Graphs, maps and tables

Showing results 1 - 10 of 23
Figure 1 Antarctica and the Australian Antarctic Territory
Figure 2 Ozone mass deficit metric

EESC = equivalent effective stratospheric chlorine; Mt = megatonne; OMI = Ozone Monitoring Instrument; OMPS = Ozone Mapping and Profiler Suite; ppb = parts per billion; TOMS = Total Ozone Mapping Spectrometer

(a) Estimated daily mass of ozone destroyed within the ozone hole, shown for individual years from 2015 to 2020 as a function of day of year from July to December. (b) Estimated total annual ozone mass loss associated with the ozone hole from 1979 to 2020 (green dots) and EESC (blue line), a measure of the stratospheric concentration of ozone-depleting substances. These figures are obtained from CSIRO analysis of daily total column ozone measurements provided from the OMPS on the Suomi National Polar-orbiting Partnership satellite. In (a), the light-blue background shows the range of daily values for 1979–2019 obtained with the TOMS instrument (1979–2003), the OMI (2004–11) and OMPS (2012–19). Gaps in the timeseries are when no TOMS measurements were made.

Source: CSIRO; after Klekociuk et al. (2021)

Figure 3 Patterns of average maximum temperatures across the Southern Hemisphere in November–December 2019

Note: Shown are differences in the maximum daily temperature averaged over November and December 2019 with respect to the climatological average for 1980–2010. The scale is degrees Celsius.

Source: After Robinson et al. (2020). Royal Netherlands Meteorological Institute Climate Explorer using data from the European Centre for Medium-range Weather Forecasts, fifth Reanalysis.

Figure 4 History of climate and atmospheric composition from Antarctic ice-core records

CO2 = carbon dioxide; ppm = parts per million

(a) Law Dome ice-core CO2 record, the world’s most accurate and detailed CO2 record for the past 2,000 years. Note the clear increase in CO2 from the start of the Industrial Revolution and the agreement of the ice-core measurements with more recent atmospheric data from Kennaook/Cape Grim, Tasmania. (b) Data from a composite of Antarctic deep ice cores reveals past changes in Antarctic (b) CO2 and (c) temperature over the past 800,000 years. The modern rise is outside the bounds of natural variability over this period. Note the close coupling of temperature and CO2 throughout the ice age cycles, which have approximately a 100,000-year periodicity.

Sources: Kennaook/Cape Grim CO2 – Kennaook/Cape Grim Baseline Air Pollution Station (Australian Bureau of Meteorology, and CSIRO Oceans and Atmosphere); Law Dome CO2MacFarling Meure et al. (2006); Antarctic ice-core composite CO2Bereiter et al. (2015); Antarctic temperature change – Jouzel et al. (2007).

Figure 5 Antarctic mass loss

Gt = gigatonne; IMBIE = Ice sheet Mass Balance Inter-comparison Exercise; mm = millimetre

(a) Antarctic mass loss was compiled from 24 separate studies by the IMBIE team (2018). (b) Ice-sheet thinning was measured by Smith et al. (2020) over 2003–19.

Sources: (a) From IMBIE team (2018). Reprinted by permission from Springer Nature Customer Service Centre GmbH: Springer, Nature. Mass balance of the Antarctic Ice Sheet from 1992 to 2017, Andrew Shepherd et al., 2018. (b) From Smith et al. (2020). Reprinted with permission from AAAS; permissions conveyed through Copyright Clearance Center, Inc.

Figure 6 East Antarctic vulnerability to ice retreat

Notes:

  1. Marine ice-sheet instability (MISI) causes regions of the ice sheet on retrograde slopes to be vulnerable to irreversible retreat, as any retreat of the grounding line increases flux and thinning.
  2. Regions of East Antarctica vulnerable to MISI include the Wilkes and Aurora subglacial basins.

Source: Produced using the Norwegian Polar Institute’s Quantarctica package.

Figure 7 Sea ice extent anomaly

km2 = square kilometre

Note: Figure shows anomaly (difference from climatological average) of monthly mean (thin lines) and 11-month running mean (thick lines) sea ice extent in the Arctic and Antarctic since 1979.

Source: Adapted from Turner & Comiso (2017) and extended using data from the National Snow and Ice Data Center. Credit: Phillip Reid, BOM

Figure 8 December 2016 sea ice concentration anomaly
Figure 9 DNA metabarcoding

Note: DNA was extracted from scats of many different predators. 1. Through DNA metabarcoding, the prey species ingested by predators were identified and compared to species caught by commercial fishing vessels. 2. DNA metabarcoding can also be used to identify seabird species to detect whether they have returned to a previously occupied breeding island.

Source: Julie McInnes

Figure 10 Colony of shy albatrosses at Albatross Island, Tasmania