Bathymetric contours and height range polygons of approaches to Mawson Station, derived from RAN Fair sheet, Aurora Australis and GEBCO soundings.

Metadata record for data from ASAC Project 1117 See the link below for public details on this project. ---- Public Summary from Project ---- The aim of this project is to determine how feasible it is to regularly sample the pelagic under-ice community during winter at a coastal site near Mawson. Very few attempts have been made to sample the water column under the ice during the winter months and the processes that occur during this period remain critical gaps in our knowledge of the Antarctic marine ecosystem. ------------------------------------- The pelagic community under the Mawson sea ice was sampled during the winter of 2001 using 'light trap' sampling devices. The 'light traps' were tested at various depths in a range of configurations to determine whether they were an appropriate instrument to sample the winter pelagic community under the ice. Fourteen successful deployments of the light traps were made on seven separate occasions from 12 June to 12 September 2001. The light traps were deployed at three different depths - the underside of the sea ice, mid water, and just above the sea floor. Two different light sources were used to attract the animals, namely fluorescent tubes and cyalume sticks. Two different configurations of the traps were tested to retain the animals inside the trap - one with plastic flaps to trap the animals, the other with no flaps, allowing the animals to move freely inside the trap. The light traps were deployed and retrieved during darkness to avoid any influence of ambient light. The objectives of the project were met and it is assessed that the pelagic community in winter can be effectively sampled using this methodology. A result of particular interest is the success of the traps in capturing Pleuragramma antarctica, a species which has proven difficult to capture using traditional sampling methods such as nets.

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 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.

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.

The ANARE Health Register, which has been in operation since 1987, is designed to gather, store, analyse and report on all health related events occurring in the ANARE population. The principal aims of the project are to: - quantify the occurrence of ill health in Antarctic personnel. - compare the incidence rates with those in the domestic population. - assess any trends in health events. - identify high risk groups, in order to modify conditions accordingly. - assess the role of pre-existing health conditions. - examine the causes of injury. - quantify the procedures performed and drugs administered. The results of all medical consultations are coded according to the International Classification of Diseases and analysed on both a monthly and an annual basis in order to assess any emerging trends. In addition to serving as a long-term data base for epidemiological studies, the Health Register is proving to be a useful tool in the day-to-day operations of the Polar Medicine Branch of the Australian Antarctic Division.

This dataset contains data on the habitats, distribution and numbers of Adelie Penguins (Pygoscellis adeliae) in the Mawson area, Antarctica during 1981 and 1988. The data are obtained from aerial photographs obtained at various times, during the 1981-82 and 1988-89 seasons. The results are listed in the documentation. Comparisons are made with census data collected in the 1971-72 summer. Data from this record has been incorporated into a larger Adelie penguin dataset described by the metadata record - Annual population counts at selected Adelie Penguin colonies within the AAT (SOE_seabird_candidate_sp_AP). It also falls under ASAC project 1219 (ASAC_1219).

The United States Department of Energy - Environmental Measurements Laboratory located in New York City has been monitoring the naturally occurring and man-made radionuclides for the past 40 years throughout the world. We have been using simple and very rugged air sampler which collect air from the surrounding environment. With this method and diverse location of sampling stations we have been able to detect with gamma counting method Beryllium 7, lead 210 as natural radionuclides and also some anthropogenic or man-made radionuclides such as Zirconium 95, Cesium 137, Cerium 144 which half-lives are fairly long. Come to visit us at: http://www.wipp.energy.gov/NAMP/EMLLegacy/index.htm and search for databases especially Surface Air Sampling Program. The Surface Air Sampling Program (SASP) database provides information on EML's archived air filter samples and sample measurements. The program was established in 1957 to track the global dispersion of radioactive debris resulting from atmospheric testing of nuclear bombs. Air filter samples were collected at locations throughout the world and analyzed for nuclear debris. In the 1980's, the program focused on the global distributions of the naturally occurring radionuclides, beryllium-7 and lead-210. The resulting database is the most comprehensive and extensive record of its kind in the world.

This dataset contains temperature and salinity data from CTD observations at Mawson, Antarctica. Profiles to 370m were attempted on an approximately monthly basis between October 1980 and October 1982. A representative value for each month of the year has been obtained during this 2 year period. The fields in this dataset are: observation_date (the date of observation, in ISO8601 format yyyy-mm-ddTHH:MM:SSZ. This information is also separated into the year, month, day, etc components) observation_date_year (the year of the observation date) observation_date_month (the month of the observation date) observation_date_day (the day of the observation date) depth (the depth at which measurements were made in m) temperature (the measured water temperature in degrees C) salinity (the measured salinity in ppt) sigma_t (kgm^-3)

Database Description The files represent the 41 different Weddell seal (Leptonychotes weddellii) call types identified at either Mawson, Davis, and/or Casey. They were collected between 60 degrees 49' E and 110o 40' E in longitude, and between 66 degrees 12' S and 68 degrees 34' S in latitude. Each call type name includes two elements. The first is a three-digit number starting at 301 to identify the call type. The second is a one to three-letter code referring to the call category that each type falls into. The 13 different possible call categories are: SymbolNameDescription OToneConstant-frequency, predominantly sinusoidal call. LGrowlConstant-frequency, broad bandwidth, long call. QWhoopConstant-frequency call with a terminal upsweep. SSqueakBrief call with constant frequency or rising frequency and an irregular waveform. WAWhistle AscendingAscending frequency, sinusoidal waveform. TCTrill Constant-FrequencyNarrow bandwidth trill with a constant-frequency beginning, sinusoidal or frequency-modulated waveform. TTrillNarrow to broad bandwidth, containing a frequency downsweep, greater than 2 seconds. WDWhistle DescendingDescending frequency, sinusoidal waveform (less than 2 seconds). MMewAbruptly descending frequency followed by a long constant-frequency ending. CChugAbruptly descending frequency followed by a brief constant-frequency ending. GGuttural Glug (Grunt)Descending-frequency call that was lower than a Chug and had a brief duration. WAGWhistle Ascending - GruntBrief Ascending Whistle followed by a Guttural Glug (Grunt), the two types alternate in a regular pattern. KKnockAbrupt, brief-duration broadband sound (from: Pahl, B.C., Terhune, J.M. and Burton, H.R. 1997). The 41 call types were divided into two sections, the first 33 (301-O to 333-K) being common call types and the last 8 (334-Q to 341-WD) being rare call types. In each call type folder, one to five different samples of each call type are provided. They are identified by a small case letter added at the end of the call type name. Each sample includes both a .WAV audio sample and a .JPG image of the call type spectrogram showing call shape, i.e., changes in call frequency (vertical) over time (horizontal). These call types were used to identify: (a) unique call types or call categories, (b) differences in call type or call category usage (the frequency of occurrence of each call type or category), and (c) differences in call features (number of elements, start frequency, frequency shift and first element duration) among the three stations. The download file also includes a spreadsheet of data and a text file explaining how to interpret the data. Analysis of this dataset is ongoing.