ArticleProceedings of the National Academy of Sciences of the United States of America2021
Precipitation isotope time series predictions from machine learning applied in Europe.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Ecology and demographic structure of an extinct ibex population in late Upper Palaeolithic Italian Alps.Scientific reports · 2026Article
- Employing artificial intelligence to predict δ¹⁸O and δ²H isotope ratios in precipitation in Iraq under changing climate patterns.Scientific reports · 2026Article
- Dual Isotope Analysis Reveals Phylogenetic Patterns and Novel Insights Into Methoxy Group Synthesis of Structural Biomolecules in Leaf and Woody Plant Tissues.Plant, cell & environment · 2025Article
- Asian continental isoscapes of tree-ring δNational science review · 2025Article
- Opposing seasonal trends in source water and sugar dampen intra-annual variability in tree rings oxygen isotopes.The New phytologist · 2025Article
- Growth and Assemblage Dynamics of Temperate Forest Tree Species Match Physiological Resilience to Changes in Atmospheric Chemistry.Global change biology · 2025Article
- Decoupling of Tree-Ring Cellulose δPlant, cell & environment · 2025Article
- Hydroclimatic extremes threaten groundwater quality and stability.Nature communications · 2025Article
- Global expansion of tropical cyclone precipitation footprint.Nature communications · 2024Article
- Different responses of oxygen and hydrogen isotopes in leaf and tree-ring organic matter to lethal soil drought.Tree physiology · 2024Article
- Detecting long-term changes in stomatal conductance: challenges and opportunities of tree-ring δThe New phytologist · 2022Article
- Isotopic composition and major ion concentrations of national and international bottled waters in Costa Rica.Data in brief · 2021Article
- Using plant physiological stable oxygen isotope models to counter food fraud.Scientific reports · 2021Article
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Authors and funding
3 authors.
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Abstract
Hydrogen and oxygen isotope values of precipitation are critically important quantities for applications in Earth, environmental, and biological sciences. However, direct measurements are not available at every location and time, and existing precipitation isotope models are often not sufficiently accurate for examining features such as long-term trends or interannual variability. This can limit applications that seek to use these values to identify the source history of water or to understand the hydrological or meteorological processes that determine these values. We developed a framework using machine learning to calculate isotope time series at monthly resolution using available climate and location data in order to improve precipitation isotope model predictions. Predictions from this model are currently available for any location in Europe for the past 70 y (1950-2019), which is the period for which all climate data used as predictor variables are available. This approach facilitates simple, user-friendly predictions of precipitation isotope time series that can be generated on demand and are accurate enough to be used for exploration of interannual and long-term variability in both hydrogen and oxygen isotopic systems. These predictions provide important isotope input variables for ecological and hydrological applications, as well as powerful targets for paleoclimate proxy calibration, and they can serve as resources for probing historic patterns in the isotopic composition of precipitation with a high level of meteorological accuracy. Predictions from our modeling framework, Piso.AI, are available at https://isotope.bot.unibas.ch/PisoAI/.
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