Cloud observations in the southern ocean pave the way to better climate models

Climate models are essential tools for understanding our planet’s future, helping scientists predict global warming patterns, sea level rise, and extreme weather events. These sophisticated computer simulations play a key role in raising awareness about climate change and informing crucial policy decisions. Thus, they can shape our response to environmental challenges over the coming decades.

However, the accuracy of a model’s predictions hinges on how well it can simulate the complex behavior of Earth’s atmosphere. Clouds, in particular, greatly influence Earth’s temperature by controlling how much solar radiation reaches the surface and how much heat escapes back to space. In polar regions, this balance becomes even more critical, as small changes in cloud properties can dramatically affect ice sheet melting and global sea levels. Currently, most climate models struggle with a fundamental challenge: They tend to overestimate the formation of ice clouds while underestimating supercooled liquid water (SLW) clouds in polar regions. Since ice clouds reflect less solar radiation than SLW clouds, this misrepresentation leads models to overestimate surface heating and causes a significant source of uncertainty in climate projections.

To address this critical gap, a research team including Professor Jun Inoue and Assistant Professor Kazutoshi Sato from the National Institute of Polar Research, Japan, conducted an extensive four-month study of cloud behavior over the Southern Ocean in Antarctica. Their findings, published online in Scientific Reports on May 28, 2025, provide much-needed observational evidence about SLW clouds that could revolutionize how climate models simulate polar weather systems.

To conduct their investigation, the team embarked on a research cruise aboard the research vessel Shirase, traversing the Southern Ocean over four months from December 2022 to March 2023. They equipped the ship with a lidar ceilometer and a microwave radiometer—advanced instruments capable of providing detailed information about cloud height, phase, and temperature. “The ceilometer can monitor the cloud phase at the cloud base, whereas the microwave radiometer can obtain the air temperature at the cloud base,” explains Prof. Inoue. “This enables an estimation of the relationship between the cloud-base temperature and the frequency of SLW cloud occurrence.”

Through meticulous observation and analysis, the researchers revealed a striking dominance of SLW clouds in the mid-troposphere, typically existing as thin layers less than 200 meters thick. Remarkably, these clouds constituted about 95% of the observed mid-level clouds, even when cloud-base temperatures dropped below −25 °C. Since these clouds are optically thick, they reflect a lot of incoming shortwave radiation from the sun. Interestingly, the team also showed that the inaccurate portrayal of these mid-tropospheric clouds at the altitude of phase transitions in the climate models results in an overestimation of net downward radiation reaching the surface.

Taken together, these findings challenge previous assumptions and provide valuable insights for accurately modelling the polar climate. “Our observational results provide ideas for improving existing models because they have difficulty reproducing SLW clouds instead of ice clouds,” noted Prof. Inoue. Worth noting, the team’s analysis of air mass movements revealed that persistent SLW clouds are primarily maintained by local atmospheric circulation during calm periods, making them crucial for understanding regional energy balance.

The results of this work have profound implications for climate science and global warming predictions. An improved representation of SLW clouds will help us resolve longstanding discrepancies in climate models, leading to more reliable projections of ice sheet melting, sea level rise, and regional climate changes that would ultimately affect billions of people worldwide. As climate scientists continue refining these essential tools for understanding our planet’s future, this piece of Antarctic research will serve as a stepping stone towards more accurate climate predictions.
 

Funding information

This study was supported by the Science Program of the Japanese Antarctic Research Expedition (JARE) as Prioritized Research Projects (AJ1005 and AJ1003), JSPS KAKENHI (grant numbers: JP23H00523 and JP24H02341), and the National Institute of Polar Research (NIPR) through research projects KP-402 and KC-401.

###

About National Institute of Polar Research, Japan
The National Institute of Polar Research (NIPR) engages in comprehensive research via observation stations in Arctic and Antarctica as a member of the Research Organization of Information and Systems (ROIS). It provides researchers throughout Japan and other countries with infrastructure and support for polar observations and works actively to promote polar science. By working under the same frameworks as various international academic organizations, NIPR is the core Japanese representative institution operating in both poles, conducting cutting-edge research on polar ecosystems, polar climate science, geology, sustainability in polar regions, and more.
Website: https://www.nipr.ac.jp/english/index.html

About Professor Jun Inoue from the National Institute of Polar Research, Japan
Dr. Jun Inoue obtained his master’s and PhD degrees from Hokkaido University, Japan, in 1999 and 2001, respectively. He currently serves as a Professor at the National Institute of Polar Research. His research interests lie in the fields of atmospheric and hydrosphere science, particularly in the Arctic and Antarctic regions. He has published over 100 papers on these topics and has received awards from the Japan Meteorological Society on three occasions.

About the Research Organization of Information and Systems (ROIS)
ROIS is a parent organization of four national institutes (National Institute of Polar Research, National Institute of Informatics, the Institute of Statistical Mathematics and National Institute of Genetics) and the Joint Support-Center for Data Science Research. It is ROIS's mission to promote integrated, cutting-edge research that goes beyond the barriers of these institutions, in addition to facilitating their research activities, as members of inter-university research institutes.