25 years of precipitation isotopic composition across the USA: Assessment of non-linearities associated with moisture source dynamics and storm track variations in the Community Earth System Model

A 25-year record from the United States Network for Isotopes in Precipitation (USNIP) using data from seventy-three sampling sites reveals the dynamic role of moisture sources and storm tracks in controlling the precipitation geochemistry at a continental scale. Our study provides a fresh perspective on processes governing the water isotope cycle beyond the classic role of temperature. We report that Climate Oscillations (COs) combine to influence synoptic climatology and atmospheric transport patterns, thereby driving spatiotemporal distribution of precipitation ¹⁸O, ²H and d-excess values. The relationship between the individual COs and the isotopic composition of precipitation is spatially, temporally, and geographically inconsistent with varying time periods of linear (positive/negative), non-linear, or no coherence. The interactions between COs drive variations in isotope fractionation associated with evaporation (moisture source dynamics) and transport (storm track pathways and degree of rainout) of moisture. These are mirrored in the spatiotemporal precipitation isotope patterns across contiguous USA and supported by airmass trajectory analysis. We use the USNIP observational dataset to validate and test process representation in the variable-resolution isotope-enabled Community Earth System Model-version 2 (VR-iCESM2) with regional grid refinement to ~12.5 km over the contiguous US. To explore the relative influences of origin, transport, and condensation of water vapor on precipitation isotope patterns, we use process-oriented water tags in the VR-iCESM2 that track physical properties at the evaporation source locations, Rayleigh rainout effect, and precipitation condensation temperature. We find the model prediction to be deficient in coastal regions which improves in the continental interior, but ‘nudging’ the model with atmospheric thermodynamic properties and grid refinement leads to an overall enhancement in model performance relative to low resolution (~100 km) iCESM simulations. Evaluating and improving water cycling processes in climate models using spatially dense, long-term observational datasets of water isotopes, such as USNIP, will improve interpretations of paleoclimate records and predictions of future changes.