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The climate observations at Orcadas represent the only southern high-latitude site where data span more than a century, and its daily measurements are presented for the first time in this paper. Although limited to a single station, the observed warming trends are among the largest found anywhere on the earth, facilitating the study of changes in extreme temperatures as well as averages. Factors that may influence Antarctic climate include natural variability; changes in greenhouse gases; and, since about the mid-1970s, the development of the ozone hole. The seasonality of observed warming and its temporal evolution during the century are both key for interpretations of Antarctic climate change. No statistically significant climate trends are observed at Orcadas from 1903 to 1950. However, statistically significant warming is evident at Orcadas throughout all four seasons of the year since 1950. Particularly in austral fall and winter, the warming of the cold extremes (coldest 5% and 10% of days) substantially exceeds the warming of the mean or of the warmest days, providing a key indicator for cold season Antarctic climate change studies. Trends in the summer season means and extremes since 1970 are approximately twice as large as those observed earlier, supporting suggestions of additional regional warming in that season because of the effects of ozone depletion on the circulation. Further, in the spring and summer seasons, significant mean warming also occurred prior to the development of the Antarctic ozone hole (i.e., 1950–70), supporting an important role for processes other than ozone depletion, such as greenhouse gas increases, for the climate changes. [ABSTRACT FROM AUTHOR]

Significant changes in physical and biological systems are occurring on all continents and in most oceans, with a concentration of available data in Europe and North America. Most of these changes are in the direction expected with warming temperature. Here we show that these changes in natural systems since at least 1970 are occurring in regions of observed temperature increases, and that these temperature increases at continental scales cannot be explained by natural climate variations alone. Given the conclusions from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report that most of the observed increase in global average temperatures since the mid-twentieth century is very likely to be due to the observed increase in anthropogenic greenhouse gas concentrations, and furthermore that it is likely that there has been significant anthropogenic warming over the past 50 years averaged over each continent except Antarctica, we conclude that anthropogenic climate change is having a significant impact on physical and biological systems globally and in some continents. [ABSTRACT FROM AUTHOR]

We analyze ensembles (four realizations) of historical and future climate transient experiments carried out with the coupled atmosphere-ocean general circulation model (AOGCM) of the Hadley Centre for Climate Prediction and Research, version HADCM2, with four scenarios of greenhouse gas (GHG) and sulfate forcing. The analysis focuses on the regional scale, and in particular on 21 regions covering all land areas in the World (except Antarctica). We examine seasonally averaged surface air temperature and precipitation for the historical period of 1961–1990 and the future climate period of 2046–2075. Compared to previous AOGCM simulations, the HADCM2 model shows a good performance in reproducing observed regional averages of summer and winter temperature and precipitation. The model, however, does not reproduce well observed interannual variability. We find that the uncertainty in regional climate change predictions associated with the spread of different realizations in an ensemble (i.e. the uncertainty related to the internal model variability) is relatively low for all scenarios and regions. In particular, this uncertainty is lower than the uncertainty due to inter-scenario variability and (by comparison with previous regional analyses of AOGCMs) with inter-model variability. The climate biases and sensitivities found for different realizations of the same ensemble were similar to the corresponding ensemble averages and the averages associated with individual realizations of the same ensemble did not differ from each other at the 5% confidence level in the vast majority of cases. These results indicate that a relatively small number of realizations (3 or 4) is sufficient to characterize an AOGCM transient climate change prediction at the regional scale. [ABSTRACT FROM AUTHOR]