WISO-SAT: A global database of stable hydrogen isotopes in water vapor from eight satellite missions

Abstract Stable isotopes of hydrogen, including deuterium (δD), provide a critical tracer for understanding Earth's hydrological cycle and climate dynamics. Recognizing this, the last two decades have seen a number of remote sensing missions geared towards measuring the ratio of HDO/H2O in water vapor. At present, however, observational gaps persist in remote regions and across satellite platforms. Furthermore, these data span different time periods, altitudes, and are inconsistently formatted, complicating intercomparison. To address this, we here describe WISO-SAT, an effort to homogenize δD and moisture concentration (qH₂O) retrievals from eight satellite missions (SCIAMACHY, GOSAT, GOSAT-2, TROPOMI, TES, AIRS, CrIS, IASI) into a unified, multi-year dataset at 1^∘×1^∘ and 5^∘×5^∘ horizontal resolutions. Key innovations and standardization of these 8 data products are made through bias correction across platforms and by providing uncertainty quantification. The dataset spans 2000-2024, enabling studies of decadal climate variability and changes in the seasonal cycle. Initial evaluation of satellite isotope ratios reveals distinct spatial and seasonal patterns: tropical enrichment in δD reflects evaporation from the ocean surface, while polar depletion aligns with rainout towards the poles and strong isotope fractionation at colder temperatures. Vertical profiles show sharp isotopic gradients in polar and subtropical subsidence zones and more gradual gradients in the tropics. This standardized and publicly available dataset of water vapor isotopes addresses a critical gap in isotopic observations from satellites across different timelines, supports climate model validation and development (e.g., isotope-enabled GCMs), and process-level studies of atmospheric phenomena such as moisture transport, rain formation and evaporation, and atmospheric rivers. An open-access repository includes NetCDF files and preprocessing codes used to format each dataset. We also provide example notebooks and scripts demonstrating model-satellite averaging kernel application and regression-based bias correction for surface δD validation. WISO-SAT enables novel applications in atmospheric science and hydrology, and provides an open data product that can be used to validate the simulation of Earth's water cycle in GCMs.