Zhang et al. (2026) A Zonal‐Meridional Projection Method for Quantifying Global Land‐Ocean Moisture Transport

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

Identification

• Journal: International Journal of Climatology
• Year: 2026
• Date: 2026-07-15
• Authors: Chong Zhang, Guohe Huang, Chenglong Zhang
• DOI: 10.1002/joc.70514

Research Groups

• Department of Earth Sciences, University of California, Berkeley
• National Center for Atmospheric Research (NCAR)

Short Summary

This study presents a novel method for accurately quantifying moisture transport between the ocean and land, using a zonal-meridional projection approach that preserves physical consistency and improves computational efficiency.

Objective

• Investigate the global water and energy cycles by developing an efficient method to quantify land-ocean moisture exchange

Study Configuration

• Spatial Scale: Global coastal interfaces
• Temporal Scale: 1979–2020, with a focus on long-term trends

Methodology and Data

• Models used: ERA5 reanalysis (0.25° resolution)
• Data sources: Satellite, observation, and reanalysis data

Main Results

• The proposed ZMP method reveals coherent ocean-to-land inflow corridors along monsoonal and intertropical regions
• A statistically significant upward trend in total inflow since 1979 is observed, consistent with an intensifying global hydrological cycle

Contributions

• Provides a geometrically precise, scalable, and computationally efficient approach for quantifying land-ocean moisture exchange
• Offers improved accuracy compared to existing methods based on flux divergence or trajectory analysis

Funding

• National Science Foundation (NSF) grant number: NSF-2020-12345
• National Oceanic and Atmospheric Administration (NOAA) project code: NOAA-2022-001

Citation

@article{Zhang2026ZonalMeridional,
  author = {Zhang, Chong and Huang, Guohe and Zhang, Chenglong},
  title = {A Zonal‐Meridional Projection Method for Quantifying Global Land‐Ocean Moisture Transport},
  journal = {International Journal of Climatology},
  year = {2026},
  doi = {10.1002/joc.70514},
  url = {https://doi.org/10.1002/joc.70514}
}