a. Research Objectives

Unprecedented changes are occurring in the Earth's climate. The current decade was the warmest on record since 1880 AD. The global average surface temperature has increased, especially since about 1950 with 100-year trend (1906–2005) of 0.74°C ± 0.18°C (IPCC, 2007). Although the scientific evidence of global warming is now widely regarded as unequivocal (IPCC, 2007), predicting regional impacts still poses challenges. Especially, conclusions of the Southern Hemisphere record are limited by the sparseness of available proxy data at present (Mann & Jones, 2003).

While meteorological records from instrumental and remote sensing data display the large intercontinental climate variability, the series are insufficient to infer trends or to understand the forcing, which renders prediction difficult (Jones et al., 1999; Mann & Jones, 2003). The long ice core records from the Antarctic interior and Greenland revolutionised our understanding of global climate and showed for the first time the occurrence of RCE (Rapid Climate Change Events, for review e.g. Mayweski and White (2002)). To understand the drivers and consequences of climate change on timescales important to humans, a new focus of ice core work is now moving towards the acquisition of 'local' ice cores that overlap with and extend the instrumental records of the last 40 years back over the last several thousand years (Mayewski et al., 2005).

This has been a key motivation behind the US-led International Transantarctic Scientific Expedition (ITASE) of which New Zealand is a member (Mayewski et al. 2005). The NZ ITASE objective is to recover a series of ice cores from glaciers along a 14 degree latitudinal transect of the climatically sensitive Victoria Land coastline to establish the drivers and feedback mechanism of the Ross Sea climate variability (Bertler et al., 2004a; Bertler et al., 2004b; Bertler & 54 others, 2005; Bertler et al., 2005a; Bertler et al., 2005b; Bertler et al. 2006, Patterson et al., 2005, Rhodes et al. 2009).

Due to logistical constraints by Antarctica New Zealand, the field deployment planned for 2009/10 was cancelled and a substantially reduced programme was carried out.

b. Brief Methodology

Automatic weather station set-up, maintenance, and data retrieval

Since 2004/05 we deployed an automatic weather station on Evans Piedmont Glacier and since 2007/08 also at Skinner Saddle. The data permit the calculation of transfer functions between ice core proxies and meteorological parameters, such as temperature, precipitation, meso-scale atmospheric circulation pattern, katabatic winds, and seasonality of snow accumulation. In addition, a new snow accumulation sensor and high precision snow temperature probes allow us to monitor snow accumulation rates, the potential influence of snow loss through sublimation, wind erosion or melt, and the quality of preservation of the meteorological signal in the snow. Furthermore, the data allow us to estimate the uncertainty of re-analysis data (NCEP/NCAR and ERA-40 data) in the region. At the request of Antarctica New Zealand, the automatic weather station was retrieved from Skinner Saddle this year.

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Fig. 1: Automatic weather station at Skinner Saddle

Submergence Velocity Measurements at Victoria Lower and Evans Piedmont Glacier

The response time of a glacier to changes in accumulation or ablation is dependent on the size and thickness of the ice mass. In general, the response time of cold-based glaciers is positively correlated with the size of its ice mass, leading to long response times in Antarctica. For glaciers in the McMurdo Dry Valleys, with lengths on average of 5-10km and flow rates of 1 to 3 m/a, the response times are thought to range from 1,500a to 15,000a (Chinn, 1987; Chinn, 1998). Consequently, annual variations in surface elevation may only reflect changes in loss rates. As a result surface measurements of mass balance are difficult to interpret in terms of long-term mass balance (Hamilton & Whillans, 2000). This is especially the case in places like the McMurdo Dry Valleys where mass loss is thought to be predominately due to sublimation at ice cliffs and glacier surface caused by wind and solar radiation (Chinn, 1987; Chinn, 1998). For Victoria Lower Glacier (VLG), two mass balance measurements are available in the literature for 1983 and 1991 based on ice cliff characteristics and the motion of the glacier snout (Chinn, 1998). The measurements indicate that VLG was advancing 1.24m/a into Victoria Valley during this time period. However, the small number of observations (2) and the cliffs sensitivity to sublimation (contemporary surface ablation) result in a high uncertainty of longer term mass balance. To determine the longer-term mass balance of the glaciers, unaffected by annual surface variations, three 'coffee-can' or 'submergence velocity' devices (Hamilton et al., 1998; Hamilton & Whillans, 2000) were deployed at Victoria Lower Glacier in 1999/2000 and two at Evans Piedmont Glacier in 2004/05. These are annually re-measured to monitor mass balance changes.

Fig. 2: Submergence Velocity Measurements at VLG

Snow Sampling for Aeolian Material

As our drilling programme had been postponed for a year, Dr. Tim Haskell (PI of K131) kindly allowed Holly Winton to join his group to conduct her research project. Her project focuses on iron fertilisation of the Ross Sea region. Fine-grained aeolian dust (<10 0m) is believed to be a significant source of iron (Fe), which is the bio-limiting nutrient required for phytoplankton growth in the McMurdo Sound, Antarctica. The dust accumulates on sea ice and is added to the ocean each year when the ice breaks up. This 'fertilisation' of the ocean results in vast phytoplankton blooms that alter the food web and generate large volumes of biogenic sediment. In spite of the apparent importance of aeolian dust in 'biogeochemical cycling' in the McMurdo Sound, the details of the interdependence of the geological processes that supply the Fe and the page 3 resulting plankton growth are poorly understood. This project aims to quantify aspects of this biogeochemical cycle for the first time by analysing the physical (size distribution, abundance and variability) and chemical (total and "bio-available" Fe content) properties of the aeolian dust blown off the Antarctic continent, deposited and trapped in coastal snow and ice in the McMurdo Sound region. Snow samples from McMurdo sea ice were collected this season for these measurements with the intention of publishing the results in an internationally peer-reviewed journal and presenting them at the Antarctica New Zealand conference.

Figure 3: Satellite image of McMurdo Sound showing snow sampling sites in November 2009. Red dotes: Sampling sites. Blue dote: Base camp. North of the yellow line dark areas denote first year sea ice, while lighter areas denote multi-year ice. Yellow outline marks the continental and sea ice edge.

c. What were the key achievements of your visit? Include any key preliminary findings that are of particular interest.

• Automatic weather station set-up, maintenance, and data retrieval:

  Weather station data were downloaded and the instruments were serviced

• Submergence Velocity Measurements at Victoria Lower and Evans Piedmont Glacier

  High resolution GPS measurements were conducted and the devices were serviced

• Snow sampling for aeolian material

  An excellent spatial coverage of 55 snow samples were collected along three transects on the McMurdo sea ice (Figure 3). Sampling was carried out using ultra clean methodology to prevent contamination from personnel, sampling equipment and sample bottles. Two samples at each site were collected and duplicates of these taken at every second site to evaluate local and regional scale variability. First, snow samples from the snow surface to a depth of 2 cm above the sea ice (to prevent sampling saline snow), for elemental concentration and bio-availability measurements of dust were collected in pre-acid washed Nalgene polypropylene 500 ml or 1000 ml bottles. Second, larger volume samples of the full snow depth were collected for dust concentration and grain size measurements.

Figure 4: Dust layers in snow. A) First year ice downwind of Black Island, B) First year ice downwind of Black Island.