Antarctic Sea Ice Area in CMIP6

Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high‐level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger‐than‐observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios

Comparison of warming trends predicted over the next century around Antarctica from two coupled models

This paper investigates the climate change in two atmosphere-ice-ocean coupled climate models - the UKMO and the CSIRO - in the Antarctic region over the next century. The objectives were to see if an enhanced level of greenhouse-gas forcing results in a surface temperature signal above background variability, and to see if this pattern of change resembles the change seen to date in Antarctica, especially the warming around the Peninsula. The models show that although reduced sea-ice compactness is responsible for regions of enhanced air-temperature anomalies, these ice-compactness anomalies are determined by different mechanisms in the respective models. The pattern of warming in both models does not match the differential rates of warming seen in the observations of temperature change over the Antarctic continent in the last few decades. Also the level of background ocean variability in the Drake Passage and Weddell Sea region hampers the clear definition of a signal over the Antarctic Peninsula in the coupled models. Although no winter enhancement in warming over the Peninsula region is found, an autumn anomaly is seen in one of the models. The mechanism for this feature is documented, and an explanation of why it does not persist throughout the winter season is presented

Improved simulation of Australian climate and ENSO-related rainfall variability in a global climate model with an interactive aerosol treatment

We assess the simulation of Australian mean climate and rainfall variability in a new version of the CSIRO coupled ocean-atmosphere global climate model (GCM). The new version, called Mark 3.6 (Mk3.6), differs from its recent predecessors (Mk3.0 and Mk3.5) by inclusion of an interactive aerosol scheme, which treats sulfate, dust, sea salt and carbonaceous aerosol. Other changes include an updated radiation scheme and a modified boundary-layer treatment. Comparison of the mean summer and winter climate simulations in Mk3.6 with those in Mk3.0 and Mk3.5 shows several improvements in the new version, especially regarding winter rainfall and sea-level pressure. The improved simulation of Australian mean seasonal climate is confirmed by calculation of a non-dimensional skill score (the 'M-statistic'), using data from all four seasons. However, the most dramatic improvement occurs in the model's simulation of the leading modes of annual rainfall variability, which we assess using empirical orthogonal teleconnections (EOTs). Compared to its predecessors and several international GCMs, Mk3.6 is best able to capture the spatial pattern of the leading rainfall mode, which represents variability due to the El Nino Southern Oscillation (ENSO). Mk3.6 is also best able to capture the spatial pattern of the second rainfall mode, which corresponds to increased rainfall in the northwest, and decreased rainfall over eastern Australia. We propose a possible mechanism for the improved simulation of rainfall variability in terms of the role of interactive dust in Mk3.6. By further suppressing convection over eastern Australia during El Nino events, dust feedbacks may enhance rainfall variability there, in tune with the model's ENSO cycle. This suggests that an interactive aerosol treatment may be important in a GCM used for the study of Australian climate change and variability. Mechanistic sensitivity studies are needed to further evaluate this hypothesis