY : Year. MM : Month. DD : Day. HH : Hour. MM : Minute. SS : Second. rigID : WaMoS II platform’s ID code (3 letters) Suffix: ’*.D2S’ : spatial mean of the spectra (that pass the WaMoS II internal quality control) averaged over WaMoS II analysis areas (up to 9) placed within the radar field of view. ‘*.D2M’ : temporal average spectra calculated using all spectra collected during the past dt=30 minutes of the time specified in the file. Time reference: CPU clock. Data Content: Spectral energy (S(kx,ky) - m*m/(Hz*rad)) as a function of wave number (kx and ky - rad/m). Data related header information MATRIX: Size of Matrix. DKX: Spectral resolution in Kx direction (2*Pi/m). DKY: Spectral resolution in Ky direction (2*Pi/m). ******************************************************************* WaMoS II frequency direction spectrum (2-D spectra): File Name: YYYY : Year. MM : Month. DD : Day. HH : Hour. MM : Minute. SS : Second. rigID : WaMoS II platform’s ID code (3 letters) Suffix: ‘*.FTH’ : spatial mean of the spectra (that pass the WaMoS II internal quality control) averaged over WaMoS II analysis areas (up to 9) placed within the radar field of view. ’*.FTM’ : temporal average spectra calculated using all spectra collected during the past dt=30 minutes of the time specified in the file. Time reference: CPU clock. Data Content: Spectral energy (S(f,θ) - m*m/(Hz*rad)) as a function of frequency (f – Hz) and direction (θ - deg). Data information Mf : number of frequency sampling points. Mth : number of direction sampling points. Data Matrix: Row 1 frequency sampling points, Column 1 direction sampling points. The dataset download also includes a file, "Available_Measurements", which is a general calendar that provides the list (day and time) of available measurements.

These data were collected on the SIPEX II voyage of the Aurora Australis in 2012. These data are floe-scale maps of Antarctic sea ice draft (m). These were collected using a multibeam instrument attached to an autonomous underwater vehicle (AUV). This AUV was the WHOI 'SeaBED-class' vehicle named 'Jaguar'. Details on the deployment and processing of this data can be found in Williams, Maksym and Wilkinson et al., 2014 (Nature Geoscience). Data are provided for SIPEX-II stations 3, 4 and 6. Station 3: October 3 2012, located at 121.03E 64.95S Station 4: October 9 2012, located at 120.87E 65.13S Station 6: October 12 2012, located at 120.02E 65.25S Data are provided on grids with 50cm horizontal spatial resolution. For each station, the mean and variance of the sea ice draft, along with the number of observations in each grid cell, are provided. Data are provided in ESRI ASCII grid format and comma-separated (CSV) text files. CSV files do not include grid cells with no observations.

This dataset contains observations of ice conditions taken from the bridge of the RV Aurora Australis during SIPEX 2012, following the Scientific Committee on Antarctic Research/CliC Antarctic Sea Ice Processes and Climate [ASPeCt] protocols. See aspect.antarctica.gov.au Observations include total and partial concentration, ice type, thickness, floe size, topography, and snow cover in each of three primary ice categories; open water characteristics, and weather summary. The dataset is comprised of the scanned pages of a single logbook, which holds hourly observations taken by observers while the ship was moving through sea-ice zone. The following persons assisted in the collection of these data: Dr R. Massom, AAD, Member of observation team Mr A. Steer, AAD, Member of observation team Prof S. Warren, UW(Seattle), USA, Member of observation team Dr J. Hutchings, IARC, UAF, USA, Member of observation team Dr T. Toyota, Inst Low Temp Science, Japan, Member of observation team Dr T. Tamura, NIPR, Japan, Member of EM observation team Dr G. Dieckmann, AWI, Germany, Member of observation team Dr E. Maksym, WHOI, USA, Member of observation team Mr R. Stevens, IMAS, Trainee on observation team Dr J. Melbourne-Thomas, ACE CRC, Trainee on observation team Dr A. Giles, ACE CRC, Trainee on observation team Ms M. Zhia, IMAS, Trainee on observation team Ms J. Jansens, IMAS, Trainee on observation team Mr R. Humphries, Univ Wollengong, Trainee on observation team Mr C. Sampson, Univ Utah, USA, Trainee on observation team Mr Olivier Lecomte, Univ Catholique, Louvain-la-Neuve, Belgium, Trainee on observation team Mr D. Lubbers, Univ Utah, USA, Trainee on observation team Ms M. Zatko, UW(Seattle), USA, Trainee on observation team Ms C. Gionfriddo, Uni Melbourne, Trainee on observation team Mr K. Nakata, EES, Japan, Trainee on observation team