Antarctic expedition reveals why Southern Ocean clouds remain one of climate science's greatest challenges

An Antarctic expedition has uncovered why cloud simulations over the Southern Ocean continue to pose significant challenges for climate scientists. The Southern Ocean plays a crucial role in regulating Earth's climate by controlling incoming sunlight and outgoing heat through clouds. However, these clouds remain one of the least understood atmospheric phenomena. Small errors in representing them can lead to large uncertainties in weather forecasts, climate models, and projections of future global warming.

Researchers from the National Institute of Polar Research in Japan and Nagoya University examined cloud observations collected during the 64th Japanese Antarctic Research Expedition (JARE64). They found that numerical models often fall short in accurately representing clouds, particularly over the Southern Ocean and Antarctica. This leads to increased errors in the surface energy budget due to biases in radiative processes.

The study, published in Geophysical Research Letters, analyzed data from ship-based instruments during the expedition, comparing observations with three widely used atmospheric reanalysis data sets (ERA5, MERRA-2) and the CAM-ATRAS climate model. While all three data sets generally captured cloud patterns, they consistently overestimated low-level clouds and underestimated downward longwave radiation reaching the surface.

Further investigation revealed that increasing aerosol concentrations in the CAM-ATRAS model led to more low-level clouds but had limited impact on surface radiation. The discrepancy was traced to the physical properties of the simulated clouds, which contained excessive ice, reducing heat emitted toward the surface. However, the researchers discovered that the models also exhibit an inherent cold temperature bias, contributing to the underestimation of downward longwave radiation.

To improve simulations, the study emphasizes the need to accurately represent both cloud phase and temperature, rather than just cloud frequency. Enhancing cloud microphysics, aerosol-cloud interactions, and the background environment can help reduce uncertainties in Earth's energy balance and lead to more reliable climate predictions.

The researchers stress the importance of incorporating sparse observations from Antarctica, particularly temperature data, into numerical models to reduce cold biases. They also suggest that utilizing underutilized observations, such as those from the PANSY radar at Japan's Syowa Station, could help improve model accuracy. By addressing these challenges, the study aims to enhance weather forecasts, climate models, and projections of Earth's changing climate.