Domestic Researchers Improve Accuracy of Precipitation Change Predictions Due to Global Warming

Professor Kim Hyung-jun of KAIST, International Collaborative Research Results

[Asia Economy Reporter Kim Bong-su] Domestic researchers have improved the prediction accuracy of climate models regarding changes in precipitation due to global warming through international collaborative research.

The Korea Advanced Institute of Science and Technology (KAIST) announced on the 28th that Professor Kim Hyung-jun of the Moonseul Graduate School of Future Strategy successfully reduced the uncertainty in climate model predictions of global precipitation changes in the late 21st century for the first time through international joint research.

Predictions of how much the global average temperature will rise in the future are usually made by multiple climate models, but there is considerable variation among them. While research to reduce uncertainty in temperature rise predictions has been successfully conducted, studies aimed at decreasing uncertainty in precipitation change predictions have not yet been reported.

Professor Kim, in collaboration with the National Institute for Environmental Studies of Japan and the University of Tokyo research team, succeeded for the first time worldwide in reducing uncertainty in precipitation change predictions by comparing simulation results of temperature and precipitation from 67 climate models with past observational data.

Prediction of temperature change by models with a past global average temperature change rate greater than observational data and models within the uncertainty range of observational data. Image provided by KAIST.

The main reason why improving uncertainty in precipitation change predictions has been difficult until now is that greenhouse gases and aerosols, which are atmospheric pollutants, acted together in past precipitation changes. In the past, both factors increased simultaneously, but unlike that, in the future, due to active air pollution control measures, aerosols will sharply decrease, and only the increase in greenhouse gases will be dominant.

In other words, future precipitation changes can mainly be explained by the increase in greenhouse gas concentrations, but since this mechanism differs from the past, it has been difficult to obtain information from observational data to reduce uncertainty in future predictions.

The research team assumed that by comparing trends between models and observations during a period when global average aerosol emissions remained nearly unchanged (1980?2014), the reliability of climate responses to greenhouse gas concentration increases could be evaluated. Under a moderate greenhouse gas emission scenario (SSP-RCP 245), 67 climate models predicted a 1.9?6.2% increase in precipitation from the late 19th century to the late 21st century. However, by considering the reliability of each climate model’s climate response to greenhouse gases, the upper limit of predicted precipitation increase (6.2%) was reduced to 5.2?5.7%, and the variance of predictions was also reduced by 8?30%.

Future average precipitation change prediction graph according to changes in average temperature and precipitation. Image provided by KAIST.

Professor Kim said, "Through this research, we have been able to improve the prediction accuracy of climate change not only for temperature but also for precipitation," adding, "We expect this to contribute to more reliable climate change impact assessments and the establishment of efficient climate change response and adaptation policies."

This research was conducted with support from the Korea Research Foundation’s Overseas Outstanding Scientist Recruitment Project (BP+), and the paper was published in the February 23 issue of the international journal Nature.

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