This dataset contains data relating to an experimental method in which sea-ice samples were measured in an S-band microwave waveguide. This was conducted as a part of the 2012 SIPEX 2 (Sea Ice Physics and Ecosystems EXperiment) marine science voyage. A specially designed waveguide apparatus was connected to an Agilent FieldFox Portable Network Analyzer. Small parallelopipeds (7 cm X 3 cm X 1.9 cm) of sea ice were cut with a hand saw in a specially designed jig which holds an initially cylindrical core. The samples were placed at the end of the waveguide, configured to measure the vertical component of the effective complex permittivity tensor, and microwaves of frequency 2.9 GHz were sent down the tube. The samples were sized precisely to fit snugly in the end of the waveguide in order to minimize spurious reflections. The FieldFox recorded the coefficients of the scattering matrix, from which the complex permittivity can be computed. Sample temperature was taken both before and immediately after insertion into the waveguide. In order to assess the presence of off-vertical components of the electromagnetic field and how they may affect the measurements, a second sample was prepared with an orthogonal orientation, adjacent to the first sample. The same microwave measurements were taken on the second sample, to be later correlated with those from the first sample. The samples were stored in the freezer for later crystallographic analysis, and subsequently melted for salinity measurements. Prior to melting the samples were measured using callipers to determine their dimensions precisely. Samples were measured along each face at their minimum and maximum point for their width in the direction of propagation. In most cases samples were measured in all dimensions for better error analysis. A thin vertical section, approximately 5mm thick, was taken from each microwave sample stored for analysis. These sections were placed between a pair of cross polarized plates and photographed. Photos of the crystallography cores can be found in the crystallography folder, in a sub folder titled microwave. Each photo also contains a tag indicating the core number, site taken, date, as well as a V or an H indicating whether the sample was used for measurement of the vertical (V) or off-vertical (H) response. The scattering parameters recorded by the Field Fox can be found in the Data folder. Each file is named according to the microwave core measurement it represents and whether the measurement was of the vertical (V) or off-vertical (H) response. Each contains a standard S11 scattering parameter, stored as a comma separated value (CSV) file. Raw data can be found in the raw folder, and data that has been processed for ease of Matlab import can be found in the Reformatted_for_matlab folder. This processing involves taking output data that by default has four entries in a single column vector and remapping the data to create a four column matrix, each with a single entry. Recorded values for each microwave sample can be found in the Master_Core_List.xls Excel spreadsheet, within the Microwave worksheet. This worksheet was generated directly from notebook data, and contains the date, core number, depth of interface between the two collected samples, the minimum, maximum, and average thickness along the axis of propagation, The recorded temperatures from before and after measurement, the salinity, and calculated brine volume fraction. Finally, the worksheet contains notes, and a column to indicate whether we believe this data is somehow bad. Measurement information for thicknesses along other axis than that of propagation can be found in notes, but this data may at some stage be incorporated into a separate column. Please see the notes section for reasons why a data point was determined invalid. Typically this was due to the corresponding sample breaking while cutting into the parallelepiped shape. Scans of the original notebooks containing measured salinity values, thicknesses, and temperatures from which the Permeability worksheet were created are provided in the notebooks directory.

This data set provides the organochlorine content found in four sea-ice samples collected in the vicinity of Davis station over a three week period in 2014/15. Sea-ice is thought to serve as a reservoir for organochlorine pesticides during the winter. The aim of the study was to investigate the movement of organochlorine pesticides in the seasonal sea-ice during ice melt. A custom made, closed-system, ice melting unit, coupled to an in-situ water filter, was implemented for sampling. Minimal ice-melt or change in organchlorine content was found over the three week period. Changes were attributed to high ventilation of the sea-ice surface caused by high wind speeds found in the Antarctic compared to the Arctic. 4 sea-ice samples were collected in the vicinity of Davis station and contaminant profiles extracted and analysed. Caution should be taken in interpretation of data as the ice/water extraction unit failed during operation.

The ASPeCt - Bio dataset is a compilation of currently available sea ice chlorophyll a (chl-a) data from pack ice (i.e., excluding fast ice) cores collected during 32 cruises to the Southern Ocean sea ice zone from 1983 to 2008 (Table S1). Data come from peer-reviewed publications, cruise reports, data repositories and direct contributions by field-research teams. During all cruises the chl-a concentration (in micrograms per litre) was measured from melted ice core sections, using standard procedures, e.g., by melting the ice at less than 5 degrees C in the dark; filtering samples onto glassfibre filters; and fluorometric analysis according to standard protocols [Holm-Hansen et al., 1965; Evans et al., 1987]. Ice samples were melted either directly or in filtered sea water, which does not yield significant differences in chl-a concentration [Dieckmann et al., 1998]. The dataset consists of 1300 geo-referenced ice cores, consisting of 8247 individual ice core sections, and including 990 vertical profiles with a minimum of three sections. An updated dataset was provided in 2017-12-15, which included a compilation Net CDF file.

Metadata record for data from ASAC Project 2500 See the link below for public details on this project. Public Weekly fast-ice and snow thicknesses from an ongoing long-term time-series together with meteorological data will be used to analyse ice-atmosphere interactions. Interannual changes will be related to climate effects. Various sites at each location will be sampled to resolve the influence of oceanic forcing on the fast-ice growth. Project objectives: Landfast sea ice (fast ice) forms on the near-coastal ocean off each of the three Australian Antarctic stations each autumn. At Mawson and Davis stations this ice cover is generally stable, increasing in thickness throughout the winter to reach its maximum thickness in October or November before decaying and eventually breaking out in late spring or summer [Heil and Allison, 2002a]. At Casey, the third Australian station, the fast-ice cover is very unstable and not suitable for the study proposed here. The fast ice at the proposed measuring sites is stationary all through the austral winter. There is no contribution due to mechanical processes (rafting or ridging) on the thickness evolution of the fast ice at the measuring sites [Heil, 2001]. Its growth and decay, and the annual maximum thickness depend primarily on thermodynamic processes [Heil et al., 1996], which are forced by energy and moisture exchanges at the atmosphere-ice interface, the thickness of the snow cover, and the thermal energy supplied to the underside of the ice from the ocean. Starting in the mid 1950s measurements of the fast-ice thickness and snow cover are available for individual years at Mawson and Davis stations. After quality control the combined record for Mawson includes data from 27 seasons; the Davis record includes 20 seasons [Heil and Allison, 2002a]. However, significant gaps exist in these historic records. The scientific value of a continuous record of fast-ice thickness as a climatic indicator has been recognised and as a consequence the fast-ice and snow measurements at Davis and Mawson have been accepted into the State of the Environment (SOE) reporting scheme by the Australian Antarctic Division. Data from ANARE fast-ice measurements have been included in scientific research (e.g., Mellor [1960], Allison [1981], Heil et al. [1996], or Heil and Allison [2002a]). For example, Heil et al. [1996] designed an inverse 1-dimensional thermodynamic sea-ice model and used historic fast-ice data from Mawson together with meteorological observations to derive the seasonal and interannual variability of the oceanic heat flux at the underside of the fast ice. They showed that the interannual variability identified from the fast-ice data was in agreement with changes in the water-mass properties observed upstream of the fast-ice site. Using the historic data together with data from ongoing measurements this project aims to quantify the local-scale interactions between atmosphere and fast ice, to derive the relative impact of oceanic forcing on the fast-ice evolution, to estimate the small-scale spatial variability of the fast-ice growth, and to explore the connection between fast-ice changes and climate change. In particular we aim: - to extend previous analysis from records of fast-ice observations for Mawson and Davis stations; - to exactly determine the growth-melt cycle of East Antarctic fast ice and its modifications due to changing environmental conditions; - to derive the statistical variability of the fast-ice evolution relative to atmospheric and oceanic forcing; - to evaluate the suitability of fast ice as indicator of changes in the Antarctic environment; - to determine the spatial coherence of fast-ice properties. Contribution of this research to achieving the relevant milestones contained in the Strategic Plan: - Contributions to Key Scientific Output 3: This research aims to derive an assessment of the links between fast-ice variability and Southern Hemisphere environmental conditions from in-situ observations. The annual maximum ice thickness, and the date at which this maximum thickness is reached, reflect the integrated conditions of the local atmospheric and oceanic parameters [Heil, in prep.]. The fast-ice measurements together with concurrent meteorological (and oceanic) observations will allow us to study the direct links of variability in the sea-ice thermodynamics to changes in the Southern Hemisphere atmospheric conditions ("weather" in KSO 3.1). This knowledge will aid our understanding of the interannual and long-term variability of the drifting sea ice, as it will allow us to separate thermodynamic effects from dynamic effects [Heil et al., 1998]. Research outcomes from this study will aid the parameterisation of thermodynamic sea-ice processes in coupled climate models, and will provide an outlook towards statistical parameterisation of fast-ice characteristics within numerical models. - Contributions to Key Scientific Output 4: Using historic data and ongoing measurements this project seeks to build an accurate and ongoing record of measurements of fast-ice and snow properties for the monitoring and detection of change in Antarctic and Southern Ocean climate. Changes identified in the fast-ice thickness or in the occurrence of the annual maximum ice thickness are due to changes in either oceanic or atmospheric heat and/or moisture transfer. Using fast-ice measurements from locations around the Antarctic continent in combination with large-scale atmospheric (and oceanic) data the external impact on the sea ice can be extrapolated. Historic climatologies of interannual variability will be updated and extended. These climatologies will be available to expedition operations, scientific research, etc. Assessment basis: * Completion of field work/primary scientific activity: The requirements of data collection for this project are in line with indicator No. 43 "Fast ice thickness at Davis and Mawson" of the State of the Environment (SOE) reporting scheme. Weekly measurements of fast-ice and snow thicknesses are required for the SOE scheme as well as for this project. Additional data on the freeboard of the ice are easily and quickly obtained during the standard measurements [Heil and Allison, 2002b]. It is worthwhile to emphasise the requirement of a long-term commitment for the field measurements in order to obtain meaningful and statistically significant records of fast-ice observations. * Completion of analysis: The evaluation of individual growth-decay seasons will be undertaken once all fast-ice data as well as all required auxiliary data (mainly meteorological measurements) are available to the CI. Where available, opportunistic oceanographic data will be acquired as part of related research projects. Analysis to assess the interaction between fast ice, atmosphere and ocean will be carried out for each growth-decay season. This will include numerical modelling of the thermodynamic processes in fast-ice growth and decay. For years, when measurements of all external forcing fields (oceanic and atmospheric) have been collected, the parameterisations of the thermodynamic model can be evaluated by comparing the model results with the observed fast-ice thickness and growth rates. Following Heil et al. [1996] the thermodynamic model can be reconfigured for use in the inverse mode, using atmospheric and fast-ice data to calculate the oceanic heat flux at the underside of the ice. Long-term records of changes in the oceanic heat flux are not available and this inverse method (driven with data derived from meteorological and fast-ice measurements) will be able to contribute to our understanding of coastal oceanography by using several measuring sites within a small area. Analysis of the interannual variability of the fast ice and its response to changing environmental conditions will be carried out on the long-term data record. The data will be analysed for long-term signals, and will be evaluated for their statistical significance. * Publication of results: Scientific findings will be written up and submitted for publication as they arise. Publications in high-impact international journals are expected about every 2 years.

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.

During voyage 1 of 1985, sixteen ice cores were drilled from sea ice. Details from those cores include the position they were drilled, length of the core, percentage of the core that was frazil ice, and comments on the state of the core, or observations of the ice make-up. Physical records are archived at the Australian Antarctic Division.

Environmental descriptors that are available for the study area (-180 degrees W/+180 degrees E; -45 degrees/-78 degrees S) and for the following periods: 1955-1964, 1965-1974, 1975-1984, 1985-1994, 1995-2012. They were compiled from different sources and transformed to the same grid resolution of 0.1 degree pixel. We also provide future projections for environmental descriptors established based on the Bio-Orable database (Tyberghein et al. 2012). They come from IPCC scenarii (B1, AIB, A2) for years 2100 and 2200 (IPCC, 4th report).

Described fully in (https://doi.org/10.21203/rs.3.rs-636839/v1 holder). Data The main CEL method, and a subsidiary Coastal Exposure Index or CEI (both described below), are based on daily sea-ice concentration products for the period 1979 through 2020. These products are derived from the multi-satellite passive-microwave brightness temperature time series using the NASA Team algorithm, mapped at 25 km x 25 km resolution and obtained from the NASA National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC). Both algorithms are designed to be adaptable for different resolution data. Complete coverage of the entire Antarctic coastal and sea-ice zones is obtained on a daily basis, except for 1979-July 1987 (once every two days). Missing single days during this period are interpolated from the adjoining day's sea-ice concentration values. Averages and climatologies are based on the period 1979-2020, unless otherwise stated. The continental land mask used (gsfc_25s.msk) is also obtained from NSIDC, and includes ice shelves (the seaward extremities of which are taken here to be coastline). Coastline grid points are defined from the continental land mask as any ocean grid point that has land/ice sheet adjacent to it. Analysis methods For this study, we developed two new but different algorithms for quantifying and monitoring Antarctic coastal exposure: the Coastal Exposure Index (CEI) and Coastal Exposure Length (CEL) method. The CEI technique is based on the detection of sea ice presence/absence radially out (northwards) from the coastline along each meridian (at one degree longitudinal spacing), following masking of the ice sheet. The CEI is simply defined as the number of longitudes with no sea ice (threshold set to less than 15% following convention) to the north of the continent, and hence runs from zero to 360. This methodology is trivial and code for this is not included. CEL is defined as the length (in kms) of the Antarctic coastal perimeter with no adjacent sea ice anywhere offshore (i.e. total exposure of the coast to the open Southern Ocean with no intervening sea ice), but excluding coastal polynyas. By this method, we use the land mask to determine if each coastal grid point has an immediately-adjacent ocean grid point that is ice-free (i.e. has a sea-ice concentration of less than 15%). If this criterion is met, then a nearest (adjoining) neighbour-testing technique is used to determine whether that ocean grid point is exposed in some way to the wider open ocean or is bound by neighbouring sea ice offshore. If any of the neighbouring grid points are classified as “exposed”, or if the total area of neighbouring ice-free grid points exceeds an arbitrary cut-off of 500,000 km2, then that coastal grid point is classified as “exposed”. Otherwise, the grid point and all sea-ice-free neighbouring grid points are deemed to be bounded by sea ice and are classified as a coastal polynya. The length of individual exposed coastal grid points is estimated by taking the square root of the respective pixel area. The length of coastal exposure, either regionally or net circum-Antarctic, is then simply the sum of the length of exposed coastal grid points. The IDL code used for calculating CEL is included here.

Antarctic sea-ice is highly influenced by the dynamic nature of the Southern Ocean. Ocean waves can propagate from tens to hundreds of kilometres into sea-ice, leaving behind a wake of broken ice sheets. As global climate change intensifies, storm intensity will increase in the Southern Ocean. Increased storm intensity will bring stronger winds and bigger waves, which has the potential for waves to travel deeper into the ice pack and increase the likelihood that ice floes break apart. To enhance our understanding of this system, our aim during SIPEXII was to improve on the scarce Antarctic waves-in-ice dataset by collecting a set of wave observations in the MIZ. In order to achieve this, we designed and produced eight custom made wave sensors. The sensors were deployed in the Antarctic marginal ice zone along a transect line perpendicular to the ice edge and spread over approximately 200 km. Every three hours, the sensors simultaneously woke and recorded their location and a burst of wave acceleration data. Each sensor performed on-board data quality control and spectral analysis before returning the wave spectrum via satellite. The sensors were powered via lithium batteries and had enough battery power to last a minimum of 6 weeks. This project involved collaboration between the Australian Antarctic Division (AAD) and the NZ's National Institute for Water and Atmospheric Research (NIWA). The work was funded by a New Zealand Foundation of Research Science and Technology Postdoctoral award to A.L.K.; the Marsden Fund Council, administered by the Royal Society of New Zealand; NIWA, through core funding under the National Climate Centre Climate Systems programme; the Antarctic Climate and Ecosystems Cooperative Research Centre; and Australian Antarctic Science project 4073. Instruments were designed and built by Inprod PTY LTD. Below is a summary of the design and hardware: Accelerometer: Kistler ServoK-Beam accelerometer. Model 8330B3. IMU: Razor IMU (3 axis acceleration, 3 axis magnetometer and 3 axis gyro) ADC: TI ADS1247 Analog-to- Digital converter CPU (main): Arduino Mega 3.3V CPU (maths): BeagleBone from BeagleBoard.org who use Texas Instruments (TI) ARM processors GPS: Skytraq Venus634FLP Temperature readings: SHT15 from SparkFun Transmission: Iridium 9602 Battery: Lithium batteries (enough to survive a minimum of 6 weeks) Inner housing: Explorer 1908OE Outer housing: The case is fitted in a fork lift tyre ( .53 m diameter and .165 m height) with an inner tube to enable floating. Aerial housing: The aerial is housed in a plastic spherical container on top of a .5 m tube attached to the tyre. Feet: 3 screws stick out of the bottom to create friction with the ice. Onboard processing: Every 3 hours, the instruments wake and record wave accelerations for 35 mins. An initial low pass analogue filter is used. We over sample at 64 Hz and decimate down to 2 Hz. Downsampling from 64 Hz to 2 Hz is achieved through a multistage decimation of 8 followed by 4, to achieve a total decimation of 32. Prior to each downsampling stage, a second order lowpass Butterworth filter is applied to remove all components above the nyquist frequency. We first apply the Butterworth filter with a cut off of 1 Hz and sample at 8 Hz and secondly with a cut off of 0.5 Hz and sample at 2 Hz. A high-pass filter was then applied and the acceleration double-integrated to provide displacement. Welch's method, using a 10% cosine window and de-trending on four segments with 50% overlap, was applied to estimate the power spectral density. Sample frequency: 2 Hz Sample duration - raw: 2048 sec Sample duration - fft: 1280 sec No. of discrete bins of fft: 512 No. of segments: 4 Below is a detailed description of each line of the raw output. Header info L1: Longitude (decimal degrees) L2: File name of attachment emailed via Iridium L3: Temperature inside the box (degrees Celsius) L4: Sensor identification number L5: Time wave record starts (24 hr format HHMMSS) L6: Date of wave record (yyyy-mm-dd) L7: Current voltage L8: Elevation (cm) L9: Latitude (decimal degrees) Wave spectrum L10-L64: The power spectral density for wave period bins (secs) centred on [24.38 19.69 18.96 18.28 17.65 17.06 16.51 16.00 15.51 15.05 14.62 14.22 13.83 13.47 3.12 12.80 12.48 12.19 11.90 11.63 11.37 11.13 10.89 10.66 10.44 10.24 10.03 9.84 9.66 9.48 9.30 9.14 8.98 8.82 8.67 8.53 8.39 8.25 8.12 8.00 7.64 7.31 7.01 6.73 6.48 6.24 6.02 5.81 5.50 5.22 4.97 4.74 4.53 4.33 4.16] Spectral moments L65-L70: m-2 - m4 Quality control L71: mean roll (degrees) L72: mean pitch (degrees) L73: mean yaw (degrees) L74: wave direction (degrees) L75: directional spread (degrees) L76: ratio term to evaluate quality of wave direction approximation (should be close to 1) L77: standard deviation of acceleration (m/s2) L78: standard deviation of gyro x axis (radians/s) L79: standard deviation of gyro y axis (radians/s) L80: standard deviation of gyro z axis (radians/s) L81: standard deviation of yaw (radians) L82: Accelerometer quality flag. 0 = good, 1 = accelerometer bad, 2 = accelerometer and imu bad L83: IMU quality flag. 0 = good, 1 = pitch/roll bad, 2 = yaw bad, 3 = both bad L84: mean acceleration removed (m/s2) L85: no. of flat spots in raw acceleration data L86: the maximum number of consecutive flat spots L87: no. of spikes (data point greater than 6 standard deviations of data set) L88: the maximum number of consecutive spikes L89: Quality flag indicating whether the total power in the time domain and frequency domain are equal. 0 = difference less than 0.01, 1 = difference greater than 0.01. Deployment method: The Helicopter Resources team, lead by Leigh Hornsby, and the Aurora crew, lead by Murray Doyle, were a crucial component to the success of the deployment. The first three sensors were deployed via helicopter. The sensor was lowered via a rope onto floe whilst the helicopter hovering about 2 m above floe. Due to weather constraints, the remaining five were deployed via crane. The ship pulled up beside a chosen floe and the sensors were lowered onto it via crane. Once deployed, the ship slowly moved forward until the floe was clear of the turbulence generated by the ship. Both the helicopter and crane deployment methods proved to be successful. See /Waves/Wave Observations/wiios_deployment.pdf for more details on the deployment procedure. Approximate floe dimensions in metres based on the images in /Waves/Ice Observations/Ice_floe/Sensor ID): Sensor ID,Freeboard,Width,Length 1,0.15,28,28 2,0.33,10,12.5 3,0.15,10,15 4,.1,12,12 5,0.15,10,16.5 6,1,10,16.5 7,0.5,11.5,24 8,1,28.5,9 Ice observations: A collection of images and movies of the ice conditions are provided in Waves/Ice Observations. The folders include: Aerial: This folder contains aerial images taken with a gopro hero 2 fixed to the underside of the helicopter. Note that the date stamp on the GoPro is incorrect. Use the following for calibration: 20121022 13:52:00 - GPS - Australian eastern standard (no daylight savings) 20110707 14:00:07 - GoPRO Ice floe: Images of floes the sensors were deployed on. Ship: Images of the ice conditions taken from the ship. /Waves/Wave Observations/raw/sensorID_yyyy-mm-dd_hhmmss.raw Maps and shapefiles.zip - contains an ArcGIS map and shapefiles containing track data. KML.zip - contains KML files (point data) showing point-in-time snapshots of the buoy positions. Raw_NIWA_data.zip - contains the raw data files.

During the Antarctic Division BIOMASS Experiment III (ADBEX III) cruise of the Nella Dan (Oct - Dec 1985), sea ice cores were drilled at 13 stations. Stratigraphy of the cores recorded, along with borehole temperatures. In addition to visual notes, photographs for each of the cores were taken - the negatives of these pictures are archived with the notes made. Physical records are archived at the Australian Antarctic Division.