The hydrological cycle couples the Earth’s energy, carbon, and water budgets through evaporation, moisture transport, and precipitation, and controls the distribution of water available to ecosystems and societies. However, there remains substantial uncertainty about how water moves through the Earth system that limits our ability to diagnose water cycle variations and their relationship to climate change. Moreover, these uncertainties limit our process-level understanding of societal impacts arising from climate changes including droughts, floods, changes in coastal systems, or from impacts due to anthropogenic land use changes.
Earth system models (ESMs) and environmental tracers are two commonly used tools to investigate and understand hydrological processes. In contemporary ESMs, each component tracks water mass balance and transport and includes representations of critical hydrological processes in that domain. Environmental tracers, such as water isotope ratios, are often used as process tracers to help elucidate these underlying hydrologic processes that are not apparent from humidity or water volume alone. Water isotope ratios vary in response to patterns of evaporation, precipitation, and mixing of water sources, and have been used across Earth system domains to probe hydrologic processes. However, despite the relatively simple physics that determine water isotope fractionation, interpretations of water isotope ratios often remain equivocal and require process-based models to aid in their interpretation.
Numerical tracers of water isotope ratios in ESMs can help link these observations to model processes and allow for extraction of more process information from observations and improved validation of model processes. Moreover, numerical tracers can be generalized to track a wide variety of processes influencing the hydrological cycle. I will: 1) introduce these “process-oriented” numerical water tracers, a capability that E3SM currently does not have but that I would like to develop, and 2) discuss how if implemented, these tracers would enable better understanding of hydrological processes across model domains.