Moffatt et al. (2026) Isotopic Variability in Precipitation: Integrating HYSPLIT Raster Data Into Isoscape Modelling

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Hydrological Processes
• Year: 2026
• Date: 2026-01-01
• Authors: P. L. Moffatt, A. F. Fowler, R. Sánchez‐Murillo, J. Boll
• DOI: 10.1002/hyp.70393

Research Groups

Not specified in the abstract.

Short Summary

This study introduces a method to rasterize HYSPLIT air mass trajectory data for isotopic analysis, demonstrating that its incorporation significantly improves deuterium composition isoscape accuracy for precipitation compared to models relying solely on surface predictors. The research also elucidates meteorological drivers of isotopic variability, identifies a significant amount effect and sub-cloud evaporation at daily scales, and determines an optimal HYSPLIT initiation height of 1000 meters.

Objective

• To introduce a novel method for rasterizing HYSPLIT air mass trajectory data for isotopic analysis.
• To assess the impact of trajectory initiation height on HYSPLIT's representation of local precipitation and temperature.
• To characterize the meteorological processes driving isotopic variability in precipitation, including seasonality and daily-scale effects.
• To improve the accuracy of deuterium composition isoscapes for precipitation by incorporating air mass trajectory data.

Study Configuration

• Spatial Scale: Regional (isoscape generation), two specific sites for daily precipitation analysis.
• Temporal Scale: Approximately 2 years for daily precipitation analysis; analysis of seasonality implies annual cycles.

Methodology and Data

• Models used: HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory model), Random Forest, Multiple Linear Regression.
• Data sources: Air mass trajectory data (from HYSPLIT), stable isotopes of hydrogen and oxygen in precipitation (observational), local precipitation and temperature (observational).

Main Results

• Incorporating HYSPLIT rasters into spatial analysis significantly improved deuterium composition isoscape accuracy for precipitation compared to models using only surface predictors (temperature, elevation).
• Resulting isoscape patterns exhibited strong, temperature-dependent seasonality, consistent with previous studies.
• Trajectory cluster analysis successfully linked meteorological patterns to observed seasonality in isotope compositions.
• Daily precipitation analysis at two sites identified a significant amount effect and evidence for sub-cloud evaporation.
• A HYSPLIT model initiation height of 1000 meters was determined to be sufficient for the study domain, with no substantial improvement observed when using the local condensation level as the initiation height for correlations with modelled and observed precipitation or temperature.

Contributions

• Introduction of a novel method to rasterize HYSPLIT air mass trajectory data, enhancing its utility for isotopic analysis.
• Demonstrated a significant improvement in deuterium composition isoscape accuracy by integrating air mass trajectory information.
• Provided new insights into the meteorological drivers of isotopic variability in precipitation, including the role of air mass origin and daily-scale processes like the amount effect and sub-cloud evaporation.
• Optimized HYSPLIT model configuration by determining an effective trajectory initiation height for isotopic studies.

Funding

Not specified in the abstract.

Citation

@article{Moffatt2026Isotopic,
  author = {Moffatt, P. L. and Fowler, A. F. and Sánchez‐Murillo, R. and Boll, J.},
  title = {Isotopic Variability in Precipitation: Integrating <scp>HYSPLIT</scp> Raster Data Into Isoscape Modelling},
  journal = {Hydrological Processes},
  year = {2026},
  doi = {10.1002/hyp.70393},
  url = {https://doi.org/10.1002/hyp.70393}
}