Zhang et al. (2026) Spatially non‐stationary relationships between sea fog and marine meteorological factors with a satellite‐based geographically weighted regression model

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

Identification

• Journal: Quarterly Journal of the Royal Meteorological Society
• Year: 2026
• Date: 2026-07-01
• Authors: Xicheng Zhang, Zhe Zeng, Ling Ke, Shanwei Liu, Hui Sheng
• DOI: 10.1002/qj.70204

Research Groups

• Key Laboratory for Arid Climate Change and Reducing Disaster of Gansu Province
• School of Atmospheric Sciences, Lanzhou University
• State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics

Short Summary

This study introduces a geographically weighted regression (GWR) model to investigate the spatially non-stationary relationships between sea fog occurrence and marine meteorological factors in the Yellow and Bohai Seas, achieving improved accuracy and comprehensive representation.

Objective

• Investigate the complex relationships between sea fog occurrence and marine meteorological factors using a GWR model

Study Configuration

• Spatial Scale: Regional scale (Yellow and Bohai Seas)
• Temporal Scale: Monthly averages for peak sea fog season (March–June)

Methodology and Data

• Models used: Geographically Weighted Regression (GWR) and Ordinary Least Squares (OLS)
• Data sources: Himawari-9 satellite-based sea fog detection, fifth-generation atmospheric reanalysis

Main Results

• Sea fog occurrence and marine meteorological factors exhibit significant spatial clustering
• GWR model performed significantly better than OLS model with an R2 value of 0.536 higher
• Optimal formation ranges for peak sea fog: MSL 1013.73–1021.74 hPa, RH 76.48%–86.38%, TD 0.18–0.84°C, WSD 5.44–6.35 m·s−1

Contributions

• Original value of the article with respect to existing literature: The study introduces a GWR model that investigates spatially non-stationary relationships between sea fog occurrence and marine meteorological factors, achieving improved accuracy and comprehensive representation.

Funding

• National Natural Science Foundation of China (Grant No. 41875064)
• Key Research Program of the Chinese Academy of Sciences (Grant No. KFZD-BR-2020)

Citation

@article{Zhang2026Spatially,
  author = {Zhang, Xicheng and Zeng, Zhe and Ke, Ling and Liu, Dan and Liu, Shanwei and Sheng, Hui},
  title = {Spatially non‐stationary relationships between sea fog and marine meteorological factors with a satellite‐based geographically weighted regression model},
  journal = {Quarterly Journal of the Royal Meteorological Society},
  year = {2026},
  doi = {10.1002/qj.70204},
  url = {https://doi.org/10.1002/qj.70204}
}