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Clouds and the Earth's radiant energy system (CERES) is a satellite-based remote sensing system designed to monitor the Earth's radiation budget. In this paper we examine uncertainties in the angular distribution models (ADMs) used by CERES over permanently snow covered surfaces with clear skies. These ADMs are a key part of the CERES data processing algorithms, used to convert the observed upwelling radiance to an estimate of the upwelling hemispheric flux. We model top-of-atmosphere anisotropic reflectance factors using an atmospheric radiative transfer model with a lower boundary condition based on extensive reflectance observations made at Dome C, Antarctica. The model results and subsequent analysis show that the CERES operational clear-sky permanent-snow ADMs are appropriate for use over Dome C, with differences of less than 5% between the model results and the ADMs at most geometries used by CERES operationally. We show that the uncertainty introduced into the flux estimates through the use of the modeled radiances used in the ADM development is small when the fluxes are averaged over time and space. Finally, we show that variations in the angular distribution of radiance at the top of the atmosphere due to atmospheric variability over permanently snow covered regions are in most cases unlikely to mask the real variations in flux caused by these atmospheric variations.

Spectral albedo and bidirectional reflectance of snow were measured at Dome C on the East Antarctic Plateau for wavelengths of 350–2400 nm and solar zenith angles of 52°–87°. A parameterization of bidirectional reflectance, based on those measurements, is used as the lower boundary condition in the atmospheric radiation model SBDART to calculate radiance and flux at the top of the atmosphere (TOA). The model's atmospheric profile is based on radiosoundings at Dome C and ozonesoundings at the South Pole. Computed TOA radiances are integrated over wavelength for comparison with the Clouds and the Earth's Radiant Energy System (CERES) shortwave channel. CERES radiance observations and flux estimates from four clear days in January 2004 and January 2005 from within 200 km of Dome C are compared with the TOA radiances and fluxes computed for the same solar zenith angle and viewing geometry, providing 11,000 comparisons. The measured radiance and flux are lower than the computed values. The median difference is about 7% for CERES on Terra, and 9% on Aqua. Sources of uncertainty in the model and observations are examined in detail and suggest that the measured values should be less than the computed values, but only by 1.7% ± 4%. The source of the discrepancy of about 6% cannot be identified here; however, the modeled values do agree with observations from another satellite instrument (Multiangle Imaging Spectroradiometer), suggesting that the CERES calibration must be considered a possible source of the discrepancy.

Sensitivity studies with global climate models show that, by their influence on the radiation balance, Antarctic clouds play a major role in the climate system, both directly at high southern latitudes and indirectly globally, as the local circulation changes lead to global teleconnections. Unfortunately, observations of cloud distribution in the Antarctic are limited and often of low quality because of the practical difficulty in observing clouds in the harsh Antarctic environment. The best surface observations suggest that the fractional cloud cover at the South Pole is around 50–60% in all seasons, whereas the cloud cover rises to around 80–90% close to the coast of the continent. Microphysical observations of cloud parameters are also very sparse in the Antarctic. However, the few measurements that do exist show predominantly ice-crystal clouds across the interior, with mixed-phase clouds close to the coasts. Crystal sizes vary from 5 to 30 mm (effective radius) in the interior to somewhat larger ice crystals and water drops near the coast. A wide range of crystal shapes is observed at all sites. This review considers the available cloud observations and highlights the importance of Antarctic clouds and the need for better observations in the future.

In previous work, whaling catch positions were used as a proxy record for the position of the Antarctic sea ice edge and mean sea ice extent greater than the present one spanning 2.8° latitude was postulated to have occurred in the pre-1950s period, compared to extents observed since 1973 from microwave satellite imagery. The previous conclusion of an extended northern latitude for ice extent in the earlier epoch applied only to the January (mid-summer) period. For this summer period, however, there are also possible differences between ship and satellite-derived measurements. Our work showed a consistent summer offset (November– December), with the ship-observed ice edge 1 - 1.5° north of the satellitederived ice edge. We further reexamine the use of whale catch as an ice edge proxy where agreement was claimed between the satellite ice edge (1973–1987) and the ship whale catch positions. This examination shows that, while there may be a linear correlation between ice edge position and whale catch data, the slope of the line deviates from unity and the ice edge is also further north in the whale catch data than in the satellite data for most latitudes. We compare the historical (direct) record and modern satellite maps of ice edge position accounting for these differences in ship and satellite observations. This comparison shows that only regional perturbations took place earlier, without significant deviations in the mean ice extents, from the pre-1950s to the post-1970s. This conclusion contradicts that previously stated from the analysis of whale catch data that indicated Antarctic sea ice extent changes were circumpolar rather than regional in nature between the two periods.

A hindcast simulation of the Arctic and Antarctic sea ice variability during 1955–2001 has been performed with a global, coarse resolution ice–ocean model driven by the National Centers for Environmental Prediction / National Center for Atmospheric Research reanalysis daily surface air temperatures and winds. Both the mean state and variability of the ice packs over the satellite observing period are reasonably well reproduced by the model. Over the 47-year period, the simulated ice area (defined as the total ice-covered oceanic area) in each hemisphere experiences large decadal variability together with a decreasing trend of ~1 % per decade. In the Southern Hemisphere, this trend is mostly caused by an abrupt retreat of the ice cover during the second half of the 1970s and the beginning of the 1980s. The modelled ice volume also exhibits pronounced decadal variability, especially in the Northern Hemisphere. Besides these fluctuations, we detected a downward trend in Arctic ice volume of 1.8 % per decade and an upward trend in Antarctic ice volume of 1.5 % per decade. However, caution must be exercised when interpreting these trends because of the shortness of the simulation and the strong decadal variations. Furthermore, sensitivity experiments have revealed that the trend in Antarctic ice volume is model-dependent.

The altitude dependent variability of ozone in the polar stratosphere is regularly observed by balloon-borne ozonesonde observations at Neumayer Station (70°S) in the Antarctic and at Koldewey Station (79°N) in the Arctic. The reasons for observed seasonal and interannual variability and long-term changes are discussed. Differences between the hemispheres are identified and discussed in light of differing dynamical and chemical conditions. Since the mid- 1980s, rapid chemical ozone loss has been recorded in the lower Antarctic stratosphere during the spring season. Using coordinated ozone soundings in some Arctic winters, similar chemical ozone loss rates have been detected related to periods of low temperatures. The currently observed cooling trend of the stratosphere, potentially caused by the increase of anthropogenic greenhouse gases, may further strengthen chemical ozone removal in the Arctic. However, the role of internal climate oscillations in observed temperature trends is still uncertain. First results of a 10000 year integration of a low order climate model indicate significant internal climate variability. on decadal time scales, that may alter the effect of increasing levels of greenhouse gases in the polar stratosphere.