Climate models are powerful tools that help scientists understand and project how the Earth’s climate might change in the future. But before we can rely on these models to make predictions, such as how much it might rain in the future, we first need to ensure they replicate past data accurately. Most of the time, the match is not perfect because our understanding of the processes driving the climate is still incomplete—it's always a work in progress and something our research group is deeply passionate about.  

Global climate models (GCMs) rely on complex rules, called parameterisations, to simulate how clouds form and rain falls. However, some of these processes are still not fully understood, especially in the tropics, where climate and weather processes tend to be highly complex due to tropical convection.  

Schematic representation of the rainout effect on δ2H and δ¹⁸O values (Source: Coplen et al. 2000) 

In a new study recently published in the Journal of Advances in Modeling Earth Systems (JAMES), we used water isotope data from the Global Network of Isotope in Precipitation (GNIP) and other published data to evaluate the performance of the NASA’s GISS-E2.1 climate model, which is one of the few models that incorporate isotope tracers. GISS climate model outputs contribute to the CMIP (Coupled Model Intercomparison Project) archive, which is used by the IPCC reports. We added a rare isotope tracer, ¹⁷O, to evaluate how well the model simulates three key isotope signals in precipitation: δ¹⁸O, d-excess, and ¹⁷O-excess.  

Overall, we find the model performance to be satisfactory in simulating most precipitation isotope patterns. The model does a good job of matching the real-world patterns of 𝛿18O and d-excess, but produces slightly low d-excess values in the tropics. Most of the simulated ¹⁷O-excess values are within the range of observed values, but it is still hard to constrain the accuracy of the model because there is not enough observational data on ¹⁷O-excess. In tropical regions, we found that evaporation of raindrops and cloud processes have a strong impact on precipitation d-excess and 17O-excess.  

Long-term annual mean of precipitation (a) δ18O, (b) d-excess and (c) 17O-excess simulated by the GISS-E2.1 model (color shading) compared to the observational data (plotted as points) (Source: Yilin Zhang/NTU Singapore)  

This study helps explain how these isotope tracers behave in the atmosphere and will support efforts to improve climate models—a crucial step toward making future climate predictions more accurate and reliable. By improving these climate models, we also hope to provide better tools for understanding droughts, floods, and long-term water resource planning in Southeast Asia and beyond.  

This work was supported by a Singapore MOE Tier 2 Grant (MOEMOET2EP10121‐0008), Singapore MOE Tier 3 Grants (MOE2019‐T3‐1‐004; MOE-MOET32022-0006) and a Stephen Riady Geoscience Scholarship.