An Integrated Process‐Based Approach for Interpreting Precipitation Isotopes Using North‐Central Texas as a Testbed

Abstract

The isotopic composition of precipitation reflects the combined influences of moisture sources, rainout history, and convective intensity, but the relative importance of these controls varies among regions and remains poorly understood in continental settings. North‐central Texas, characterized by increasing 1‐day extreme precipitation and strong seasonal changes in moisture provenance, provides an ideal testbed for evaluating these interacting controls on precipitation isotope variability at daily and sub‐daily scales. Here, we test the hypothesis that precipitation isotope variability is governed primarily by the combined effects of moisture source origin and local convective intensity rather than rainfall type alone. To evaluate this, precipitation isotope data ( N  = 459; 2022, 2023, and 2024) collected in Arlington, Texas (Dallas‐Fort Worth metroplex, USA) were integrated with surface meteorological observations, vertical soundings, satellite and radar products, and air mass back trajectories using linear and nonlinear machine‐learning regression models. Results show that seasonal isotope variability is strongly controlled by relative humidity conditions at the moisture source, whereas daily and sub‐daily isotope depletion is primarily associated with cloud‐top brightness temperature, reflecting enhanced deep convection. These findings demonstrate that precipitation isotope variability in north‐central Texas is controlled by regional and local atmospheric processes, challenging interpretations based solely on rainfall type. This study introduces an integrated process‐based approach for interpreting precipitation isotopes and provides new insights into the links among atmospheric transport, local convective activity, and isotopic fractionation in continental midlatitude environments.