This dataset contains records of ice thickness and snow thickness from Mawson, Antarctica. Measurements were attempted on a weekly basis and have been recorded since 1954 and are ongoing, although this record only contains data up until the end of 1989. The observations are not continuous however. The dataset is available via the provided URL. These data were also collected as part of ASAC projects 189 and 741. Logbooks(s): Glaciology Sea Ice Log, Mawson 1969 Glaciology Mawson Sea Ice Logs, 1995-2000

Metadata record for data from ASAC Project 1212. See the link below for public details on this project. ---- Public Summary from Project ---- This project aims to improve ship-based sea-ice thickness measurements made using an electromagnetic induction device by performing a theoretical analysis of the sensitivity of the electromagnetic instrument to factors such as instrument height and orientation, ice conductivity and thickness, and seawater conductivity. The results of the theoretical study will be used to assist the interpretation of an existing sea-ice thickness data set from the Mertz Glacier polynya cruise (V1, 1999/2000). The data set consists of the results of numerical modelling of the response of the EM31 electromagnetic instrument to typical one- and three-dimensional sea ice structures. One-dimensional model calculations were performed using software written specifically for the project. Three-dimensional model calculations were performed using Marco_air version 2.3, written by Z. Xiong and A. Raiche, CSIRO Mathematical Geophysics Group. Technical descriptions of this program are given in the preceding References section. The download file below contains some numerical output from the models, as well as a detailed description of the models used.

Observations of the sea ice cover at Wilkes base in Autumn-Winter 1963. Includes water temperature, air temperature, wind speed and direction, cloud cover, relative humidity, and general notes. These documents have been archived at the Australian Antarctic Division.

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.

We observed total thickness (snow thickness + ice thickness) of sea-ice floes along 100m transects using an electromagnetic (EM) sensor. The data were read from the EM and written by hand into a log book as we moved along the transect. They were then transferred into an Excel spreadsheet. The parameters included are: - distance along transect - conductivity (vertical) - conductivity (horizontal) - total thickness (derived from vertical and horizontal conductivities)

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

Taken from the "Supporting Information" for the main paper. See the referenced papers for more information. Our results are based on numerical simulation of Southern Ocean sea ice, conducted using the Los Alamos numerical sea-ice model CICE version 4.0 [CICE4; Bailey et al., 2010] configured in stand-alone mode on a 0.25 degree x 0.25 degree grid, extending to 45 degrees S, with 3-hourly output [Stevens, 2013]. The atmospheric forcing for CICE4 came from the hemispheric forecasting model Polar Limited Area Prediction Systems [Polar- LAPS; Adams, 2006] and ocean forcing from the global ocean general circulation model Australian Climate Ocean Model [AusCOM; Bi and Marsland, 2010]. The model is well-constrained in its representation of processes of sea ice formation and melt, and comparison with observed areal ice extent shows minimal deviations over the 1998-2003 period, particularly during winter [Stevens 2013]. Stevens [2013] evaluates the sensitivity of the model to the number of ice thickness categories. Sea ice thickness sensitivities in the CICE model are considered in detail in Hunke [2010, 2014]. For the warm climate scenario, changes were implemented that are consistent with the A1B scenario from the Fourth Assessment from the IPCC [Meehl et al., 2007]. This is a mid-range scenario that assumes rapid economic growth before introduction of new and more efficient technologies mid century. Specifically, the following changes were applied uniformly to the current climate forcing field for a single year: a 2 degrees C increase in air temperature, a 0.2 mm/day increase in rain, a 1.5% increase in cloud fraction, a -2.3 hPa change in surface air pressure, a 25% increase in wind, a 12 Wm-2 increase in long wave downward radiation and a 20% increase in humidity. Outputs and forcings from CICE4 that are relevant for consideration of under-ice habitats for larval krill include: snow depth, ice thickness, ice concentration, movement, ridging rate, day length (dependent on day-of-year and latitude), radiation above the ice (influenced by cloud cover), and radiation below the ice (influenced by ice and snow depth). Table 1 in the main text describes how these were used in the following two filters and one overlay for evaluating the location and suitability of potential larval krill habitat during winter. Taken from the abstract of the main paper: Over-wintering of larvae underneath Antarctic pack ice is a critical stage in the life cycle of Antarctic krill. However, there are no circumpolar assessments of available habitat for larval krill, making it difficult to evaluate how climate change may impact this life stage. We use outputs from a circumpolar sea-ice model, together with a set of simple assumptions regarding key habitat features, to identify possible regions of larval krill habitat around Antarctica during winter. In particular we assume that the location and suitability of habitat is determined by both food availability and three dimensional complexity of the sea ice. We then compare the combined area of these regions under current conditions to that under a warm climate scenario. Results indicate that, while total areal sea-ice extent decreases, there is a consistently larger area of potential larval krill habitat under warm conditions. These findings highlight that decreases in sea-ice extent may not necessarily be detrimental for krill populations and underline the complexity of predicting future trajectories for this key species in the Antarctic ecosystem.

This indicator is no longer maintained, and is considered OBSOLETE. INDICATOR DEFINITION Regular measurements of the thickness of the fast ice, and of the snow cover that forms on it, are made through drilled holes at several sites near both Mawson and Davis. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: CONDITION RATIONALE FOR INDICATOR SELECTION Each season around the end of March, the ocean surface around Antarctica freezes to form sea ice. Close to the coast in some regions (e.g. near Mawson and Davis stations) this ice remains fastened to the land throughout the winter and is called fast ice. The thickness and growth rate of fast ice are determined purely by energy exchanges at the air-ice and ice-water interfaces. This contrasts with moving pack ice where deformational processes of rafting and ridging also determine the ice thickness. The maximum thickness that the fast ice reaches, and the date on which it reaches that maximum, represent an integration of the atmospheric and oceanic conditions. Changes in ice thickness represent changes in either oceanic or atmospheric heat transfer. Thicker fast ice reflects either a decrease in air temperature or decreasing oceanic heat flux. These effects can be extrapolated to encompass large-scale ocean-atmosphere processes and potentially, global climate change. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial Scale: At sites near Australian Antarctic continental stations: Davis; Mawson. Frequency: at least weekly, reported annually Measurement Technique: Tape measurements through freshly drilled 5 cm diameter holes in the ice at marked sites. RESEARCH ISSUES To more effectively analyse the changes in Antarctic fast ice a detailed long-term dataset of sea ice conditions needs to be established. This would provide a baseline for future comparisons and contribute important data for climate modelling and aid the detection of changes that may occur due to climate or environmental change. LINKS TO OTHER INDICATORS SOE Indicator 1 - Monthly mean air temperatures at Australian Antarctic stations SOE Indicator 40 - Average sea surface temperatures in latitude bands 40-50oS, 50-60oS, 60oS-continent SOE Indicator 41 - Average sea surface salinity in latitude bands: 40-50oS, 50-60oS, 60oS-continent SOE Indicator 42 - Antarctic sea ice extent and concentration The fast ice data are also available as a direct download via the url given below. The data are in word documents, and are divided up by year and site (there are three sites (a,b,c) at each station). Snow thickness data have also been included. A pdf document detailing how the observations are collected is also available for download.

Zooplankton were collected during the winter-spring transition during two cruises of the Aurora Australis: SIPEX in 2007 and SIPEX II in 2012. As part of the collections sea ice cores were collected to describe the ice habitat during the period of zooplankton collections. Ice cores were taken with a 20 cm diameter SIPRE corer and sectioned in the field with an ice core. Temperature was measured in the section using a spike thermometer and slivers of each section were melted without filtered water to record salinity. The remainders of each section were melted at 4oC in filtered seawater and the melted water was used to measure chlorophyll a concentration, and meiofauna species and abundance.

Public Summary for project 2901 This research will contribute to a large multi-disciplinary study of the physics and biology of the Antarctic sea ice zone in early Spring 2007. The physical characteristics of the sea ice will be directly measured using satellite-tracked drifting buoys, ice core analysis and drilled measurements, with detailed measurements of snow cover thickness and properties. Aircraft-based instrumentation will be used to expand our survey area beyond the ship's track and for remote sampling. The data collected will provide valuable ground-truthing for existing and future satellite missions and improve our understanding of the role of sea ice in the climate system. Project objectives: (i) to quantify the spatial variability in sea ice and snow cover properties over scales of metres to hundreds of kilometres in the region of 110 - 130 degrees E, in order to improve the accuracy of sea ice thickness estimates from satellite altimetry and polarimetric synthetic aperture radar (SAR) data. (ii) To determine the drift characteristics, and internal stress, of sea ice in the region 110 - 130 degrees E. (iii) To investigate the relationships between the physical sea ice environment and the structure of Southern Ocean ecosystems (joint with AAS Proposal 2767). Taken from the abstract of the PhD thesis accompanying the dataset: Antarctic sea ice and its snow cover are integral components of the global climate system, yet many aspects of their vertical dimensions are poorly understood, making their representation in global climate models poor. Remote sensing is the key to monitoring the dynamic nature of sea ice and its snow cover. Reliable and accurate snow thickness data from an airborne platform is currently a highly sought after data product. Remotely sensed snow thickness measurements can provide an indication of precipitation levels. These are predicted to increase with effects of climate change, and are difficult to measure as snow fall is frequently lost to wind-blown redistribution, sublimation and snow-ice formation. Additionally, accurate regional scale snow thickness data will increase the accuracy of sea ice thickness retrieval from satellite altimeter freeboard estimates. Airborne snow-depth investigation techniques are one method for providing regional estimation of these parameters. The airborne datasets are better suited to validating satellite algorithms, and are themselves easier to validate with in-situ measurement. The development and practicality of measuring snow thickness over sea ice in Antarctica using a helicopter-borne radar forms the subject of this thesis. The radar design, a 2-8 GHz Frequency Modulated Continuous Wave Radar, is a product of collaboration and the expertise at the Centre for Remote Sensing of Ice Sheets, Kansas University. This thesis presents a review of the theoretical basis of the interactions of electromagnetic waves with the snow and sea ice. The dominant general physical parameters pertinent to electromagnetic sensing are presented, and the necessary conditions for unambiguous identification of the air/snow and snow/ice interfaces by the radar are derived. It is found that the roughness's of the snow and ice surfaces are dominant determinants in the effectiveness of layer identification in this radar. Motivated by these results, the minimum sensitivity requirements for the radar are presented. Experiments with the radar mounted on a sled confirm that the radar is capable of unambiguously detecting snow thickness. Helicopter-borne experiments conducted during two voyages into the East Antarctic sea-ice zone show however, that the airborne data are highly affected by sweep frequency non-linearities, making identification of snow thickness difficult. A model for the source of these non-linearities in the radar is developed and verified, motivating the derivation of an error correcting algorithm. Application of the algorithm to the airborne data demonstrates that the radar is indeed receiving reflections from the air/snow and snow/ice interfaces. Consequently, this thesis presents the first in-situ validated snow thickness estimates over sea ice in Antarctica derived from a Frequency Modulated Continuous Wave radar on a helicopter-borne platform. Additionally, the ability of the radar to independently identify the air/snow and snow/ice interfaces allows for a relative estimate of roughness of the sea ice to be derived. This parameter is a critical component necessary for assessing the integrity of satellite snow-depth retrieval algorithms such as those using the data product provided by the Advanced Microwave Scanning Radiometer - Earth Observing System sensor on board NASA's Aqua satellite. This thesis provides a description, solution or mitigation of the many difficulties of operating a radar from a helicopter-borne platform, as well as tackling the difficulties presented in the study of heterogeneous media such as sea ice and its snow cover. In the future the accuracy of the snow-depth retrieval results can be increased as technical difficulties are overcome, and at the same time the radar architecture simplified. However, further validation studies are suggested to better understand the effect of heterogeneous nature of sea ice and its snow cover on the radar signature. RAASTI = Radar For Antarctic Snow Thickness Investigation