Exploring Precipitation Triple Oxygen Isotope Dynamics: Insights From GISS-E2.1 Simulations

Abstract

Precipitation isotopes are valuable tracers for understanding the hydrologic cycle and climate variations. Distinct from d-excess, ¹⁷O-excess has recently emerged as a promising new tracer of precipitation processes because of its insensitivity to moisture source temperature. However, the control mechanisms on precipitation ¹⁷O-excess remain poorly understood. In this study, we evaluated the performance of the GISS-E2.1 climate model in simulating the precipitation isotopes, focusing on ¹⁷O-excess. Through comprehensive analysis, we explored how variations in seawater isotopes, rain evaporation, kinetic isotope fractionation parameters, and supersaturation factors influence the simulated precipitation d-excess and ¹⁷O-excess. Our findings reveal that GISS-E2.1 accurately captures the spatial distribution and temporal variations of precipitation δ¹⁸O. Moreover, it reasonably reproduces the spatial patterns of precipitation d-excess, though slightly underestimating the mean value in the low latitudes. Although most simulated ¹⁷O-excess values fall within the observed range, evaluating the accuracy of ¹⁷O-excess simulations is challenging due to the limited availability of observational data. Notably, in tropical regions, the spatiotemporal distributions of d-excess and ¹⁷O-excess are sensitive to convective processes, such as rain evaporation. The model's limitations in ¹⁷O-excess simulation suggest that current formulations are inadequate to fully capture the variability of ¹⁷O-excess. This underscores the complexity of the processes influencing ¹⁷O-excess and highlights the need for additional data and further research to comprehensively understand its controlling factors. Our findings contribute to our understanding of the mechanisms driving the observed variation in precipitation triple oxygen isotopes and to the validation and improvement of climate models.