Statistical Analysis of Wind Direction in the Gulf of Thailand
Accurate characterization of wind directionality is essential for the safety and reliability of offshore operations in the Gulf of Thailand. The application of conventional linear statistical methods to angular measurements often faces challenges with their intrinsic circular topology. Consequently, directional estimates under bimodal monsoon regimes might be suboptimal, introducing potential uncertainties in fatigue life assessments. This study presents a circular statistical analysis of wind-direction characteristics using ERA5 reanalysis data across three strategic locations covering the Gulf of Thailand. Advanced circular probability models, including the von Mises, wrapped normal, and wrapped Cauchy distributions, are implemented through mixture modeling to represent these inherently multimodal monsoon-driven wind patterns. Results reveal a strongly bimodal wind regime centered near 100° and 230°, corresponding to the Northeast and Southwest monsoons. All models exhibit excellent statistical performance; the von Mises mixture effectively captures sharply concentrated directional peaks, while the wrapped Cauchy mixture demonstrates superior robustness for wide angular dispersion. By deriving localized circular parameters, this framework provides a more accurate representation of directional wind behavior than linear methods, providing a site-specific environmental baseline for assessing directional loading, station-keeping response, and mooring-line fatigue.
Authors
- Dong Trong Nguyen (ORCID: https://orcid.org/0000-0002-8026-3761)
- Damrongsak Rinchumphu (ORCID: https://orcid.org/0000-0002-6037-4974)
- Chatchawan Chaichana (ORCID: https://orcid.org/0000-0002-9392-7088)
- Xu Han (ORCID: https://orcid.org/0000-0002-5223-2431)
- Chana Sinsabvarodom (ORCID: https://orcid.org/0000-0002-1860-4860)
- Wei Vivien Shi (ORCID: https://orcid.org/0000-0002-6312-0494)
- Thepparat Tharana
Institutions
- Norwegian University of Science and Technology (NO)
- Dalian University of Technology (CN)
- State Key Laboratory of Coastal and Offshore Engineering (CN)
- Chiang Mai University (TH)
Publication Details
- Journal
- Earth
- Published
- 2026-10-27
- DOI
- https://doi.org/10.3390/earth7060177
- Primary Topic
- Statistical Distribution Estimation and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chiang Mai University